Robust estimation of the effect of an exposure on the change in a continuous outcome.

BACKGROUND: The change in two measurements of a continuous outcome can be modelled directly with a linear regression model, or indirectly with a random effects model (REM) of the individual measurements. These methods are susceptible to model misspecifications, which are commonly addressed by applying monotonic transformations (e.g., Box-Cox transformation) to the outcomes. However, transforming the outcomes complicates the data analysis, especially when variable selection is involved. We propose a robust alternative through a novel application of the conditional probit (cprobit) model. METHODS: The cprobit model analyzes the ordered outcomes within each subject, making the estimate invariant to monotonic transformation on the outcome. By scaling the estimate from the cprobit model, we obtain the exposure effect on the change in the observed or Box-Cox transformed outcome, pending the adequacy of the normality assumption on the raw or transformed scale. RESULTS: Using simulated data, we demonstrated a similar good performance of the cprobit model and REM with and without transformation, except for some bias from both methods when the Box-Cox transformation was applied to scenarios with small sample size and strong effects. Only the cprobit model was robust to skewed subject-specific intercept terms when a Box-Cox transformation was used. Using two real datasets from the breast cancer and inpatient glycemic variability studies which utilize electronic medical records, we illustrated the application of our proposed robust approach as a seamless three-step workflow that facilitates the use of Box-Cox transformation to address non-normality with a common underlying model. CONCLUSIONS: The cprobit model provides a seamless and robust inference on the change in continuous outcomes, and its three-step workflow is implemented in an R package for easy accessibility.

Using marginal standardisation to estimate relative risk without dichotomising continuous outcomes.

BACKGROUND: Although criticisms regarding the dichotomisation of continuous variables are well known, applying logit model to dichotomised outcomes is the convention because the odds ratios are easily obtained and they approximate the relative risks (RRs) for rare events. METHODS: To avoid dichotomisation when estimating RR, the marginal standardisation method that transforms estimates from logit or probit model to RR estimate is extended to include estimates from linear model in the transformation. We conducted a simulation study to compare the statistical properties of the estimates from: (i) marginal standardisation method between models for continuous (i.e., linear model) and dichotomised outcomes (i.e., logit or probit model), and (ii) marginal standardisation method and distributional approach (i.e., marginal mean method) applied to linear model. We also compared the diagnostic test for probit, logit and linear models. For the real dataset analysis, we applied these analytical approaches to assess the management of inpatient hyperglycaemia in a pilot intervention study. RESULTS: Although the RR estimates from the marginal standardisation method were generally unbiased for all models in the simulation study, the marginal standardisation method for linear model provided estimates with higher precision and power than logit or probit model, especially when the baseline risks were at the extremes. When comparing approaches that avoid dichotomisation, RR estimates from these approaches had comparable performance. Assessing the assumption of error distribution was less powerful for logit or probit model via link test when compared with diagnostic test for linear model. After accounting for multiple thresholds representing varying levels of severity in hyperglycaemia, marginal standardisation method for linear model provided stronger evidence of reduced hyperglycaemia risk after intervention in the real dataset analysis although the RR estimates were similar across various approaches. CONCLUSIONS: When compared with approaches that do not avoid dichotomisation, the RR estimated from linear model is more precise and powerful, and the diagnostic test from linear model is more powerful in detecting mis-specified error distributional assumption than the diagnostic test from logit or probit model. Our work describes and assesses the methods available to analyse data involving studies of continuous outcomes with binary representations.

Measurement equivalence of the English, Chinese and Malay versions of the World Health Organization quality of life (WHOQOL-BREF) questionnaires.

