Predictors of mortality among hemodialysis patients in Hamadan province using random survival forests.
Hemodialysis
Kidney Failure
Random Survival Forest
Survival
Journal
Journal of preventive medicine and hygiene
ISSN: 2421-4248
Titre abrégé: J Prev Med Hyg
Pays: Italy
ID NLM: 9214440
Informations de publication
Date de publication:
Sep 2020
Sep 2020
Historique:
received:
03
11
2019
accepted:
24
06
2020
entrez:
5
11
2020
pubmed:
6
11
2020
medline:
11
11
2021
Statut:
epublish
Résumé
Hemodialysis patients are at a high risk for morbidity and mortality. This study aimed to find the predictors of mortality and survival in hemodialysis patients in Hamadan province of Iran. A number of 785 patients during the entire 10 years were enrolled into this historical cohort study. Data were gathered by a checklist of hospital records. The survival time was the time between the start of hemodialysis treatment to patient's death as the end point. Random survival forests (RSF) method was used to identify the main predictors of survival among the patients. The median survival time was 613 days. The number of 376 deaths was occurred. The three most important predictors of survival were hemoglobin, CRP and albumin. RSF method predicted survival better than the conventional Cox-proportional hazards model (out-of-bag C-index of 0.808 for RSF vs. 0.727 for Cox model). We found that positivity of CRP, low serum albumin and low serum hemoglobin were the top three most important predictors of low survival for HD patients.
Sections du résumé
BACKGROUND
BACKGROUND
Hemodialysis patients are at a high risk for morbidity and mortality. This study aimed to find the predictors of mortality and survival in hemodialysis patients in Hamadan province of Iran.
METHODS
METHODS
A number of 785 patients during the entire 10 years were enrolled into this historical cohort study. Data were gathered by a checklist of hospital records. The survival time was the time between the start of hemodialysis treatment to patient's death as the end point. Random survival forests (RSF) method was used to identify the main predictors of survival among the patients.
RESULTS
RESULTS
The median survival time was 613 days. The number of 376 deaths was occurred. The three most important predictors of survival were hemoglobin, CRP and albumin. RSF method predicted survival better than the conventional Cox-proportional hazards model (out-of-bag C-index of 0.808 for RSF vs. 0.727 for Cox model).
CONCLUSIONS
CONCLUSIONS
We found that positivity of CRP, low serum albumin and low serum hemoglobin were the top three most important predictors of low survival for HD patients.
Identifiants
pubmed: 33150237
doi: 10.15167/2421-4248/jpmh2020.61.3.1421
pmc: PMC7595073
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
E482-E488Informations de copyright
©2020 Pacini Editore SRL, Pisa, Italy.
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