Behavioural dysfunction is a key feature of genetic frontotemporal dementia (FTD) but validated clinical scales measuring behaviour are lacking at present.C9orf72, 76 MAPT, 195 GRN) and 267 non‐mutation carriers (controls). All mutation carriers were stratified according to their global CDR plus NACC FTLD score into three groups: asymptomatic (CDR = 0), prodromal (CDR = 0.5) and symptomatic (CDR = 1+). Mixed‐effects models adjusted for age, education, sex and family clustering were used to compare between the groups. Neuroanatomical correlates of the individual domains were assessed within each genetic group.We assessed behaviour using the revised version of the Cambridge Behavioural Inventory (CBI‐R) in 733 participants from the Genetic FTD Initiative study: 466 mutation carriers (195 C9orf72 mean 70.5 (standard deviation 27.8), GRN 56.2 (33.5), MAPT 62.1 (36.9)] as well as their respective CDR 0.5 groups  and CDR 0 groups . The C9orf72 and GRN 0.5 groups scored significantly higher than the controls. The greatest impairment was seen in the Motivation domain for the C9orf72 and GRN symptomatic groups, whilst in the symptomatic MAPTgroup, the highest‐scoring domains were Stereotypic and Motor Behaviours and Memory and Orientation. Neural correlates of each CBI‐R domain largely overlapped across the different mutation carrier groups.CBI‐R total scores were significantly higher in all CDR 1+ mutation carrier groups compared with controls [The CBI‐R detects early behavioural change in genetic FTD, suggesting that it could be a useful measure within future clinical trials. MAPT),GRN)C9orf72).Frontotemporal dementia (FTD) is a heterogeneous neurodegenerative disease associated with changes in behaviour, language and cognition.Unlike a number of already existing scales such as the Neuropsychiatric Inventory (NPI)The aim of this study was therefore to assess the CBI‐R as a measure of behavioural and functional change in genetic FTD using data from the Genetic FTD Initiative (GENFI) cohort, an international study of the natural history of genetic FTD with the aim of identifying early biomarkers.GRN, MAPT or C9orf72, including those who were symptomatic as well as those who were at‐risk first‐degree relatives of mutation carriers. This second group consists of both presymptomatic mutation carriers and mutation‐negative family members who therefore act as healthy controls. Of the 849 participants recruited into the fifth data freeze, cross‐sectional data on the CBI‐R was available from 733 participants: 466 mutation carriers  and 267 mutation‐negative healthy controls. The study procedures were approved by local ethics committees and all participants provided informed written consent.Data were collected from participants from the fifth data freeze of the GENFI study including sites in the UK, Canada, Sweden, Netherlands, Belgium, Spain, Portugal, Italy and Germany. Participants were recruited from families with a confirmed pathogenic genetic mutation in All participants underwent the standardised GENFI clinical assessment battery including history and examination, the Mini‐Mental State Examination (MMSE), the Frontotemporal dementia Rating Scale (FRS) and the Clinical Dementia Rating Scale plus National Alzheimer Coordinating Centre FTLD module (CDR plus NACC FTLD). A global CDR plus NACC FTLD score gives a summary of the current disease stage, where 0 is asymptomatic, 0.5 is prodromal or very mildly symptomatic and 1, 2 and 3 represent the mild, moderate and severe fully symptomatic stages. For the purposes of this study, the fully symptomatic mutation carriers were grouped together as 1+. The CDR plus NACC FTLD sum of boxes score in which the total score on each domain is added together (max score = 24) provides a measure of disease severity.All participants had a CBI‐R questionnaire completed by a close informant, usually either a family member or a close friend. The CBI‐R assesses the frequency of the given behaviour over the past month on a scale of 0–4C9orf72, 182 GRN and 69 MAPT mutation carriers.Participants underwent volumetric T1‐weighted magnetic resonance imaging according to the harmonised GENFI protocol on a 3T scanner. This usually occurred on the same day as the clinical assessment but occasionally on a different day at a maximum of 12 weeks apart. All images were checked for quality control, and scans with movement or artefacts were removed from the analysis. Only scans from mutation carriers were included in the correlative analysis: of the 466 participants, 430 scans were available for the analysis: 179 Neuroanatomical regions of interest were subsequently generated as previously described using an automated atlas segmentation propagation and label fusion strategy called Geodesic Information Flow.All statistical analyses were performed using StataCorp. 2016. Stata Statistical Software: Version 14. College Station, TV: StataCorp LLC.Demographic data were compared between groups using a linear regression model, with bootstrapping when the data were not normally distributed.U test was used.In the healthy control group, Spearman's rank correlations were performed to evaluate the relationship between the CBI‐R total score and both age and education. To assess the relationship of CBI‐R total score with sex, a Mann–Whitney In order to compare the CBI‐R total score between groups, a mixed‐effects model was used that adjusted for age, education, sex and family clustering, along with bootstrapped confidence intervals with 2000 repetitions as the data were not normally distributed.The relationship of the CBI‐R total score with disease severity (both CDR plus NACC FTLD sum of boxes and FRS) was assessed using Spearman’s rank correlations within each genetic group.Similar mixed‐effects models as performed above were used to assess differences in each of the individual CBI‐R domains firstly, between genetic groups, and secondly, within groups (symptomatic mutation carriers only).Neural correlates of each individual CBI‐R domain were investigated in each genetic group by assessing non‐parametric partial correlations (adjusting for age and disease severity) of the domain score with the neuroanatomical regions of interest.GRN mutation carriers were significantly older than controls  while the asymptomatic MAPT mutation carriers were younger than controls (p < 0.001). Within each of the genetic groups, the symptomatic mutation carriers were significantly older than the prodromal and asymptomatic mutation carriers . The symptomatic C9orf72 group contained more males than controls (p < 0.001) and compared with their asymptomatic and prodromal groups (p = 0.002 and p = 0.019 respectively), but there were no other differences in sex compared with controls or between genetic groups. Symptomatic C9orf72 and GRN mutation carriers spent significantly fewer years in education than controls (p = 0.004 and p < 0.001 respectively) and their respective asymptomatic groups , and for the GRN group also less than their prodromal mutation carriers (p = 0.011).The age, sex and education of the participants are shown in Table r = 0.06, p = 0.310) or education , and there was no difference in score between men and women (p = 0.435).Healthy controls (i.e. mutation‐negative family members) had very low scores on the CBI‐R with the highest scoring domain being Memory and Orientation [mean (standard deviation) 1.3 (2.3)] and Mood [1.1 (1.6)]. The mean CBI‐R total score was only 5.2 (standard deviation 7.8) out of 180. There were no significant correlations of CBI‐R total score with either age (C9orf72 70.5 (27.8), GRN 56.2 (33.5), MAPT 62.1 (36.9). In the prodromal groups, the C9orf72 and GRN mutation carriers scored significantly higher than controls  with only a trend for a higher score in the MAPT mutation carriers: 9.4 (10.4). In the asymptomatic mutation carriers, there was no difference between the C9orf72 [6.0 (7.9) or GRN 3.6 (6.0)] and controls but there was a significantly higher score in the MAPT mutation carriers: 8.9 (13.3).All symptomatic mutation carrier groups scored significantly higher than controls . There were also no differences between the prodromal mutation carriers. In the asymptomatic mutation carriers, the MAPT group scored significantly higher than the GRN group but there were no other differences.Comparing Figure C9orf72 r = 0.78, GRN r = 0.82, MAPT r = 0.60, all p = <0.001) .There was a significant positive correlation between the CBI‐R total score and the CDR plus NACC FTLD sum of boxes in all mutation carrier groups  .A significant negative correlation was seen in each mutation carrier group between CBI‐R total scores and FRS . Symptomatic MAPT mutation carriers scored higher than GRN mutation carriers for Stereotypic and Motor Behaviours and vice versa for Sleep. Although there were no differences between the prodromal groups, in the asymptomatic groups, the MAPT mutation carriers scored higher than the GRN mutation carriers for Motivation, Stereotypic and Motor Behaviours, Mood and Sleep and higher than the C9orf72 mutation carriers for Sleep.Comparing between domains in each of the symptomatic mutation carrier groups , the highest‐scoring domain was Motivation in both C9orf72 mutation carriers (significantly higher than the other domains apart from Everyday Skills and Memory and Orientation) and GRN mutation carriers , whilst in the MAPT mutation carriers, it was Memory and Orientation  followed by Stereotypic and Motor Behaviours .Comparing C9orf72 and GRN mutation carriers. Eating Habits score negatively correlated particularly with insula volume  in the C9orf72 and GRN mutation carriers and with frontal lobe volumes to a lesser extent in all three groups. The Abnormal Behaviour domain scores negatively correlated with hippocampal volume (right more than left) in the C9orf72 and GRN mutation carriers and with left insula volume in the MAPT mutation carriers. Beliefs score negatively correlated with thalamus volume in both the C9orf72 and GRN mutation carriers but also the frontal and temporal lobes and striatum in the C9orf72 group. Mood and Sleep both negatively correlated with medial temporal lobe volumes in the GRN group, with Mood showing a similar correlation in the C9orf72 mutation carriers. The Everyday Skills domain score negatively correlated with frontal and temporal lobe volumes in C9orf72 and MAPT mutation carriers, with the insula in C9orf72 and GRN mutation carriers, and with the striatum in the GRN and MAPT groups. Self Care score negatively correlated with frontal, insula and parietal volumes in the C9orf72 group, but quite widespread, mainly right‐sided, cortical and subcortical volumes in the GRN group. Lastly, Memory and Orientation negatively correlated with hippocampal volume in all three groups and additionally with the thalamus in the C9orf72 mutation carriers.Partial correlations between scores in each of the 10 domains and the neuroanatomical regions of interest adjusting for age and disease severity for each genetic group are shown in Tables S4–S6. There were no significant correlations with the Motivation domain. However, the Stereotypic and Motor Behaviours domain score negatively correlated with the hippocampal and amygdala volume (particularly on the right) in