Literature DB >> 33644804

Predictive Validity of the Cubbin-Jackson and Braden Skin Risk Tools in Critical Care Patients: A Multisite Project.

Jill M Delawder1, Samantha L Leontie2, Ralitsa S Maduro3, Merri K Morgan4, Kathie S Zimbro5.   

Abstract

BACKGROUND: Patients in intensive care units are 5 times more likely to have skin integrity issues develop than patients in other units. Identifying the most appropriate assessment tool may be critical to preventing pressure injuries in intensive care patients.
OBJECTIVES: To validate the Cubbin-Jackson skin risk assessment in the critical care setting and to compare the predictive accuracy of the Cubbin-Jackson and Braden scales for the same patients.
METHODS: In 5 intensive care units, the Cubbin-Jackson and Braden assessments were completed by different clinicians within 61 minutes of each other for 4137 patients between October 2017 and March 2018. Bivariate correlations and the Fisher exact test were used to check for associations between the scores.
RESULTS: The Cubbin-Jackson and Braden scores were significantly and positively correlated (r = 0.80, P < .001). Both tools were significant predictors of skin changes and identified as "at risk" 100% of the patients who had a change in skin integrity occur. The specificity was 18.4% for the Cubbin-Jackson scale and 27.9% for the Braden scale, and the area under the curve was 0.75 (P < .001) for the Cubbin-Jackson scale and 0.76 (P < .001) for the Braden scale. These findings show acceptable construct validity for both scales.
CONCLUSIONS: The predictive validities of the Cubbin-Jackson and Braden scales are similar, but both are sub-optimal because of poor specificity and positive predictive value. Change in practice may not be warranted, because there are no differences between the 2 scales of practical benefit to bedside nurses. ©2021 American Association of Critical-Care Nurses.

Entities:  

Year:  2021        PMID: 33644804     DOI: 10.4037/ajcc2021669

Source DB:  PubMed          Journal:  Am J Crit Care        ISSN: 1062-3264            Impact factor:   2.228


  2 in total

1.  Explainable Artificial Intelligence for Predicting Hospital-Acquired Pressure Injuries in COVID-19-Positive Critical Care Patients.

Authors:  Jenny Alderden; Susan M Kennerly; Andrew Wilson; Jonathan Dimas; Casey McFarland; David Y Yap; Lucy Zhao; Tracey L Yap
Journal:  Comput Inform Nurs       Date:  2022-10-01       Impact factor: 2.146

2.  Pressure Injuries in Critical Care Patients in US Hospitals: Results of the International Pressure Ulcer Prevalence Survey.

Authors:  Jill Cox; Laura E Edsberg; Kimberly Koloms; Catherine A VanGilder
Journal:  J Wound Ostomy Continence Nurs       Date:  2022 Jan-Feb 01       Impact factor: 1.970

  2 in total

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