Health status classification model for medical adherence system in retirement township

Medical adherence and remote patient monitoring have gained huge attention from researchers recently, especially with the need to observe the patients’ health outside hospitals due to the ongoing pandemic. The main goal of this research work is to propose a health status classification model that provides a numerical indicator of the overall health condition of a patient via four major vital signs, which are body temperature, blood pressure, blood oxygen saturation level, and heart rate. A dataset has been prepared based on the data obtained from hospital records, with these four vital signs extracted for each patient. This dataset provides a label associating each patient to the number of medical diagnoses. Generally, the number of diagnoses correlates with the patient's medical condition, with no diagnoses indicating normal condition, one to two diagnoses suggest low risk, and more than that implies high risk. Thus, we propose a method to classify a patient’s health status into three classes, which are normal, low risk and high risk. This would provide guidance for healthcare workers on the patient's medical condition. By training the classification model using the prepared dataset, the seriousness of a patient's health condition can be predicted. This prediction is performed by classifying the patients based on their four vital signs. Our tests have yielded encouraging results using precision and recall as the evaluation metrics. The key outcome of this work is a trained classification model that quantifies a patient's health condition based on four vital signs. Nevertheless, the model can be further improved by considering more input features such as medical history. The results obtained from this research can assist medical personnel by providing a secondary advice regarding the health status for the patients who are located remotely from the medical facilities.

Clinical outcomes of paliperidone long-acting injection in patients with schizophrenia: a 1-year retrospective cohort study

Background Schizophrenia is a severe psychiatric disorder. Poor medical adherence increases relapse rate. Long-acting injection of antipsychotic agent is developed for improving medical adherence. In this study, we examined the effect of paliperidone long-acting injection (PLAI) treatment in patients with schizophrenia in a real-world setting. Methods In this retrospective cohort study, 467 patients with schizophrenia were enrolled, treated with risperidone PLAI or oral antipsychotics, and followed for 1 year. Concomitant medication, namely anticonvulsants, antidepressants, anxiolytics, sedatives or hypnotics, anticholinergics, and beta-blockers, were administered. Patients were classified into 2 groups: the LAI group (patients received LAI for treatment) and the NLAI group (patients taking only oral antipsychotics). The incidence of hospitalization, the length of hospitalization, and the incidence of emergency room visits were assessed. Results The LAI group had a higher incidence of psychiatric acute ward admission (NLAI group = 4.8%; LAI = 30.3%) and emergency room visits (NLAI group = 7.3%; LAI group = 36.0%) before enrolment. During the one-year follow-up, the incidence of acute ward admission and emergency room visit did not differ in the NLAI group (P = .586 and .241) compared with before enrolment, whereas both incidences were significantly decreased in the LAI group (P < .0001 in both of them). Conclusions PLAI reduces the incidence of admission and emergency room visits.

Genetic and nongenetic factors in assessing the prognosis of patients after myocardial infarction with high medical adherence

Aim. During one-year follow-up, to assess the effect of genetic and nongenetic factors on the risk of poor outcomes in patients after myocardial infarction (MI) with high medical adherence.Material and methods. The study included 250 patients admitted to the hospital due to MI in the period from September 1, 2018 to May 1, 2019 and with a potentially high medical adherence. Twelve months after MI, patients were assessed for adherence to therapy and the effect of genetic and nongenetic factors on the patient prognosis.Results. Within 12 months after MI, 70 (28,0%) patients had a composite endpoint: all-cause death, MI, cerebral stroke, and nonelective coronary revascularization. There were following factors increasing the risk of composite endpoint: non-Q-wave MI (relative risk (RR), 2,63; 95% confidence interval (CI): 1,63-4,25 (p=0,001); left ventricular ejection fraction ≤35% — RR, 2,03; 95% CI: 1,17-3,50 (p<0,0001); CYP2C19 GA/AA genotype (RR, 1,58; 95% CI: 1,06-2,37 (p<0,00001)).Conclusion. The study results allow identifying patients with a high risk of poor outcome: patients with non-Q-wave MI, left ventricular ejection fraction ≤35%, and CYP2C19 GA/AA genotype.

Can Personality Traits be Related to Medical Adherence in Patients with Myocardial Infarction?

Background: For myocardial infarction survivors, long-term pharmacotherapy is an important element of a complex treatment and a better prognosis may be achieved through better medication adherence. Aim: The purpose of this study is to find out whether it is possible to predict medication adherence of the patients who survived myocardial infarction via assessing their personality. Design and Setting: Analytic cross-sectional study. Methods: The study was held in Hospital of Lithuanian University of Health Sciences Kaunas clinics (HLUHS KK) department of cardiology. Patients with ST-segment elevation myocardial infarction were randomly included and completed questionnaire before discharge from Cardiology unit. We recruited 198 patients with myocardial infarction who completed questionnaire (ICD-10 diagnoses I21.0, I21.1 or I21.2). Medical adherence association with personality was assessed with Morisky-Green medical adherence scale (MMAS-8) and the Big-Five inventory. Results: Medical adherence was associated with conscientiousness, agreeableness, neuroticism and extraversion. There was no significant association with openness to experiences. Neuroticism negatively affected medical adherence. It was determined, that conscientiousness, agreeableness and extraversion positively affected medical adherence. Conclusion: This study demonstrated that good medical adherence in patients with ST-segment elevation myocardial infarction was associated with higher scores in conscientiousness and agreeableness personality traits and lower scores in neuroticism.