Pathogenic bacteria and treatment resistance in older cardiovascular disease patients with lung infection and risk prediction model.

cardiovascular disease drug resistance pathogenic bacteria pulmonary infection risk prediction model

Journal

Open life sciences
ISSN: 2391-5412
Titre abrégé: Open Life Sci
Pays: Poland
ID NLM: 101669614

Informations de publication

Date de publication:
2023
Historique:
received: 24 07 2023
revised: 13 09 2023
accepted: 16 09 2023
medline: 28 12 2023
pubmed: 28 12 2023
entrez: 28 12 2023
Statut: epublish

Résumé

This study analyzes the distribution of pathogenic bacteria and their antimicrobial susceptibilities in elderly patients with cardiovascular diseases to identify risk factors for pulmonary infections. A risk prediction model is established, aiming to serve as a clinical tool for early prevention and management of pulmonary infections in this vulnerable population. A total of 600 patients were categorized into infected and uninfected groups. Independent risk factors such as older age, diabetes history, hypoproteinemia, invasive procedures, high cardiac function grade, and a hospital stay of ≥10 days were identified through logistic regression. A predictive model was constructed, with a Hosmer-Lemeshow goodness of fit (

Identifiants

pubmed: 38152575
doi: 10.1515/biol-2022-0756
pii: biol-2022-0756
pmc: PMC10751996
doi:

Types de publication

Journal Article

Langues

eng

Pagination

20220756

Informations de copyright

© 2023 the author(s), published by De Gruyter.

Déclaration de conflit d'intérêts

Conflict of interest: Authors state no conflict of interest.

Auteurs

Hongbo Liu (H)

The Municipal Hospital of Qingdao Cadre Health Section, Qingdao, Shandong 266000, China.

Liyan Xie (L)

Qingdao Municipal Hospital, Health Care Clinic, Qingdao, Shandong 266000, China.

Cong Xing (C)

Health Promotion Centre, Baoji Maternal and Child Health Care Hospital, Baoji, Shaanxi 721000, China.

Classifications MeSH