BackgroundLittle is known about the health, nutrition, and quality of life of the aging population in Nepal. Consequently, we aimed to assess the nutritional status, depression and health-related quality of life (HRQOL) of Nepali older patients and evaluate the associated factors. Furthermore, a secondary aim was to investigate the proposed mediation-moderation models between depression, nutrition, and HRQOL.MethodsA cross-sectional survey was conducted from January–April of 2017 among 289 Nepali older patients in an outpatient clinic at Nepal Medical College in Kathmandu. Nutritional status, depression and HRQOL were assessed using a mini nutritional assessment, geriatric depression scales, and the European quality of life tool, respectively. Linear regression models were used to find the factors associated with nutritional status, depression, and HRQOL. The potential mediating and moderating role of nutritional status on the relationship between depression and HRQOL was explored; likewise, for depression on the relationship between nutritional status and HRQOL.ResultsThe prevalence of malnutrition and depression was 10% and 57.4% respectively; depression-malnutrition comorbidity was 7%. After adjusting for age and gender, nutritional score (β = 2.87; BCa 95%CI = 2.12, 3.62) was positively associated and depression score (β = − 1.23; BCa 95%CI = − 1.72, − 0.72) was negatively associated with HRQOL. After controlling for covariates, nutritional status mediated 41% of the total effect of depression on HRQOL, while depression mediated 6.0% of the total effect of the nutrition on HRQOL.ConclusionsA sizeable proportion of older patients had malnutrition and depression. Given that nutritional status had a significant direct (independently) and indirect (as a mediator) effect on HRQOL, we believe that nutritional screening and optimal nutrition among the older patients can make a significant contribution to the health and well-being of Nepali older patients. Nonetheless, these findings should be replicated in prospective studies before generalization.

The risk of cardiovascular disease is higher in chronic kidney disease patients compared to the general population and its impact is higher in developing countries compared to the developed countries. With this background in mind, we aimed to evaluate the prevalence of different cardiovascular risk factors in patients on maintenance hemodialysis in a tertiary care center. Chronic kidney disease patients aged 18 years and above who were under maintenance hemodialysis in the hemodialysis unit of Nepal Medical College were included in the study. Pre-dialysis venous blood samples from the participants were collected and analyzed for serum calcium, phosphorus, total protein, albumin and hemoglobin. Calcium phosphate product was calculated. Out of 100 study participants, 52% were male and 48% were female. Age-wise distribution showed 38% of the participants were below 40 years. The mean age of the participants was 45.86 ± 14.4 years. Ninety-three percent had hypertension and 29% had diabetes mellitus. Hypocalcemia was present in 80%, hyperphosphatemia was seen among 81% and high calcium phosphate product was present in 33% of the participants. Low hemoglobin (< 10gm/dL) was found in 86%. The cardiovascular risk trend in the Nepalese chronic kidney disease population is fairly different compared to the western population. Participants were younger. Prevalence of hypertension and diabetes was high. The high prevalence of anemia might be due to unaffordability of the participants for regular erythropoietin therapy. Inadequately managed hyperphosphatemia despite the widespread use of phosphorus binders, is still a major clinical challenge in patients on hemodialysis.

Introduction: Glucose meters are gaining popularity in monitoring of blood glucose at household levels and in health care set-ups due to their portability, affordability and convenience of use over the laboratory based reference methods. Still they are not free of limitations. Operator’s technique, extreme temperatures, humidity, patients’ medication, hematocrit values can affect the reliability of glucose meter results. Hence, the accuracy of glucose meter has been the topic of concern since years. Therefore, present study aims to evaluate the analytical and clinical accuracy of glucose meter using International Organization for Standardization 15197 guideline. Methods: A community based descriptive cross-sectional study was conducted in Kapan, Kathmandu, Nepal in April 2018. Glucose levels were measured using glucose meter and reference laboratory method simultaneously among 203 adults ≥20 years, after an overnight fasting and two hours of ingestion of 75 grams glucose. Modified Bland-Altman plots were created by incorporating ISO 15197 guidelines to check the analytical accuracy and Park error grid was used to evaluate the clinical accuracy of the device. Results: Modified Bland-Altman plots showed>95% of the test results were beyond the acceptable analytical criteria of ISO 15197:2003 and 2013. Park Error Grid-Analysis showed 99% of the data within zones A and B of the consensus error grid. Conclusions: Glucose meter readings were within clinically acceptable parameters despite discrepancies on analytical merit. Possible sources of interferences must be avoided during the measurement to minimize the disparities and the values should be interpreted with caution.

Background: Diabetes mellitus is a global public health problem, with its prevalence escalating each decade. Serum uric acid is said to have a strong correlation with diabetes and might contribute to its risk. The present study aimed to compare the levels of serum uric acid in diabetic, pre-diabetic, and non-diabetic patients visiting a tertiary care center. Methods: This hospital-based cross-sectional study was conducted among 320 patients visiting medicine OPD of Universal College of Medical Sciences. Of them, 182 were diabetics, 48 were pre-diabetics, and 90 were non-diabetics. Serum uric acid, fasting blood glucose, post-prandial blood glucose, and glycated hemoglobin levels were measured. Kruskal-Wallis test, Chi-square test and Spearman’s correlation were performed for analysis. Finally, a multiple linear regression analysis was done to adjust for the confounding effects of various parameters. At a 95% confidence level, a p-value less than 0.05 was considered statistically significant. Results: Unadjusted serum uric acid levels were significantly different among non-diabetics, pre-diabetes and diabetes group. Serum uric acid levels also correlated positively but weakly with all the glycemic parameters (p < 0.001). However, after adjusting for the confounders like age, sex, diet, BMI, smoking, alcoholism, and hypertension, serum uric acid levels did not vary significantly among the study groups. There was no significant association of serum uric acid with glycemic parameters. Conclusions: Serum uric acid levels did not vary significantly among the diabetic, pre-diabetic, and non-diabetic individuals. Different modifiable and non-modifiable risk factors need to be considered in hyperuricemia in diabetic patients.