Predicting Pressure Ulcers in Critically Ill Patients

Introduction

In the article “The challenge of predicting pressure ulcers in critically ill patients: A multicenter cohort study”, Ranzani, Simpson, Japiassú, and Noritomi (2016) focused on the risks of having pressure ulcers that are faced by patients with severe health problems. Professionals underlined that even though these preventable events are often discussed by healthcare practitioners and scientists, the validity of the Braden scale as a predictive tool appropriate for those clients who are critically ill is not adequate.

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In order to fill in the existing gap, the authors of this work conducted a quantitative research study. With its help, they hoped to validate and improve the mentioned tool so that its usefulness cannot be denied. Ranzani et al. (2016) used obtained results and knowledge to improve the scale, adding to its clinical variables. They believed this objective to be appropriate and necessary because of the extreme vulnerability of the discussed population.

Analysis

In order to reveal quantitative relationships and obtain clear results, professionals conducted a cohort study. They focused on the patients of 12 Brazilian intensive care units except for those who came with pressure ulcers or developed them in the first two days. The sample included more than 9,600 patients, and almost 160 of them had pressure ulcers. The authors assessed the scale using competing for risk analysis.

The variables added to the scale included age, “sex, diabetes mellitus, hematological malignancy, peripheral artery disease, hypotension at ICU admission, and the need for mechanical ventilation or renal replacement therapy in the first 24 hours after ICU admission” (Ranzani et al., 2016, p. 1775). Discrimination was assessed with the Concordance index. The calibration plot was used to evaluate calibration.

Even though professionals did not pay much attention to the reliability and validity of the instruments they used for assessment and measurement, some peculiarities are identified. With the help of bootstrapping the authors received an opportunity to maintain internal validation. In this way, the 95% confidence interval was received. To consider the way discrimination alters with the course of time, the authors calculated the C-index every day for a month.

Thus, they noticed changes in the time-dependent area. Dealing with calibration, they also paid attention to the cumulative incidence and actual risk. The researchers admitted that even though they tried to make their findings unbiased and concrete, they presuppose that they could have been affected by local staff compliance and case-mix differences.

The general clinical data for the research was collected from the database of Epimed Solutions that is provided by case managers and maintained by the Amil Critical Care Group. The records ensured the patient’s anonymity but identified all information required for the research. At the same time, the pressure ulcer data was obtained from the Centers for Disease Control and Prevention database. The information received from two databases was then linked on the basis of the hospital registry with the help of the software Link Plus. As a result, the opportunity to calculate the Braden scale score was obtained.

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Conclusion

Professionals maintained statistical analysis, revealing categorical variables as percentages. Fisher’s exact test, unpaired T-test, and Mann-Whitney U-test were used to distribute categorical variables. On the basis of the results, they created a clinical prediction model that was meant to improve decision-making procedures. A complete case analysis gave an opportunity to assess the performance of the final model of the Braden scale and to meet the objectives of the study, which proves that the selected methods of data analysis were appropriate to the design and purpose of research.

Reference

Ranzani, O., Simpson, E., Japiassú, A., & Noritomi, D. (2016). The challenge of predicting pressure ulcers in critically ill patients: A multicenter cohort study. Annals of the American Thoracic Society, 13(10), 1775-1783.

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StudyCorgi. (2021, February 23). Predicting Pressure Ulcers in Critically Ill Patients. Retrieved from https://studycorgi.com/predicting-pressure-ulcers-in-critically-ill-patients/

Work Cited

"Predicting Pressure Ulcers in Critically Ill Patients." StudyCorgi, 23 Feb. 2021, studycorgi.com/predicting-pressure-ulcers-in-critically-ill-patients/.

1. StudyCorgi. "Predicting Pressure Ulcers in Critically Ill Patients." February 23, 2021. https://studycorgi.com/predicting-pressure-ulcers-in-critically-ill-patients/.


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StudyCorgi. "Predicting Pressure Ulcers in Critically Ill Patients." February 23, 2021. https://studycorgi.com/predicting-pressure-ulcers-in-critically-ill-patients/.

References

StudyCorgi. 2021. "Predicting Pressure Ulcers in Critically Ill Patients." February 23, 2021. https://studycorgi.com/predicting-pressure-ulcers-in-critically-ill-patients/.

References

StudyCorgi. (2021) 'Predicting Pressure Ulcers in Critically Ill Patients'. 23 February.

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