the C9orf72 and GRN groups, and Stereotypic and Motor Behaviours and Memory and Orientation in the MAPT group. CBI‐R total score was positively correlated with CDR plus NACC FTLD sum of boxes score and negatively correlated with the FRS which suggest that progression of overall behavioural change as measured by the CBI‐R tracks with disease severity. Lastly, we found overlapping neural correlates of individual CBI‐R domains across the different genetic groups.In this study, we have shown that the CBI‐R detects early behavioural change in familial FTD, with overlapping but distinct patterns of impairment in the three major genetic groups. The highest‐scoring domain was Motivation in the symptomatic C9orf72 mutation carriers scored highest in the CBI‐R. This may relate in part to the particular presence of neuropsychiatric features such as delusions and hallucinations (here recorded as Beliefs) in C9orf72 mutation carriers which occur more commonly in this group in addition to the core behavioural features common to all three genetic forms.C9orf72 mutation carriers can be multifactorial due to a combination of behavioural, cognitive and motor deficits.In symptomatic mutation carriers, we found that the CBI‐R can detect behavioural and functional differences across the range of domains included. In this study, we found that symptomatic C9orf72 and GRN groups, we found that Motivation was the highest scoring domain. This domain includes questions about both apathy and loss of empathy, both core behavioural features of FTD and both symptoms reported to be prominent in these two forms of genetic FTD.MAPT group, Stereotypic and Motor Behaviours (i.e. obsessive–compulsive behaviour) was the most common behavioural domain impaired, a feature described in prior studies.MAPT group also scored highly in the Memory and Orientation domain, consistent with prior studies showing early episodic memory impairment in this subgroup.In both symptomatic GRN and C9orf72 mutation carriers in our study. By this time, structural and functional brain changes have occurred,MAPT mutation carriers in the prodromal stage scored slightly lower than the C9orf72 and GRN groups, with only a trend to a higher score than controls. However, MAPT mutation carriers in the asymptomatic period scored at a similar level to the other groups, but here were significantly more impaired than controls. The domains significantly affected in this asymptomatic MAPT group were Stereotypic Behaviours  as well as Mood and Sleep. Potentially, the CBI‐R can therefore pick up the very early behavioural change in genetic FTD, here detecting symptoms many years before likely onset.Behavioural changes have been reported presymptomatically in genetic FTD in a number of previous studies.C9orf72 and GRN mutation carriers. The occurrence of disinhibition has been associated mainly with (orbito)frontal lobe atrophy previously, but some studies have implicated the right medial temporal lobe, suggesting a disruption of normal reward processing.C9orf72 and GRN groups. This association of hallucinations and delusions has been shown previously in C9orf72 mutation carriersGRN mutation carriers. For the cognitive domain of Memory and Orientation, there was an association with hippocampal volume in all three groups, consistent with the known role of the medial temporal lobe in episodic memory. However, there was an additional association with thalamus atrophy in the C9orf72 mutation carriers, a region long associated with episodic memory function.Neural correlates overlapped across the different genetic groups, although with some differences. The Stereotypic and Motor Behaviours domain was associated with medial temporal lobe atrophy, consistent with prior studies showing that obsessive–compulsive behaviours in FTD correlate with hippocampal and amygdala volumesMAPT mutation carriers, for example the prodromal MAPT group was relatively small, and negative results here may relate to the small sample size. We have also focused here on cross‐sectional data, extrapolating to changes over time across individuals but future research examining how the CBI‐R changes longitudinally over time within an individual will be important. Lastly, as the CBI‐R was commonly completed by an informant from a family with genetic FTD, it may be that they were more alert to the presence of behavioural symptoms, particularly in those who were prodromal, leading to potentially higher CBI‐R scores than in those with sporadic FTD.A limitation of our study was the relatively small sample size of the cohort once it is stratified, particularly for the As we move into clinical trials for genetic FTD, the need for outcome measures that are both easy to assess and not time‐consuming is required. There are still few validated assessment scales that focus on the behavioural and functional deficits prominent in people with FTD. The benefit of the CBI‐R is that it includes core behavioural, neuropsychiatric, functional and cognitive measures within the same scale. Our study suggests the CBI‐R can detect early behavioural change in genetic FTD, making it potentially a useful marker in a clinical trial setting. Measuring individual changes in behaviour over time will now be an important next step in understanding how the CBI‐R might be used in such trials.None.•Sónia Afonso – Instituto Ciencias Nucleares Aplicadas a Saude, Universidade de Coimbra, Coimbra, Portugal;•Maria Rosario Almeida – Faculty of Medicine, University of Coimbra, Coimbra, Portugal;•Sarah Anderl‐Straub – Department of Neurology, University of Ulm, Ulm, Germany;•Christin Andersson – Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden;•Anna Antonell – Alzheimer’s disease and Other Cognitive Disorders Unit, Neurology Service, Hospital Clínic, Barcelona, Spain;•Silvana Archetti – Biotechnology Laboratory, Department of Diagnostics, ASST Brescia Hospital, Brescia, Italy;•Andrea Arighi – Fondazione IRCCS Ca′ Granda Ospedale Maggiore Policlinico, Neurodegenerative Diseases Unit, Milan, Italy; University of Milan, Centro Dino Ferrari, Milan, Italy;•Mircea Balasa – Alzheimer’s disease and Other Cognitive Disorders Unit, Neurology Service, Hospital Clínic, Barcelona, Spain;•Myriam Barandiaran – Cognitive Disorders Unit, Department of Neurology, Donostia University Hospital, San Sebastian, Gipuzkoa, Spain; Neuroscience Area, Biodonostia Health Research Insitute, San Sebastian, Gipuzkoa, Spain;•Nuria Bargalló – Imaging Diagnostic Center, Hospital Clínic, Barcelona, Spain;•Robart Bartha – Department of Medical Biophysics, The University of Western Ontario, London, Ontario, Canada; Centre for Functional and Metabolic Mapping, Robarts Research Institute, The University of Western Ontario, London, Ontario, Canada;•Benjamin Bender – Department of Diagnostic and Interventional Neuroradiology, University of Tübingen, Tübingen, Germany;•Alberto Benussi – Centre for Neurodegenerative Disorders, Department of Clinical and Experimental Sciences, University of Brescia, Italy;•Maxime Bertoux – Inserm 1172, Lille, France; CHU, CNR‐MAJ, Labex Distalz, LiCEND Lille, France;•Anne Bertrand – Sorbonne Université, Paris Brain Institute – Institut du Cerveau – ICM, Inserm U1127, CNRS UMR 7225, AP‐HP – Hôpital Pitié‐Salpêtrière, Paris, France; Inria, Aramis project‐team, F‐75013, Paris, France; Centre pour l'Acquisition et le Traitement des Images, Institut du Cerveau et la Moelle, Paris, France•Valentina Bessi – Department of Neuroscience, Psychology, Drug Research, and Child Health, University of Florence, Florence, Italy;•Sandra Black – Sunnybrook Health Sciences Centre, Sunnybrook Research Institute, University of Toronto, Toronto, Canada;•Martina Bocchetta – Dementia Research Centre, Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, London, UK;•Sergi Borrego‐Ecija – Alzheimer’s disease and Other Cognitive Disorders Unit, Neurology Service, Hospital Clínic, Barcelona, Spain;•Jose Bras – Center for Neurodegenerative Science, Van Andel Institute, Grand Rapids, Michigan, MI 49503, USA;•Alexis Brice – Sorbonne Université, Paris Brain Institute – Institut du Cerveau – ICM, Inserm U1127, CNRS UMR 7225, AP‐HP – Hôpital Pitié‐Salpêtrière, Paris, France; Reference Network for Rare Neurological Diseases (ERN‐RND);•Rose Bruffaerts – Laboratory for Cognitive Neurology, Department of Neurosciences, KU Leuven, Leuven, Belgium;•Agnès Camuzat – Sorbonne Université, Paris Brain Institute – Institut du Cerveau – ICM, Inserm U1127, CNRS UMR 7225, AP‐HP – Hôpital Pitié‐Salpêtrière, Paris, France;•Marta Cañada – CITA Alzheimer, San Sebastian, Gipuzkoa, Spain•Valentina Cantoni – Centre for Neurodegenerative Disorders, Neurology Unit, Department of Clinical and Experimental Sciences, University of Brescia, Brescia, Italy;•Paola Caroppo – Fondazione IRCCS Istituto Neurologico Carlo Besta, Milano, Italy;•David Cash – Dementia Research Centre, Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, London, UK;•Miguel Castelo‐Branco – Faculty of Medicine, University of Coimbra, Coimbra, Portugal;•Olivier Colliot – Sorbonne Université, Paris Brain Institute – Institut du Cerveau – ICM, Inserm U1127, CNRS UMR 7225, AP‐HP – Hôpital Pitié‐Salpêtrière, Paris, France; Inria, Aramis project‐team, F‐75013, Paris, France; Centre pour l'Acquisition et le Traitement des Images, Institut du Cerveau et la Moelle, Paris, France;•Thomas Cope – Department of Clinical Neuroscience, University of Cambridge, Cambridge, UK;•Vincent Deramecourt – Univ Lille, France; Inserm 1172, Lille, France; CHU, CNR‐MAJ, Labex Distalz, LiCEND Lille, France;•María de Arriba – Neuroscience Area, Biodonostia Health Research Insitute, San Sebastian, Gipuzkoa, Spain;•Giuseppe Di Fede – Fondazione IRCCS Istituto Neurologico Carlo Besta, Milano, Italy;•Alina Díez – Neuroscience Area, Biodonostia Health Research Insitute, San Sebastian, Gipuzkoa, Spain•Diana Duro – Faculty of Medicine, University of Coimbra, Coimbra, Portugal;•Chiara Fenoglio – Fondazione IRCCS Ca′ Granda Ospedale Maggiore Policlinico, Neurodegenerative Diseases Unit, Milan, Italy; University of Milan, Centro Dino Ferrari, Milan, Italy;•Camilla Ferrari – Department of Neuroscience, Psychology, Drug Research, and Child Health, University of Florence, Florence, Italy;•Catarina B. Ferreira ‐Laboratory of Neurosciences, Institute of Molecular Medicine, Faculty of Medicine, University of Lisbon, Lisbon, Portugal;•Nick Fox – Dementia Research Centre, Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, London, UK;•Morris Freedman – Baycrest Health Sciences, Rotman Research Institute, University of Toronto, Toronto, Canada;•Giorgio Fumagalli – Fondazione IRCCS Ca′ Granda Ospedale Maggiore Policlinico, Neurodegenerative Diseases Unit, Milan, Italy; University of Milan, Centro Dino Ferrari, Milan, Italy;•Aurélie Funkiewiez – Centre de référence des démences rares ou précoces, IM2A, Département de Neurologie, AP‐HP – Hôpital Pitié‐Salpêtrière, Paris, France; Sorbonne Université, Paris Brain Institute – Institut du Cerveau – ICM, Inserm U1127, CNRS UMR 7225, AP‐HP – Hôpital Pitié‐Salpêtrière, Paris, France;•Alazne Gabilondo ‐Neuroscience Area, Biodonostia Health Research Insitute, San Sebastian, Gipuzkoa, Spain;•Roberto Gasparotti – Neuroradiology Unit, University of