MétaCan
Menu
Retour à la cohorte
Enregistrement W3025282583 · doi:10.1016/s2215-0366(20)30203-0

Psychiatric and neuropsychiatric presentations associated with severe coronavirus infections: a systematic review and meta-analysis with comparison to the COVID-19 pandemic

2020· review· en· W3025282583 sur OpenAlexaboutno aff
Jonathan Rogers, Edward Chesney, Dominic Oliver, Thomas Pollak, Philip McGuire, Paolo Fusar‐Poli, Michael S. Zandi, Glyn Lewis, Anthony S. David

Notice bibliographique

RevueThe Lancet Psychiatry · 2020
Typereview
Langueen
DomaineMedicine
ThématiqueLong-Term Effects of COVID-19
Établissements canadiensnon disponible
Organismes subventionnairesKing's College LondonUCLH Biomedical Research CentreMedical Research CouncilNational Institute for Health and Care ResearchUniversity College LondonWellcome Trust
Mots-clésMeta-analysisPsycINFOMedicinePandemicMEDLINECoronavirusMiddle East respiratory syndrome coronavirusPsychiatrySystematic reviewMental healthCoronavirus disease 2019 (COVID-19)Internal medicineDiseaseInfectious disease (medical specialty)

Résumé

récupéré en direct d'OpenAlex

Background Before the COVID-19 pandemic, coronaviruses caused two noteworthy outbreaks: severe acute respiratory syndrome (SARS), starting in 2002, and Middle East respiratory syndrome (MERS), starting in 2012.We aimed to assess the psychiatric and neuropsychiatric presentations of SARS, MERS, and COVID-19.Methods In this systematic review and meta-analysis, MEDLINE, Embase, PsycINFO, and the Cumulative Index to Nursing and Allied Health Literature databases (from their inception until March 18, 2020), and medRxiv, bioRxiv, and PsyArXiv (between Jan 1, 2020, and April 10, 2020) were searched by two independent researchers for all Englishlanguage studies or preprints reporting data on the psychiatric and neuropsychiatric presentations of individuals with suspected or laboratory-confirmed coronavirus infection (SARS coronavirus, MERS coronavirus, or SARS coronavirus 2).We excluded studies limited to neurological complications without specified neuropsychiatric presentations and those investigating the indirect effects of coronavirus infections on the mental health of people who are not infected, such as those mediated through physical distancing measures such as self-isolation or quarantine.Outcomes were psychiatric signs or symptoms; symptom severity; diagnoses based on ICD-10, DSM-IV, or the Chinese Classification of Mental Disorders (third edition) or psychometric scales; quality of life; and employment.Both the systematic review and the meta-analysis stratified outcomes across illness stages (acute vs post-illness) for SARS and MERS.We used a random-effects model for the meta-analysis, and the meta-analytical effect size was prevalence for relevant outcomes, I² statistics, and assessment of study quality.Findings 1963 studies and 87 preprints were identified by the systematic search, of which 65 peer-reviewed studies and seven preprints met inclusion criteria.The number of coronavirus cases of the included studies was 3559, ranging from 1 to 997, and the mean age of participants in studies ranged from 12•2 years (SD 4•1) to 68•0 years (single case report).Studies were from China, Hong Kong, South Korea, Canada, Saudi Arabia, France, Japan, Singapore, the UK, and the USA.Follow-up time for the post-illness studies varied between 60 days and 12 years.The systematic review revealed that during the acute illness, common symptoms among patients admitted to hospital for SARS or MERS included confusion (36 [27•9%; 95% CI 20•5-36•0] of 129 patients), depressed mood (42 [32•6%; 24•7-40•9] of 129), anxiety (46 [35•7%; 27•6-44•2] of 129), impaired memory (44 [34•1%; 26•2-42•5] of 129), and insomnia (54 [41•9%; 22•5-50•5] of 129).Steroid-induced mania and psychosis were reported in 13 (0•7%) of 1744 patients with SARS in the acute stage in one study.In the post-illness stage, depressed mood (35 [10•5%; 95% CI 7•5-14•1] of 332 patients), insomnia (34 [12•1%; 8•6-16•3] of 280), anxiety (21 [12•3%; 7•7-17•7] of 171), irritability (28 [12•8%; 8•7-17•6] of 218), memory impairment (44 [18•9%; 14•1-24•2] of 233), fatigue (61 [19•3%; 15•1-23•9] of 316), and in one study traumatic memories (55 [30•4%; 23•9-37•3] of 181) and sleep disorder (14 [100•0%; 88•0-100•0] of 14) were frequently reported.The meta-analysis indicated that in the post-illness stage the point prevalence of post-traumatic stress disorder was 32•2% (95% CI 23•7-42•0; 121 of 402 cases from four studies), that of depression was 14•9% (12•1-18•2; 77 of 517 cases from five studies), and that of anxiety disorders was 14•8% (11•1-19•4; 42 of 284 cases from three studies).446 (76•9%; 95% CI 68•1-84•6) of 580 patients from six studies had returned to work at a mean follow-up time of 35•3 months (SD 40•1).When data for patients with COVID-19 were examined (including preprint data), there was evidence for delirium (confusion in 26 [65%] of 40 intensive care unit patients and agitation in 40 [69%] of 58 intensive care unit patients in one study, and altered consciousness in 17 [21%] of 82 patients who subsequently died in another study).At discharge, 15 (33%) of 45 patients with COVID-19 who were assessed had a dysexecutive syndrome in one study.At the time of writing, there were two reports of hypoxic encephalopathy and one report of encephalitis.68 (94%) of the 72 studies were of either low or medium quality.Interpretation If infection with SARS-CoV-2 follows a similar course to that with SARS-CoV or MERS-CoV, most patients should recover without experiencing mental illness.SARS-CoV-2 might cause delirium in a significant proportion of patients in the acute stage.Clinicians should be aware of the possibility of depression, anxiety, fatigue, post-traumatic stress disorder, and rarer neuropsychiatric syndromes in the longer term.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,010
score de la tête « metaresearch » (Gemma)0,030
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Méta-analyse · Signal consensuel: aucune
GenreSignal candidat: Synthèse · Signal consensuel: Synthèse
Score de désaccord entre enseignants0,015
Score d'incertitude au seuil0,051

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0100,030
Méta-épidémiologie (sens strict)0,0020,001
Méta-épidémiologie (sens large)0,0150,029
Bibliométrie0,0080,009
Études des sciences et des technologies0,0010,001
Communication savante0,0030,002
Science ouverte0,0020,002
Intégrité de la recherche0,0020,001
Charge utile insuffisante (le modèle a refusé de juger)0,0030,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,124
Tête enseignante GPT0,415
Écart entre enseignants0,292 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeMéta-analyse
Domainenon disponible
GenreSynthèse

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations2 508
Publié2020
Routes d'admission1
Résumé présentoui

Explorer davantage

Même revueThe Lancet PsychiatryMême sujetLong-Term Effects of COVID-19Travaux en français237 207