BACKGROUND: The WHOQOL-BREF is a widely used questionnaire for measuring quality of life. It is important to establish the measurement equivalence of various language versions of WHOQOL-BREF so that scores from different language versions may be pooled together. The primary aim of this article was to evaluate the measurement equivalence of the English, Chinese and Malay versions of the WHOQOL-BREF. METHODS: We analysed data from the previously published, cross-sectional, WONDERS study and used linear regression models to adjust for potential confounding variables. Based on equivalence clinical trial methods, measurement equivalence was assessed by comparing 90% confidence interval (CI) of differences in scores across language versions with a predefined equivalence margin of 0.3 SD. Equivalence was achieved if the 90% CI fell within 0.3 SD. Data from 1203 participants, aged above 21 years, were analysed. RESULTS: Participants who completed the different language versions of WHOQOL-BREF expectedly differed in age, ethnicity, highest education level, marital status, smoking status and Body Mass Index (BMI). The English and Malay language versions were definitely equivalent for all domains. The English and Chinese language versions were definitely equivalent for physical and environmental domains but inconclusive for psychological and social domains. Likewise, for Chinese and Malay versions. CONCLUSION: The English, Chinese and Malay language versions of the WHOQOL-BREF questionnaire may be considered equivalent, with evidence being more robust for some domains than the others. Given the large number of people who speak/ read Chinese and Malay, this study has widespread relevance.

Utilizing distributional analytics and electronic records to assess timeliness of inpatient blood glucose monitoring in non-critical care wards.

BACKGROUND: Regular and timely monitoring of blood glucose (BG) levels in hospitalized patients with diabetes mellitus is crucial to optimizing inpatient glycaemic control. However, methods to quantify timeliness as a measurement of quality of care are lacking. We propose an analytical approach that utilizes BG measurements from electronic records to assess adherence to an inpatient BG monitoring protocol in hospital wards. METHODS: We applied our proposed analytical approach to electronic records obtained from 24 non-critical care wards in November and December 2013 from a tertiary care hospital in Singapore. We applied distributional analytics to evaluate daily adherence to BG monitoring timings. A one-sample Kolmogorov-Smirnov (1S-KS) test was performed to test daily BG timings against non-adherence represented by the uniform distribution. This test was performed among wards with high power, determined through simulation. The 1S-KS test was coupled with visualization via the cumulative distribution function (cdf) plot and a two-sample Kolmogorov-Smirnov (2S-KS) test, enabling comparison of the BG timing distributions between two consecutive days. We also applied mixture modelling to identify the key features in daily BG timings. RESULTS: We found that 11 out of the 24 wards had high power. Among these wards, 1S-KS test with cdf plots indicated adherence to BG monitoring protocols. Integrating both 1S-KS and 2S-KS information within a moving window consisting of two consecutive days did not suggest frequent potential change from or towards non-adherence to protocol. From mixture modelling among wards with high power, we consistently identified four components with high concentration of BG measurements taken before mealtimes and around bedtime. This agnostic analysis provided additional evidence that the wards were adherent to BG monitoring protocols. CONCLUSIONS: We demonstrated the utility of our proposed analytical approach as a monitoring tool. It provided information to healthcare providers regarding the timeliness of daily BG measurements. From the real data application, there were empirical evidences suggesting adherence of BG timings to protocol among wards with adequate power for assessing timeliness. Our approach is extendable to other areas of healthcare where timeliness of patient care processes is important.

Psychometric analysis of an eating behaviour questionnaire for an overweight and obese Chinese population in Singapore.

OBJECTIVES: Previous studies reveal that the Three-Factor Eating Questionnaire (TFEQ), which assesses eating behaviour, performs differently across population groups and cultures. We aimed to identify the factor structure that is most appropriate to capture eating behaviour in an overweight and obese Chinese population in Singapore. METHODS: TFEQ-51 was administered to 444 Chinese subjects pooled from four separate studies and scored according to various alternative versions of the TFEQ. Confirmatory factor analyses and goodness of fit indices were used to determine the most appropriate factor structure. Known-group validity analyses were conducted. RESULTS: Niemeier's Disinhibition Factors and the TFEQ-R18 factor structures were found to be the most applicable in our population based on goodness of fit indices, with a x(2)/df ratio of <3, RMSEA of ≤ 0.6 and a CFI value of >0.9 for both. Only two of three factors (Emotional Eating and Uncontrolled Eating) of the TFEQ-R18 showed good internal consistency, while none of Niemeier's Disinhibition Factors showed good internal consistency. Known-group validity showed that Emotional Eating and Internal Disinhibition were significantly associated with higher BMI. CONCLUSION: We found that the TFEQ-R18 factor structure is the most appropriate and practical for use in measuring eating behaviour in an overweight and obese Chinese population in Singapore.

A fully convolutional neural network for comprehensive compartmentalization of abdominal adipose tissue compartments in MRI.

