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. 2022 Jun 17:14:834273.
doi: 10.3389/fnagi.2022.834273. eCollection 2022.

Combined Functional Assessment for Predicting Clinical Outcomes in Stroke Patients After Post-acute Care: A Retrospective Multi-Center Cohort in Central Taiwan

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Combined Functional Assessment for Predicting Clinical Outcomes in Stroke Patients After Post-acute Care: A Retrospective Multi-Center Cohort in Central Taiwan

Shuo-Chun Weng et al. Front Aging Neurosci. .

Abstract

Background and objective: In 2014, Taiwan's National Health Insurance administration launched a post-acute care (PAC) program for patients to improve their functions after acute stroke. The present study was aimed to determine PAC assessment parameters, either alone or in combination, for predicting clinical outcomes.

Methods: We retrospectively enrolled stroke adult patients through one PAC network in central Taiwan between January 2014 and December 2020. We collected data on post-stroke patients' functional ability at baseline and after PAC stay. The comprehensive assessment included the following: Modified Rankin Scale (MRS), Functional Oral Intake Scale (FOIS), Mini-Nutritional Assessment (MNA), Berg Balance Scale (BBS), Fugl-Meyer Assessment (FMA), Mini-Mental State Examination (MMSE), aphasia test, and quality of life. The above items were assessed first at baseline and again at discharge from PAC. Logistic regression was used to determine factors that were associated with PAC length of stay (LOS), 14-day hospital readmission, and 1-year mortality.

Results: A total of 267 adults (mean age 67.2 ± 14.7 years) with completed data were analyzed. MRS, activities of daily living (ADLs), instrumental activities of daily living (IADLs), BBS, and MMSE all had improved between disease onset and PAC discharge. Higher baseline and greater improvement of physical and cognitive functions between initial and final PAC assessments were significantly associated with less readmission, and lower mortality. Furthermore, the improved ADLs, FOIS, MNA, FMA-motor, and MMSE scores were related to LOS during PAC. Using logistic regression, we found that functional improvements ≥5 items [adjusted odds ratio (aOR) = 0.16; 95% confidence interval (CI) = 0.05-0.45] and improved MMSE (aOR = 0.19; 95% CI = 0.05-0.68) were significantly associated with reduced post-PAC mortality or readmission. Whereas, functional improvements ≥7 items, improved FOIS, and MNA significantly prolonged LOS during PAC.

Conclusion: Physical performance parameters of patients with acute stroke improved after PAC. PAC assessment with multiple parameters better predicted clinical outcomes. These parameters could provide information on rehabilitation therapy for acute stroke patients receiving PAC.

Keywords: Berg Balance Scale; Fugl-Meyer Assessment; Functional Oral Intake Scale; mortality; post-acute care; readmission.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

FIGURE 1
FIGURE 1
A simple schematic diagram illustrating the assessment and measurement protocol executed in the general hospital, followed by post-acute care units. PAC, post-acute care. Some images are edited by Freepik free website and software, https://www.freepik.com/home.
FIGURE 2
FIGURE 2
Flowchart of patient selection. MRS, Modified Rankin Scale; ADLs, activities of daily living; IADLs, instrumental activities of daily living; FOIS, Functional Oral Intake Scale; MNA, Mini-Nutritional Assessment; BBS, Berg Balance Scale; FMA, Fugl-Meyer Assessment; MMSE, Mini-Mental State Examination; CCAT, Concise Chinese Aphasia Test; EQ-5D-3L, 3-level 5-dimensional European Quality of Life questionnaire; PAC, post-acute care.
FIGURE 3
FIGURE 3
Outcome prediction assessed by numbers of improved functionality items in the area under the ROC curve (AUC) analysis. (A) For primary outcome (1-year mortality or 14-day readmission). (B) For secondary outcome (length of hospital stay >42 days). ROC, receiver operating characteristic curve; AUC, area under curve; PAC, post-acute care; CI, confidence interval; PPV, positive predictive value; NPV, negative predictive value. **p < 0.01.

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