Improved nonparametric survival prediction using CoxPH, Random Survival Forest & DeepHit Neural Network.

In recent times, time-to-event data such as time to failure or death is routinely collected alongside high-throughput covariates. These high-dimensional bioinformatics data often challenge classical survival models, which are either infeasible to fit or produce low prediction accuracy due to overfitting. To address this issue, the focus has shifted towards introducing a novel approaches for feature selection and survival prediction. In this article, we propose a new hybrid feature selection approach that handles high-dimensional bioinformatics datasets for improved survival prediction. This study explores the efficacy of four distinct variable selection techniques: LASSO, RSF-vs, SCAD, and CoxBoost, in the context of non-parametric biomedical survival prediction. Leveraging these methods, we conducted comprehensive variable selection processes. Subsequently, survival analysis models-specifically CoxPH, RSF, and DeepHit NN-were employed to construct predictive models based on the selected variables. Furthermore, we introduce a novel approach wherein only variables consistently selected by a majority of the aforementioned feature selection techniques are considered. This innovative strategy, referred to as the proposed method, aims to enhance the reliability and robustness of variable selection, subsequently improving the predictive performance of the survival analysis models. To evaluate the effectiveness of the proposed method, we compare the performance of the proposed approach with the existing LASSO, RSF-vs, SCAD, and CoxBoost techniques using various performance metrics including integrated brier score (IBS), concordance index (C-Index) and integrated absolute error (IAE) for numerous high-dimensional survival datasets. The real data applications reveal that the proposed method outperforms the competing methods in terms of survival prediction accuracy.

Impact of Comorbidity on the Duration from Symptom Onset to Death in Patients with Coronavirus Disease 2019: A Retrospective Study of 104,753 Cases in Pakistan.

(1) Background: The evidence indicates that comorbidities are associated with an increase in the risk of death from coronavirus disease 2019 (COVID-19). It is unclear whether such an association is different for various combinations of chronic disease comorbidities. (2) Methods: From 16 March 2020 to 30 November 2021, 104,753 patients with confirmed COVID-19 from Khyber Pakhtunkhwa Province, Pakistan, were studied to determine the association between comorbidities and the duration from symptom onset to death in patients with COVID-19 by stratifying their comorbidity status. (3) Results: The patients with comorbidities had an 84% (OR, 0.16; 95% CI, 0.14 to 0.17) decrease in the duration from symptom onset to death, as opposed to patients without a comorbidity. Among the patients with only one comorbidity, chronic lung disease (OR, 0.06; 95% CI, 0.03 to 0.09) had a greater impact on the duration from symptom onset to death than hypertension (OR, 0.15; 95% CI, 0.13 to 0.18) or diabetes (OR, 0.15; 95% CI, 0.12 to 0.18). The patients with both hypertension and diabetes had the shortest duration (OR, 0.17; 95% CI, 0.14 to 0.20) among the patients with two comorbidities. (4) Conclusions: Comorbidity yielded significant adverse impacts on the duration from symptom onset to death in COVID-19 patients in Pakistan. The impact varied with different combinations of chronic disease comorbidities in terms of the number and type of comorbidities.

Two-Dose Vaccination Significantly Prolongs the Duration from Symptom Onset to Death: A Retrospective Study Based on 173,894 SARS-CoV-2 Cases in Khyber Pakhtunkhwa, Pakistan.

This research was carried out to quantify the duration from symptom onset to recovery/death (SOR/SOD) during the first four waves and the Alpha/Delta period of the epidemic in Khyber Pakhtunkhwa, Pakistan, and identify the associated factors. A total of 173,894 COVID-19 cases were admitted between 16 March 2020 and 30 November 2021, including 458 intensive care unit (ICU) cases. The results showed that the case fatality rate (CFR) increased with age, and females had a higher CFR. The median SOR of ICU cases was longer than that of non-ICU cases (27.6 vs. 17.0 days), while the median SOD was much shorter (6.9 vs. 8.4 days). The SOR and SOD in the Delta period were slightly shortened than the Alpha period. Age, cardiovascular diseases, chronic lung disease, diabetes, fever, breathing issues, and ICU admission were risk factors that were significantly associated with SOD (p < 0.001). A control measure, in-home quarantine, was found to be significantly associated with longer SOD (odds ratio = 9.49, p < 0.001). Infected vaccinated individuals had longer SOD than unvaccinated individuals, especially for cases that had received two vaccine doses (p < 0.001). Finally, an advice on getting full-dose vaccination is given specifically to individuals aged 20-59 years.

The frequency of various diseases among patients attending Tehsil Headquarter Hospital Khwazakela, Swat.

This hospital-based study was conducted in THQ (Tehsil Headquarter) Hospital Khwazakhela, district Swat in April 2018, to determine the incidence of various diseases among patients in general and the cases attended in the OPD (out patients department) in particular. One year of data was taken from April 2017 to March 2018, of all the patients who attended the THQ Hospital to check the frequency of individual diseases, month wise, gender wise, age wise as well as, case wise. Information on patients attending OPD with respiratory, gastro intestinal, urinary tract diseases and other communicable diseases were compiled. A total of 219,056 patients attended Civil Hospital Khwazakhela during that period, with an average of 18,254.66 patients per month. This comprised 104,349(47.63%) males and 114,707 (52.36%) females. Most patients were in the age group of 15 to 59 years which comprised a total of 109,217 (49.85%) patients. In this age group 42,713 (39.10%) were males and 66,504 (60.89%) were females. A total of 77,286 patients attended OPD having respiratory, gastro intestinal, urinary tract diseases and communicable diseases. Among these patients, about 28,115 (36.37%) had respiratory diseases, 23,045 (29.81%) had gastro intestinal diseases, 18,060 (23.36%) had urinary tract diseases and 8,066 (10.43%) had other communicable diseases. Respiratory diseases were the most common in our study. The ratio of female cases was higher than males. Most of the patients were in the age group of 15-59 years. The emerging challenges for health practitioners are to prevent respiratory diseases that pose a major healthcare burden in the region.

Risk factors of cardiovascular disease in district Swat.

OBJECTIVE: To identify different risk factors of cardiovascular disease, to examine the association of these risk factors with the disease, and to assess the incidence of the disease in the study region. METHODS: The cross-sectional study was carried out at the Cardiology Department of Saidu Teaching Hospital, Swat, Pakistan, from September2013 to February2014, and comprised patients presenting with cardiac problems. Data was collected through cardiovascular risk assessment questionnaire by arranging a scheduled interview. Cardiovascular risk assessment questionnaire included modifiable, non-modifiable and contextual risk factors. RESULTS: Among 582 individuals interviewed, 356(61.16%) were positive for cardiovascular disease, and 226(38.83%) were negative. Of the 356 positive individuals, 206(57.86%) were males and 150(42.13%) were females. There was a significant association of education, household population, marital status, blood pressure, blood sugar, age, family history, stress and sleep with cardiovascular diseases (p<0.05 each). However, gender, smoking, diet, residence and socio-economic status had no association (p>0.05 each). CONCLUSIONS: Stress and contextual risk factors played an important role in contributing to cardiovascular disease.