BACKGROUND: Existing literature has highlighted structural, physiological, and pathological disparities among abdominal adipose tissue (AAT) sub-depots. Accurate separation and quantification of these sub-depots are crucial for advancing our understanding of obesity and its comorbidities. However, the absence of clear boundaries between the sub-depots in medical imaging data has challenged their separation, particularly for internal adipose tissue (IAT) sub-depots. To date, the quantification of AAT sub-depots remains challenging, marked by a time-consuming, costly, and complex process. PURPOSE: To implement and evaluate a convolutional neural network to enable granular assessment of AAT by compartmentalization of subcutaneous adipose tissue (SAT) into superficial subcutaneous (SSAT) and deep subcutaneous (DSAT) adipose tissue, and IAT into intraperitoneal (IPAT), retroperitoneal (RPAT), and paraspinal (PSAT) adipose tissue. MATERIAL AND METHODS: MRI datasets were retrospectively collected from Singapore Preconception Study for Long-Term Maternal and Child Outcomes (S-PRESTO: 389 women aged 31.4 ± 3.9 years) and Singapore Adult Metabolism Study (SAMS: 50 men aged 28.7 ± 5.7 years). For all datasets, ground truth segmentation masks were created through manual segmentation. A Res-Net based 3D-UNet was trained and evaluated via 5-fold cross-validation on S-PRESTO data (N = 300). The model's final performance was assessed on a hold-out (N = 89) and an external test set (N = 50, SAMS). RESULTS: The proposed method enabled reliable segmentation of individual AAT sub-depots in 3D MRI volumes with high mean Dice similarity scores of 98.3%, 97.2%, 96.5%, 96.3%, and 95.9% for SSAT, DSAT, IPAT, RPAT, and PSAT respectively. CONCLUSION: Convolutional neural networks can accurately sub-divide abdominal SAT into SSAT and DSAT, and abdominal IAT into IPAT, RPAT, and PSAT with high accuracy. The presented method has the potential to significantly contribute to advancements in the field of obesity imaging and precision medicine.

Long-term effects of bariatric surgery on cardiovascular risk factors in Singapore.

INTRODUCTION: Bariatric surgery is considered an effective treatment for weight loss and for improving the metabolic profile of patients with obesity. Obesity-related comorbidities such as hyperlipidaemia and type 2 diabetes mellitus (DM) are significant cardiovascular risk factors. Additionally, prospective clinical trials have shown that statins increase the risk of development of DM, and many patients with obesity are on statins. We retrospectively examined the effect of bariatric surgery on lipid profile, DM control and weight loss at the five-year follow-up. METHODS: In total, 104 patients undergoing bariatric surgery from 2008 to 2012 were retrospectively studied. 36 patients were on preoperative statins. Their lipid profile, DM control and weight loss were examined at the one-year and five-year follow-ups. RESULTS: Both high-density lipoprotein and triglyceride levels showed significant improvement at the one-year and five-year follow-ups (p = 0.01). Total cholesterol showed significant improvement at the one-year follow-up (-0.30 mmol/dL, p = 0.0338); however, better control was not sustained at the five-year follow-up (-0.15 mmol/dL, p = 0.133). Low-density lipoprotein did not show any considerable improvement at the one- and five-year follow-ups (-0.27 mmol/dL, p = 0.150 and -0.24 mmol/dL, p = 0.138, respectively). A statistically significant improvement in DM control was observed in these patients and in those on preoperative statins. Weight loss was sustained at one and five years. CONCLUSION: Bariatric surgery does not confer a uniform improvement in lipid profile in the long term. It does, however, induce efficient weight loss and improvement in diabetic profile, even in patients on preoperative statins.

Branched Chain Amino Acid Supplementation to a Hypocaloric Diet Does Not Affect Resting Metabolic Rate but Increases Postprandial Fat Oxidation Response in Overweight and Obese Adults after Weight Loss Intervention.

