Mortality from adverse drug reaction-related hospitalizations in south-west Ethiopia: A cross-sectional study.

WHAT IS KNOWN AND OBJECTIVE: Adverse drug reactions (ADRs) are an important cause of mortality during medical care. To our knowledge, no Ethiopian studies have reported on mortality due to ADRs in patients presenting to hospital from the community setting. The aim of this study was to determine the mortality rate attributable to ADRs in patients presenting to hospital, identify drugs implicated in the ADR-related deaths and identify factors contributing to ADR-related mortality at Jimma University Specialised Hospital (JUSH), south-west Ethiopia METHODS: This cross-sectional study included 1001 patients aged ≥18 years consecutively admitted to medical wards from May 2015 to August 2016. ADR-related mortality was determined through detailed review of medical records, laboratory tests and patient interviews followed by causality assessment by the Naranjo algorithm and expert consensus. RESULTS: Of 1001 patients, 15, 1.5% (95% confidence interval [CI]: 0.80%-2.30%) died with an ADR. The primary suspected causes of death were drug-induced hepatotoxicity (7, 43.8%) followed by acute kidney injury (4, 25.0%). Isoniazid (6, 33.3%), pyrazinamide (3, 16.7%), efavirenz (2, 11.1%) and tenofovir (2, 11.1%) were commonly implicated drugs. The majority of ADRs (14, 93.8%) were preventable. Unadjusted bivariate comparisons suggested patients who died with ADRs were more likely to have pre-existing liver disease (40.0% vs 7.0%; 95% confidence interval [CI]: 8.1%-57.8%), a history of ADRs (40% vs 1.4%; 95% CI: 13.8%-63.4%), a lower mean (±SD) body mass index (BMI, 17.6 ± 2.1 vs 20.0 ± 2.9 kg/m2 ; 95% CI = 0.9-3.9), exposure to antitubercular (46.7% vs 18.9%; 95% CI: 2.3%-53.1%) and antiretroviral (40.0% vs 7.7%; 95% CI: 7.5%-57.2%) therapies, and a higher mean number of medications (7.1 ± 3.3 vs 3.8 ± 2.1; 95% CI: 2.2-4.4) and Charlson Comorbidity Index (3.9 ± 2.9 vs 1.6 ± 1.8; 95% CI: 1.4-3.2) than surviving patients without ADRs. WHAT IS NEW AND CONCLUSION: Fatal ADRs were common in patients presenting to hospital. The drugs implicated were mostly antitubercular and antiretroviral therapies, reflecting the high burden of HIV and tuberculosis in the study population. ADR-related deaths were significantly associated with poor nutritional status. The majority of ADR-related deaths were preventable, highlighting the need to develop a multidisciplinary approach to closely monitor patients who are prescribed antitubercular and antiretroviral therapies, particularly in patients with hepatic disease, a history of ADRs, who are malnourished and who are exposed to multiple medications.

Evidence-to-practice gaps in the management of community-dwelling Australian patients with ischaemic heart disease.

WHAT IS KNOWN AND OBJECTIVE: Ischaemic heart disease (IHD) is a major cause of death in developed countries. Patients with IHD are at greater risk of subsequent myocardial infarction (MI). International studies suggest that guideline recommended therapies proven to reduce this risk are underutilised. The objectives of this study were to review the use of guideline-recommended medications for the secondary prevention of IHD in Australians and identify patient characteristics influencing use of these medications. METHODS: The medication regimens of community dwelling Australians with documented IHD who received a Home Medicines Review (HMR) between January 2010 and September 2012 were extracted from a pharmacist decision support software database and retrospectively reviewed. Each patient's use of antithrombotics; angiotensin converting enzyme inhibitors (ACEIs) or angiotensin receptor blockers (ARBs); statins; and ß-blockers (BBs) or non-dihydropyridine calcium channel blockers (CCBs) was evaluated in conjunction with documented contraindications. Guideline concordance in all four categories was classified as 'Optimal Medical Therapy' (OMT). Univariate and multivariate analyses identified patient characteristics influencing OMT use. RESULTS AND DISCUSSION: Of the 5396 patient medication regimens reviewed, 24·3% demonstrated OMT. Guideline concordance was observed in 91·6%, 75·6%, 74·8%, and 42·4% of patients for antithrombotics, statins, ACEI/ARBs, and BB/CCBs, respectively. The independent predictors of not receiving OMT were age 75 years or over (adjusted odds ratio [AOR] 0·76; 95% confidence interval [CI] 0·67-0·87), asthma (AOR 0·69; 95% CI 0·57-0·84), and depression or anxiety (AOR 0·84; 95% CI 0·71-0·99). Diabetes (AOR 1·20; 95% CI 1·04-1·38), hypertension (AOR 1·56; 95% CI 1·36-1·79) and a high Charlson Comorbidity Index score (AOR 1·37; 95% CI 1·15-1·64) independently predicted receipt of OMT. WHAT IS NEW AND CONCLUSION: Only one quarter of community dwelling Australian patients with IHD receive antithrombotics, ACEI/ARBs, BB/CCBs and statins. The potential consequences of these evidence-to-practice gaps are exacerbated by Australia's increasing prevalence of IHD. Healthcare professionals must work to ensure that recommended therapies are prescribed and adhered to long-term, especially in the elderly and patients with asthma and mental health problems, to reduce IHD-related mortality and morbidity and the consequent healthcare and financial impact.

Comparison of methods for calculating serum osmolality form chemical concentrations, and the prognostic value of such calculations.

Sodium, potassium, glucose, blood urea nitrogen, and osmolality were determined for 715 hospital-patient sera. The chemical concentrations were used to calculate osmolalities according to 13 different methods taken from the literature. The goodness of the comparison between calculated and measured osmolality was quite similar for several of the better methods. The aggreement was unimproved when molal chemical concentrations were used instead of molar values. The difference between measured and calculated osmolality was unrelated to whether a patient was discharged from the hospital after a short or long period or ultimately died. The equation we found to yield the most accurately calculated osmolalities is Osmolality = 1.86 Na + (Glu/18) + - (BUN/2.8) + 9.