Brescia, Brescia, Italy•Serge Gauthier – Alzheimer Disease Research Unit, McGill Centre for Studies in Ageing, Department of Neurology & Neurosurgery, McGill University, Montreal, Québec, Canada;•Stefano Gazzina – Neurology, ASST Brescia Hospital, Brescia, Italy•Giorgio Giaccone – Fondazione IRCCS Istituto Neurologico Carlo Besta, Milano, Italy;•Ana Gorostidi – Neuroscience Area, Biodonostia Health Research Insitute, San Sebastian, Gipuzkoa, Spain;•Caroline Greaves – Dementia Research Centre, Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, London, UK;•Rita Guerreiro – Center for Neurodegenerative Science, Van Andel Institute, Grand Rapids, Michigan, MI 49503, USA;•Carolin Heller – Dementia Research Centre, Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, London, UK;•Tobias Hoegen – Neurologische Klinik, Ludwig‐Maximilians‐Universität München, Munich, Germany;•Begoña Indakoetxea – Cognitive Disorders Unit, Department of Neurology, Donostia University Hospital, San Sebastian, Gipuzkoa, Spain; Neuroscience Area, Biodonostia Health Research Insitute, San Sebastian, Gipuzkoa, Spain;•Vesna Jelic – Division of Clinical Geriatrics, Karolinska Institutet, Stockholm, Sweden;•Hans‐Otto Karnath – Division of Neuropsychology, Hertie‐Institute for Clinical Brain Research and Center of Neurology, University of Tübingen, Tübingen, Germany;•Ron Keren ‐The University Health Network, Toronto Rehabilitation Institute, Toronto, Canada;•Gregory Kuchcinski – Univ Lille, France; Inserm 1172, Lille, France; CHU, CNR‐MAJ, Labex Distalz, LiCEND Lille, France;•Tobias Langheinrich – Division of Neuroscience and Experimental Psychology, Wolfson Molecular Imaging Centre, University of Manchester, Manchester, UK; Manchester Centre for Clinical Neurosciences, Department of Neurology, Salford Royal NHS Foundation Trust, Manchester, UK;•Thibaud Lebouvier – Univ Lille, France; Inserm 1172, Lille, France; CHU, CNR‐MAJ, Labex Distalz, LiCEND Lille, France;•Maria João Leitão – Centre of Neurosciences and Cell Biology, Universidade de Coimbra, Coimbra, Portugal;•Albert Lladó – Alzheimer's disease and Other Cognitive Disorders Unit, Neurology Service, Hospital Clínic, Barcelona, Spain;•Gemma Lombardi – Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Florence, Italy;•Sandra Loosli ‐Neurologische Klinik, Ludwig‐Maximilians‐Universität München, Munich, Germany;•Carolina Maruta – Laboratory of Language Research, Centro de Estudos Egas Moniz, Faculty of Medicine, University of Lisbon, Lisbon, Portugal;•Simon Mead – MRC Prion Unit, Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, London, UK;•Lieke Meeter – Department of Neurology, Erasmus Medical Center, Rotterdam, Netherlands;•Gabriel Miltenberger – Faculty of Medicine, University of Lisbon, Lisbon, Portugal;•Rick van Minkelen – Department of Clinical Genetics, Erasmus Medical Center, Rotterdam, Netherlands;•Sara Mitchell – Sunnybrook Health Sciences Centre, Sunnybrook Research Institute, University of Toronto, Toronto, Canada;•Katrina Moore – Dementia Research Centre, Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, London UK;•Benedetta Nacmias – Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Florence, Italy;•Linn Öijerstedt – Center for Alzheimer Research, Division of Neurogeriatrics, Department of Neurobiology, Care Sciences and Society, Bioclinicum, Karolinska Institutet, Solna, Sweden; Unit for Hereditary Dementias, Theme Ageing, Karolinska University Hospital, Solna, Sweden;•Jaume Olives – Alzheimer's disease and Other Cognitive Disorders Unit, Neurology Service, Hospital Clínic, Barcelona, Spain;•Sebastien Ourselin – School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK;•Alessandro Padovani – Centre for Neurodegenerative Disorders, Department of Clinical and Experimental Sciences, University of Brescia, Italy•Jessica Panman – Department of Neurology, Erasmus Medical Center, Rotterdam, Netherlands;•Janne M. Papma – Department of Neurology, Erasmus Medical Center, Rotterdam;•Yolande Pijnenburg – Amsterdam University Medical Centre, Amsterdam VUmc, Amsterdam, Netherlands;•Cristina Polito – Department of Biomedical, Experimental and Clinical Sciences “Mario Serio”, Nuclear Medicine Unit, University of Florence, Florence, Italy•Enrico Premi – Stroke Unit, ASST Brescia Hospital, Brescia, Italy•Sara Prioni – Fondazione IRCCS Istituto Neurologico Carlo Besta, Milano, Italy;•Catharina Prix ‐Neurologische Klinik, Ludwig‐Maximilians‐Universität München, Munich, Germany;•Rosa Rademakers [as London Ontario geneticist] – Department of Neurosciences, Mayo Clinic, Jacksonville, Florida, USA;•Veronica Redaelli ‐Fondazione IRCCS Istituto Neurologico Carlo Besta, Milano, Italy;•Daisy Rinaldi – Centre de référence des démences rares ou précoces, IM2A, Département de Neurologie, AP‐HP – Hôpital Pitié‐Salpêtrière, Paris, France; Sorbonne Université, Paris Brain Institute – Institut du Cerveau – ICM, Inserm U1127, CNRS UMR 7225, AP‐HP – Hôpital Pitié‐Salpêtrière, Paris, France; Département de Neurologie, AP‐HP – Hôpital Pitié‐Salpêtrière, Paris, France; Reference Network for Rare Neurological Diseases (ERN‐RND);•Tim Rittman – Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK;•Ekaterina Rogaeva ‐Tanz Centre for Research in Neurodegenerative Diseases, University of Toronto, Toronto, Canada;•Adeline Rollin – CHU, CNR‐MAJ, Labex Distalz, LiCEND Lille, France;•Pedro Rosa‐Neto ‐Translational Neuroimaging Laboratory, McGill Centre for Studies in Ageing, McGill University, Montreal, Québec, Canada;•Giacomina Rossi – Fondazione IRCCS Istituto Neurologico Carlo Besta, Milano, Italy;•Martin Rossor – Dementia Research Centre, Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, London, UK;•Beatriz Santiago – Neurology Department, Centro Hospitalar e Universitario de Coimbra, Coimbra, Portugal;•Dario Saracino – Sorbonne Université, Paris Brain Institute – Institut du Cerveau – ICM, Inserm U1127, CNRS UMR 7225, AP‐HP – Hôpital Pitié‐Salpêtrière, Paris, France; Inria, Aramis project‐team, F‐75013, Paris, France; Centre de référence des démences rares ou précoces, IM2A, Département de Neurologie, AP‐HP – Hôpital Pitié‐Salpêtrière, Paris, France;•Sabrina Sayah – Sorbonne Université, Paris Brain Institute – Institut du Cerveau – ICM, Inserm U1127, CNRS UMR 7225, AP‐HP – Hôpital Pitié‐Salpêtrière, Paris, France;•Elio Scarpini – Fondazione IRCCS Ca′ Granda Ospedale Maggiore Policlinico, Neurodegenerative Diseases Unit, Milan, Italy; University of Milan, Centro Dino Ferrari, Milan, Italy;•Sonja Schönecker – Neurologische Klinik, Ludwig‐Maximilians‐Universität München, Munich, Germany;•Harro Seelaar – Department of Neurology, Erasmus Medical Centre, Rotterdam, Netherlands;•Elisa Semler ‐Department of Neurology, University of Ulm, Ulm;•Rachelle Shafei – Dementia Research Centre, Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, London, UK;•Christen Shoesmith – Department of Clinical Neurological Sciences, University of Western Ontario, London, Ontario, Canada;•Imogen Swift – Department of Neurodegenerative Disease, Dementia Research Centre, UCL Institute of Neurology, Queen Square, London, UK;•Miguel Tábuas‐Pereira – Neurology Department, Centro Hospitalar e Universitario de Coimbra, Coimbra, Portugal;•Mikel Tainta – Neuroscience Area, Biodonostia Health Research Insitute, San Sebastian, Gipuzkoa, Spain;•Ricardo Taipa – Neuropathology Unit and Department of Neurology, Centro Hospitalar do Porto – Hospital de Santo António, Oporto, Portugal;•David Tang‐Wai ‐The University Health Network, Krembil Research Institute, Toronto, Canada;•David L Thomas – Neuroimaging Analysis Centre, Department of Brain Repair and Rehabilitation, UCL Institute of Neurology, Queen Square, London, UK;•Paul Thompson – Division of Neuroscience and Experimental Psychology, Wolfson Molecular Imaging Centre, University of Manchester, Manchester, UK;•Hakan Thonberg – Center for Alzheimer Research, Division of Neurogeriatrics, Karolinska Institutet, Stockholm, Sweden;•Carolyn Timberlake – Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK;•Pietro Tiraboschi – Fondazione IRCCS Istituto Neurologico Carlo Besta, Milano, Italy;•Emily Todd – Dementia Research Centre, Department of Neurodegenerative Disease, UCL Institute of Neurology, UK;•Philip Van Damme – Neurology Service, University Hospitals Leuven, Belgium; Laboratory for Neurobiology, VIB‐KU Leuven Centre for Brain Research, Leuven, Belgium;•Mathieu Vandenbulcke – Geriatric Psychiatry Service, University Hospitals Leuven, Belgium; Neuropsychiatry, Department of Neurosciences, KU Leuven, Leuven, Belgium;•Michele Veldsman – Nuffield Department of Clinical Neurosciences, Medical Sciences Division, University of Oxford, Oxford, UK;•Ana Verdelho – Department of Neurosciences and Mental Health, Centro Hospitalar Lisboa Norte – Hospital de Santa Maria & Faculty of Medicine, University of Lisbon, Lisbon, Portugal;•Jorge Villanua – OSATEK, University of Donostia, San Sebastian, Gipuzkoa, Spain;•Jason Warren – Dementia Research Centre, Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, London, UK;•Carlo Wilke – Department of Neurodegenerative Diseases, Hertie‐Institute for Clinical Brain Research and Center of Neurology, University of Tübingen, Tübingen, Germany; Center for Neurodegenerative Diseases (DZNE), Tübingen, Germany;•Elisabeth Wlasich – Neurologische Klinik, Ludwig‐Maximilians‐Universität München, Munich, Germany;•Henrik Zetterberg – Dementia Research Institute, Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, London, UK;•Miren Zulaica – Neuroscience Area, Biodonostia Health Research Insitute, San Sebastian, Gipuzkoa, Spain.Table S1. Adjusted mean differences with 95% bootstrapped bias‐corrected confidence intervals in the comparison of CBI‐R total scores between healthy controls and each of the genetic groups stratified by global CDR plus NACC FTLD score.Table S2. Adjusted mean differences in each of the ten CBI‐R domains scores between the genetic groups stratified by global CDR plus NACC FTLD scores, with 95% bootstrapped bias‐corrected confidence intervals.Table S3. Adjusted mean differences from within‐group analysis of each of the ten CBI‐R domains for symptomatic mutation carriers ((A) C9orf72, (B) GRN, (C) MAPT) with 95% bootstrapped bias‐corrected confidence intervals.Table S4. Partial correlations between scores in the 10 domains of the CBI‐R and volumes of neuroanatomical regions of interest adjusting for disease severity and age  for the C9orf72 mutation carriers.Table S5. Partial correlations between scores in the 10 domains of the CBI‐R and volumes of neuroanatomical regions of interest adjusting for disease severity and age  for the GRN mutation carriers.Table S6. Partial correlations between scores in the 10 domains of the CBI‐R and volumes of neuroanatomical regions of interest adjusting for disease severity and age  for the MAPT mutation carriers.Figure S1. Correlations between CBI‐R total scores and (i) on the left, CDR plus NACC FTLD sum of boxes scores , and (ii) on the right, FRS scores .Figure S2. CBI‐R individual domain scores (as a percentage) in each of the ten domains in all symptomatic mutation carrier groups: (A) C9orf72, (B) GRN, (C) MAPT. The error bars represent standard error of the mean.Click here for additional data file.


