Background Prediabetes has become a pandemic. This study aimed to identify a better predictor for the incidence of prediabetes, which we hypothesize to be the triglyceride-glucose (TyG) index, a simplified insulin resistance index. We compared its predictive value with the other common risk factors of prediabetes. Methods The participants of this analysis were derived from the Risk Evaluation of cAncers in Chinese diabeTic Individuals: a lONgitudinal (REACTION) study. A total of 4543 participants without initial prediabetes or diabetes were followed up for 3.25 years. Using multivariate logistic regression model, the associations between baseline obesity, lipid profiles and non-insulin-based insulin resistance indices with the incidence of prediabetes were analyzed. To assess which is better predictor for the incidence of prediabetes, the area under curves (AUCs) calculated from the receiver operating characteristic curve analyses were used to evaluate and compare with the predictive value of the different indices. Results During the 3.25 years, 1071 out of the 4543 participants developed prediabetes. Using the logistic regression analysis adjusted for some potential confounders, the risk of incidence of prediabetes increased 1.38 (1.28–1.48) fold for each 1–SD increment of TyG index. The predictive ability (assessed by AUCs) of TyG index for predicting prediabetes was 0.60 (0.58–0.62), which was superior to the indices of obesity, lipid profiles and other non-insulin-based insulin resistance indices. Although the predictive ability of the TyG index was overall similar to fasting plasma glucose (FPG) (P = 0.4340), TyG index trended higher than FPG in females (0.62 (0.59–0.64) vs. 0.59 (0.57–0.61), P = 0.0872) and obese subjects (0.59 (0.57–0.62) vs. 0.57 (0.54–0.59), P = 0.1313). TyG index had superior predictive ability for the prediabetic phenotype with isolated impaired glucose tolerance compared with FPG (P <  0.05) and other indices. Furthermore, TyG index significantly improved the C statistic (0.62 (0.60–0.64)), integrated discrimination improvement (1.89% (1.44–2.33%)) and net reclassification index (28.76% (21.84–35.67%)) of conventional model in predicting prediabetes than other indices. Conclusions TyG could be a potential predictor to identify the high risk individuals of prediabetes.

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Nomenclature c p specific heat capacity at constant pressure (J kg

ObjectivesFluid management is important in ensuring haemodynamic stability in critically ill patients, but can easily lead to fluid overload (FO). However, the optimal fluid balance plot or range for critically ill patients is unknown. This study aimed to explore the dose–response relationship between FO and in-hospital mortality in critically ill patients.DesignMulticentre, prospective, observational study.SettingEighteen intensive care units (ICUs) of 16 tertiary hospitals in China.ParticipantsCritically ill patients in the ICU for more than 3 days.Primary outcome measures and analysesFO was defined as the ratio of the cumulative fluid balance (L) and initial body weight (kg) on ICU admission, expressed as a percentage. Maximum FO was defined as the peak value of FO during the first 3 days of ICU admission. Logistic regression models with restricted cubic splines were used to explore the pattern and magnitude of the association between maximum FO and risk of in-hospital mortality. Age, sex, Acute Physiology and Chronic Health Evaluation II score, Sequential Organ Failure Assessment score on admission, main diagnosis on admission to ICU, comorbidities, time of maximum FO, mechanical ventilation, renal replacement therapy, use of vasopressors and centres were adjusted in multivariable analysis.ResultsA total of 3850 patients were included in the study, 929 (24.1%) of whom died in the hospital. For each 1% L/kg increase in maximum FO, the risk of in-hospital mortality increased by 4% (adjusted HR (aHR) 1.04, 95% CI 1.03 to 1.05, p<0.001). A maximum FO greater than 10% was associated with a 44% increased HR of in-hospital mortality compared with an FO less than 5% (aHR 1.44, 95% CI 1.27 to 1.67). Notably, we found a non-linear dose–response association between maximum FO and in-hospital mortality.ConclusionsBoth higher and negative fluid balance levels were associated with an increased risk of in-hospital mortality in critically ill patients.Trial registration numberChiCTR-ECH-13003934.