OBJECTIVES: The study examined the prevalence of elevated thyroid stimulating hormone (TSH) and its association with dyslipidemia and non-alcoholic fatty liver disease (NAFLD) among Filipino adults undergoing executive check-up.

METHODS: Clinical characteristics such as age, vital signs, anthropometrics, FBS, lipid profile, liver function tests, TSH and hepatobiliary ultrasound were reviewed from the charts of 580 patients to determine the prevalence of elevated TSH, NAFLD, and dyslipidemia. Binary logistic regression analysis was performed to determine association between TSH levels, NAFLD, and dyslipidemia.

RESULTS: The prevalence of elevated TSH was 3.10%. Patients with increased total cholesterol was approximately 4.18 times as likely (95% CI 1.20 to 14.61%, p = 0.025) to have elevated TSH. However, after adjusting for age and sex, we had insufficient evidence to demonstrate an association between NAFLD and lipid levels with elevated TSH levels.

CONCLUSION: The prevalence of elevated TSH in this group of patients from a highly urbanized area was 3.1%. We had insufficient evidence to demonstrate an association between NAFLD, lipid levels, and elevated TSH levels after adjusting for age and sex.

Human ; Male ; Female ; Middle Aged ; Thyrotropin ; Non-alcoholic Fatty Liver Disease ; Prevalence ; Liver Function Tests ; Dyslipidemias ; Hypercholesterolemia ; Digestive System ; Cholesterol ; Lipids

Background: Although elevated glucose levels are associated with adverse outcomes in the critically ill, HbA1c-based adjusted glycemic variables have not been extensively utilized as a tool to evaluate patients in the acute critical condition. Objective: This study aims to determine whether glycemic gap can predict adverse outcomes in patients with type 2 diabetes diagnosed with COVID-19. Methodology: A single center and retrospective study of adult patients with type 2 diabetes diagnosed with COVID- 19. Glycemic gap was calculated as the difference between the admission blood glucose and A1c‐derived average glucose. Logistic regression was used to determine association of glycemic gap and several adverse clinical outcomes. A decision curve analysis was used to determine the clinical utility of a clinical decision model based on this cut-off. Results: A total of 150 diabetic patients with COVID-19 were analyzed. Median baseline HbA1c was 7.5% (range 4.79–18.42), while median admitting blood glucose was 196 (range 71–506) mg/dL. From these, computed glycemic gaps ranged from -180.5 to 312.8 mg/dL, with a median of 13.75 mg/dL. On univariate analysis, for every unit increase in glycemic gap, odds of developing ARDS increased five times (cOR 4.798, 95% CI 2.08 to 11.09); odds of developing shock increased four times (cOR 4.48, 95% CI 1.48 to 13.44). No single cut-off value for glycemic gap was able to discriminate patients with favorable outcome from those with adverse outcome. The decision curve analysis graphically shows that glycemic gap has a positive net benefit for threshold risk of 50% or higher. Conclusion Higher glycemic gaps were significantly associated with increased risk for poor outcomes in diabetic patients with COVID-19. Glycemic gap should be correlated with clinical status and other laboratory parameters to make it a more powerful discriminant among COVID-19 infected patients.
Diabetes Mellitus, Type 2 ; COVID-19

Objectives: The study aimed to identify whether pre-operative glycosylated hemoglobin level (HbA1c) and fasting blood sugar (FBS) can be used as markers for the development of acute kidney injury (AKI) in the immediate post-operative period of type 2 diabetic patients after elective abdominal surgery.

Methods: This retrospective cohort pilot study included seventy-four diabetic patients who underwent elective abdominal surgery from 2015 to 2018. HbA1c and FBS, demographic data, comorbidities, type and indication of surgery, and treatment history were correlated with the development of AKI using logistic regression analysis.

Results: In this cohort, 12% of subjects developed AKI. Univariate and multivariate logistic regression analysis, however, showed that neither HbA1c and FBS nor other studied factors were predictive for the occurrence of AKI (OR 2.55, p= 0.26 and OR 0.64, p= 0.72 respectively).

Conclusion: Pre-operative HbA1c and one-time FBS values in diabetic patients undergoing elective abdominal surgery procedures were not statistically predictive of AKI in the present data. However, the observed trend towards the risk of AKI among the elevated HbA1c subset of patients should drive further studies with a greater sample size and of a prospective nature looking at other metabolic factors contributing to AKI.

Pre-operative Glycosylated Hemoglobin Level ; Fasting Blood Sugar ; Acute Kidney Injury