Background: To evaluate the accuracy of arm circumference (AC) compared with other anthropometric and functional indicators as a predictor of sarcopenia risk in community-dwelling older adults. Methods: This was a cross-sectional, analytical, population-based study derived from a household survey involving individuals aged 60 years or older. Measurements of AC, calf circumference (CC), and variables related to muscle strength, muscle mass, and functional performance were collected, including the Timed Up and Go test, sit-to-stand test, and gait speed. Results: The sample comprised 708 older adults, predominantly female (64.7%), aged between 60 and 94 years. The prevalence of sarcopenia was 14.7%, with 4.9% classified as severe. AC showed a negative association with sarcopenia (β=–0.01, 95% confidence interval [CI] 0.75–0.92, p<0.01) and reduced the odds of sarcopenia by 17% for each additional centimeter (odds ratio=0.83, 95% CI 0.75–0.92). The comparison of the areas under the receiver operating characteristic curves (AUC) indicated similar performance between AC and CC (z=0.24, p=0.81). The diagnostic accuracy of AC was slightly higher than that of CC in male (27.1% vs. 26.6%) and female (43.0% vs. 37.6%). Conclusion Both AC and CC demonstrated high discriminative capacity for sarcopenia, with cutoff points that balanced sensitivity and specificity. AC stands out as a viable, simple, and effective alternative for sarcopenia screening in community-dwelling older adults.

Background: The genetic basis for hyperglycaemia in pregnancy remain unclear. This study aimed to uncover the genetic determinants of gestational diabetes mellitus (GDM) and investigate their applications. Methods: We performed a meta-analysis of genome-wide association studies (GWAS) for GDM in Chinese women (464 cases and 1,217 controls), followed by de novo replications in an independent Chinese cohort (564 cases and 572 controls) and in silico replication in European (12,332 cases and 131,109 controls) and multi-ethnic populations (5,485 cases and 347,856 controls). A polygenic risk score (PRS) was derived based on the identified variants. Results: Using the genome-wide scan and candidate gene approaches, we identified four susceptibility loci for GDM. These included three previously reported loci for GDM and type 2 diabetes mellitus (T2DM) at MTNR1B (rs7945617, odds ratio [OR], 1.64; 95% confidence interval [CI],1.38 to 1.96]), CDKAL1 (rs7754840, OR, 1.33; 95% CI, 1.13 to 1.58), and INS-IGF2-KCNQ1 (rs2237897, OR, 1.48; 95% CI, 1.23 to 1.79), as well as a novel genome-wide significant locus near TBR1-SLC4A10 (rs117781972, OR, 2.05; 95% CI, 1.61 to 2.62; Pmeta=7.6×10-9), which has not been previously reported in GWAS for T2DM or glycaemic traits. Moreover, we found that women with a high PRS (top quintile) had over threefold (95% CI, 2.30 to 4.09; Pmeta=3.1×10-14) and 71% (95% CI, 1.08 to 2.71; P=0.0220) higher risk for GDM and abnormal glucose tolerance post-pregnancy, respectively, compared to other individuals. Conclusion Our results indicate that the genetic architecture of glucose metabolism exhibits both similarities and differences between the pregnant and non-pregnant states. Integrating genetic information can facilitate identification of pregnant women at a higher risk of developing GDM or later diabetes.

