• Jing Cao, Hebin Xie, Zikai Yu, and Yu Zhang.
• The Affiliated Changsha Central Hospital, Hengyang Medical School, University of South China, Changsha 410004, China.
• Arch Iran Med. 2024 Jun 1; 27 (6): 334340334-340.

BackgroundThis study aimed to explore the factors associated with extended length of stay (LOSE) for patients with tuberculosis (TB) in China, and construct a nomogram to predict it. In addition, the impact of extended hospital stay on short-term readmission after discharge was assessed.MethodsA retrospective observational study was conducted at Changsha Central Hospital, from January 2018 to December 2020. Patients (≥18 years who were first admitted to hospital for TB treatment) with non-multidrug-resistant TB were selected using the World Health Organization's International Classification of Diseases, 10th Revision (ICD-10-CM), and the hospital's electronic medical record system.ResultsA multivariate logistic regression analysis was used to evaluate the associations between TB and LOSE. The relationship between length of hospital stay and readmission within 31 days after discharge was assessed using a univariate Cox proportional risk model. A total of 14259 patients were included in this study (13629 patients in the development group and 630 in the validation group). The factors associated with extended hospital stays were age, smear positivity, extrapulmonary involvement, surgery, transfer from other medical structures, smoking, chronic liver disease, and drug-induced hepatitis. There was no statistical significance in the 31-day readmission rate of TB between the LOSE and length of stay≤14 days groups (hazards ratio: 0.92, 95% CI: 0.80-1.06, P=0.229).ConclusionLOSE with TB was influenced by several patient-level factors, which were combined to construct a nomograph. The established nomograph can help hospital administrator and clinicians to identify patients with TB requiring extended hospital stays, and more efficiently plan for treatment programs and resource needs.© 2024 The Author(s). This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

20 keywords...

hide…