Using Evidence to Prevent Risk Associated With Perioperative Pressure Injuries

Betts, Hanna; Dale, Scott; Makic, Mary Beth Flynn

doi:10.1016/j.jopan.2021.08.010

Cited by 6 publications

(3 citation statements)

References 23 publications

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“…Sedative drug treatment also leads to a higher incidence of PI in patients with ATAAD before surgery. 10 Thus, it is of utmost importance that these patients receive appropriate PI prevention and care. 9 Clinical staff should focus on skin care for PI prevention and ensure the skin is kept dry to reduce the incidence of postoperative PI in patients with ATAAD.…”

Section: Discussionmentioning

confidence: 99%

Prediction Model for Postoperative Pressure Injury in Patients with Acute Type A Aortic Dissection

Wang,

Feng,

et al. 2024

Adv Skin Wound Care

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OBJECTIVE To establish a risk assessment model to predict postoperative National Pressure Injury Advisory Panel stage 2 or higher pressure injury (PI) risk in patients undergoing acute type A aortic dissection surgery. METHODS This retrospective assessment included consecutive patients undergoing acute type A aortic dissection surgery in the authors’ hospital from September 2017 to June 2021. The authors used LASSO (logistic least absolute shrinkage and selection operator) regression analysis to identify the most relevant variables associated with PI by running cyclic coordinate descent with 10-times cross-validation. The variables selected by LASSO regression analysis were subjected to multivariate logistic analysis. A calibration plot, receiver operating characteristic curve, and decision curve analysis were used to validate the model. RESULTS There were 469 patients in the study, including 94 (27.5%) with postoperative PI. Ten variables were selected from LASSO regression: body mass index, diabetes, Marfan syndrome, stroke, preoperative skin moisture, hemoglobin, albumin, serum creatinine, platelet, and d-dimer. Four risk factors emerged after multivariate logistic regression: Marfan syndrome, preoperative skin moisture, albumin, and serum creatinine. The area under the receiver operating characteristic curve of the model was 0.765. The calibration plot and the decision curve analysis both suggested that the model was suitable for predicting postoperative PI. CONCLUSIONS This study built an efficient predictive model that could help identify high-risk patients.

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Section: Discussionmentioning

confidence: 99%

Prediction Model for Postoperative Pressure Injury in Patients with Acute Type A Aortic Dissection

Wang,

Feng,

et al. 2024

Adv Skin Wound Care

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Section: Discussionmentioning

confidence: 99%

“…[8,26] Future research aiming to replicate our findings should consider including patient-level characteristics such as comorbidities, immobility and poor nutrition, as potential risk factors in the analysis. [27] The cross-sectional nature of the study design limits our ability to establish causality between PPU and LOS. That is, it is challenging to determine if PPU caused prolonged hospital stays or vice versa based on this type of analysis.…”

Section: Study Limitationsmentioning

confidence: 99%

Trends and racial disparity in primary pressure ulcer hospitalizations outcomes in the US from 2005 to 2014

Bazargan-Hejazi,

Ambriz,

Ullah

et al. 2023

Medicine

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In the United States (US), pressure ulcers affect ≤3 million people and costs exceed 26.8 billion US dollars in spending. To examine trends in primary pressure ulcer (PPU) hospitalization mortality, length of hospital stay (LOS), and inflation-adjusted charges (IAC) in the US from 2005 to 2014 by race/ethnicity. We secondarily examined the relationship between race/ethnicity with PPU mortality, LOS, and IAC with race/ethnicity. This cross-sectional study used Nationwide Inpatient Sample (NIS) data from 2005 to 2014. The study sample included all hospitalizations with the designated ICD-9-CM code of 707.20-25 (pressure ulcer). There was a notable decline in PPU hospitalization from 11.5% to 7.77 % between 2005 and 2014. The mean mortality decreased from 2.32% to 1.12% (P < .001), the mean LOS declined from 9.39 days (P < .001), and the mean IAC per hospitalization decreased from $30,935 to $29,432 (P < .001). Positive changes observed in mortality, LOS, and IAC trends were consistent across different racial and ethnic groups. The results of multivariable logistic and linear regression analyses revealed that Black patients (β = 0.68, 95% CI 0.36–1.01, P < .001) and patients belonging to the Other race/ethnic category (β = 0.93, 95% CI 0.18–1.69) had longer hospital stays compared to their White counterparts. Regarding IAC, Black patients (β = 2846, 95% CI 1254–4439, P < .005), Hispanic patients (β = 6527, 95% CI 4925–8130), and patients from the Other race/ethnic category (β = 3473, 95% CI 1771–5174) had higher IAC for PPU treatment compared to their White counterparts. PPU hospitalization discharges, as well as hospitalization mortality, LOS, and IAC, decreased during the study period, however, our findings revealed disparities in PPU outcomes among different racial/ethnic groups. Implications of the findings are discussed.

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Preventing Medical Device-Related Pressure Injuries

Cuaycong,

Flynn Makic

2023

Journal of PeriAnesthesia Nursing

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Using Evidence to Prevent Risk Associated With Perioperative Pressure Injuries

Cited by 6 publications

References 23 publications

Prediction Model for Postoperative Pressure Injury in Patients with Acute Type A Aortic Dissection

Prediction Model for Postoperative Pressure Injury in Patients with Acute Type A Aortic Dissection

Trends and racial disparity in primary pressure ulcer hospitalizations outcomes in the US from 2005 to 2014

Preventing Medical Device-Related Pressure Injuries

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