Background: The genetic basis for hyperglycaemia in pregnancy remain unclear. This study aimed to uncover the genetic determinants of gestational diabetes mellitus (GDM) and investigate their applications. Methods: We performed a meta-analysis of genome-wide association studies (GWAS) for GDM in Chinese women (464 cases and 1,217 controls), followed by de novo replications in an independent Chinese cohort (564 cases and 572 controls) and in silico replication in European (12,332 cases and 131,109 controls) and multi-ethnic populations (5,485 cases and 347,856 controls). A polygenic risk score (PRS) was derived based on the identified variants. Results: Using the genome-wide scan and candidate gene approaches, we identified four susceptibility loci for GDM. These included three previously reported loci for GDM and type 2 diabetes mellitus (T2DM) at MTNR1B (rs7945617, odds ratio [OR], 1.64; 95% confidence interval [CI],1.38 to 1.96]), CDKAL1 (rs7754840, OR, 1.33; 95% CI, 1.13 to 1.58), and INS-IGF2-KCNQ1 (rs2237897, OR, 1.48; 95% CI, 1.23 to 1.79), as well as a novel genome-wide significant locus near TBR1-SLC4A10 (rs117781972, OR, 2.05; 95% CI, 1.61 to 2.62; Pmeta=7.6×10-9), which has not been previously reported in GWAS for T2DM or glycaemic traits. Moreover, we found that women with a high PRS (top quintile) had over threefold (95% CI, 2.30 to 4.09; Pmeta=3.1×10-14) and 71% (95% CI, 1.08 to 2.71; P=0.0220) higher risk for GDM and abnormal glucose tolerance post-pregnancy, respectively, compared to other individuals. Conclusion Our results indicate that the genetic architecture of glucose metabolism exhibits both similarities and differences between the pregnant and non-pregnant states. Integrating genetic information can facilitate identification of pregnant women at a higher risk of developing GDM or later diabetes.

Background: The genetic basis for hyperglycaemia in pregnancy remain unclear. This study aimed to uncover the genetic determinants of gestational diabetes mellitus (GDM) and investigate their applications. Methods: We performed a meta-analysis of genome-wide association studies (GWAS) for GDM in Chinese women (464 cases and 1,217 controls), followed by de novo replications in an independent Chinese cohort (564 cases and 572 controls) and in silico replication in European (12,332 cases and 131,109 controls) and multi-ethnic populations (5,485 cases and 347,856 controls). A polygenic risk score (PRS) was derived based on the identified variants. Results: Using the genome-wide scan and candidate gene approaches, we identified four susceptibility loci for GDM. These included three previously reported loci for GDM and type 2 diabetes mellitus (T2DM) at MTNR1B (rs7945617, odds ratio [OR], 1.64; 95% confidence interval [CI],1.38 to 1.96]), CDKAL1 (rs7754840, OR, 1.33; 95% CI, 1.13 to 1.58), and INS-IGF2-KCNQ1 (rs2237897, OR, 1.48; 95% CI, 1.23 to 1.79), as well as a novel genome-wide significant locus near TBR1-SLC4A10 (rs117781972, OR, 2.05; 95% CI, 1.61 to 2.62; Pmeta=7.6×10-9), which has not been previously reported in GWAS for T2DM or glycaemic traits. Moreover, we found that women with a high PRS (top quintile) had over threefold (95% CI, 2.30 to 4.09; Pmeta=3.1×10-14) and 71% (95% CI, 1.08 to 2.71; P=0.0220) higher risk for GDM and abnormal glucose tolerance post-pregnancy, respectively, compared to other individuals. Conclusion Our results indicate that the genetic architecture of glucose metabolism exhibits both similarities and differences between the pregnant and non-pregnant states. Integrating genetic information can facilitate identification of pregnant women at a higher risk of developing GDM or later diabetes.

Background: The genetic basis for hyperglycaemia in pregnancy remain unclear. This study aimed to uncover the genetic determinants of gestational diabetes mellitus (GDM) and investigate their applications. Methods: We performed a meta-analysis of genome-wide association studies (GWAS) for GDM in Chinese women (464 cases and 1,217 controls), followed by de novo replications in an independent Chinese cohort (564 cases and 572 controls) and in silico replication in European (12,332 cases and 131,109 controls) and multi-ethnic populations (5,485 cases and 347,856 controls). A polygenic risk score (PRS) was derived based on the identified variants. Results: Using the genome-wide scan and candidate gene approaches, we identified four susceptibility loci for GDM. These included three previously reported loci for GDM and type 2 diabetes mellitus (T2DM) at MTNR1B (rs7945617, odds ratio [OR], 1.64; 95% confidence interval [CI],1.38 to 1.96]), CDKAL1 (rs7754840, OR, 1.33; 95% CI, 1.13 to 1.58), and INS-IGF2-KCNQ1 (rs2237897, OR, 1.48; 95% CI, 1.23 to 1.79), as well as a novel genome-wide significant locus near TBR1-SLC4A10 (rs117781972, OR, 2.05; 95% CI, 1.61 to 2.62; Pmeta=7.6×10-9), which has not been previously reported in GWAS for T2DM or glycaemic traits. Moreover, we found that women with a high PRS (top quintile) had over threefold (95% CI, 2.30 to 4.09; Pmeta=3.1×10-14) and 71% (95% CI, 1.08 to 2.71; P=0.0220) higher risk for GDM and abnormal glucose tolerance post-pregnancy, respectively, compared to other individuals. Conclusion Our results indicate that the genetic architecture of glucose metabolism exhibits both similarities and differences between the pregnant and non-pregnant states. Integrating genetic information can facilitate identification of pregnant women at a higher risk of developing GDM or later diabetes.