Affiliations 2 and 6.Due to a production error, there was an error in author Acknowledgements, “The Regional Center of Medical Genetics Timis, Clinical Emergency Hospital for Children “Louis Turcanu” Timisoara, Timis, Romania is part of European Reference Network ERN ITHACA. The Department of Ophthalmology, Municipal Clinical Emergency Hospital of Timisoara, Timisoara, Romania is part of European Reference Network ERN-EYE.”A correction has been added to The publisher apologizes for this mistake. The original version of this article has been updated.


This article was corrected online.In the Original Investigation titled “Trends in Ransomware Attacks on US Hospitals, Clinics, and Other Health Care Delivery Organizations, 2016-2021,”


Journal of the American Medical Informatics Association, 2022; ocac065, https://doi.org/10.1093/jamia/ocac065This is a correction to: H Echo Wang, Matthew Landers, Roy Adams, Adarsh Subbaswamy, Hadi Kharrazi, Darrell J Gaskin, Suchi Saria, A bias evaluation checklist for predictive models and its pilot application for 30-day hospital readmission models, In the originally published version of this manuscript, the first author’s name includes an extra word “Echo”, the first author’s name should be “H. Echo Wang”This error has been corrected (online).


Correction: BMC Primary Care 23, 179 (2022)10.1186/s12875-022-01791-yFollowing publication of the original article , the aut•Fiona Walter should have a middle initial ‘M’ i.e. “Fiona M. Walter”•Affiliation 2 should be “Wolfson Institute of Population Health, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, EC1M 6BQ, UK”The mistakes were rectified in this article and in the original article.


In the original article, there was an error in affiliation [3]. Instead of “Department of Emergency Medicine, Faculty of Paramedical, University of Medical Sciences, Kermanshah, Iran,” it should be “Department of Emergency Medicine, Faculty of Paramedics, Kermanshah University of Medical Sciences, Kermanshah, Iran.”In the original article, Arsalan Naderipour's name was spelt incorrectly in the metadata. Instead of “Arsalan Naderipor” it should be, “Arsalan Naderipour.”The authors apologize for this error and state that this does not change the scientific conclusions of the article in any way. The original article has been updated.


The original publication of this article contained an incorrect affiliation. The incorrect and correct affiliation is shown in this correction article. The original article  has beenIncorrectFaculty of Medicine and Science at the Universidad San Sebastian, Providencia, Santiago de Chile, Región MetropolitanaCorrectFacultad de Medicina y Ciencia, Universidad San Sebastian, Providencia, Santiago, Región Metropolitana, Chile


In the published article, there was an error in affiliation 3. Instead of “Department of Radiology, Inner Mongolia International Hospital, Hohhot, China”, it should be “Department of Radiology, Affiliated Hospital of Inner Mongolia Medical University, Hohhot, China”.The authors apologize for this error and state that this does not change the scientific conclusions of the article in any way. The original article has been updated.


In the published article, there was an error in affiliation(s) [6]. Instead of “Agricultural Technology Extension Center, Jinxi County Agriculture and Rural Bureau, Fuzhou, China,” it should be “Jiangxi Agricultural Technology Extension Center, Nanchang, China.”In the published article, there was an error in affiliation(s) [7]. Instead of “Animal Epidemic Prevention and Quarantine Unit, Fengcheng Agricultural and Rural Bureau, Fengcheng, China,” it should be “Agricultural Technology Extension Center, Jinxi County Agriculture and Rural Bureau, Fuzhou, China.”In the published article, there was an error in affiliation(s) [8 (Guangbin Zhou)]. Instead of “Yichun Agriculture and Rural Affairs Bureau, Yichun, China,” it should be “Animal Epidemic Prevention and Quarantine Unit, Fengcheng Agricultural and Rural Bureau, Fengcheng, China.”The authors apologize for this error and state that this does not change the scientific conclusions of the article in any way. The original article has been updated.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Instead of “5Department of Cardiovascular, Neural and Metabolic Sciences, Sleep Disorders Center, Istituto Auxologico Italiano IRCCS, Milan, Italy, 6Department of Medicine and Surgery, University of Milano-Bicocca, Monza, Italy,” it should be “5Department of Cardiovascular, Neural and Metabolic Sciences, Sleep Disorders Center, Istituto Auxologico Italiano IRCCS, Milan, Italy.”In the published article, there was an error in affiliation for Elisa Perger. Instead of “2Psychology Research Laboratory, Istituto Auxologico Italiano IRCCS, Milan, Italy, 3Faculty of Psychology, eCampus University, Milan, Italy,” it should be “3Faculty of Psychology, eCampus University, Milan, Italy.”In the published article, there was an error in affiliation for Gian Mauro Manzoni. Instead of “The authors apologize for these errors and state that this does not change the scientific conclusions of the article in any way. The original article has been updated.


