Clinical predictors of one-week Mortality among red tag cardiac Patients in emergency department, Hospital universiti sains malaysia

• Main Author: Ahmad, Azma Haryaty
• Format: Thesis
• Language: English
• Published: 2012
• Subjects: R Medicine (General); RB151-214 Theories of disease. Etiology. Pathogenesis; RC666-701 Diseases of the circulatory (Cardiovascular) system
• Online Access: http://eprints.usm.my/60971/1/DR%20AZMA%20HARYATY%20BINTI%20AHMAD%20-%20e.pdf; http://eprints.usm.my/60971/

CLINICAL PREDICTORS OF ONE-WEEK MORTALITY AMONG RED TAG CARDIAC PATIENTS IN EMERGENCY DEPARTMENT, HOSPITAL UNIVERSITI SAINS MALAYSIA. Critically ill patients made up a substantial part of ED patient populations. Cardiac disease is the major part of the critically ill patients. The distribution and mortality outcome of critical cardiac cases in Malaysian ED was not studied. This study focused mainly on establishing the clinical predictors of one-week mortality in cardiac patients presented to critical zone. We hypothesize the mortality outcome within one week involving cardiac patients was more than 20% and there is a significant association between clinical parameters and one week mortality among critical cardiac cases. To determine the clinical predictors for one-week mortality in red-tag cardiac patients who presented to ED, HUSM. To obtain the distribution, ward admission, length of stay in ED and mortality of red tag cardiac patients within the study period. To determine the demographic and clinical profile of red-tag cardiac patients at ED, HUSM. To determine the clinical predictors for predicting mortality within one-week in red-tag cardiac patients within the study period. This one-year prospective study was conducted from June 2010 until May 2011 on the eligible critical or red-tag cardiac patients presented to ED, HUSM. This included all attended cardiac patients who been tagged as red or critical. Those who did not been triaged as red, not treated as cardiac cases, trauma cases, brought in dead patients and who had been transferred to other hospitals due to any reason were excluded. Physiological parameters along with demographic data were recorded. Patient’s outcome was follow up within 7 days following resuscitation in ED. The association between each clinical predictor and mortality at 7 days was analyzed using SPSS version 18.0. Total of 345 patients were eligible for analysis. Thirty-six patients (10.4%) died within 7 days. The mean (SD) age of patients was 60.77 (13.08) years. Univariable Logistic Regression analysis demonstrated a significant association between these variables (age, gender, parameters include SBP, DBP, MAP, heart rate, Oxygen saturation, blood sugar, Shock Index, chief complaint such as chest pain, dyspnoea, palpitation, background history of IHD, HPL and HPT, background history of renal disease, post PCI and CPR in ED, length of stay in ED and in ward) and 7 days mortality (p < value 0.025). The adjusted multivariate analysis showed that a person with an decrement in 1 mmHg of diastolic blood pressure had 0.94 time the odds (95% CI 0.91, 0.97,p < 0.001), an increased in 1 beat per minute of heart rate had 1.02 time the odds (95% CI 1.00, 1.03, p = 0.050) and a reduction of oxygen saturation had 0.88 time the odds to die within a week (95% CI 0.81, 0.95, p 0.001). Other predictors of dying within a week were person with past medical history of ischemic heart disease had the 0.17 times the odds (95% CI 0.05, 0.56, p = 0.003), a person who underwent CPR during ED stayed had 0.01 times the odds compared to those who did not (95% CI 0.00, 0.10, p < 0.001) and those who stayed a day longer had 0.54 times the odds compared to others (95% CI 0.40, 0.72, p <0.001). There are significant numbers of patients with cardiac diseases in red zone. The mortality rate was minimum (10.4%). Independent predictors for one week mortality were (1) reduction in DBP (2) reduction in oxygen saturation (3) increased in heart rate (4) background of ischaemic heart disease (5) history of CPR in ED and (6) longer length of stay in ward following Multiple Logistic Regression analysis adjusted for other parameters.