BACKGROUND: Branched chain amino acids (BCAA) supplementation is reported to aid in lean mass preservation, which may in turn minimize the reduction in resting metabolic rate (RMR) during weight loss. Our study aimed to examine the effect of BCAA supplementation to a hypocaloric diet on RMR and substrate utilization during a weight loss intervention. METHODS: A total of 111 Chinese subjects comprising 55 males and 56 females aged 21 to 45 years old with BMI between 25 and 36 kg/m2 were randomized into three hypocaloric diet groups: (1) standard-protein (14%) with placebo (CT), (2) standard-protein with BCAA, and (3) high-protein (27%) with placebo. Indirect calorimetry was used to measure RMR, carbohydrate, and fat oxidation before and after 16 weeks of dietary intervention. RESULTS: RMR was reduced from 1600 ± 270 kcal/day to 1500 ± 264 kcal/day (p < 0.0005) after weight loss, but no significant differences in the change of RMR, respiratory quotient, and percentage of fat and carbohydrate oxidation were observed among the three diet groups. Subjects with BCAA supplementation had an increased postprandial fat (p = 0.021) and decreased postprandial carbohydrate (p = 0.044) oxidation responses compared to the CT group after dietary intervention. CONCLUSIONS: BCAA-supplemented standard-protein diet did not significantly attenuate reduction of RMR compared to standard-protein and high-protein diets. However, the postprandial fat oxidation response increased after BCAA-supplemented weight loss intervention.

Evaluating the effectiveness of a multi-faceted inpatient diabetes management program among hospitalised patients with diabetes mellitus.

BACKGROUND: Diabetes mellitus (DM) is one of the most common chronic diseases. Individuals with DM are more likely to be hospitalised and stay longer than those without DM. Inpatient hypoglycemia and hyperglycemia, which are associated with adverse outcomes, are common, but can be prevented through hospital quality improvement programs. METHODS: We designed a multi-faceted intervention program with the aim of reducing inpatient hypoglycemia and hyperglycemia. This was implemented over seven phases between September 2013 to January 2016, and covered all the non-critical care wards in a tertiary hospital. The program represented a pragmatic approach that leveraged on existing resources and infrastructure within the hospital. We calculated glucometric outcomes in June to August 2016 and compared them with those in June to August 2013 to assess the overall effectiveness of the program. We used regression models with generalised estimating equations to adjust for potential confounders and account for correlations of repeated outcomes within patients and admissions. RESULTS: We observed significant reductions in patient-days affected by hypoglycemia (any glucose reading < 4 mmol/L: OR = 0.71, 95% CI: 0.61 to 0.83, p <  0.001), and hyperglycemia (any glucose reading > 14 mmol/L: OR = 0.84, 95% CI: 0.71 to 0.99, p = 0.041). Similar findings were observed for admission-level hypoglycemia and hyperglycemia. Further analyses suggested that these reductions started to occur four to 6 months post-implementation. CONCLUSIONS: Our program was associated with sustained improvements in clinically relevant outcomes. Our described intervention could be feasibly implemented by other secondary and tertiary care hospitals by leveraging on existing infrastructure and work force.

Effects of external counter-pulsation on endothelial function assessed by peripheral artery tonometry, levels of glycaemia and metabolic markers in individuals with type 2 diabetes mellitus.

BACKGROUND AND AIMS: External counter-pulsation (ECP) generates sheer stress thereby improving endothelial function and anginal symptoms in coronary artery disease. Endothelial dysfunction is also involved in the pathogenesis of T2DM. The aim of this pilot study was to investigate the use of ECP at different doses in improving endothelial function and glycaemic markers in T2DM. METHODS: This prospective study involved 46 subjects with T2DM randomly assigned to receive 35 sessions of ECP at different regimens (0.5 h versus 1 h) and duration (7 versus 12 weeks). Endothelial function was evaluated by reactive hyperaemia index (RHI) via peripheral arterial tonometry at the start, midpoint and end of study. Other secondary outcomes included fasting glucose, HOMA-IR, HbA1c, blood pressure, lipid profile, weight and vibration sense. RESULTS: There was no change in RHI across all 3 regimens of ECP individually or collectively at the end of the study (ΔRHI +0.01%, p = 0.458). Glycaemic markers also remained unchanged at endpoint. Subgroup analysis showed an improvement in RHI (ΔRHI +20.6%, p = 0.0178) in subjects with more severe endothelial dysfunction at baseline. CONCLUSION: ECP did not show a beneficial effect on endothelial function or glycemic control in this South-East Asian population with T2DM at any of the three regimens. This may partly be explained by less severe endothelial dysfunction and less insulin resistance in our population at baseline.

