[Cognitive impairment after intensive care unit discharge: a Meta-analysis].
Notice bibliographique
Résumé
OBJECTIVE: To investigate the cognitive impairment after intensive care unit (ICU) discharge and provide theoretical basis for prevention and intervention. METHODS: Studies about cognitive impairment after ICU discharge were retrieved in PubMed, Embase, Cochrane Library, Web of Science, Wanfang data, CNKI and SinoMed from their foundation to December 2019. The literature screening and data extraction were performed by two researchers independently, and the quality of different types of researches was evaluated using Cochrane Handbook 5.1.0, Newcastle-Ottawa scale (NOS) and agency for healthcare research and quality criteria (AHRQ). The Meta-analysis was performed by Stata 13.0 software. Sensitivity analysis was used to determine the reliability of the combined effect values. Funnel plot and Egger test were used to analyze publication bias. The non-parametric clipping was used to evaluate the impact of publication bias on the results. RESULTS: A total of 35 studies were enrolled, including 27 prospective cohort studies, 4 retrospective cohort studies, 2 randomized controlled trial (RCT) studies, 1 case-control study, and 1 cross-sectional study. Three literatures were published in Chinese and 32 were in English, which covered 13 countries, and a total of 102 504 ICU survivors were followed up successfully. Literature quality evaluation results showed that the NOS scores of 31 cohort studies were between 6 and 9, of which the case-control study scored 9. The quality grade of 2 RCT studies were both B. According to the AHRQ criteria, 1 cross-sectional study's design was scientifically rigorous and of high quality. Thirty-five studies reported that the overall incidence of cognitive impairment after ICU discharge ranged from 2.47% to 66.07%. For the multiple follow-ups studies, the first survey data was selected for Meta-analysis, and the results showed that the pooled incidence was 38.44% [95% confidence interval (95%CI) was 29.32-47.55]. Each study was removed for sensitivity analysis and the pooled results did not change much, which indicated that the results were reliable. The sub-group analysis was performed on different evaluation methods for cognitive impairment after ICU discharge, different types of ICU patients, and different follow-up time. The results showed that the pooled incidence of studies using neuropsychological test to evaluate cognitive impairment after ICU discharge was 31.42% (95%CI was 21.82-41.02), the pooled incidence of studies using questionnaires or scales was 38.75% (95%CI was 29.54-47.96), and the difference between the two groups was statistically significant (P < 0.01). The pooled incidence of cognitive impairment after ICU discharge in general ICU patients was 43.42% (95%CI was 30.88-55.95), acute respiratory distress syndrome (ARDS) patients' pooled incidence was 34.40% (95%CI was 23.02-45.79), and the pooled incidence of elderly ICU patients was 12.93% (95%CI was 8.48-17.37), the difference among the three groups was statistically significant (P < 0.01). The incidences of cognitive impairment < 1 year, 1 to 4 years, ≥ 5 years after ICU discharge were 43.30% (95%CI was 29.47-57.13), 34.21% (95%CI was 26.70-41.72), and 20.22% (95%CI was 4.89-35.55), respectively, and the differences among the three groups were statistically significant (P < 0.01). The funnel plot showed that the distribution of all studies was asymmetric, and the Egger test result also suggested that there might be publication bias (P < 0.05). The non-parametric clipping was used to estimate the impact of publication bias on the results, and the result showed that the difference in the incidence of cognitive impairment after ICU discharge before and after non-parametric clipping was large, suggesting that publication bias might influence the stability of the research results. CONCLUSIONS: The incidence of cognitive impairment after ICU discharge is relatively high and persistent for a long time, but diagnostic criteria of cognitive impairment and follow-up time are quite different. It is necessary to develop consistent evaluation criteria and rigorous designed research in the further.
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 enseignantsNi 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.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,012 | 0,026 |
| Méta-épidémiologie (sens strict) | 0,003 | 0,001 |
| Méta-épidémiologie (sens large) | 0,014 | 0,046 |
| Bibliométrie | 0,008 | 0,006 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,003 | 0,002 |
| Science ouverte | 0,002 | 0,001 |
| Intégrité de la recherche | 0,003 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 0,000 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».