Development of a nomogram for predicting nasogastric tube-associated pressure injuries in intensive care unit patients
| Autor: | Rui-Ling Nan, Li He, Xiping Shen, Hai-Xia Chen, Ju-Hong Pei, Long Ge, Xin-Man Dou, Ya-Bin Zhang, Ling Gou, Xing-Lei Wang |
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| Rok vydání: | 2020 |
| Předmět: |
Adult
Male medicine.medical_specialty genetic structures Dermatology urologic and male genital diseases Logistic regression Pathology and Forensic Medicine law.invention Body Mass Index Cohort Studies 030207 dermatology & venereal diseases 03 medical and health sciences 0302 clinical medicine law Risk Factors Odds Ratio Medicine Humans Prospective Studies Risk factor Program Development Prospective cohort study Intubation Gastrointestinal Aged Pressure Ulcer 030504 nursing business.industry Incidence (epidemiology) Area under the curve Regression analysis Nomogram Middle Aged Intensive care unit Intensive Care Units Nomograms Logistic Models ROC Curve Area Under Curve Emergency medicine Female 0305 other medical science business |
| Zdroj: | Journal of tissue viability. 30(3) |
| ISSN: | 0965-206X |
| Popis: | Here, we aimed to build a nomogram model to estimate the probability of nasogastric tube-associated pressure injuries (NTAPIs) in intensive care unit(ICU)patients. This prospective cohort study included 219ICU patients with nasogastric tube between September 2019 and January 2020.Univariate and multivariate logistic regression analyses were used to develop the nomogram model. The resulting nomogram was tested for calibration, discrimination, and clinical usefulness. Of the included patients, 58 developed NTAPIs, representing an incidence rate of 26.5%. Binary logistic regression analysis revealed that the prediction nomogram included C-reactive protein, vasopressor use, albumin level, nasogastric tube duration, and Sequential Organ Failure Assessment score. The value of these predictors was again confirmed using theLasso regression analysis. Internal validation presented a good discrimination of the nomogram, with an area under the curve value of 0.850, and good calibration (Hosmer–Lemeshow test, P = 0.177). The decision curve analysis also demonstrated preferable net benefit along with the threshold probability in the prediction nomogram. The nomogram model can accurately predict the risk factors for NTAPIs, to formulate intervention strategies as early as possible to reduce NTAPI incidence. |
| Databáze: | OpenAIRE |
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