Meta-analysis of serological biomarkers at hospital admission for the likelihood of developing delirium during hospitalization
Notice bibliographique
Résumé
Importance Identifying biomarkers that, at hospital admission, predict subsequent delirium will help to focus our clinical efforts on prevention and management. Objective The study aimed to investigate biomarkers at hospital admission that may be associated with delirium during hospitalization. Data sources A librarian at the Fraser Health Authority Health Sciences Library performed searches from 28 June 2021 to 9 July 2021, using the following sources: Medline, EMBASE, Cochrane Database of Systematic Reviews, Cochrane Central Register of Controlled Trials, Cochrane Methodology Register, and the Database of Abstracts of Reviews and Effects. Study selection The inclusion criteria were articles in English that investigated the link between serum concentration of biomarkers at hospital admission and delirium during hospitalization. Exclusion criteria were single case reports, case series, comments, editorials, letters to the editor, articles that were not relevant to the review objective, and articles concerning pediatrics. After excluding duplicates, 55 studies were included. Data extraction and synthesis This meta-analysis followed the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) protocol. Independent extraction, with the consensus of multiple reviewers, was used to determine the final studies included. The weight and heterogeneity of the manuscripts were calculated using inverse covariance with a random-effects model. Main outcome(s) and measure(s) Differences in mean serum concentration of biomarkers at hospital admission between patients who did and did not develop delirium during hospitalization. Results Our search found evidence that patients who developed delirium during hospitalization had, at hospital admission, significantly greater concentrations of certain inflammatory biomarkers and one blood–brain barrier leakage marker than patients who did not develop delirium during hospitalization (differences in the mean: cortisol: 3.36 ng/ml, p < 0.0001; CRP: 41.39 mg/L, p < 0.00001; IL-6: 24.05 pg/ml, p < 0.00001; S100β 0.07 ng/ml, p < 0.00001). These differences were independent of other confounding variables such as the patient's severity of illness. A significantly lower serum concentration, at hospital admission, of acetylcholinesterase (difference in the means −0.86 U/ml, p = 0.004) was also associated with an increased vulnerability to developing delirium during hospitalization. Conclusion and relevance Our meta-analysis supports the hypothesis that patients with hypothalamic-pituitary axis dysfunction, increased blood–brain barrier permeability, and chronic overload of the cholinergic system, at hospital admission, are more vulnerable to developing delirium during hospitalization.
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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 | 0,032 | 0,089 |
| Méta-épidémiologie (sens strict) | 0,003 | 0,002 |
| Méta-épidémiologie (sens large) | 0,020 | 0,076 |
| Bibliométrie | 0,009 | 0,008 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,005 | 0,002 |
| Science ouverte | 0,003 | 0,002 |
| Intégrité de la recherche | 0,004 | 0,003 |
| 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 ».