The aim of this study is to summarize the evidence on the dose–response relationship between body mass index (BMI) and mortality in patients with chronic obstructive pulmonary disease (COPD). We performed a systemic literature search in PubMed, Embase, and Web of Science for relevant studies that were published until June 2015. A random effects meta-analysis was used to estimate the pooled relative risks (RRs) of all-cause mortality in COPD patients with normal weight compared with those who were underweight, overweight, or obese. In addition, a dose–response meta-analysis was conducted to explore the dose–response relationship between BMI and all-cause mortality in COPD patients. A total of 17 observational studies involving 30,182 COPD patients among 285,960 participants were included. Compared with the reference category, the RRs of underweight, overweight, and obese individuals were 1.40 (95% confidence interval (CI), 1.20–1.63), 0.80 (95% CI, 0.67–0.96), and 0.77 (95% CI, 0.62–0.95), respectively. A significant nonlinear relationship between BMI and mortality of COPD patients was found by using a random effects model. COPD patients with BMI of 32 kg/m2. Our findings indicate that overweight is associated with a lower risk of all-cause mortality among patients with COPD whereas underweight is associated with a higher risk of all-cause mortality in these patients. However, there is limited evidence to support the association between obesity and the risk of all-cause mortality in patients with COPD.

Background: The role of 18-fluorodeoxyglucose positron emission tomography CT (¹⁸FDG PET/CT), as a prognostic factor for survival in colorectal cancer patients with liver metastases, is still controversial. We sought to perform a meta-analysis of the literature to address this issue. Methods: A systematic literature search was performed to identify the studies that associated ¹⁸FDG PET/CT to clinical survival outcomes of patients with liver metastases. Methodological qualities of the included studies were also assessed. The summarized hazard ratio (HR) was estimated by using fixed- or random-effect model according to heterogeneity between trails. Results: By analyzing a total of 867 patients from 15 studies, we found that PET/CT for metabolic response to the therapy was capable of predicting event-free survival (EFS) and overall survival (OS) with statistical significance, and the HR was 0.45 (95 % confidence interval [CI], 0.26–0.78) and 0.36 (95 % CI, 0.18–0.71), respectively. Furthermore, pre-treatment ¹⁸FDG PET/CT with high standardized uptake value (SUV) was also significantly associated with poorer OS HR, 1.24; (95 % CI, 1.06–1.45). However, we did not find a statistically significant effect of post-treatment SUV for predicting OS HR, 1.68; (95 % CI, 0.63–4.52). Conclusions: The present meta-analysis confirms that ¹⁸FDG PET/CT is a useful tool to help predict survival outcomes in patients with liver metastases.

In this study, we aimed to investigate the prevalence, awareness, treatment, and control of diabetes in Shanghai, China. A sample of 3600 residents aged from 18 to 80 years selected by a randomized stratified multiple-stage sampling method in Shanghai was investigated, with blood samples collected. Diabetes was defined as fasting plasma glucose (FPG) ≥ 7.0 mmol/L, or glycated haemoglobin (HbA1c) ≥ 6.5% (48 mmol/mol), or previous diagnosis by a physician. Adequate control of diabetes was taken as a level of HbA1c < 7.0% (53 mmol/mol) among people with treated diabetes. Multivariable regression analysis was used to explore associated factors for diabetes and prediabetes. In the 3136 participants suitable for analysis, the prevalences of diabetes, prediabetes, and previously diagnosed diabetes were 15.91%, 37.37%, and 4.46%, respectively. Among those with diabetes, only 28.06% were aware of their condition, 25.85% were currently undergoing medication treatment, and 12.42% achieved glycaemic control. Logistic regression showed that old age, preobesity, obesity, elevated triglyceride (TG), elevated C-reactive protein (CRP), and lower education level were associated with an increased risk of diabetes; old age, obesity, elevated TG, and elevated low-density lipoprotein (LDL) were associated with an increased risk of prediabetes, while male sex and rural residence were associated with a decreased risk of prediabetes. In summary, the state of diabetes in China is alarming; the rates of awareness, treatment, and control were relatively low. More efforts should be made to promote the prevention and control of diabetes in china.

Background: Frailty is a common characteristic of older people with the ageing process. We aimed to develop and validate a dynamic statistical prediction model to calculate the risk of death in people aged ≥65 years, using a longitudinal frailty index (FI). Methods: One training dataset and three validation datasets from the Chinese Longitudinal Healthy Longevity Survey (CLHLS) were used in our study. The training dataset and validation datasets 1 to 3 included data from 9,748, 7,459, 9,093 and 6,368 individuals, respectively. We used 35 health deficits to construct the FI and a longitudinal FI based on repeated measurement of FI at every wave of the CLHLS. A joint model was used to build a dynamic prediction model considering both baseline covariates and the longitudinal FI. Areas under time-dependent receiver operating characteristic curves (AUCs) and calibration curves were employed to assess the predictive performance of the model. Results: A linear mixed-effects model used time, sex, residence (city, town, or rural), living alone, smoking and alcohol consumption to calculate a subject-specific longitudinal FI. The dynamic prediction model was built using the longitudinal FI, age, residence, sex and an FI–age interaction term. The AUCs ranged from 0.64 to 0.84, and both the AUCs and the calibration curves showed good predictive ability. Conclusions: We developed a dynamic prediction model that was able to update predictions of the risk of death as updated measurements of FI became available. This model could be used to estimate the risk of death in individuals aged >65 years.

Objective: This study aimed to explore the association between base excess (BE) and the risk of 30-day mortality among patients with acute kidney injury (AKI) in the intensive care unit (ICU).Methods: This retrospective study included patients with AKI from the Medical Information Mart for Intensive Care (MIMIC)-IV database. We used a multivariate Cox proportional-hazards model to obtain the hazard ratio (HR) for the risk of 30-day mortality among patients with AKI. Furthermore, we utilized a Cox proportional-hazard model with restricted cubic splines (RCS) to explore the potential non-linear associations.Results: Among the 14,238 ICU patients with AKI, BE showed a U-shaped relationship with risk of 30-day mortality for patients with AKI, and higher or lower BE values could increase the risk. Compared with normal base excess (−3~3 mEq/L), patients in different groups (BE ≤ −9 mEq/L, −9 mEq/L < BE ≤ −3 mEq/L, 3 mEq/L < BE ≤ 9 mEq/L, and BE > 9 mEq/L) had different HRs for mortality: 1.57 (1.40, 1.76), 1.26 (1.14, 1.39), 0.97 (0.83, 1.12), 1.53 (1.17, 2.02), respectively. The RCS analyses also showed a U-shaped curve between BE and the 30-day mortality risk.Conclusion: Our results suggest that higher and lower BE in patients with AKI would increase the risk of 30-day mortality. BE measured at administration could be a critical prognostic indicator for ICU patients with AKI and provide guidance for clinicians.