In the published article, there was an error regarding the affiliations for “Mirjam Renovanz.” Mirjam Renovanz's affiliations should be:4 Department of Neurology and Interdisciplinary Neuro-Oncology, Hertie Institute for Clinical Brain Research, Eberhard-Karls University of Tübingen, Tübingen, Germany“5 Center for Neuro-Oncology, Comprehensive Cancer Center Tübingen-Stuttgart, University Hospital of Tuebingen, Eberhard Karls University of Tübingen, Tübingen, Germany6 Department of Neurosurgery, University Hospital Tübingen, Eberhard Karls University Tübingen, Tübingen, Germany”The authors apologize for this error and state that this does not change the scientific conclusions of the article in any way. The original article has been updated.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


First episode of psychosis (FEP) patients display a wide variety of metabolic disturbances at onset, which might underlie these patients’ increased morbidity and early mortality. Glycemic abnormalities have been previously related to pharmacological agents; however, recent research highlights the impact of early life events. Birth weight (BW), an indirect marker of the fetal environment, has been related to glucose abnormalities in the general population over time. We aim to evaluate if BW correlates with glucose values in a sample of FEP patients treated with different antipsychotics. Two hundred and thirty-six patients were included and evaluated for clinical and metabolic variables at baseline and at 2, 6, 12, and 24 months of follow-up. Pearson correlations and linear mixed model analysis were conducted to analyze the data. Antipsychotic treatment was grouped due to its metabolic risk profile. In our sample of FEP patients, BW was negatively correlated with glucose values at 24 months of follow-up . BW showed a trend towards significance in the association with glucose values over the 24-month period  despite other confounders such as age, time, sex, body mass index, antipsychotic type, and chlorpromazine dosage. This finding suggests that BW is involved in the evolution of glucose values over time in a cohort of patients with an FEP, independently of the type of pharmacological agent used in treatment. Our results highlight the importance of early life events in the later metabolic outcome of patients. The Pathology of Mind, that “Diabetes is a disease which often shows itself in families in which insanity prevails” (First episode of psychosis (FEP) is characterized by a wide variety of clinical symptomatology characterized by the presence of psychosis , with a pooled median point and 12-month prevalence of approximately four persons per 1,000  after fasting overnight and stored initially at 4°C. The antipsychotic mean daily dose was calculated in chlorpromazine equivalents  was collected from maternal interviews. Body weight, height, and waist circumference were assessed at baseline and at 2-, 6-, 12-, and 24-month visits. Body mass index (BMI) is defined as body mass divided by the square of the body height and is universally expressed in units of kg/mivalents .We categorized the patients taking antipsychotic medication into three groups according to their antipsychotic-induced weight gain (AIWG) risk  . As prevThe demographic and baseline clinical variables were described for the total sample and stratified by sex. For continuous variables, the mean and standard deviation was described. Categorical variables were analyzed by analysis of frequencies.We used the Pearson correlation to evaluate the association between two continuous variables at every time point (as independent measures). Subsequently, and based on glucose findings at 24 months, we decided to use linear mixed model analysis (LMMA) to evaluate the glucose evolution over time  while including the effect of time and other potential confounders, as we accept that individual data might not be independent at each time point.LMMA is strongly recommended and a standard way to handle the dependencies of longitudinal data at hand; the model with maximum likelihood estimation has the advantage of coping with participant drop-out in an efficient way . LMMA alThe LMMA model used the glucose value over time as the dependent variable, while time, sex, antipsychotic drug type, BMI over the time period, chlorpromazine equivalents over the period time, age, and BW were used as independent variables.To evaluate the level of the association between glucose values over the study period and BW, we used the predictive values derived from the LMMA. These were plotted to correlate with BW in order to describe graphically the predicted value of glucose values over time for given any BW.Data were managed and analyzed with the IBM SPSS Statistics v.24.Clinical and sociodemographic baseline characteristics of the sample are described in Two hundred and thirty-six patients were included in the analysis at baseline. Pearson correlations between BW and glucose at baseline were , at 2 months , at 6 months , at 12 months , and at 24 months .Two hundred and twenty-six patients were included in the LMMA. Fixed effects are described for sex , age , time , antipsychotic drug type , equivalent doses of chlorpromazine , BMI , and BW .2 = 0.029, p<0.001) and quadratic correlation . When stratified by sex, correlations were as follows: for female participants, linear  and quadratic correlation , and for male participants, linear  and quadratic correlation   Figure 1Our results confirm that BW correlates and shows a trend towards significance with glucose values at a 24-month period of follow-up in a cohort of FEP patients minimally treated before inclusion. The association holds despite diverse confounding factors such as type or dose of antipsychotic, BMI, sex, or age.These findings suggest that early life events (represented by an indirect marker of the intrauterine milieu such as BW) play an important role in the metabolic abnormalities described in FEP, which could underlie the increased burden of morbidity and reduced life expectancy described at onset , 33.Sex showed a trend towards significance, presenting higher values for male participants than female. Interestingly, male fetuses tend to grow faster than female at early stages making them more vulnerable to stressors  such as Several studies have described factors affecting antipsychotic-induced weight gain in FEP patients, which can be theoretically translated as factors of glucose abnormalities , 36. HowOur results reflect a negative relationship, with lower BW correlating with higher glucose values, which is similar to findings in a previous study where lower BW correlated with higher adiposity in treatment-resistant patients . ObstetrSurprisingly, no differences in the pharmacological treatment arose between the groups evaluated based on their metabolic profile . This neThere are several limitations associated with our study. Firstly, BW is a surrogate marker of the intrauterine environment and is affected by birth length and gestational age, which were not recorded and may have biased our results. Although several meta-analyses confirm the association between BW and glucose values in the general population , 48, recOur findings show a correlation between BW and glucose values over a 24-month follow-up period and a trend towards significance in the association between BW and glucose values over this period. However, we must highlight the fact that the number of subjects included was low compared with studies in the general population, and patients were relatively young. In the meta-analysis by Knop , most ofOur results highlight the clinical importance of the prenatal environment to the later morbidity and early mortality risks of FEP patients.Sílvia Amoretti, Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Madrid, Spain; Department of Psychiatry, Hospital Universitari Vall d'Hebron; Group of Psychiatry, Mental Health and Addictions, Psychiatric Genetics Unit, Vall d'Hebron Research Institute (VHIR), Barcelona, Spain; Biomedical Network Research Centre on Mental Health (CIBERSAM), Spain; Universitat Autònoma de Barcelona, Barcelona, Spain; Ana Meseguer, Barcelona Clínic Schizophrenia Unit, Institute of Neuroscience, Hospital Clínic of Barcelona, University of Barcelona, Barcelona, Spain; Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Madrid, Spain; Institut d’investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain; David Fraguas, Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Madrid, Spain; Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, IiSGM, School of Medicine, Universidad Complutense, Madrid, Spain; Carmen Moreno, Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Madrid, Spain; Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, IiSGM, School of Medicine, Universidad Complutense, Madrid, Spain; Anna Alonso, Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Madrid, Spain; Department of Psychiatry, Hospital de la Santa Creu i Sant Pau, Barcelona, Spain; Eva Mª Grasa, Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Madrid, Spain; Department of Psychiatry, Hospital de la Santa Creu i Sant Pau, Barcelona, Spain; Jessica Fernandez, Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Madrid, Spain; Hospital Universitario de Alava, Servicio de Psiquiatría, BIOARABA, University of the Basque Country, Vitoria, Spain; Sainza García, Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Madrid, Spain; Hospital Universitario de Alava, Servicio de Psiquiatría, BIOARABA, University of the Basque Country, Vitoria, Spain; Maria Fe Barcones, Department of Medicine and Psychiatry, University of Zaragoza, Instituto de Investigación Sanitaria Aragón (IIS Aragón), Zaragoza, Spain; Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Madrid, Spain; Concepción de la Cámara, Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Madrid, Spain; Department of Medicine and Psychiatry, University of Zaragoza, Instituto de Investigación Sanitaria Aragón (IIS Aragón), Zaragoza, Spain; Julio Sanjuan, Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Madrid, Spain; INCLIVA, Universidad de Valencia, Hospital Clínico Universitario de Valencia, Spain; Hospital Clínico Universitario de Valencia, Spain; Mª Dolores Moltó, Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Madrid, Spain; INCLIVA, Universidad de Valencia, Hospital Clínico Universitario de Valencia, Spain; Antonio Bulbena, Institut de Neuropsiquiatria i Addiccions, Hospital del Mar, Barcelona, Spain; IMIM , Barcelona; Department of Psychiatry and Forensic Medicine, Autonomous University of Barcelona UAB, Bellaterra, Spain; Purificación Salgado, Institut de Neuropsiquiatria i Addiccions, Hospital del Mar, Barcelona, Spain; IMIM , Barcelona; Department of Psychiatry and Forensic Medicine, Autonomous University of Barcelona UAB, Bellaterra, Spain; Laura Montejo, Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Madrid, Spain; Institut d’investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain; Bipolar and Depressive Disorders Unit, Hospital Clinic, Institute of Neuroscience, University of Barcelona, Institut d’investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Centro de Investigacion Biomedica en Red de Salud Mental (CIBERSAM), Barcelona, Spain; Justo Pinzón, Bipolar and Depressive Disorders Unit, Hospital Clinic, Institute of Neuroscience, University of Barcelona, Institut d’investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Centro de Investigacion Biomedica en Red de Salud Mental (CIBERSAM), Madrid, Spain; Institut d’investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain; Child and Adolescent Psychiatry and Psychology Department, Hospital Clinic of Barcelona, Institute of Neurosciences, University of Barcelona, Barcelona, Spain; Josefina Castro, Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Madrid, Spain; Institut d’investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain; Child and Adolescent Psychiatry and Psychology Department, Hospital Clinic of Barcelona, Institute of Neurosciences, University of Barcelona, Barcelona, Spain; José Manuel Menchón, Psychiatry Department, Bellvitge University Hospital-IDIBELL, L'Hospitalet de Llobregat, Spain; Fernando Contreras, Psychiatry Department, Bellvitge University Hospital-IDIBELL, L'Hospitalet de Llobregat, Spain; Leticia García-Alvarez, Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Madrid, Spain; Department of Psychiatry, University of Oviedo, Oviedo, Spain. Instituto de Investigación Sanitaria del Principado de Asturias (ISPA), Oviedo, Spain; Leticia Gonzalez-Blanco, Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Madrid, Spain; Department of Psychiatry, University of Oviedo, Oviedo, Spain. Instituto de Investigación Sanitaria del Principado de Asturias (ISPA), Oviedo, Spain; Rafael Segarra, Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Madrid, Spain. Department of Neurosciences, University of the Basque Country, Cruces University Hospital, Biocruces Bizkaia Health Research Institute, Vizcaya, Spain; Neurosciences Department, Araba University Hospital, University of the Basque Country (UPV/ EHU), Vitoria, Spain; Arantzazu Zabala, Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Madrid, Spain. Department of Neurosciences, University of the Basque Country, Cruces University Hospital, Biocruces Bizkaia Health Research Institute, Vizcaya, Spain; Isabel Morales-Muñoz, Instituto de Investigacion Sanitaria, Hospital 12 de Octubre (imas12), Madrid, Spain; Mónica Dompablo, Instituto de Investigacion Sanitaria, Hospital 12 de Octubre (imas12), Madrid, Spain; Judith Usall, Parc Sanitari Sant Joan de Déu, Institut de Recerca Sant Joan de Déu, Sant Boi de Llobregat, Barcelona, Spain Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Madrid, Spain; Anna Butjosa, Parc Sanitari Sant Joan de Déu, Institut de Recerca Sant Joan de Déu, Sant Boi de Llobregat, Barcelona, Spain Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Madrid, Spain; Fundació Sant Joan de Déu, Institut de Recerca Sant Joan de Déu, Esplugues de Llobregat, Barcelona, Spain; Salvador Sarró, Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Madrid, Spain; FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain; Ramón Landín-Romero, Neuroscience Research Australia, Sydney, NSW, Australia School of Medical Sciences, University of New South Wales, Sydney, NSW, Australia ARC Centre of Excellence in Cognition and its Disorders, Sydney, NSW, Australia; Ángela Ibañez, Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Madrid, Spain; Department of Psychiatry, Hospital Universitario Ramón y Cajal, IRYCIS, Universidad de Alcalá, Madrid, Spain; Manuel J Cuesta, Department of Psychiatry, Complejo Hospitalario de Navarra, Pamplona, Spain; IdiSNA, Navarra Institute for Health Research, Pamplona, Spain; Vicent Balanzá-Martínez Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Madrid, Spain; Teaching Unit of Psychiatry, Department of Medicine, University of Valencia, Valencia, Spain.The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.The PEPS study was conducted in accordance with the ethical principles stated on the Declaration of Helsinki. The protocol was reviewed and approved by ethics committees at each participating center. A written and signed informed consent was obtained from all participants or their legal guardians after providing a full explanation of the study's procedures.CG-R designed the current study, wrote the first draft of the manuscript, and with MG undertook the statistical analysis. BC, MBi, GM, MG and EF-E managed the literature searches. AL, AG-P, CD-C, IC, EV, IB, MG-P, MG-F, RR-J and MBe contributed to the earlier versions of the manuscript. All authors contributed to the article and approved the submitted version.This study is part of a coordinated-multicentre Project, funded by the Ministerio de Economía y Competitividad , Instituto de Salud Carlos III, Fondo Europeo de Desarrollo Regional. Unión Europea. Una manera de hacer Europa, Centro de Investigación Biomédica en Red de salud Mental, CIBERSAM, by the CERCA Programme/Generalitat de Catalunya and Secretaria d’Universitats i Recerca del Departament d’Economia I Coneixement (2017SGR1355). This study has been funded by Instituto de Salud Carlos III (ISCIII) through the project “PI20/00661” and co-funded by the European Union. This work was developed (in part) at the Centro Esther Koplowitz (Barcelona). This project is also grateful for the support of the Institut de Neurociències, Universitat de Barcelona. This research was supported by CIBER -Consorcio Centro de Investigación Biomédica en Red- (código CIBER), Instituto de Salud Carlos III, Ministerio de Ciencia e Innovación and Unión Europea – European Regional Development Fund.We are extremely grateful to all subjects who took part in this study. The authors thank Ferran Torres , Hospital Clinic, Barcelona) and Cristina V. Oliveira  for their methodological support. IB thanks the Instituto de Salud Carlos III-ISCIII for its support (INT19/00021). AG-P has received grants and served as consultant, advisor or CME speaker for the following entities: the Spanish Ministry of Science and Innovation CIBERSAM, the Ministry of Science Carlos III Institute, the Basque Government, and the Stanley Medical Research Institute. CD-C holds a Juan Rodés grant JR19/00024, Instituto de Salud Carlos III, Spanish Ministry of Science and Innovation, and has received honoraria from AbbVie, Sanofi, and Exeltis. EV has received grants and served as consultant, advisor or CME speaker for the following entities; the Brain and Behaviour Foundation, the Spanish Ministry of Science and Innovation CIBERSAM, the Seventh European Framework Programme ENBREC, and the Stanley Medical Research Institute. IB has received , research support from Fundacio´n Alicia Koplowitz and grants from the Spanish Ministry of Health, Instituto de Salud Carlos III. RR-J has been a consultant for, spoken in activities of, or received grants from: Instituto de Salud Carlos III, Fondo de Investigación Sanitaria FIS, Centro de Investigación Biomédica en Red de Salud Mental CIBERSAM, Madrid Regional Government S2010/BMD-2422 AGES. CG-R has obtained research funding from the Spanish Ministry of Science and Education, the Spanish Ministry of Economy and Competiveness, Centro de Investigación Biomédica en Red de Salud Mental CIBERSAM, by the Government of Catalonia, Secretaria d’Universitats i Recerca del Departament d’Economia i Coneixement 2014SGR441, Foundation European Group for Research In Schizophrenia EGRIS, and the 7th Framework Program of the European Union.CG-R has received honoraria/travel support from Abbott, Adamed, Angelini, Cassen-Recordati, Janssen-Cilag and Lundbeck. MBi has been a consultant for, received grant/research support and honoraria from, and been on the speakers/advisory board of has received honoraria from talks and/or consultancy of Adamed, Angelini, Ferrer, Janssen-Cilag, Lundbeck, Neuraxpharm, Otsuka, Pfizer and Sanofi. AL has received honorarium or travel support from Lundbeck and Sanofi. AG-P has received grants and served as consultant, advisor or CME speaker for the following entities: Almirall, AstraZeneca,Bristol-Myers Squibb, Cephalon, Eli Lilly, Glaxo-Smith-Kline, Janssen-Cilag, Ferrer, Johnson & Johnson, Lundbeck, Merck, Otsuka, Pfizer,Sanofi-Aventis, Servier, Shering-Plough, Solvay, and and Wyeth. CD-C has received honoraria from AbbVie, Sanofi, and Exeltis. IC has received research grants and served as consultant, advisor or speaker for the companies Otsuka and Ferrer. EV has received grants and served as consultant, advisor or CME speaker for the following entities: AB-Biotics, Allergan, Angelini, AstraZeneca, Bristol-Myers Squibb, Dainippon Sumitomo Pharma, Farmindustria, Ferrer, Forest Research Institute, Gedeon Richter, Glaxo-Smith-Kline, Janssen, Lundbeck, Otsuka, Pfizer, Roche, Sanofi-Aventis, Servier, Shire, Sunovion, and Takeda. IB has received honoraria or travel support from Otsuka, and Angelini and Janssen. MG-P has been a consultant to and/or has received honoraria/grants from Angelini, Alianza Otsuka- Lundbeck, Instituto de Salud Carlos III, Janssen-Cilag, Lundbeck, Otsuka, Pfizer, and SAGE Therapeutics. MG-F has been on the speakers/advisory board of Janssen-Cilag. RR-J has been a consultant for, spoken in activities of, or received grants from: Janssen Cilag, Lundbeck, Otsuka, Pfizer, Ferrer, Juste. MB has been a consultant for, received grant/research support and honoraria from, and been on the speakers/advisory board of AB-Biotics, Adamed, Angelini, Casen Recordati, Janssen-Cilag, Menarini, Roviand Takeda.The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be constructed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


