10 research outputs found
Anaemia, renal dysfunction and in-hospital outcomes in patients with heart failure in Botswana
Background. Anaemia and renal dysfunction are associated with an increased morbidity and mortality in heart failure (HF) patients.Objective. To estimate the frequency and impact of anaemia and renal dysfunction on in-hospital outcomes in patients with HF.Methods. A total of 193 consecutive patients with HF admitted to Princess Marina Hospital, Gaborone, Botswana, from February 2014 to February 2015, were studied. Anaemia was defined as haemoglobin <13 g/dL for men and <12 g/dL for women. Renal dysfunction was defined by an estimated glomerular filtration rate (eGFR) <60 mL/min/1.73 m2, calculated by the simplified Modification of Diet in Renal Disease formula. The in-hospital outcomes included length of hospital stay and mortality.Results. The mean (standard deviation (SD)) age was 54.2 (17.1) years and 53.9% of the patients were men. The overall median eGFR was 75.9 mL/min/1.73 m2 and renal dysfunction was detected in 60 (31.1%) patients. Renal dysfunction was associated with hypertension (p=0.01), diabetes mellitus (p=0.01) and a lower haemoglobin level (p=0.008). The mean (SD) haemoglobin was 12.0 (3.0) g/dL and 54.9% of the patients were anaemic. Microcytic, normocytic and macrocytic anaemia were found in 32.1%, 57.5% and 10.4% of patients, respectively. The mean (SD) haemoglobin level for males was significantly higher than for females (12.4 (3.3) g/dL v. 11.5 (2.5) g/dL; p=0.038). Anaemia was more common in patients with diabetes (p=0.028) and in those with increased left ventricular ejection fraction (p=0.005). Neither renal dysfunction nor anaemia was significantly associated with the length of hospital stay or in-hospital mortality.Conclusion. Anaemia and renal dysfunction are prevalent in HF patients, but neither was an independent predictor of length of stay or in-hospital mortality in this population. These findings indicate that HF data in developed countries may not apply to countries in sub-Saharan Africa, and call for more studies to be done in this region
Relationship between CD4 count and quality of life over time among HIV patients in Uganda: A cohort study
© 2015 Mwesigire et al. Background: Immunological markers (CD4 count) are used in developing countries to decide on initiation of antiretroviral therapy and monitor HIV/AIDS disease progression. HIV is an incurable chronic illness, making quality of life paramount. The direct relationship between quality of life and CD4 count is unclear. The purpose of this study is to determine the relationship between change in CD4 count and quality of life measures in a Ugandan cohort of people living with HIV. Methods: We prospectively assessed quality of life among 1274 HIV patients attending an HIV clinic within a national referral hospital over a period of 6months. Quality of life was measured using an objective measure, the Medical Outcomes Study HIV health survey summarized as Physical Health Score and Mental Health Score and a subjective measure, the Global Person Generated Index. Generalized estimating equations were used to analyze the data. The primary predictor variable was change in CD4 count, and the outcome was quality of life scores. We controlled for sociodemographic characteristics, clinical factors and behavioral factors. Twenty in-depth interviews were conducted to assess patient perception of quality of life and factors influencing quality of life. Results: Of the 1274 patients enrolled 1159 had CD4 count at baseline and six months and 586 (51%) received antiretroviral therapy. There was no association found between change in CD4 count and quality of life scores at univariate and multivariate analysis among the study participants whether on or not on antiretroviral therapy. Participants perceived quality of life as happiness and well-being, influenced by economic status, psychosocial factors, and health status. Conclusions: Clinicians and policy makers cannot rely on change in immunological markers to predict quality of life in this era of initiating antiretroviral therapy among relatively healthy patients. In addition to monitoring immunological markers, socioeconomic and psychosocial factors should be underscored in management of HIV patients
Bivariate analysis of partner’s fertility desire and decision making variables versus unintended pregnancy, Ethiopia, 2011.
<p>Bivariate analysis of partner’s fertility desire and decision making variables versus unintended pregnancy, Ethiopia, 2011.</p
Socio-demographic characteristics of pregnant study participants, Ethiopia, 2011.
<p>Socio-demographic characteristics of pregnant study participants, Ethiopia, 2011.</p
Reproductive characteristics of pregnant study participants, Ethiopia, 2011.
<p>Reproductive characteristics of pregnant study participants, Ethiopia, 2011.</p
Bivariate analysis of socio-demographic and reproductive characteristics versus unintended pregnancy, Ethiopia, 2011.
<p>Bivariate analysis of socio-demographic and reproductive characteristics versus unintended pregnancy, Ethiopia, 2011.</p
HIV hospital admissions attributable to specific opportunistic infections and factors associated with them at a Botswana Referral Hospital
Hospital admissions among people living with HIV (PLWH) in Botswana are high. Opportunistic infections (OIs) are responsible for most of these admissions. Although leading OIs causing these admissions have been identified in the region, their correlates are poorly understood. This study aimed to: 1) evaluate major OIs responsible for admissions among HIV patients at Princess Marina Hospital (PMH) in Botswana; 2) estimate the proportion and identify the most frequent admissions attributable to specific OIs; 3) characterize major correlates of admissions attributable to each specific OIs and identify populations most at risk as a base for effective policy and resource orientation. HIV infected patients were randomly selected from hospital record lists. Biomedical, sociodemographic and economic data were collected from the records and from face-to-face patient interviews and analyzed. Tuberculosis was the most important OI responsible for 234.6 per 1000 HIV admissions. Cryptococcal meningitis accounted for 162.0 per 1000 admissions. Patients with a CD4-cell count 350/µL and females. The risk of admission due to cryptococcal meningitis was also high among patients with low socioeconomic status (SES). Females were more at risk for Cryptosporidium, Bacterial pneumonia (BP), Pneumocystis Carinii Pneumonia (PCP), Herpes and candidiasis-specific admissions than male and, patients not on co-trimoxazole were more likely to be admitted than those on co-trimoxazole.Comprehensive implementation strategies to address OIs among PLWH are needed. To be effective, such strategies should address not only biomedical factors but should also focus on PLWH’s SES