METHODS: In this retrospective multicenter study conducted from 2016-2019, enrolled patients were divided into 2 treatment groups. Group 1 patients were started on Antiviral drug (oseltamivir) alone therapy. Group 2 patients were initiated on Antiviral drug (oseltamivir) in combination with Antibiotic therapy. Using acute respiratory illness scoring, symptom severity score was assessed daily for 8 symptoms namely, fever, fatigue, headache, cough, sore throat, wheezing, muscle ache and nasal congestion. For each symptom the severity was scored from scale 0-3. Results: Overall mean ARI severity score was statistically significantly lower (p less than 0.05) on day 2 (14.65-vs-13.68), day 3 (12.95-vs-11.67) and day 4 (10.31-vs-9.12 ) for influenza-A (non-H1N1) while day 3 (12.52-vs-11.87) and day 4 (11.21-vs-10.18) for influenza-B patients for patients who were initiated on oseltamivir-antibiotic combination therapy. Fever, cough and nasal congestion showed statistically significant improvement within 4 days of initiation of combination treatment. Fatigue, sore throat and muscle ache improvement pattern was same for both treatment protocols.
CONCLUSION: Oseltamivir-antibiotic combination treatment showed early resolution of some symptoms with cumulatively reduced mean symptom severity score in severe influenza infection hospitalized patients.
MATERIAL AND METHODS: A total of 300 elderly Malay participants (age ≥ 65 years) with CKD, attending the Hospital University Sains Malaysia were included in the study. Demographic data and history were also recorded. Serum creatinine was assayed by Chemistry Analyzer Model Architect-C8000 (Jaffe method). While serum cystatin C was examined by Human cystatin C ELISA kit (Sigma-Aldrich) using Thermo Scientific Varioskan Flash ELISA reader.
RESULTS: Out of 300 study participants, 169 (56.3%) were females. Mean age of patients was 67.6 ± 6.7 years. 64 male (64.6%) and 35 female (35.4%) patients were between 70 and 79 years. When estimated by MDRD equation, the prevalence of CKD stage 3 (defined as eGFR = 30 - 59 mL/min/1.73m2) was 27.7%, while based on CKD-EPIcr, CKD-EPIcys, and CKD-EPIcr-cys equations, it was 28%, 36.3%, and 36.3%, respectively. The prevalence of CKD stage 4 (defined as eGFR = 15 - 29 mL/min/1.73m2) when estimated by MDRD was 37.6%, whereas based on CKD-EPIcr, CKD-EPIcys, and CKD-EPIcr-cys equations, it was 36.3%, 46.4%, and 46.4%, respectively. CKD stage 5 (defined as eGFR < 15 mL/min/1.73m2) when estimated by the MDRD equation was 34.7%. While based on CKD-EPIcr, CKD-EPIcys, and CKD-EPIcr-cys equations, the prevalence of CKD stage 5 was 35.7%, 17.3%, and 17.3%, respectively.
CONCLUSION: The staging of CKD is different between the creatinine- and cystatin C-based equations. Creatinine-based equations classify patients as having CKD stage 5 twice as often as cystatin C-based equations.
Methods: A multi-center cross sectional study was conducted for a month in out-patient wards of hospitals in Khobar, Dammam, Makkah, and Madinah, Saudi Arabia. Patients were randomly selected from a registered patient pools at hospitals and the item-subject ratio was kept at 1:20. The tool was assessed for factorial, construct, convergent, known group and predictive validities as well as, reliability and internal consistency of scale were also evaluated. Sensitivity, specificity, and accuracy were also evaluated. Data were analyzed using SPSS v24 and MedCalc v19.2. The study was approved by concerned ethics committees (IRB-129-25/6/1439) and (IRB-2019-05-002).
Results: A total of 282 responses were received. The values for normed fit index (NFI), comparative fit index (CFI), Tucker Lewis index (TLI) and incremental fit index (IFI) were 0.960, 0.979, 0.954 and 0.980. All values were >0.95. The value for root mean square error of approximation (RMSEA) was 0.059, i.e., <0.06. Hence, factorial validity was established. The average factor loading of the scale was 0.725, i.e., >0.7, that established convergent validity. Known group validity was established by obtaining significant p-value <0.05, for the associations based on hypotheses. Cronbach's α was 0.865, i.e., >0.7. Predictive validity was established by evaluating odds ratios (OR) of demographic factors with adherence score using logistic regression. Sensitivity was 78.16%, specificity was 76.85% and, accuracy of the tool was 77.66%, i.e., >70%.
Conclusion: The Arabic version of GMAS achieved all required statistical parameters and was validated in Saudi patients with chronic diseases.
Methods: A cross sectional study was conducted for 2 months in out-patient departments at a tertiary care hospital in Khobar, Saudi Arabia. The study collected data from patients with chronic illnesses through convenience sampling. Pearson correlation (ρ) was conducted to report concurrent validity of GMAS. A correlation coefficient value ≥ 0.5 with p-value SAR 10,000, i.e., USD 2666.2 (56.4%). The mean adherence scores obtained from MARS, ARMS and GMAS were 7.09, 19.9, and 27.4. The correlation (ρ) between GMAS and MARS scores was 0.65, and between GMAS and ARMS scores was -0.79, p
Methods: A cross-sectional study was conducted for three months, in patients with type 2 diabetes who visited three community pharmacies located in Khobar, Saudi Arabia. Patients' disease knowledge and their adherence to medications were documented using Arabic versions of the Michigan Diabetes Knowledge Test and the General Medication Adherence Scale respectively. Data were analyzed through SPSS version 23. Chi-square test was used to report association of demographics with adherence. Spearman's rank correlation was employed to report the relationship among HbA1c values, disease knowledge and adherence. Logistic regression model was utilized to report the determinants of medication adherence and their corresponding adjusted odds ratio. Study was approved by concerned ethical committee (IRB-UGS-2019-05-001).
Results: A total of 318 patients consented to participate in the study. Mean HbA1c value was 8.1%. A third of patients (N = 105, 33%) had high adherence and half of patients (N = 162, 50.9%) had disease knowledge between 51% - 75%. A significantly weak-to-moderate and positive correlation (ρ = 0.221, p < 0.01) between medication adherence and disease knowledge was reported. Patients with >50% correct answers in the diabetes knowledge test questionnaire were more likely to be adherent to their medications (AOR 4.46, p < 0.01).
Conclusion: Disease knowledge in most patients was average and half of patients had high-to-good adherence. Patients with better knowledge were 4 to 5 times more likely to have high adherence. This highlights the importance of patient education and awareness regarding medication adherence in managing diabetes.