Association of Mean Weekly Epoetin Alfa Dose with Mortality Risk in a Retrospective Cohort Study of Medicare Hemodialysis Patients

2011 ◽  
Vol 34 (4) ◽  
pp. 298-308 ◽  
Author(s):  
Eric D. Weinhandl ◽  
David T. Gilbertson ◽  
Allan J. Collins
Keyword(s):  
Cohort Study ◽  
Mortality Risk ◽  
Retrospective Cohort Study ◽  
Retrospective Cohort ◽  
Hemodialysis Patients ◽  
Epoetin Alfa

EFFECTIVENESS OF EPOETIN ALFA IN ANEMIA OF CRITICAL ILLNESS: A RETROSPECTIVE COHORT STUDY

2004 ◽  
Vol 32 (Supplement) ◽  
pp. A164
Author(s):  
Jill Hara ◽  
Maria I Rudis ◽  
Arie Barlev ◽  
Patrick O Bonnet ◽  
Kathleen A Johnson
Keyword(s):  
Cohort Study ◽  
Critical Illness ◽  
Retrospective Cohort Study ◽  
Retrospective Cohort ◽  
Epoetin Alfa

scholarly journals Cryptococcal meningitis in a tertiary hospital in Pretoria, mortality and risk factors – A retrospective cohort study

2016 ◽  
Vol 28 (5) ◽  
pp. 480-485 ◽  
Author(s):  
J Hiesgen ◽  
C Schutte ◽  
S Olorunju ◽  
J Retief
Keyword(s):  
Risk Factors ◽  
Logistic Regression ◽  
Cohort Study ◽  
Antiretroviral Therapy ◽  
Mortality Risk ◽  
Retrospective Cohort Study ◽  
Cryptococcal Meningitis ◽  
Retrospective Cohort ◽  
Nausea And Vomiting ◽  
People Living With Hiv

Aim This retrospective cohort study analyzes the impact of possible risk factors on the survival chance of patients with cryptococcal meningitis. These factors include the patient’s socio-economic background, age, gender, presenting symptoms, comorbidities, laboratory findings and, in particular, non-adherence versus adherence to therapy. Methods Data were collected from all adult patients admitted to Kalafong Hospital with laboratory confirmed cryptococcal meningitis over a period of 24 months. We analyzed the data by the presentation of descriptive summary statistics, logistic regression was used to assess factors which showed association between outcome of measure and factor. Furthermore, multivariable logistic regression analysis using all the factors that showed significant association in the cross tabulation was applied to determine which factors had an impact on the patients’ mortality risk. Results A total of 87 patients were identified. All except one were HIV-positive, of which 55.2% were antiretroviral therapy naïve. A history of previous tuberculosis was given by 25 patients (28.7%) and 49 (56.3%) were on tuberculosis treatment at admission or started during their hospital stay. In-hospital mortality was 31%. Statistical analysis showed that antiretroviral therapy naïve patients had 9.9 (CI 95% 1.2–81.2, p < 0.0032) times greater odds of dying compared to those on antiretroviral therapy, with 17 from 48 patients (35.4%) dying compared with 1 out of 21 patients (4.8%) on treatment. Defaulters had 14.7 (CI 95% 1.6–131.6, p < 0.016) times greater odds of dying, with 9 from 18 patients dying (50%), compared to the non-defaulters. In addition, patients who presented with nausea and vomiting had a 6.3 (95% CI 1.7–23.1, p < 0.005) times greater odds of dying (18/47, 38.3%); this remained significant when adjusted for antiretroviral therapy naïve patients and defaulters. Conclusion Cryptococcal meningitis is still a common opportunistic infection in people living with HIV/AIDS resulting in hospitalization and a high mortality. Defaulting antiretroviral therapy and presentation with nausea and vomiting were associated with a significantly increased mortality risk.

scholarly journals Risk factors associated with morbidity and mortality outcomes of COVID-19 patients on the 28th day of the disease course: a retrospective cohort study in Bangladesh

2020 ◽  
Vol 148 ◽  
Author(s):  
M. Z. Islam ◽  
B. K. Riaz ◽  
A. N. M. S. Islam ◽  
F. Khanam ◽  
J. Akhter ◽  
...  
Keyword(s):  
Risk Factors ◽  
Cohort Study ◽  
Mortality Risk ◽  
Retrospective Cohort Study ◽  
Retrospective Cohort ◽  
Morbidity And Mortality ◽  
Morbidity Rate ◽  
Disease Course ◽  
Factors Associated ◽  
Morbidity Risk

Abstract Diverse risk factors intercede the outcomes of coronavirus disease 2019 (COVID-19). We conducted this retrospective cohort study with a cohort of 1016 COVID-19 patients diagnosed in May 2020 to identify the risk factors associated with morbidity and mortality outcomes. Data were collected by telephone-interview and reviewing records using a questionnaire and checklist. The study identified morbidity and mortality risk factors on the 28th day of the disease course. The majority of the patients were male (64.1%) and belonged to the age group 25–39 years (39.4%). Urban patients were higher in proportion than rural (69.3% vs. 30.7%). Major comorbidities included 35.0% diabetes mellitus (DM), 28.4% hypertension (HTN), 16.6% chronic obstructive pulmonary disease (COPD), and 7.8% coronary heart disease (CHD). The morbidity rate (not-cured) was 6.0%, and the mortality rate (non-survivor) was 2.5%. Morbidity risk factors included elderly (AOR = 2.56, 95% CI = 1.31–4.99), having comorbidity (AOR = 1.43, 95% CI = 0.83–2.47), and smokeless tobacco use (AOR = 2.17, 95% CI = 0.84–5.61). The morbidity risk was higher with COPD (RR = 2.68), chronic kidney disease (CKD) (RR = 3.33) and chronic liver disease (CLD) (RR = 3.99). Mortality risk factors included elderly (AOR = 7.56, 95% CI = 3.19–17.92), having comorbidity (AOR = 5.27, 95% CI = 1.88–14.79) and SLT use (AOR = 1.93, 95% CI = 0.50–7.46). The mortality risk was higher with COPD (RR = 7.30), DM (RR = 2.63), CHD (RR = 4.65), HTN (RR = 3.38), CKD (RR = 9.03), CLD (RR = 10.52) and malignant diseases (RR = 9.73). We must espouse programme interventions considering the morbidity and mortality risk factors to condense the aggressive outcomes of COVID-19.

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