2011Journal of Nursing Science (วารสารพยาบาลศาสตร์)Requires access

Factors Predicting Developmant of Pressure Ulcer in non-Diabetic Elderly Stroke Patients

Chophaka Suttipong, Siriorn Sinduh

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Abstract

Purpose: To determine predicting factors of pressure ulcerdevelopment in elderly stroke patients. Design: A predictive study design. Methods: The 107 elderly stroke patients from urbancommunities in 3 districts; Bangkok Noi, Thonburi andPasicharoen; were recruited for this study. Data were collected byusing the demographic questionnaire, the skin Assessment tool,and the Braden risk assessment scale for each patient. The resultswere analyzed using descriptive statistics, chi-square test, andlogistic regression analysis. Main findings: The results revealed that sensory perception(χ2 = 12.4, p = .002) mobility (χ2 = 34.5, p < .001) activity (χ2 = 33.9, p < .001) moisture (χ2 = 41.0, p < .001) friction and shearing(χ2 = 53.7, p < .001) and nutrition (χ2 = 32.3, p < .001) weresignificantly associated with pressure ulcers. Multiple LogisticRegression analysis was applied to calculate the odds ratio. Threerisk factors were statistically significant in predicting pressureulcer. There were moisture (OR = 2.2, 95%CI = 1.12 - 4.12, p <.05) friction and shearing (OR = 11.2, 95%CI = 2.61 - 47.91, p =.001) and nutrition (OR = 2.8, 95%CI = 1.36 - 5.85, p < .01).Pseudo R2 indicated that 75.2 % of the variation in pressure ulcerdevelopment was explained by the binary logistic regressionmodel. Overall, the correct prediction rate was 86%. Conclusion and recommendations: Health care providersshould develop a clinical practice guidelines for prevention andrisk factors management of pressure ulcer development, especiallymoisture, friction, shearing, and nutrition to reduce the incidencerate of pressure ulcers in elderly stroke patients.

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What this paper is about

Purpose: To determine predicting factors of pressure ulcerdevelopment in elderly stroke patients. Design: A predictive study design. Methods: The 107 elderly stroke patients from urbancommunities in 3 districts; Bangkok Noi, Thonburi andPasicharoen; were recruited for this study. Data were collected byusing the demographic questionnaire, the skin Assessment tool,and the Braden risk assessment scale for each patient. The resultswere analyzed using descriptive statistics, chi-square test, andlogistic regression analysis. Main findings: The results revealed that sensory perception(χ2 = 12.4, p = .002) mobility (χ2 = 34.5, p < .001) activity (χ2 = 33.9, p < .001) moisture (χ2 = 41.0, p < .001) friction and shearing(χ2 = 53.7, p < .001) and nutrition (χ2 = 32.3, p < .001) weresignificantly associated with pressure ulcers. Multiple LogisticRegression analysis was applied to calculate the odds ratio. Threerisk factors were statistically significant in predicting pressureulcer. There were moisture (OR = 2.2, 95%CI = 1.12 - 4.12, p <.05) friction and shearing (OR = 11.2, 95%CI = 2.61 - 47.91, p =.001) and nutrition (OR = 2.8, 95%CI = 1.36 - 5.85, p < .01).Pseudo R2 indicated that 75.2 % of the variation in pressure ulcerdevelopment was explained by the binary logistic regressionmodel. Overall, the correct prediction rate was 86%. Conclusion and recommendations: Health care providersshould develop a clinical practice guidelines for prevention andrisk factors management of pressure ulcer development, especiallymoisture, friction, shearing, and nutrition to reduce the incidencerate of pressure ulcers in elderly stroke patients.

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Available abstract

Purpose: To determine predicting factors of pressure ulcerdevelopment in elderly stroke patients. Design: A predictive study design. Methods: The 107 elderly stroke patients from urbancommunities in 3 districts; Bangkok Noi, Thonburi andPasicharoen; were recruited for this study. Data were collected byusing the demographic questionnaire, the skin Assessment tool,and the Braden risk assessment scale for each patient. The resultswere analyzed using descriptive statistics, chi-square test, andlogistic regression analysis. Main findings: The results revealed that sensory perception(χ2 = 12.4, p = .002) mobility (χ2 = 34.5, p < .001) activity (χ2 = 33.9, p < .001) moisture (χ2 = 41.0, p < .001) friction and shearing(χ2 = 53.7, p < .001) and nutrition (χ2 = 32.3, p < .001) weresignificantly associated with pressure ulcers. Multiple LogisticRegression analysis was applied to calculate the odds ratio. Threerisk factors were statistically significant in predicting pressureulcer. There were moisture (OR = 2.2, 95%CI = 1.12 - 4.12, p <.05) friction and shearing (OR = 11.2, 95%CI = 2.61 - 47.91, p =.001) and nutrition (OR = 2.8, 95%CI = 1.36 - 5.85, p < .01).Pseudo R2 indicated that 75.2 % of the variation in pressure ulcerdevelopment was explained by the binary logistic regressionmodel. Overall, the correct prediction rate was 86%. Conclusion and recommendations: Health care providersshould develop a clinical practice guidelines for prevention andrisk factors management of pressure ulcer development, especiallymoisture, friction, shearing, and nutrition to reduce the incidencerate of pressure ulcers in elderly stroke patients.

Key concepts: Medicine, Logistic regression, Internal medicine, Stroke (engine), Odds ratio, Physical therapy, Engineering, Mechanical engineering

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