[Clinical study on the factors associated with long-term cognitive function in patients with sepsis].
Notice bibliographique
Résumé
OBJECTIVE: To investigate the occurrence and influencing factors of long-term cognitive impairment in patients with sepsis. METHODS: The septic patients admitted to intensive care unit (ICU) of Tianjin Third Central Hospital from July 2014 to September 2017 were enrolled. Montreal cognitive assessment scale (MoCA) was used to assess the cognitive function of patients at 3, 12 and 24 months after discharge from hospital. The patients were divided into cognitive impairment group (MoCA score < 26) and normal cognitive function group (MoCA score ≥ 26) according to the MoCA scores at 12 months after discharge from hospital. The basic characteristics and clinical data were recorded in both groups, the variables with statistical significance in univariate analysis were enrolled in bivariate Logistic regression analysis, and the influencing factors of cognitive impairment in patients with sepsis were screened. RESULTS: During the study period, 1 748 patients with sepsis were admitted, 210 survived and discharged, and 125 patients participated in the follow-up. Cognitive impairment occurred in 61.6% (77/125), 54.4% (56/103) and 54.2% (39/72) of the septic patients at 3, 12 and 24 months after discharge, respectively. The MoCA score of 103 patients who completed 12-month follow-up was significantly higher than that of 3-month follow-up (23.4±5.7 vs. 23.0±6.0, P < 0.01); the MoCA score of 72 patients who completed 24-month follow-up was only slightly lower than that of 12-month follow-up (23.6±5.4 vs. 23.7±5.0, P > 0.05). Following up for 12 months, 47 patients were enrolled in the normal cognitive function group and 56 in the cognitive impairment group. Compared with the normal cognitive function group, the cognitive dysfunction group had more female [51.8% (29/56) vs. 31.9% (15/47)] and older patients (years old: 66.1±15.9 vs. 52.4±18.9), also had shorter time to receive education (years: 7.6±4.0 vs. 11.2±3.1), longer duration of delirium [days: 2 (0, 3) vs. 0 (0, 1)], with significant differences (all P < 0.05). There was no significant difference in the marital status, severity of infection, underlying diseases, routes of transfer, total length of hospital stay, the length of ICU stay, acute physiology and chronic health evaluation II (APACHE II) score, sequential organ failure assessment (SOFA) score, Charlson comorbidity index (CCI) score within 24 hours of admission to ICU, hypoxemia, hypotension, mechanical ventilation, hemofiltration, or drug use between the two groups. Bivariate Logistic regression analysis showed that the duration of education was a protective factor for cognitive impairment in patients with sepsis who were followed up for 12 months [odds ratio (OR) = 0.791, 95% confidence interval (95%CI) = 0.678-0.923, P = 0.003], and age and duration of delirium were risk factors (age: OR = 1.038, 95%CI = 1.009-1.068, P = 0.010; duration of delirium: OR = 1.314, 95%CI = 1.002-1.724, P = 0.048). CONCLUSIONS: Long-term cognitive impairment occurs in many septic patients after discharge and improves over time. Duration of education is a protective factor for cognitive impairment in patients with sepsis, while age and delirium duration are risk factors.
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 | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 ».