METHODS: Scientific literature was thoroughly searched to find 1) DKA treatment guidelines, 2) studies reporting hypokalemia in DKA, 3) and literature elaborating mechanisms involved in hypokalemia.
RESULTS: Acidosis affects SK and its regulators including insulin, catecholamines and aldosterone. Current conceptual framework is an argument to gauge the degree of hypokalemia before it strikes DKA patients utilizing SK level after adjusting it with pH. Suggested approach will reduce hypokalemia risk and its associated complications. The nomogram calculates pH-adjusted potassium and expected potassium loss. It also ranks hypokalemia associated risk, and proposes the potassium-replacement rate over given time period. The differences between current DKA treatment guidelines and proposed strategy are also discussed. Moreover, reasons and risk of hyperkalemia due to early initiation of potassium replacement and remedial actions are debated.
CONCLUSION: In light of proposed strategy, utilizing the nomogram ensures reduced incidence of hypokalemia in DKA resulting in improved clinical and patient outcomes. Pharmacoeconomic benefits can also be expected when avoiding hypokalemia ensures early discharge.
Materials and Methods: A cross-sectional study was conducted at Hospital Universiti Sains Malaysia (Hospital USM), Health Campus, Kubang Kerian, Kelantan, Malaysia. Thirty newly diagnosed patients with PCOS attending gynecology clinic between July 2016 and April 2017 were recruited. Fasting venous blood samples were collected from the subjects. Serum AMH, insulin, adiponectin, triglycerides, high-density lipoprotein cholesterol (HDL-C), and plasma glucose levels were measured, and insulin resistance was calculated based on homeostasis model of assessment-insulin resistance (HOMA-IR). The serum AMH level was estimated, and the correlation of serum AMH level with the metabolic parameters was analyzed.
Results: The median of serum AMH levels in women with PCOS was 6.8 ng/mL (interquartile range: 7.38 ng/mL). There was a significant negative correlation between serum AMH and HOMA-IR or triglyceride levels (r = -0.49, P = 0.006 and r = -0.55, P = 0.002, respectively). A significant positive correlation was observed between serum AMH and serum HDL-C or serum adiponectin levels (r = 0.56, P = 0.001 and r = 0.44, P = 0.014, respectively) in all study subjects.
Conclusion: The serum AMH level is associated with HOMA-IR, triglycerides, HDL-C, and adiponectin levels, and hence it may be used as a potential cardiometabolic risk marker in women with PCOS.
METHODS: A set of 74 items based on a conceptual framework analysis underwent revision and its content validity was established. Items were grouped into three domains. A development study was conducted to establish evidence regarding their factorial structure. A construct validation study was then conducted in which the retained items were tested in an independent sample using confirmatory factor analysis (CFA).
RESULTS: Four factors emerged from our development study and were labelled as pre-travel preparation-insect bites, pre-travel preparation-consultation, insulin and glycaemic control and travel risk behaviour. A CFA confirmed the factorial structure identified in the development study in an independent sample. Each factor loading had a significant (P insulin and glycaemic control (6.45), followed by travel risk behaviour (5.21) and pre-travel preparation (4.15).
CONCLUSIONS: This valid questionnaire for measuring the degree of preparedness of travellers with type 1 diabetes may prove a useful tool in studies involving travellers with type1 diabetes. Our results suggest that improvements are needed in relation to timely pre-travel consultation and screening for diabetic complications.
Methodology: This sub-analysis included Filipino patients with T1DM or T2DM, aged 18 years and older, treated with insulin for more than 12 months, who completed the two-part self-assessment questionnaires (SAQ1 and SAQ2) and patient diaries that recorded hypoglycemia during retrospective (6 months/4 weeks before baseline) and prospective period (4 weeks after baseline) (ClinicalTrials.gov number: NCT02306681).
Results: A total of 671 patients were enrolled and completed the SAQ1 (62 patients with T1DM and 609 patients with T2DM). Almost all patients (100% in T1DM and 99.3% in T2DM) experienced at least 1 hypoglycemic event prospectively. The incidence of any hypoglycemia was also high in the prospective period compared to retrospective period (72.6 [95% CI: 64.8, 80.9] events PPY and 43.6 [95% CI: 37.8, 49.9] events PPY; p=0.001, respectively) in T1DM patients.
Conclusion: Among insulin-treated patients, higher rates of hypoglycemia were reported prospectively than retrospectively. This indicates that the patients in real-life setting often under-report hypoglycemia. Patient education can help in accurate reporting and appropriate management of hypoglycemia and diabetes.