Predictive validity of the braden scale for pressure injury risk assessment in adults: A systematic review and meta‐analysis

Huang, Can; Ma, Yanhui; Wang, Chenxia; Jiang, Mengyao; Foon, Loretta Yuet; Lv, Lin; Han, Lin

doi:10.1002/nop2.792

Cited by 73 publications

(86 citation statements)

References 77 publications

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“…The optimal cut-off value found for the Braden Scale was 11, which is lower than the generally used cut-off value used in clinical settings (18 points). 38 A higher cut-off value may overestimate the risk of pressure injury, potentially leading to the overuse of interventions, increasing healthcare costs and nursing workload, 39 and reducing the predictive accuracy related to pressure injury. 40 The optimal cut-off value for the Braden Scale for predicting the risk of pressure injuries in ICU is still controversial.The Braden Scale may not be sufficiently suitable for prediction of pressure injuries.…”

Section: Discussionmentioning

confidence: 99%

Application of an infrared thermography-based model to detect pressure injuries: a prospective cohort study

Jiang

Wang

et al. 2022

British Journal of Dermatology

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Background It is challenging to detect pressure injuries at an early stage of their development. Objectives To assess the ability of an infrared thermography (IRT)‐based model, constructed using a convolution neural network, to reliably detect pressure injuries. Methods A prospective cohort study compared validity in patients with pressure injury (n = 58) and without pressure injury (n = 205) using different methods. Each patient was followed up for 10 days. Results The optimal cut‐off values of the IRT‐based model were 0·53 for identifying tissue damage 1 day before visual detection of pressure injury and 0·88 for pressure injury detection on the day visual detection is possible. Kaplan–Meier curves and Cox proportional hazard regression model analysis showed that the risk of pressure injury increased 13‐fold 1 day before visual detection with a cut‐off value higher than 0·53 [hazard ratio (HR) 13·04, 95% confidence interval (CI) 6·32–26·91; P < 0·001]. The ability of the IRT‐based model to detect pressure injuries [area under the receiver operating characteristic curve (AUC)lag 0 days, 0·98, 95% CI 0·95–1·00] was better than that of other methods. Conclusions The IRT‐based model is a useful and reliable method for clinical dermatologists and nurses to detect pressure injuries. It can objectively and accurately detect pressure injuries 1 day before visual detection and is therefore able to guide prevention earlier than would otherwise be possible. What is already known about this topic? Detection of pressure injuries at an early stage is challenging. Infrared thermography can be used for the physiological and anatomical evaluation of subcutaneous tissue abnormalities. A convolutional neural network is increasingly used in medical imaging analysis. What does this study add? The optimal cut‐off values of the IRT‐based model were 0·53 for identifying tissue damage 1 day before visual detection of pressure injury and 0·88 for pressure injury detection on the day visual detection is possible. Infrared thermography‐based models can be used by clinical dermatologists and nurses to detect pressure injuries at an early stage objectively and accurately.

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Section: Discussionmentioning

confidence: 99%

Application of an infrared thermography-based model to detect pressure injuries: a prospective cohort study

Jiang

Wang

et al. 2022

British Journal of Dermatology

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“…The Braden Scale is a widely used tool among clinicians. This scale has been shown to be a valid predictor of the development of pressure ulcers [ 7 , 8 ], in addition to possessing a better balance between the values of sensitivity and specificity compared to other similar tools [ 9 ]. In addition, several studies have assessed the predictive value that the different subscales alone may have for the assessment of PU risk [ 10 , 11 , 12 ].…”

Section: Introductionmentioning

confidence: 99%

Pressure Ulcers Risk Assessment According to Nursing Criteria

et al. 2022

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Pressure ulcers (PU) represent a health problem with a significant impact on the morbidity and mortality of immobilized patients, and on the quality of life of affected people and their families. Risk assessment of pressure ulcers incidence must be carried out in a structured and comprehensive manner. The Braden Scale is the result of an analysis of risk factors that includes subscales that define exactly what should be interpreted in each one. The healthcare work with evidence-based practice with an objective criterion by the nursing professional is an essential addition for the application of preventive measures. Explanatory models based on the different subscales of Braden Scale purvey an estimation to level changes in the risk of suffering PU. A binary-response logistic regression model, supported by a study with an analytical, observational, longitudinal, and prospective design in the Granada-Metropolitan Primary Healthcare District (DSGM) in Andalusia (Southern Spain), with a sample of 16,215 immobilized status patients, using a Braden Scale log, is performed. A model that includes the mobility and activity scales achieves a correct classification rate of 86% (sensitivity (S) = 87.57%, specificity (SP) = 81.69%, positive predictive value (PPV) = 91.78%, and negative preventive value (NPV) = 73.78%), while if we add the skin moisture subscale to this model, the correct classification rate is 96% (S = 90.74%, SP = 88.83%, PPV = 95.00%, and NPV = 80.42%). The six subscales provide a model with a 99.5% correct classification rate (S = 99.93%, SP = 98.50%, PPV = 99.36%, and NPV = 99.83%). This analysis provides useful information to help predict this risk in this group of patients through objective nursing criteria.

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“…Risk stratification is essential in the ICU, but current risk assessment instruments, such as the widely used Braden Scale, 4 lack specificity and end up classifying most ICU patients as "high risk" and therefore hinder nurses from differentiating HAPrI risk among patients. [5][6][7][8][9] Moreover, special subgroups and conditions within the ICU population may have unique HAPrI risk profiles. For example, ICU patients with COVID-19 experience high severity of illness in the context of a unique constellation of HAPrI risk factors, including hypoxemia, altered perfusion, and care-related factors such as prone positioning.…”

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confidence: 99%

“…Still, prevention may be better served with a more precise risk stratification approach and associated preventive interventions, given that every patient does not require the same level of care, nursing resources are limited and constrained by competing priorities (consider the COVID-19 pandemic), and cost-saving measures are further impacting care delivery. Risk stratification is essential in the ICU, but current risk assessment instruments, such as the widely used Braden Scale, 4 lack specificity and end up classifying most ICU patients as “high risk” and therefore hinder nurses from differentiating HAPrI risk among patients 5–9 . Moreover, special subgroups and conditions within the ICU population may have unique HAPrI risk profiles.…”

mentioning

confidence: 99%

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

Alderden

Kennerly

Wilson

et al. 2022

CIN: Computers, Informatics, Nursing

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Hospital-acquired pressure injury risk assessment is vital for prevention, but current risk assessment instruments such as the Braden Scale lack specificity in critical-care patients. The current study shows good discrimination for predicting hospital-acquired pressure injuries in critical-care patients using machine learning algorithms combined into an ensemble SuperLearner. Explainable artificial intelligence was used to create transparent machine learning models at the global and singlepatient levels. The most important variables in the top-performing model were hemoglobin, fragile skin, and serum albumin.

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Predictive validity of the braden scale for pressure injury risk assessment in adults: A systematic review and meta‐analysis

Abstract: This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

Cited by 73 publications

References 77 publications

Application of an infrared thermography-based model to detect pressure injuries: a prospective cohort study

Application of an infrared thermography-based model to detect pressure injuries: a prospective cohort study

Pressure Ulcers Risk Assessment According to Nursing Criteria

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

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