Coronavirus disease 2019 (COVID-19) was first identified in Wuhan, China, in December 2019. Although previous studies have described the clinical aspects of COVID-19, few studies have focused on the early detection of severe COVID-19. Therefore, this study aimed to identify the predictors of severe COVID-19 and to compare clinical features between patients with severe COVID-19 and those with less severe COVID-19. Patients admitted to designated hospital in the Henan Province of China who were either discharged or died prior to February 15, 2020 were enrolled retrospectively. Additionally, patients who underwent at least one of the following treatments were assigned to the severe group: continuous renal replacement therapy, high-flow oxygen absorption, noninvasive and invasive mechanical ventilation, or extracorporeal membrane oxygenation. The remaining patients were assigned to the non-severe group. Demographic information, initial symptoms, and first visit examination results were collected from the electronic medical records and compared between the groups. Multivariate logistic regression analysis was performed to determine the predictors of severe COVID-19. A receiver operating characteristic curve was used to identify a threshold for each predictor. Altogether,104 patients were enrolled in our study with 30 and 74 patients in the severe and non-severe groups, respectively. Multivariate logistic analysis indicated that patients aged �63 years (odds ratio = 41.0; 95% CI: 2.8, 592.4), with an absolute lymphocyte value of �1.02×10 9 /L (odds ratio = 6.1; 95% CI = 1.5, 25.2) and a C-reactive protein level of �65.08mg/L (odds ratio = 8.9; 95% CI = 1.0, 74.2) were at a higher risk of severe illness. Thus, our results could be helpful in the early detection of patients at risk for severe illness, enabling the implementation of effective interventions and likely lowering the morbidity of COVID-19 patients.

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Background Elevated low-density lipoprotein cholesterol (LDL-C) levels in childhood have recently been found to be the strongest predictive risk factor for coronary artery disease in adulthood. There is an increased level of LDL-C in children and adolescents with short stature. However, the underlying factors associated with increased LDL-C levels in children and adolescents with short stature are unknown. In addition, the insulin-like growth factor 1 (IGF-1) level in the short-stature population is usually below the normal reference range. The aim of this study was to investigate the relationship between IGF-1 standard deviation score (IGF-1 SDS) and LDL-C level in children and adolescents with short stature. Methods A cross-sectional study was conducted in a single centre of China, 557 short-stature children and adolescents whose height SDS was lower than − 2 SD after adjustment for age and gender were included. The related clinical and laboratory examinations, including anthropometric parameters, lipid profiles, IGF-1 levels and the levels of other cofactors, were assessed in all participants. Results The univariate analysis results showed a significant negative correlation between IGF-1 SDS and LDL-C levels ( P = 0.006). Furthermore, a nonlinear relationship was observed between IGF-1 SDS and LDL-C by smooth curve fitting after adjusting for possible confounders. A multivariate piecewise linear regression model revealed a significant negative correlation between IGF-1 SDS and LDL-C when the IGF-1 level was greater than − 2 SDS (β − 0.07, 95% CI -0.12, − 0.02; P = 0.006). However, we did not observe a significant relationship between IGF-1 SDS and LDL-C when the IGF-1 level was lower than − 2 SDS (β 0.08, 95% CI -0.02, 0.17; P = 0.119). Conclusion This study demonstrated a nonlinear relationship between IGF-1 and LDL-C independent of other potential confounding factors, suggesting that circulating IGF-1 may contribute to the regulation of LDL-C levels, thus meriting further investigation. Electronic supplementary material The online version of this article (10.1186/s12944-019-1062-z) contains supplementary material, which is available to authorized users.

Background Elevated triglyceride (TG) levels are a biomarker for cardiovascular disease (CVD) risk. The correlation between serum uric acid (SUA) and TG concentrations in adults or obese children is well established. However, studies on SUA and TG in children with short stature are limited. Aim To determine the relationship between SUA and TG levels in short children and adolescents. Method This was a cross-sectional evaluation of a cohort of 1095 patients with short stature (720 males and 375 females). The related clinical characteristics, including anthropometric and biochemical parameters, were determined. Results Smooth curve fitting, adjusted for potential confounders was performed, which indicated the existence of a non-linear relationship between these measures. Piecewise multivariate linear analysis revealed a significant positive relationship between SUA and TG at SUA concentrations over 7 mg/dL (β = 0.13, 95% CI: 0.05–0.22, P = 0.002) but no significant correlation at lower SUA levels (β = 0.01, 95% CI: 0.01–0.04, P = 0.799). Furthermore, a stratified analysis was performed to appraise changes in this relationship for different sexes and standard deviation levels of body mass index (BMI). The non-linear relationship remained consistent in males and females with BMI standard deviation scores (BMI SDS) ≥ 0, with inflection points of 6.71 mg/dL and 3.93 mg/dL, respectively. Within these two groups, SUA and TG levels showed a positive association when SUA levels were higher than the inflection point (β = 0.21, 95% CI: 0.11–0.31, P < 0.001 for males and β = 0.1, 95% CI: 0.03–0.17, P = 0.005 for females). However, a specific relationship was not observed at lower SUA levels. No significant relationships were found between SUA and TG levels in males and females with BMI SDS < 0. Conclusion The present study identified the non-linear association of SUA and TG levels with short children and adolescents. This relationship was based on BMI status. This finding suggests that health status should be considered for short stature children with high SUA levels, especially in children with a high BMI standard deviation score.