Scales that detect noninvasive ventilation (NIV) failure need to have adequate clinimetric properties to be reliable. This study aimed to compare the clinimetric properties of the Heart rate, Acidosis, Consciousness, Oxygenation, Respiratory rate (HACOR) and updated HACOR scales when applied to hypoxemic adult patients undergoing NIV. Methods: This prospective study applied the HACOR and updated HACOR scales to hypoxemic patients after one hour of NIV in an emergency department setting. A second application of the scales was performed after ten minutes to assess reliability (intraclass correlation coefficient), measurement error (standard error of measurement and minimum detectable difference), ceiling and floor effects, convergent validity by correlation (Pearson’s r) with peripheral oximetry saturation (SpO2), and predictive validity (area under the receiver operating characteristic [ROC] curve) for the outcome of needing invasive mechanical ventilation. Results: Sixty patients were included in this study (59.45±17.48 years; Simplified Acute Physiology Score III, 56.1±13.95; 30% with respiratory disease and 25% with cardiovascular disease). After 1 hour of NIV, patients had a HACOR score of 3 (interquartile range [IQR], 1.0–5.0) and an updated HACOR score of 5 (IQR, 3.0–8.87). Clinimetric properties were adequate for both versions of the HACOR scale but were superior for the updated version, including predictive validity (ROC [95% CI], 0.78 [0.64–0.91] vs. 0.73 [0.57–0.89]) and the absence of the ceiling effect. Conclusions: Both versions of the HACOR scale demonstrated adequate clinimetric properties for predicting NIV failure, with the updated HACOR version showing superior predictive validity and no ceiling effect compared with the original version.

Objective: This post-hoc analysis of the AtTEnd trial explored differences in the prognostic characteristics and in the efficacy of atezolizumab between Asians and non-Asians. Methods: The role of Asian race was evaluated on progression-free survival (PFS) using Cox-models and on time to appearance of new lesions using Fine and Gray models. Results: From October 2018 to February 2022, 549 patients were randomized, of whom, 20.4% were Asian. Asians showed a better prognostic profile in terms of age, body mass index, Eastern Cooperative Oncology Group performance status, disease status and previous treatments. The prognostic impact of Asian race on PFS was confirmed in the placebo arm (adjusted hazard ratio [HR]=0.41; 95% confidence interval [CI]=0.24–0.70). In proficient mismatch repair (pMMR) tumors, the HRs for PFS comparing atezolizumab versus placebo were 0.82 (95% CI=0.63–1.05) in non-Asians, and 1.42 (95% CI=0.80–2.50) in Asians. In the pMMR population randomized to atezolizumab, the subdistribution HRs comparing Asians to non-Asians were 0.68 (95% CI=0.43–1.09) for progression with new lesions and 1.21 (95% CI=0.73–2.03) for progression without new lesions. Asians showed a higher occurrence of severe adverse events in atezolizumab compared to placebo arm (Asians: 82.1% vs. 64.3%, p=0.036; non-Asian: 63.3% vs. 63.6%, p=0.949). Conclusion Race seems to affect the safety of the addition of atezolizumab and, in pMMR tumors, also its efficacy. In the atezolizumab arm, Asian patients seem to have a lower cumulative incidence of new lesions when primary tumor regrowth was considered a competing risk, and a higher cumulative incidence of primary tumor regrowth when new lesions appearance was the competing risk.