At the time of publication, the author was affiliated to both “Department of Cardiovascular Surgery, Japanese Red Cross Nagoya First Hospital, Nagoya, Japan” and “Department of Cardiac Surgery, Nagoya University Graduate School of Medicine, Nagoya, Japan”.


Scientific Data 10.1038/s41597-022-01579-w, published online 16 August 2022Correction to: In the html version of this article the affiliation details for Marco Antonio Correa Varella were incorrectly given as ‘eduLab21, Ayrton Senna Institute, São Paulo, 05423-040, Brazil’, but should have been ‘Department of Experimental Psychology, Institute of Psychology, University of São Paulo, São Paulo, 05508-030, Brazil’. This has now been corrected in the HTML version of the Article. The PDF version of the Article was correct at the time of publication.


In the published article, there was an error in affiliation 12. Instead of “Center for Digestive Disease, The Seventh Affiliated Hospital, Sun Yat-sen University, Guangzhou, China,” it should read “Center for Digestive Disease, The Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen, China.”In the published article, there was an error regarding the affiliation for Lili Wang. Instead of “Diagnosis and Treatment Center of Hepatobiliary Diseases, Nanyang First People's Hospital, Nanyang, China,” it should read “Department of Radiology, The First Hospital of Lanzhou University, Lanzhou, China.”There was an error regarding the affiliation for Lei Ma. Instead of “Department of Infection, The Second Hospital of Dalian Medical University, Dalian, China,” it should read “Diagnosis and Treatment Center of Hepatobiliary Diseases, Nanyang First People's Hospital, Nanyang, China.”The authors apologize for this error and state that this does not change the scientific conclusions of the article in any way. The original article has been updated.