Self-reported hypoglycaemia in insulin-treated patients with diabetes mellitus: results from the Singapore cohort of the International Operations Hypoglycaemia Assessment Tool study.

INTRODUCTION: Hypoglycaemia constitutes a significant barrier to achieving glycaemic control with insulin in both Type 1 (T1DM) and Type 2 diabetes mellitus (T2DM). The International Operations Hypoglycaemia Assessment Tool (IO HAT) study was designed to determine the incidence of hypoglycaemia in insulin-treated patients with T1DM and T2DM. METHODS: The IO HAT study retrospectively and prospectively assessed the incidence of hypoglycaemia in patients with insulin-treated diabetes mellitus in nine countries. This sub-analysis included patients from Singapore with T1DM or T2DM who were aged ≥ 21 years and had completed two self-assessment questionnaires (SAQ1 and SAQ2). RESULTS: Of the 50 T1DM and 320 T2DM patients who completed the SAQ1, 39 T1DM and 265 T2DM patients completed SAQ2; 100% and 90.9%, respectively, experienced at least one hypoglycaemic event prospectively. The incidence rates of any hypoglycaemia were 49.5 events per patient-year (EPPY) and 16.1 EPPY for T1DM and T2DM patients, respectively, in the four-week prospective period. Hypoglycaemia rate did not differ in terms of glycated haemoglobin level. The vast majority of T1DM or T2DM patients (92.0% and 90.7%, respectively) knew the overall definition of hypoglycaemia before study participation, although over half of the patients (T1DM 54.0%, T2DM 51.9%) defined hypoglycaemia based only on symptoms. CONCLUSION: High proportions of insulin-treated patients with diabetes mellitus in Singapore reported hypoglycaemic events prospectively, showing that they had underreported hypoglycaemic episodes retrospectively. Patient education can help in improving hypoglycaemia awareness and its management in the region.

The effect of coffee consumption on insulin sensitivity and other biological risk factors for type 2 diabetes: a randomized placebo-controlled trial.

BACKGROUND: In observational studies, coffee consumption has been consistently associated with a lower risk of type 2 diabetes mellitus. Trials examining the effect of coffee consumption on glucose metabolism have been limited by the use of surrogate insulin sensitivity indices, small sample sizes, lack of blinding, and short follow-up duration. OBJECTIVES: We aimed to overcome limitations of previously conducted coffee trials in a randomized placebo-controlled trial of the effect of coffee consumption on insulin sensitivity. METHODS: We conducted a 24-wk randomized placebo-controlled trial in 126 overweight, non-insulin sensitive (HOMA-IR ≥1.30), Chinese, Malay, and Asian-Indian males and females aged 35-69 y. Participants were randomly assigned to receive 4 cups of instant regular coffee (n = 62) or 4 cups of a coffee-like placebo beverage (n = 64) per day. The primary outcome was the amount of glucose metabolized per kilogram of body weight per minute (Mbw) assessed during steady-state conditions with a hyperinsulinemic euglycemic clamp. Secondary outcomes included other clamp-based insulin sensitivity measures, biological mediators of insulin sensitivity, and measures of fasting glucose metabolism. RESULTS: Coffee consumption did not significantly change insulin sensitivity compared with placebo (percentage mean difference in Mbw = 4.0%; 95% CI: -8.3, 18.0%; P = 0.53). Furthermore, no significant differences in fasting plasma glucose (2.9%; 95% CI: -0.4, 6.3%; P = 0.09) or biological mediators of insulin resistance, such as plasma adiponectin (2.3%; 95% CI: -1.4, 6.2%; P = 0.22), were observed between coffee and placebo groups over 24 wk of intervention. Participants in the coffee arm experienced a loss of fat mass (FM) (-3.7%; 95% CI: -6.3, -1.1%; P = 0.006) and reduction in urinary creatinine concentrations (-21.2%; 95% CI: -31.4, -9.5%; P = 0.001) compared with participants in the placebo arm over 24 wk of intervention. CONCLUSIONS: Consuming 4 cups/d of caffeinated coffee for 24 wk had no significant effect on insulin sensitivity or biological mediators of insulin resistance but was associated with a modest loss of FM and reduction in urinary creatinine concentrations.This trial was registered at clinicaltrials.gov as NCT01738399. Registered on November 28, 2012. Trial sponsor: Nestlé Research, Lausanne, Switzerland. Trial site: National University of Singapore.

