Search

Analysis through logistic regression explored to investigate the relationship between binary or multivariable ordinal response probability and in one or more explanatory variables. The main objectives of this study to investigate advanced prediction risk factor of Coronary Heart Disease (CHD) using a logit model. Attempts made to reduce risk factors, increase public or professional awareness. Logit model used to evaluate the probability of a person develop CHD, considering any factors such as age, gender, high low-density lipoprotein (LDL) cholesterol, low high-density lipoprotein (HDL) cholesterol, high blood pressure, family history of CHD younger than 45, diabetes, smoking, being post-menopausal for women and being older than 45 for men. Logit concept of brief statistics described with slight modification to estimate the parameters testing for the significance of the coefficients, confidence interval fits the simple, multiple logit models. Besides, interpretation of the fitted logit regression model introduced. Variables showing best results within the scientific context, good explanation data assessed to fit an estimated logit model containing chosen variables, this present experiment used the statistical inference procedure; chi-square distribution, likelihood ratio, Score, or Wald test and goodness-of-fit. Health promotion started with increased public or professional awareness improved for early detection of CHD, to reduce the risk of mortality, aimed to be Saudi vision by 2030.

Introduction: COVID-19 has caused approximately one million deaths worldwide as of November 24, 2020. Markers of disease activity like ferritin, C-reactive protein (CRP), and D-dimers are frequently monitored to detect the best opportunity for intensive treatment. Methods: All patients of >18 years of age were included. The primary variables of interest, ferritin, CRP, and D-dimers, for each patient throughout hospitalization were recorded. Primary clinical outcomes of length of stay in ICU and survival were recorded. Demographics: age, gender, BMI, and nationality. Ferritin, CRP, and D-dimers were recorded daily if available for the whole ICU stay, and all other variables were recorded on admission day to ICU. Results: The sample includes 235 records. More than 95% of patients have all markers on the day of admission to ICU were ferritin (median 1,278; IQR 1,424), D-dimer 1.21 (3.4), and CRP 129.5 (121). Daily average levels of markers were different from their admission day level: ferritin 1,395 (1,331), D-dimer 3.11 (5.52), and CRP 107 (75.8). Multiple logistic regression analysis determined that average CRP during the stay was the only predictor of survival. Discussion: Data on markers utilization to detect the acute phase of inflammation help clinicians focus on the opportunity window for intensive treatment. Conclusion: Average CRP during the stay in ICU is higher than CRP on admission. Average CRP is the only factor that predicts survival.

Background: This study is a quality improvement project that aimed at improving patient flow in Male Urgent Area (MUA), one of the busiest areas in the largest emergency department in the state of Qatar. Methods: The baseline process was designed by mapping and drawing a cause-and-effect diagram. Pre- and post-auditing was done after careful intervention of introducing a phlebotomy room in Male See and Treat area, the main feeder to MUA. The feeding areas to MUA and the daily flow of patients were studied in detail. Points of interest in the baseline process map were identified and targeted. Supporting data of about 398 patients helped in designing the process map and identifying the point of interest. Results: Post-intervention analysis showed a remarkable improvement in time to phlebotomy in Hamad General Hospital Emergency Department. The proportion of patients moving to MUA and receiving phlebotomy increased from 48.6% to 84.1% in the first hour. Patients' hematological laboratory workup that helps MUA's physicians in decision making was readily available. Conclusion: Patient flow and phlebotomy time can be significantly improved by introducing a dedicated phlebotomy room in a busy emergency department. It is concluded that identification and targeting of the main point of interest in baseline process mapping is crucial and of considerable importance in a quality improvement project. Keywords: Emergency department, phlebotomy time, patient flow