Hanson K, Brikci N, Erlangga D, et al. The Lancet Global Health Commission on financing primary health care: putting people at the centre. Lancet Glob Health 10: e715–722022; —In this Commission, Lauren Hashiguchi's name had been misspelt in the Acknowledgments section. This correction has been made as of Jan 13, 2023.


Postherpetic neuralgia (PHN) is a common, complex, and refractory type of neuropathic pain. Several systematic reviews support the efficacy of acupuncture and related treatments for PHN. Nevertheless, the efficacy of various acupuncture-related treatments for PHN remains debatable.We aimed to assess the efficacy and safety of acupuncture-related treatments for PHN, identify the most effective acupuncture-related treatments, and expound on the current inadequacies and prospects in the applications of acupuncture-related therapies.We searched PubMed, Cochrane Central Register of Controlled Trials, Embase, Web of Science, Google Scholar, four Chinese databases , clinical research registration platform  for relevant studies. We also examined previous meta-analyses; gray literature; and reference lists of the selected studies. We then evaluated the risk of bias in the included studies and performed a Bayesian multiple network meta-analysis.We included 29 randomized controlled trials comprising 1,973 patients, of which five studies showed a high risk of bias. The pairwise meta-analysis results revealed that the efficacy of all acupuncture-related treatments for pain relief related to PHN was significantly better than antiepileptics. The network meta-analysis results showed that pricking and cupping plus antiepileptics were the most effective treatment, followed by electroacupuncture (EA) plus antiepileptics for pain relief in patients with PHN. EA plus antiepileptics ranked the best regarding reduced Pittsburgh Sleep Quality Index (PSQI) and Self-Rating Depression Scale (SDS) scores in patients with PHN. No results were found regarding the total response rate or quality of life in this study. Acupuncture-related treatments showed a lower incidence of adverse events than that of antiepileptics.Acupuncture-related therapies are potential treatment options for PHN and are safe. Pricking and cupping plus antiepileptics, are the most effective acupuncture-related techniques for pain relief, while EA plus antiepileptics is the best acupuncture-related technique for improving PHN-related insomnia and depression symptoms. However, owing to the limitations of this study, these conclusions should be cautiously interpreted, and future high-quality studies are needed.https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42021226422, identifier CRD42021226422. Postherpetic neuralgia (PHN) is a complex and refractory type of neuropathy , and is The incidence and prevalence of PHN vary according to the definition used; 19.5 and 13.7% of patients with herpes zoster developed PHN at least 1 month and 3 months after symptom onset, respectively . One metUnfortunately, PHN management remains challenging. The only well-documented means of PHN prevention is herpes zoster prevention . HoweverAcupuncture therapy, an essential part of traditional Chinese medicine, is valuable in pain management  and has To compare the analgesic effects of various acupuncture therapies on PHN, we conducted a pairwise and network meta-analysis (NMA) to comprehensively and critically evaluate all available and eligible clinical evidence to provide evidence-based recommendations for selecting the best therapeutic acupuncture schedule. Additionally, we expound on the current insufficiency and prospects in the applications of acupuncture-related therapies, to provide a reference for subsequent research.This study strictly followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA)  and PRISWe searched eight electronic databases, including PubMed, Embase, Cochrane Library, Web of Science, Google Scholar, China National Knowledge Infrastructure, China Biomedical, Chongqing VIP, and Wan Fang, from inception to December 7, 2022; language was restricted to English and Chinese.English search terms included: “neuralgia, postherpetic”, “postherpetic neuralgia”, “post-herpetic pain,”; “acupuncture analgesia”, “acupuncture therapy”, “acupuncture”, “manual acupuncture”, “surrounding acupuncture”, “surround needling”, “acupuncture, ear”, “auricular acupuncture”, “ear acupuncture”, “electroacupuncture”, “electro-acupuncture”, “fire needling”, “fire needle”, “warm needling”, “warm needle”, “moxibustion”, “thermal moxibustion”, “medicated thread moxibustion”, “pricking and cupping”, “pricking blood and cupping”, “blood-letting puncture and cupping”, “Fu’s subcutaneous needling”, “Fu’s acupuncture”, “acupoint catgut embedding”, “catgut embedding”, “dry needling”, “dry needle”, “laser acupuncture”.Chinese search terms included: “带状疱疹后神经痛”, “带状疱疹后疼痛”, “针灸”, “针刺”, “围刺”, “耳针”, “耳穴”, “电针”, “火针”, “温针”, “艾灸”, “热敏灸”, “药线灸”, “刺络拔罐”, “刺血拔罐”, “梅花针”, “浮针”, “埋线”, “干针”, “激光针”.The complete search strategy used for the Cochrane Central Register of Controlled Trials and other databases is shown in 1 China Clinical Trial Registration Center,2 previous meta-analyses, and gray literature.3Additionally, we searched the World Health Organization International Clinical Trial Registration platform,Two researchers crosschecked the search results and searched the reference lists of the included studies.We predefined inclusion criteria following the PICOS protocol :(1)Participants: to address the inconsistent diagnostic criteria for PHN are inconsistent, we referred to the International Association for the Study of Pain Classification of Chronic Pain for the International Classification of Diseases-11, which defines PHN as pain persisting for over 3 months after the onset of rash , and the(2)Treatment group: treatment groups involving a single type of acupuncture combined with pharmacotherapy were included. Acupuncture techniques were defined as manual, electro- (EA), and other acupuncture used in clinical practice ; however, acupoint injections were excluded. No limitations on needle material, acupoint matching, duration of needle retention, and treatment course were imposed.(3)Control group: controls received pharmacotherapy, a different single type of acupuncture than the treatment group, or sham acupuncture. To ensure homogeneity, pharmacotherapies were limited to evidence-based effective agents for PHN, including antiepileptics , tricyclic antidepressants , opioids , and topical treatments (5% lidocaine or capsaicin patches) . When an(4)Outcome indicators: primary outcome was reduced pain intensity, indicated by the change from baseline. The pain was measured using a visual analog scale (VAS) or numerical rating scale. Secondary outcomes were improvement in pain-related outcomes in Pittsburgh Sleep Quality Index (PSQI) score, Self-Rating Depression Scale (SDS) score, clinical response rate , quality of life, and adverse events (AEs).(5)Study design: studies based on needle insertion or stimulation of acupoints for therapeutic purposes, including randomized controlled trials (RCTs) that evaluated acupuncture and related therapies for PHN, were included.Exclusion criteria were:(1)Secondary analysis or duplicate publication .(2)Full text was unavailable after contacting the corresponding author.(3)Flawed study design, such as not strictly following the principle of randomization .(4)Missing baseline data.(5)Unspecified diagnostic criteria.(6)Outcome indicators are unobtainable or not applicable to the NMA.(7)Interventions included acupuncture combined with other acupuncture therapies.(8)Interventions were single drug treatment with no evidence-based efficacy  .After deleting duplicate records using EndNote X9 , two researchers independently reviewed all titles and abstracts based on the inclusion and exclusion criteria; studies that did not meet the inclusion criteria were excluded. Subsequently, full texts of the studies that met the inclusion criteria were carefully reviewed to determine if they should be included. Differences of opinion were resolved through discussions. If no agreement could be reached, a decision arbitrator was consulted. All researchers are licensed physicians with more than 2 years of clinical acupuncture experience.The following information was extracted according to a fixed protocol. After the final selection, two researchers extracted the data independently and created summary tables. Data were extracted according to a template, including the study  and participant characteristics , intervention , and outcome indicators. The results were then cross-checked.Under the Cochrane Collaboration recommendation , two resP < 0.05 indicated statistical significance. A fixed-effects model was used for analysis ; otherwise, a random-effects model was used.A pairwise meta-analysis was performed using STATA software version 15.1 . Weighted mean differences (WMDs) and corresponding 95% confidence intervals (CIs) were used to analyze continuous variables. The similarity hypothesis is one of the most important assumptions in NMA, which states that factors affecting the effect size are similar among all studies and different control groups. Only when the similarity hypothesis is satisfied can NMA produce reliable results; otherwise, bias is present. In this study, descriptive statistical analysis was performed on the RCTs’ population characteristics, and participants’ baseline levels were evaluated, including mean age and disease duration. Line graphs were drawn for visualization.P > 0.05, indicated that direct and indirect comparisons had better consistency. A convergence diagnosis plot was used to monitor the convergence of the model  and the “gemtc” package, which interfaces with OpenBUGS. Network plots were created in STATA (StataCorp LLC). A random-effects model was computed using Markov chain Monte Carlo  methods,he model  by calcuhe model . A rank The initial search resulted in 3,992 pending records, and we selected 253 potentially eligible articles for full-text review. After further screening, 224 studies were excluded; the reasons for excluding each study are detailed in n = 1010) were women. The average sample size of included studies was 64 (range: 37–115), and included seven types of acupuncture-related therapies: manual acupuncture, EA, fire needling, pricking and cupping, Fu’s acupuncture, medicated thread moxibustion, and acupoint catgut embedding in addition to pharmacotherapy. Only comparisons between acupuncture-related therapies and antiepileptic drugs were found for the pharmacotherapy group, and no eligible studies compared acupuncture with tricyclic antidepressants, opioids, or topical treatments. The Ashi point (82.76%) was the most frequently used acupoint among the included studies, followed by the Jiaji point (51.72%). Interestingly, pain reduction in all studies was reported according to a VAS. The details of each trial are provided in All included studies were conducted in China, published in Chinese, and included a total of 1,973 patients (mean age: 46.91–66.79 years); 54.45% (Twenty-nine studies implemented the correct randomization method. Five studies  were claP = 0.000 < 0.001), EA , fire needling , pricking and cupping , Fu’s acupuncture , EA plus antiepileptics , fire needling plus antiepileptics , pricking and cupping plus antiepileptics , and acupoint catgut embedding plus antiepileptics  were all more efficacious in reducing VAS scores. However, EA plus antiepileptics had a greater effect than EA alone . Nevertheless, in terms of VAS score reduction, no significant differences were observed between manual acupuncture and fire needling, manual acupuncture and pricking and cupping, medicated thread moxibustion and fire needling, and pricking and cupping and fire needling. No significant differences were observed between EA and antiepileptics in reducing PSQI , which demonstrated no evidence of inconsistency. A convergence diagnosis plot was used to test the convergence of the model. The results showed that the shrink factor’s median and 97.5% value tended to be 1 and stabilized after 50,000 iterations, with continued stability of the curve fitting and merging, indicating that the convergence of the model was excellent  Acupuncture modulates the interaction between nociceptive receptors and the inflammatory immune response, inhibiting the release of inflammatory cytokines, lipids, prostaglandin E2, 5-hydroxytryptamine, histamine, and nerve growth factor by immune cells, inhibiting peripheral receptor nociceptor sensitization and transient receptor potential cation channel subfamily V member 1 phosphorylation, alleviating peripheral sensitization resulting in pain relief . (2) SodWe analyzed 16 RCTs that reported AEs—summarized into five aspects: local pain from acupuncture, subcutaneous hematoma, nausea and diarrhea, vertigo and drowsiness, and other symptoms. Vertigo and drowsiness, subcutaneous hematoma, and local pain from acupuncture were the most common AEs. Antiepileptics- (including combined acupuncture treatments) mainly relate to vertigo and drowsiness, and acupuncture-related techniques mainly caused subcutaneous hematoma and local pain. Therefore, we do not recommend antiepileptics for patients with PHN comorbid with neurological diseases or older people, although combined therapy is better than acupuncture alone for pain relief. Patients with renal deficiency should also avoid antiepileptics due to drug contraindications. Patients should be informed of the possibility of mild pain and subcutaneous hematoma before acupuncture-related treatment; if they are intolerant, acupuncture should also be avoided. Concisely, acupuncture is relatively safe compared to antiepileptics because acupuncture pain is mild and transient.In conclusion, for the sole purpose of relieving pain, the clinician should choose pricking and cupping plus antiepileptics, while PHN patients with negative emotions and insomnia should use electroacupuncture plus antiepileptics. Nevertheless, these two treatments both had the most AEs, combining the side effects of both antiepileptic and acupuncture treatments. This presents a thought-provoking approach to personalized precision therapy. In future clinical research, patients should be divided according to degrees of pain; for example, combined treatment is recommended for severe and moderate pain, and acupuncture alone is recommended for mild pain. This indicates the future direction of combined acupuncture and Western medicine treatments for PHN and may inspire other combined acupuncture and Western medicine treatment programs. However, this is currently only a hypothesis that requires further testing.P-values of the inconsistent node-splitting analysis were all greater than 0.05, and all curves of the diagnostic convergence graph approach 1.First, this review was strictly conducted using PRISMA and PRISMA-NMA guidelines. Second, to ensure adequate retrieval, we searched eight Chinese and English electronic databases and searched two clinical trial registration platforms, previous meta-analyses, gray literature, and reference lists of selected studies. Third, because RCTs are the gold standard for clinical trials, we excluded unqualified RCTs or non-RCTs, which might have affected our outcomes. Fourth, we tried to divide Western drugs by category to improve the quality of evidence comparison, although only one drug met the criteria. Fifth, we used Bayesian multiple-treatment NMA to acquire more accurate estimates than the frequentist framework method. Finally, the network results of our study are reliable because the First, high-quality RCTs were rare, and the sample sizes in most studies were small; therefore, this finding’s power is limited. Second, we used two diagnostic criteria, which increased heterogeneity, affecting the power of evidence. Third, the long-term efficacy of the interventions involved in this study has not been verified. Fourth, all included studies were performed in China; thus, language bias is possible. Fifth, there is no evidence to guide the choice of optimal acupoints, treatment frequency, or duration in this study. Finally, the study lacked clinical response rate and quality-of-life indicators.in vitro experiments to detect changes in related metabolites and signal pathway molecules at all levels in patients with PHN before and after acupuncture, further clarifying the mechanism of action and exploring the potential value of acupuncture therapy for PHN. Third, subsequent studies should unify the diagnostic criteria of PHN and modify the expert consensus to facilitate the comparison, and improve the quality, of evidence. Fourth, existing studies lack quality-of-life outcomes and unified evaluation criteria for the clinical response rates. Follow-up studies should adopt unified clinical efficacy evaluation criteria and gradually establish a set of homogeneous outcome indicators directly related to patient interests. Fifth, long-term follow-up and acupuncture placebo groups should be in future studies to clarify thelong-term efficacy and placebo effect of acupuncture. Sixth, there are no comparative studies on the long-term efficacy of different acupuncture techniques for chronic pain; therefore a relevant NMA should be conducted to find the best acupuncture-related technique. Seventh, given the mixed nature and complexity of acupuncture techniques and antiepileptics for PHN, further research should focus on classifying the degree of pain in patients with PHN into discrete subtypes, ultimately providing the basis for more personalized clinical treatment schemes. Eighth, the clinical treatment of acupuncture and moxibustion should adopt unified and standardized techniques, such as the same basic points, acupuncture depth, acupuncture frequency, and treatment course. This is not contradictory to individualized treatment, although it is more convenient for evidence comparisons, thus reducing the heterogeneity of acupuncture clinical research and improving the quality of evidence. Finally, most Chinese studies on acupuncture do not share original research data. Data sharing and transparency in clinical studies should be supported to facilitate data mining and reusing clinical data for acupuncture therapy.In the future, basic studies should explore the potential mechanism of acupuncture, fully utilizing modern neurobiological technology to explore the complex network mechanism of acupuncture treatment for PHN. Second, basic research should focus on more than just animal models, as research on human biochemical indicators is lacking. Multiomics technology can conduct Coincidentally, one study on a similar topic  was publIn addition, we compared the protocol of Based on the evidence from our analysis, acupuncture-related therapies may be potential treatment options for PHN and are relatively safe with only mild side effects. Pricking and cupping plus antiepileptics is the most effective acupuncture-related technique for PHN pain reduction, followed by EA plus antiepileptics. Moreover, EA plus antiepileptics is the best acupuncture-related technique for improving PHN-related insomnia and depression symptoms. Nevertheless, owing to the limitations of this study, these conclusions should be cautiously interpreted, and future high-quality studies are needed.The original contributions presented in this study are included in this article/YC: conception and design and drafting and writing. XYZ, QL, DW, and JZ: retrieval and screening of studies and extraction of data. XXZ and QH: evaluation of the methodological quality of included studies. RY, SX, and DZ: statistical analysis. XM and SZ: revision of chart. HY and ZS: review and revision. All authors contributed to the article and approved the submitted version.


