Risk factors and the potential of nomogram for predicting hospital‐acquired pressure injuries
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Summary
The excellent performance of the nomogram makes it a convenient and reliable tool for the risk prediction of HAPIs.
- Type
- article
- Published
- 2020-04-07
- Cited by
- 16
- References
- 38
- Access
- Open access
- OpenAlex
- https://openalex.org/W3014240535
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:215409384
Keywords
Nomogram, Medicine, Univariate, Multivariate statistics, Receiver operating characteristic
References
- The development of a Pressure Ulcer Risk Assessment Framework and Minimum Data Set
- Pressure ulcers in the intensive care unit: the relationship between nursing workload, illness severity and pressure ulcer risk.
- Knowledge and practice of nurses towards prevention of pressure ulcer and associated factors in Gondar University Hospital, Northwest Ethiopia
- Low serum albumin level as an independent risk factor for the onset of pressure ulcers in intensive care unit patients
- Guidelines for the prevention of pressure ulcers
- How and why to do pressure ulcer risk assessment.
- What influences the impact of pressure ulcers on health-related quality of life? A qualitative patient-focused exploration of contributory factors.
- Serum albumin level is a limited nutritional marker for predicting wound healing in patients with pressure ulcer: two multicenter prospective cohort studies.
- Hospital‐Acquired Pressure Ulcers: Results from the National Medicare Patient Safety Monitoring System Study
- Decision Curve Analysis: A Novel Method for Evaluating Prediction Models
- Developing a pressure ulcer risk factor minimum data set and risk assessment framework
- Impact of Pressure Ulcers on Quality of Life in Older Patients: A Systematic Review
- Nomograms in Oncology – More than Meets the Eye
- Pressure ulcers in intensive care patients: a review of risks and prevention
- Prediction of cancer specific survival after radical nephroureterectomy for upper tract urothelial carcinoma: development of an optimized postoperative nomogram using decision curve analysis.
- Pressure UlceR Programme Of reSEarch (PURPOSE): using mixed methods (systematic reviews, prospective cohort, case study, consensus and psychometrics) to identify patient and organisational risk, develop a risk assessment tool and patient-reported outcome Quality of Life and Health Utility measures
- The incidence of pressure ulcers in surgical patients of the last 5 years: a systematic review.
- Never Say Never: A Descriptive Study of Hospital-Acquired Pressure Ulcers in a Hospital Setting
- A Predictive Model for Pressure Ulcer Outcome: The Wound Healing Index
- Successful factors to prevent pressure ulcers – an interview study
Cited by
- Establishment and verification of a nomogram prediction model of hypertension risk in Xinjiang Kazakhs
- Development and validation of a machine learning algorithm–based risk prediction model of pressure injury in the intensive care unit
- Biomarkers for the early detection of pressure injury: A systematic review and meta-analysis.
- Application of an infrared thermography‐based model to detect pressure injuries: a prospective cohort study *
- Development and validation of a nomogram for predicting the risk of pressure injury in adult patients undergoing abdominal surgery
- Risk factors and the nomogram model for intraoperatively acquired pressure injuries in children with brain tumours: A retrospective study
- Construction and external validation of a nomogram model for predicting the risk of esophageal stricture after endoscopic submucosal dissection: a multicenter case–control study
- Systematic Review for Risks of Pressure Injury and Prediction Models Using Machine Learning Algorithms
- Exploration of pressure injury risk in adult inpatients: An integrated Braden scale and rough set approach.
- Evaluation of the risk prediction model of pressure injuries in hospitalized patient: A systematic review and meta-analysis.
- A Predictive Model of Pressure Injury in Children Undergoing Living Donor Liver Transplantation Based on Machine Learning Algorithm
- A Fused Multi-Channel Prediction Model of Pressure Injury for Adult Hospitalized Patients—The “EADB” Model
- INDICADORES PREDITIVOS DA LESÃO POR PRESSÃO EM ADULTOS E IDOSOS HOSPITALIZADOS
- Patterns of Co-Occurring Pressure Injuries: A Data-Driven Study Using Real-World Clinical Records
- Risk factors for hospital-acquired pressure injury in neurosurgery inpatients: a real-world prospective cohort study
- Identifying Candidate Predictors of Hospital-Acquired Pressure Injuries among Adult, Medical-Surgical Patients Using Clinical Expert Knowledge
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