Length of Stay in In-Patient Rehabilitation after Stroke in Qatar
Author(s) -
Loganathan Venkatachalm,
Ana Bobinac Georgievski,
Wafaa Al Yazeedi,
Rajvir Singh,
Hilda Uribazo Garrido
Publication year - 2008
Publication title -
the scientific world journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.453
H-Index - 93
eISSN - 2356-6140
pISSN - 1537-744X
DOI - 10.1100/tsw.2008.81
Subject(s) - medicine , rehabilitation , stroke (engine) , multivariate analysis , functional independence measure , ischemic stroke , medical record , bayesian multivariate linear regression , physical therapy , emergency medicine , regression analysis , ischemia , mechanical engineering , machine learning , computer science , engineering
The objective of this study was to analyze the factors predicting length of stay in a stroke patient rehabilitation unit at Hamad Medical Corporation (HMC) in Qatar. The medical rehabilitation data of 100 stroke patients discharged from a 15-bed inpatient rehabilitation unit (IPRU) were collected retrospectively from medical records during the period from September 2004 to April 2007. A questionnaire was developed, and variables included in the study were age of the patient, length of stay in acute care (LOSa), length of stay in rehabilitation (LOSr), functional independence measure on admission and discharge (FIMa and FIMd), modified disability scale, and modified mobility scale. Patients were grouped by impairments defined by cause as ischemic or hemorrhagic stroke, and right or left body side deficit. A significant negative correlation was observed between LOSr and FIMa (r = -0.44, p = 0.00), and positive correlation between LOSr and LOSa (r = 0.37, p = 0.00). There was no correlation between LOSr and FIMd (r = -0.03, p = 0.76). We observed that low admission FIMa and FIMd were related to extended LOS in both acute and IPRU. Multivariate regression analysis was performed by taking age, LOSa, cause of hemorrhage or ischemia, and FIMa as independent variables, and LOSr as dependent variable. The model could explain only 26% variation for LOSr. This study supports the hypothesis of an association between LOSr, LOSa, and FIMa. Further research is needed to confirm the results of this and other similar studies.
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