A stratification approach using logit-based models for confounder adjustment in the study of continuous outcomes.

The control of confounding is an area of extensive epidemiological research, especially in the field of causal inference for observational studies. Matched cohort and case-control study designs are commonly implemented to control for confounding effects without specifying the functional form of the relationship between the outcome and confounders. This paper extends the commonly used regression models in matched designs for binary and survival outcomes (i.e. conditional logistic and stratified Cox proportional hazards) to studies of continuous outcomes through a novel interpretation and application of logit-based regression models from the econometrics and marketing research literature. We compare the performance of the maximum likelihood estimators using simulated data and propose a heuristic argument for obtaining the residuals for model diagnostics. We illustrate our proposed approach with two real data applications. Our simulation studies demonstrate that our stratification approach is robust to model misspecification and that the distribution of the estimated residuals provides a useful diagnostic when the strata are of moderate size. In our applications to real data, we demonstrate that parity and menopausal status are associated with percent mammographic density, and that the mean level and variability of inpatient blood glucose readings vary between medical and surgical wards within a national tertiary hospital. Our work highlights how the same class of regression models, available in most statistical software, can be used to adjust for confounding in the study of binary, time-to-event and continuous outcomes.

Large-scale lipidomics identifies associations between plasma sphingolipids and T2DM incidence.

BACKGROUND: Sphingolipids (SPs) are ubiquitous, structurally diverse molecules that include ceramides, sphingomyelins, and sphingosines. They are involved in various pathologies including obesity and type 2 diabetes mellitus (T2DM). Therefore, it is likely that perturbations in plasma concentrations of SPs are associated with disease. Identifying these associations may reveal useful biomarkers or provide insight into disease processes. METHODS: We performed a lipidomics evaluation of molecularly-distinct SPs in the plasma of 2,302 ethnically-Chinese Singaporeans using electrospray ionization mass spectrometry coupled with liquid chromatography. SP profiles were compared to clinical and biochemical characteristics, and subjects were evaluated by follow-up visits for 11 years. RESULTS: We found that ceramides correlate positively but hexosylceramides correlate negatively with body mass index (BMI) and homeostatic model assessment of insulin resistance (HOMA-IR). Furthermore, SPs with a d16:1 sphingoid backbone correlate more positively with BMI and HOMA-IR, while d18:2 SPs correlate less positively, relative to canonical d18:1 SPs. We also found that higher concentrations of two distinct sphingomyelins were associated with a higher risk of T2DM (HR 1.45, 95% CI 1.18-1.78 for SM d16:1/C18:0; and HR 1.40, 95% CI 1.17-1.68 for SM d18:1/C18:0). CONCLUSION: We identified significant associations between SPs and obesity/T2DM characteristics, specifically, that of hexosylceramides, d16:1 SPs, and d18:2 SPs. This suggests that the balance of SP metabolism, rather than ceramide accumulation, is associated with the pathology of obesity. We further identified two specific SPs that may represent prognostic biomarkers for T2DM. FUNDING: Funding sources are listed in the Acknowledgements section.

Ethnicity-Specific Skeletal Muscle Transcriptional Signatures and Their Relevance to Insulin Resistance in Singapore.

Context: Insulin resistance (IR) and obesity differ among ethnic groups in Singapore, with the Malays more obese yet less IR than Asian-Indians. However, the molecular basis underlying these differences is not clear. Objective: As the skeletal muscle (SM) is metabolically relevant to IR, we investigated molecular pathways in SM that are associated with ethnic differences in IR, obesity, and related traits. Design, Setting, and Main Outcome Measures: We integrated transcriptomic, genomic, and phenotypic analyses in 156 healthy subjects representing three major ethnicities in the Singapore Adult Metabolism Study. Patients: This study contains Chinese (n = 63), Malay (n = 51), and Asian-Indian (n = 42) men, aged 21 to 40 years, without systemic diseases. Results: We found remarkable diversity in the SM transcriptome among the three ethnicities, with >8000 differentially expressed genes (40% of all genes expressed in SM). Comparison with blood transcriptome from a separate Singaporean cohort showed that >95% of SM expression differences among ethnicities were unique to SM. We identified a network of 46 genes that were specifically downregulated in Malays, suggesting dysregulation of components of cellular respiration in SM of Malay individuals. We also report 28 differentially expressed gene clusters, four of which were also enriched for genes that were found in genome-wide association studies of metabolic traits and disease and correlated with variation in IR, obesity, and related traits. Conclusion: We identified extensive gene-expression changes in SM among the three Singaporean ethnicities and report specific genes and molecular pathways that might underpin and explain the differences in IR among these ethnic groups.