Aboagye were incorrectly given as ‘Institute of Cancer Research NIHR Biomedical Research Centre, London, UK’ but should have been ‘Cancer Imaging Centre, Department of Surgery & Cancer, Imperial College London, London, UK’. The original article has been corrected.”


In the manuscript titled “Could serum total cortisol level at admission predict mortality due to coronavirus disease 2019 in the intensive care unit? A prospective study”, DOI number 10.1590/1516-3180.2020.0722.R1.2302021, published in the Sao Paulo Medical Journal, volume 139, issue number 4, pages 398-404, on page 399:Where it read:“The study protocol was approved by the Clinical Research Ethics Committee of the Health Sciences University Gazi Yaşargil Training and Research Hospital  .”It should read:“The study protocol was approved by the Clinical Research Ethics Committee of the Health Sciences University Gazi Yaşargil Training and Research Hospital  .”


GBD 2019 HIV Collaborators. Global, regional, and national sex-specific burden and control of the HIV epidemic, 1990–2019, for 204 countries and territories: the Global Burden of Diseases Study 2019. Lancet HIV 8: e633–512021; —In this Article, the original figure 2, titled “Male-to-female sex ratios for 204 countries and territories in 2019” is in fact figure 3, and the original figure 3, titled “Change in HIV burden by GBD super-region for both sexes combined, by decade, from 1990 to 2019” is in fact figure 2. These corrections have been made to the online version as of Feb 21, 2022.


In the published article, there was an error in affiliation number 2. Instead of “Department of Medical and Surgical Sciences, Istituti di Ricovero e Cura a Carattere Scientifico (IRCCS) Azienda Ospedaliero-Universitaria di Bologna, Bologna, Italy”, it should be removed.In the published article, there was an error in affiliation number 3. Instead of “Pediatric Surgery Department, Istituti di Ricovero e Cura a Carattere Scientifico (IRCCS) Azienda Ospedaliero-Universitaria di Bologna, Istituti di Ricovero e Cura a Carattere Scientifico (IRCCS), Bologna, Italy”, it should be “Pediatric Surgery Department, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Bologna, Italy”.In the published article, there was an error in affiliation number 4. Instead of “Division of Gynaecology and Human Reproduction Physiopathology, Istituti di Ricovero e Cura a Carattere Scientifico (IRCCS) Azienda Ospedaliero-Universitaria di Bologna, Istituti di Ricovero e Cura a Carattere Scientifico (IRCCS), Bologna, Italy”, it should be affiliation number 2 and changed as following “Division of Gynaecology and Human Reproduction Physiopathology, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Bologna, Italy”.In the published article, there was an error in affiliation number 5. Instead of “Department of Medical and Surgical Sciences, Division of Gynaecology and Human Reproduction Physiopathology, Istituti di Ricovero e Cura a Carattere Scientifico (IRCCS) Azienda Ospedaliero-Universitaria di Bologna, University of Bologna, Bologna, Italy”, it should be removed.The authors apologize for these error sand state that they do not change the scientific conclusions of the article in any way. The original article has been updated.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.