METHODS: Two thousand seven hundred twenty five apparently healthy adults comprising all ages, both genders and three principal races were recruited through voluntary participation. FBC was performed on two analysers, Sysmex XE-5000 and Unicel DxH 800, in addition to blood smears and haemoglobin analysis. Serum ferritin, soluble transferrin receptor and C-reactive protein assays were performed in selected subjects. All parameters of qualified subjects were tested for normality followed by determination of reference intervals, measures of central tendency and dispersion along with point estimates for each subgroup.
RESULTS: Complete data was available in 2440 subjects of whom 56% (907 women and 469 men) were included in reference interval calculation. Compared to other populations there were significant differences for haemoglobin, red blood cell count, platelet count and haematocrit in Malaysians. There were differences between men and women, and between younger and older men; unlike in other populations, haemoglobin was similar in younger and older women. However ethnicity and smoking had little impact. 70% of anemia in premenopausal women, 24% in postmenopausal women and 20% of males is attributable to iron deficiency. There was excellent correlation between Sysmex XE-5000 and Unicel DxH 800.
CONCLUSION: Our data confirms the importance of population specific haematological parameters and supports the need for local guidelines rather than adoption of generalised reference intervals and cut-offs.
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.
METHODS: Using the national hospital admission records database, we included all stroke patients who were discharged alive between 2008 and 2015 for this secondary data analysis. The risk of readmissions was described in proportion and trends. Reasons were coded according to the International Classification of Diseases, 10th Edition. Multivariable logistic regression was performed to identify factors associated with readmissions.
RESULTS: Among 151729 patients, 11 to 13% were readmitted within 28 days post-discharge from their stroke events each year. The trend was constant for ischemic stroke but decreasing for hemorrhagic stroke. The leading causes for readmissions were recurrent stroke (32.1%), pneumonia (13.0%) and sepsis (4.8%). The risk of 28-day readmission was higher among those with stroke of hemorrhagic (adjusted odds ratio (AOR): 1.52) and subarachnoid hemorrhage (AOR: 2.56) subtypes, and length of index admission >3 days (AOR: 1.48), but lower among younger age groups of 35-64 (AORs: 0.61-0.75), p values <0.001.
CONCLUSION: The risk of 28-day readmission remained constant from 2008 to 2015, where one in eight stroke patients required readmission, mainly attributable to preventable causes. Age, ethnicity, stroke subtypes and duration of the index admission influenced the risk of readmission. Efforts should focus on minimizing potentially preventable admissions, especially among those at higher risk.
MATERIAL AND METHODS: We performed a systematic search via PubMed, MEDLINE, SCOPUS, Science Direct, Cochrane library, Emerald Insight, and Google scholar for identifying studies published on BC risk factors up to March 2021. Pooled odds ratios (OR) are calculated using fixed and random-effect models. Data were processed using Review Manager 5.4 (RevMan 5.4).
RESULTS: From a total of 73 articles, seven case-control studies met the criteria for systematic review. Meta-analysis results showed that of the known modifiable risk factors for BC, diabetes mellitus (DM) had the highest odds ratio (OR = 4.97, 95% CI 3.00- 8.25) followed by hypertension (OR = 3.21, 95% CI 1.96-5.23), obesity (BMI >30 Kg/m2) (OR = 2.90, 95% CI 2.00- 4.21), and passive smoking (OR = 1.50, 95% CI 1.12- 2.02). Controversially, breastfeeding (OR = 0.37, 95% CI 0.23- 0.61) was protective factor in BC. Of non-modifiable risk factors for BC has reached menopause had the highest odds ratio (OR = 3.74, 95% CI 2.64- 5.29), followed by family history of BC (OR = 2.63, 95% CI 1.07-6.44) and age (≥ 40 years) (OR = 2.49, 95% CI 1.43-4.34).
CONCLUSIONS: The most significant predictors of BC in Palestine were DM, hypertension, passive smokers, age (>40), reached menopause, and family history of BC. Almost all these risk factors are consistent with known risk factors for breast cancer in other parts of the world.
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