Mean Rank, Equipercentile, and Regression Mapping of World Health Organization Quality of Life Brief (WHOQOL-BREF) to EuroQoL 5 Dimensions 5 Levels (EQ-5D-5L) Utilities.

BACKGROUND: Existing methods to link preference-based and profile-based health-related quality of life (HRQoL) questionnaires have their limitations. Hence, we developed a new mapping method (the mean rank method, MRM) and applied it to map the World Health Organization Quality of Life Questionnaire (WHOQOL-BREF) to the EuroQoL 5 Dimensions 5 Levels (EQ-5D-5L). We then compared the new MRM with current methods; i.e., regression-mapped (OLS method) and equipercentile method (EPM). METHODS: Singapore residents, aged ≥21 y, were recruited from the general population and 2 outpatient clinics in acute care hospitals. Performance of the MRM was evaluated using both simulation and split-sample validation ( n = 658 in training and n = 657 in validation samples). Using the training sample, we derived 3 sets of mapped EQ-5D-5L utilities based on MRM, OLS method and EPM. Using simulation and the validation sample, we compared the performance of the mapping methods in terms of distribution parameters, mean utility by strata, association with health covariates, and prediction errors at the individual level, among others. RESULTS: The WHOQOL-BREF Physical Health domain is the only domain significantly associated with EQ-5D-5L utilities. Simulation showed that MRM more accurately reproduced the variance and percentiles of the distribution of the observed utilities than did the OLS method or EPM. OLS method tended to underestimate the mean utility of good health states, overestimate the mean utility of poor health states, and underestimate the association with covariates. An analysis of validation sample gave similar results. CONCLUSION: In scenarios similar to the mapping of WHOQOL-BREF to the EQ-5D-5L, the MRM outperformed the OLS method and EPM in important-though not all-aspects. The simplicity and reproducibility of the MRM makes it an attractive alternative to current methods.

Feasibility of representing adherence to blood glucose monitoring through visualizations: A pilot survey study among healthcare workers.

BACKGROUND: Measuring adherence to processes is one of the established ways to quantify the quality of healthcare. Providing timely feedback to healthcare workers on the level of adherence can improve process measures. However, it is challenging to present data on adherence to repetitive time-sensitive tasks in a clear manner. OBJECTIVES: We used inpatient glucose monitoring as a test case to explore the feasibility of using visualizations to communicate adherence to repetitive scheduled tasks to healthcare workers. METHODS: We selected four candidate plots that represented distribution across time: histogram, probability density function plot (pdf plot), violin plot and cumulative density function plot (cdf plot). Doctors and nurses involved in inpatient diabetes care in a tertiary hospital were invited to complete a self-administered questionnaire that measured self-reported baseline knowledge, performance, and perception towards the visualizations. Performance was assessed by determining if a participant was able to correctly identify visualizations representing protocol adherence. We also assessed the perception of usability of these visualizations for monitoring protocol adherence. Binomial regression models were used to identify factors associated with overall performance and perception. Logistic regression models with generalized estimating equation were used to compare performance and perception between visualizations, and identify effect modifiers. RESULTS: A total of 57 doctors and nurses completed the questionnaire. Participants were most familiar with histogram (87.7%), followed by cdf plot (61.4%), pdf plot (40.4%), and violin plot (7%). However, the percentages of participants who identified non-adherence using these plots were generally lower, ranging from 29.8% to 40.4%. Participants' perception of usability ranged from 14% to 17.5% across these visualizations. More favorable perceptions were found among participants with baseline knowledge for two or more visualizations (adjusted odds ratio: 3.21; 95%CI: 1.29, 7.96; p-value: 0.012) and having identified two or more non-adherent visualizations (adjusted odds ratio: 4.23; 95%CI: 1.95, 9.16; p-value: < 0.001). CONCLUSIONS: Adherence to repetitive time-sensitive tasks can be presented in the form of visualizations. However, nurses' and doctors' knowledge and understanding of these visualizations are generally poor. This may influence their perception of usability of these plots. Therefore, these visualizations need to be implemented in tandem with training on their interpretation, to enhance the usefulness of these plots in motivating quality improvement.

