Death during hospitalization in patients on chronic hemodialysis
Notice bibliographique
Résumé
Mortality from various causes is higher in patients on chronic hemodialysis (HD) than in the general population. There is evidence suggesting that some of the deaths in HD patients are preventable. To identify potentially preventable causes of death, we analyzed deaths that occurred in HD patients during hospitalization over a period of 15 years. We performed a retrospective cohort analysis of 410 patients on HD for at least 6 months between 1995 and 2009 (included), who had all their hospitalizations in the same hospital. The patients were classified into 3 groups: Those who died during hospitalization (group A, n=120), those who died away from the hospital (group B, n=135), and those who were alive at the end of the observation period (group C, n=155). Continuous variables were compared between groups by the Kruskall-Wallis statistic. Logistic regression was used to identify predictors of dying during the observation period and predictors of death in the hospital. For the whole HD group of 410 patients, only 9 (2.2%) were women. 59% of the patients had diabetes mellitus. Age at the onset of HD was 65.8 ± 11.5 years and the duration of HD was 34.4 ± 27.9 months. Group A patients had a higher annual rate and duration of hospitalization and a higher Charlson comorbidity index than either of the other 2 groups, and, in comparison with patients in group C, were older at the end of observation and had a shorter duration of HD. Cardiac disease (19.2%), vascular access complications (18.3%), peripheral vascular disease (16.7%), infections (15.8%), trauma (11.7%), central nervous system disease (7.5%), respiratory failure (4.2%), malignancy (3.3%), and gastrointestinal disease (3.3%) were the causes of the last hospitalization in group A. Compared with the patients who died during hospitalization without discontinuing HD, group A patients who discontinued HD had a longer duration of their last hospitalization (52.7 ± 77.7 vs. 14.3 ± 23.8 days, P<0.001). Discontinuation of HD occurred in 80% of the hospitalizations for respiratory failure, 75% of the hospitalizations for malignancy, 57% of the hospitalizations for trauma, and 56% of the hospitalizations for central nervous system disease. Logistic regression identified a high Charlson index, advanced age, and short duration of HD as predictors of death, and an absence of diabetes, high Charlson index, prolonged annual duration of hospitalization, and short distance of the patient's domicile from the dialysis unit as predictors of death in the hospital. A substantial number of hospitalizations leading to the death of HD patients are caused by potentially preventable conditions, including vascular access complications, peripheral vascular disease, and trauma. Implementation of measures preventing these hospitalizations is a worthwhile undertaking.
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 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| 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 ».