Abstract
BackgroundMedications are frequently used for treating schizophrenia, however, anti-psychotic drug use is known to lead to cases of pneumonia. The purpose of our study is to build a model for predicting hospital-acquired pneumonia among schizophrenic patients by adopting machine learning techniques.MethodsData related to a total of 185 schizophrenic in-patients at a Taiwanese district mental hospital diagnosed with pneumonia between 2013 ~ 2018 were gathered. Eleven predictors, including gender, age, clozapine use, drug-drug interaction, dosage, duration of medication, coughing, change of leukocyte count, change of neutrophil count, change of blood sugar level, change of body weight, were used to predict the onset of pneumonia. Seven machine learning algorithms, including classification and regression tree, decision tree, k-nearest neighbors, naïve Bayes, random forest, support vector machine, and logistic regression were utilized to build predictive models used in this study. Accuracy, area under receiver operating characteristic curve, sensitivity, specificity, and kappa were used to measure overall model performance.ResultsAmong the seven adopted machine learning algorithms, random forest and decision tree exhibited the optimal predictive accuracy versus the remaining algorithms. Further, six most important risk factors, including, dosage, clozapine use, duration of medication, change of neutrophil count, change of leukocyte count, and drug-drug interaction, were also identified.ConclusionsAlthough schizophrenic patients remain susceptible to the threat of pneumonia whenever treated with anti-psychotic drugs, our predictive model may serve as a useful support tool for physicians treating such patients.
Highlights
Medications are frequently used for treating schizophrenia, anti-psychotic drug use is known to lead to cases of pneumonia
area under receiver operating characteristic curve (AUC), sensitivity, specificity, and kappa were used to assess the performance of those seven methods
Since we adopted ten-fold cross validation for estimating model performance, the means and standard deviations of the above five metrics can be calculated for the training sample
Summary
Medications are frequently used for treating schizophrenia, anti-psychotic drug use is known to lead to cases of pneumonia. Evidence reveals that pneumonia-related deaths are more prevalent when compared with pneumonia-unrelated deaths [2]. Schizophrenic patients are reported to be more likely to die early than the general public due to preventable diseases related to cardiovascular disease, metabolic disease and infections [3]. Schizophrenia can be treated with medications and psychological support [3]; evidence [5, 6], reports that anti-psychotic medicine is effective but may lead to cases of pneumonia. Considering that people with schizophrenia are usually vulnerable and may face discrimination or violation of their basic human rights [3], the very real question of how to prevent fatal diseases such as pneumonia that often
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