The Utility of Brief Cognitive Tests for Patients With Type 2 Diabetes Mellitus: A Systematic Review.

BACKGROUND: Type 2 diabetes mellitus (T2DM) is associated with an increased risk for mild cognitive impairment and dementia in both middle-aged and older individuals. Brief cognitive tests can potentially serve as a reliable and cost effective approach to detect for cognitive decrements in clinical practice. OBJECTIVE: This systematic review examined the utility of brief cognitive tests in studies with patients with T2DM. METHOD: This systematic review was conducted according to guidelines of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses. "PubMed," "PsychINFO," "ScienceDirect," and "ProQuest" electronic databases were searched to identify articles published from January 1, 2005 to December 31, 2015. RESULTS: The search yielded 22 studies, with only 8 using brief tests as a cognitive screening tool, whereas the majority using these tests as a measure of global cognitive functions. In regard to cognitive screening studies, most had failed to fulfil the standard reporting of diagnostic test accuracy criteria such as Standards for Reporting of Diagnostic Accuracy for dementia and cognitive impairment. Moreover, few studies reported discriminant indices such as sensitivity, specificity, and positive and negative predictive values of brief cognitive tests in detecting cognitive impairment in patients with T2DM. Among studies which used brief cognitive tests as a measure of global cognitive function, patients with diabetes tended to perform worse than patients without diabetes. Processing speed appeared to be particularly impaired among patients with diabetes, therefore, measures of processing speed such as the Digit Symbol Substitution Test may add value to brief cognitive tests such as the Montreal Cognitive Assessment. CONCLUSIONS: The Montreal Cognitive Assessment supplemented by the Digit Symbol Substitution Test indicate initial promise in screening for cognitive impairment in T2DM.

A randomized placebo-controlled trial of the effect of coffee consumption on insulin sensitivity: Design and baseline characteristics of the Coffee for METabolic Health (COMETH) study.

BACKGROUND: Coffee consumption has been consistently associated with a lower risk of type 2 diabetes mellitus in cohort studies. In addition, coffee components increased insulin sensitivity in animal models. However, data from intervention studies on the effect of coffee consumption on glucose metabolism have been limited by small sample sizes, lack of blinding, short follow-up duration and the use of surrogate indices of insulin sensitivity. We designed the Coffee for Metabolic Health (COMETH) study to evaluate the effect of coffee consumption on insulin sensitivity. METHODOLOGY: The COMETH study is a double-blind randomized placebo-controlled 24-week trial. Participants were overweight, male and female habitual coffee consumers who were of Chinese, Malay and Asian-Indian ethnicity. We excluded smokers, persons with diabetes, and persons with low insulin resistance (HOMA-IR < 1.30). Participants were randomly assigned to receive daily 4 cups of instant regular coffee or 4 cups of a coffee-like placebo beverage. The hyperinsulinemic euglycemic clamp was performed at baseline and at the end of 24 weeks to determine changes in the bodyweight standardized M-value. Secondary outcomes included changes in fasting glucose and insulin sensitivity mediators such as adiponectin, markers of inflammation, liver function, and oxidative stress.We enrolled 128 participants, 126 (57.1% males; aged 35-67 years) of whom completed baseline assessments. DISCUSSION: If improvement in insulin sensitivity in the coffee group is significantly greater than that of the placebo group, this would support the hypothesis that coffee consumption reduced risk of type 2 diabetes through biological pathways involving insulin sensitivity. TRIAL REGISTRATION: ClinicalTrials.gov identifier: NCT01738399. Registered on 28 November 2012. Trial Sponsor: Nestlé Research Center, Lausanne, Switzerland. Trial Site: National University of Singapore.