Factors affecting the length of stay of patients with traumatic spinal cord injury in Tianjin, China. (1st May 2013)

• Record Type: Journal Article
• Authors: Wu, Qiang; Ning, Guang-Zhi; Li, Yu-Lin; Feng, Hong-Yong; Feng, Shi-Qing
• Is Part Of: Journal of spinal cord medicine. Volume 36:Number 3(2013:May)
• Page Start: 237
• Page End: 242
• Publication Date: 2013-05-01
• Subjects: Spinal cord -- Wounds and injuries -- Periodicals; Spinal cord -- Diseases -- Periodicals; 616.8305
• DOI: 10.1179/2045772313Y.0000000090
• Languages: English
• ISSNs: 1079-0268

Abstract

<abstract> <title> <x xml:space="preserve">Abstract</x> </title> <p> <bold>Purpose:</bold> </p> <p>To describe the acute care length of stay (ACLOS) of adult patients with traumatic spinal cord injury (TSCI) in Tianjin, China, and identify the associated demographic and clinical factors.</p> <p> <bold>Methods:</bold> </p> <p>TSCI patients admitted to a general hospital in Tianjin, China from 2004 to 2007 were identified. The predictor variables were demographic and clinical factors, including age, gender, etiology, level of injury, severity, associated injuries, surgery, and complications. The outcome variable was ACLOS. Multivariable linear regression analysis models were used to examine the association between predictor and outcome variables.</p> <p> <bold>Results:</bold> </p> <p>This study included 631 TSCI patients. The mean ACLOS was 32.4 ± 37.7 days, with a range of 1-294 days. The median number of hospitalization days was 21 days. Admission to a suburban hospital surgery, urinary infection, poorer functional status, pressure ulcers, and associated injuries were significantly associated with ACLOS.</p> <p> <bold>Conclusion:</bold> </p> <p>This study examined the effect of epidemiological and clinical factors on ACLOS in Tianjin, China. The factors that influenced the ACLOS were different from factors reported in other studies. More studies are needed in China to determine the effect of these factors on ACLOS in TSCI patients and to propose a predictive model.</p> </abstract>