Predictive model for early functional outcomes following acute care after traumatic brain injuries: A machine learning-based development and validation study

Zhao, Meng; Guo, Ming; Wang, Zihao; Liu, Haimin; Bai, Xue; Cui, Shengnan; Guo, Xiaopeng; Gao, Lu; Gao, Lingling; Liao, Aimin; Xing, Bing; Wang, Yi

doi:10.1016/j.injury.2023.01.004

Cited by 5 publications

(2 citation statements)

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“…Additionally, logistic regression models were also performed to find out which of the five extracted factors were the best predictors of job satisfaction. The calibration of this logistic model was evaluated using the Hosmer-Lemeshow test and the area under the curve (AUC) [29][30][31]. Discrimination of the model was deemed acceptable if the AUC was � 0.7.…”

Section: Discussionmentioning

confidence: 99%

Job satisfaction of hospital pharmacists in a representative province in Mekong Delta, Vietnam

Tran,

Vo,

Nguyen Di

et al. 2023

PLoS ONE

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Background Job satisfaction is an important factor affecting job performance and turnover of healthcare workers, especially hospital pharmacists. Nevertheless, limited studies have reported this issue in the context of Vietnam. Objectives To help maintain the quality and size of the limited hospital pharmacy workforce in Vietnam, especially in the Mekong Delta area, this study investigated the job satisfaction of hospital pharmacists, and the associated factors, in Vinh Long province, a representative province in the central Mekong Delta. Methods A cross-sectional survey was conducted, recruiting hospital pharmacists working in all 17 province/district-affiliated healthcare facilities across Vinh Long province, Vietnam, between August and September 2022. Results Among the 235 survey participants (representing a response rate of 97.1%), 189 pharmacists (80.4%) reported that they were satisfied with their job. Working conditions, leadership styles, and benefits were factors found to significantly influence job satisfaction. Pharmacists who had worked in the field for 3–5 years (OR = 3.752, 95% CI = 1.036–13.595), more than 5 years (OR = 6.361, 95% CI = 2.264–17.875), did not have additional duties besides their primary responsibilities (OR = 2.046, 95% CI = 1.005–4.163), and worked in a private healthcare facility (OR = 12.021, 95% CI = 1.470–98.316), were significantly more likely to be satisfied with their job. Conclusions Most hospital pharmacists were satisfied with their current job. To further improve job satisfaction in this population, further improvements to working conditions are necessary.

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Section: Discussionmentioning

confidence: 99%

Job satisfaction of hospital pharmacists in a representative province in Mekong Delta, Vietnam

Tran,

Vo,

Nguyen Di

et al. 2023

PLoS ONE

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“…The initial input features were sociodemographic characteristics (e.g., age, sex, marital status, employment status, education level, and body mass index), causes of trauma, preexisting diseases (e.g., diabetes, hypertension, heart failure, chronic kidney disease, liver diseases, chronic obstructive pulmonary disorder, stroke, anemia, hip fracture, Parkinson’s disease, and dementia), clinical events (e.g., ICU admission and hospital rehabilitation), and baseline assessment scores (e.g., BI score, CCI score, CFS score, RTS, ED_ISS, HOSP_ISS, and ISS). The outcome feature was functional status determined using the patients’ BI scores calculated 6 months after injury; on the basis of their BI scores, the patients were categorized into two groups: functionally independent (BI >60) and functionally dependent (BI ≤60) groups ( 16 , 25 ).…”

Section: Methodsmentioning

confidence: 99%

Prediction of posttraumatic functional recovery in middle-aged and older patients through dynamic ensemble selection modeling

Nhu

Kang

Yeh

et al. 2023

Front. Public Health

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IntroductionAge-specific risk factors may delay posttraumatic functional recovery; complex interactions exist between these factors. In this study, we investigated the prediction ability of machine learning models for posttraumatic (6 months) functional recovery in middle-aged and older patients on the basis of their preexisting health conditions.MethodsData obtained from injured patients aged ≥45 years were divided into training–validation (n = 368) and test (n = 159) data sets. The input features were the sociodemographic characteristics and baseline health conditions of the patients. The output feature was functional status 6 months after injury; this was assessed using the Barthel Index (BI). On the basis of their BI scores, the patients were categorized into functionally independent (BI >60) and functionally dependent (BI ≤60) groups. The permutation feature importance method was used for feature selection. Six algorithms were validated through cross-validation with hyperparameter optimization. The algorithms exhibiting satisfactory performance were subjected to bagging to construct stacking, voting, and dynamic ensemble selection models. The best model was evaluated on the test data set. Partial dependence (PD) and individual conditional expectation (ICE) plots were created.ResultsIn total, nineteen of twenty-seven features were selected. Logistic regression, linear discrimination analysis, and Gaussian Naive Bayes algorithms exhibited satisfactory performances and were, therefore, used to construct ensemble models. The k-Nearest Oracle Elimination model outperformed the other models when evaluated on the training–validation data set (sensitivity: 0.732, 95% CI: 0.702–0.761; specificity: 0.813, 95% CI: 0.805–0.822); it exhibited compatible performance on the test data set (sensitivity: 0.779, 95% CI: 0.559–0.950; specificity: 0.859, 95% CI: 0.799–0.912). The PD and ICE plots showed consistent patterns with practical tendencies.ConclusionPreexisting health conditions can predict long-term functional outcomes in injured middle-aged and older patients, thus predicting prognosis and facilitating clinical decision-making.

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Prediction Model for Unfavorable Outcome in Primary Decompressive Craniectomy for Isolated Moderate to Severe Traumatic Brain Injury in India: A Prospective Observational Study

Kaur,

Bidyut Panda,

Mahajan

et al. 2024

World Neurosurgery

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Predictive model for early functional outcomes following acute care after traumatic brain injuries: A machine learning-based development and validation study

Cited by 5 publications

References 36 publications

Job satisfaction of hospital pharmacists in a representative province in Mekong Delta, Vietnam

Job satisfaction of hospital pharmacists in a representative province in Mekong Delta, Vietnam

Prediction of posttraumatic functional recovery in middle-aged and older patients through dynamic ensemble selection modeling

Prediction Model for Unfavorable Outcome in Primary Decompressive Craniectomy for Isolated Moderate to Severe Traumatic Brain Injury in India: A Prospective Observational Study

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