METHODS: A cross-sectional study (n = 230) was conducted using the Pressure Management Inventory on several female dominated health professions within a large public hospital. Analysis of variance was used to show relationship between sources and outcome of pressure. Linear regressions were used to predict which sources of pressure (IV) was linked to the outcomes of occupational pressure (DV).
RESULTS: The number one source of occupational pressure is relationships at work (i.e. with supervisors), and not workload. 'Relationship' is also the key predictor of several negative outcomes of pressure at work. Analysis of variance showed significant differences in two sources of pressures, i.e. Workload (P = 0.04) and Home-work balance (P = 0.03).
CONCLUSION: This paper provides insights into the occupational pressure of women health professionals by highlighting the organisational sources of pressure and the implications for preventing occupational dysfunction secondary to stress at work.
SETTING: Five medical and cardiology wards of a tertiary care center in Malaysia.
SUBJECTS: Five hundred cardiac inpatients, who received ACEIs concomitantly with other interacting drugs.
METHOD: This was a prospective cohort study of 500 patients with cardiovascular diseases admitted to Penang Hospital between January to August 2006, who received ACEIs concomitantly with other interacting drugs. ACEI-drug interactions of clinical significance were identified using available drug information resources. Drug Interaction Probability Scale (DIPS) was used to assess the causality of association between ACEI-drug interactions and the adverse outcome (hyperkalemia).
MAIN OUTCOME MEASURE: Hyperkalemia as an adverse clinical outcome of the interaction was identified from laboratory investigations.
RESULTS: Of the 489 patients included in the analysis, 48 (9.8%) had hyperkalemia thought to be associated with ACEI-drug interactions. Univariate analysis using binary logistic regression revealed that advanced age (60 years or more), and taking more than 15 medications were independent risk factors significantly associated with hyperkalemia. However, current and previous smoking history appeared to be a protective factor. Risk factors identified as predictors of hyperkalemia secondary to ACEI-drug interactions by multi-logistic regression were: advanced age (adjusted OR 2.3, CI 1.07-5.01); renal disease (adjusted OR 4.7, CI 2.37-9.39); hepatic disease (adjusted OR 5.2, CI 1.08-25.03); taking 15-20 medications (adjusted OR 4.4, CI 2.08-9.19); and taking 21-26 medications (adjusted OR 9.0, CI 1.64-49.74).
CONCLUSION: Cardiac patients receiving ACEIs concomitantly with potentially interacting drugs are at high risk of experiencing hyperkalemia. Old age, renal disease, hepatic disease, and receiving large number of medications are factors that may significantly increase their vulnerability towards this adverse outcome; thus, frequent monitoring is advocated.