Association of COVID-19 Lockdown With Gestational Diabetes Mellitus.

Importance: The ongoing pandemic of COVID-19 is still affecting our life, but the effects of lockdown measures on gestational diabetes mellitus (GDM) in pregnant women remain unclear. Aim: To investigate the association between COVID-19 lockdown and GDM. Subjects and Methods: Medical records of 140844 pregnant women during 2015-2020 were extracted from 5 hospitals in Guangdong Province, China. Pregnant women who underwent the COVID-19 Level I lockdown (1/23 - 2/24/2020) during pregnancy were defined as the exposed group (N=20472) and pregnant women who underwent the same calendar months during 2015-2019 (1/23 - 2/24) were defined as the unexposed group (N=120372). Subgroup analyses were used to explore the potential susceptible exposure window of COVID-19 lockdown on GDM. Cumulative exposure is quantitatively estimated by assigning different weights to response periods with different exposure intensities. A logistic regression model was used to estimate the association between COVID-19 lockdown exposure and GDM. Results: The rates of GDM in the exposed and unexposed groups were 15.2% and 12.4%, respectively. The overall analyses showed positive associations (odds ratio, OR=1.22, 95%CI: 1.17, 1.27) between lockdown exposure and GDM risk in all pregnant women. More pronounced associations were found in women who underwent the COVID-19 lockdown in their first four months of pregnancy, and the adjusted OR values ranged from 1.24 (95%CI: 1.10, 1.39) in women with 5-8 gestational weeks (GWs) to 1.35 (95%CI: 1.20, 1.52) with < 5 GWs. In addition, we found a positive exposure-response association of cumulative lockdown exposure with the risk of GDM. Conclusions: The COVID-19 lockdown was associated with an increased risk of GDM, and the first four months of pregnancy may be the window for sensitive exposure.

Association of COVID-19 Lockdown With Gestational Diabetes Mellitus

Importance The ongoing pandemic of COVID-19 is still affecting our life, but the effects of lockdown measures on gestational diabetes mellitus (GDM) in pregnant women remain unclear. Aim To investigate the association between COVID-19 lockdown and GDM. Subjects and Methods Medical records of 140844 pregnant women during 2015-2020 were extracted from 5 hospitals in Guangdong Province, China. Pregnant women who underwent the COVID-19 Level I lockdown (1/23 - 2/24/2020) during pregnancy were defined as the exposed group (N=20472) and pregnant women who underwent the same calendar months during 2015-2019 (1/23 - 2/24) were defined as the unexposed group (N=120372). Subgroup analyses were used to explore the potential susceptible exposure window of COVID-19 lockdown on GDM. Cumulative exposure is quantitatively estimated by assigning different weights to response periods with different exposure intensities. A logistic regression model was used to estimate the association between COVID-19 lockdown exposure and GDM. Results The rates of GDM in the exposed and unexposed groups were 15.2% and 12.4%, respectively. The overall analyses showed positive associations (odds ratio, OR=1.22, 95%CI: 1.17, 1.27) between lockdown exposure and GDM risk in all pregnant women. More pronounced associations were found in women who underwent the COVID-19 lockdown in their first four months of pregnancy, and the adjusted OR values ranged from 1.24 (95%CI: 1.10, 1.39) in women with 5-8 gestational weeks (GWs) to 1.35 (95%CI: 1.20, 1.52) with < 5 GWs. In addition, we found a positive exposure-response association of cumulative lockdown exposure with the risk of GDM. Conclusions The COVID-19 lockdown was associated with an increased risk of GDM, and the first four months of pregnancy may be the window for sensitive exposure.

Associations of COVID-19 lockdown with gestational length and preterm birth in China.

BACKGROUND: The effects of COVID-19 lockdown measures on maternal and fetal health remain unclear. We examined the associations of COVID-19 lockdown with gestational length and preterm birth (PTB) in a Chinese population. METHODS: We obtained medical records of 595,396 singleton live infants born between 2015 and 2020 in 5 cities in Guangdong Province, South China. The exposed group (N = 101,900) included women who experienced the COVID-19 Level I lockdown (1/23-2/24/2020) during pregnancy, while the unexposed group (N = 493,496) included women who were pregnant during the same calendar months in 2015-2019. Cumulative exposure was calculated based on days exposed to different levels of emergency responses with different weighting. Generalized linear regression models were applied to estimate the associations of lockdown exposure with gestational length and risk of PTB (< 37 weeks). RESULTS: The exposed group had a shorter mean gestational length than the unexposed group (38.66 vs 38.74 weeks: adjusted ß = - 0.06 week [95%CI, - 0.07, - 0.05 week]). The exposed group also had a higher risk of PTB (5.7% vs 5.3%; adjusted OR = 1.08 [95%CI, 1.05, 1.11]). These associations seemed to be stronger when exposure occurred before or during the 23rd gestational week (GW) than during or after the 24th GW. Similarly, higher cumulative lockdown exposure was associated with a shorter gestational length and a higher risk of PTB. CONCLUSIONS: The COVID-19 lockdown measures were associated with a slightly shorter gestational length and a moderately higher risk of PTB. Early and middle pregnancy periods may be a more susceptible exposure window.

Hospitalization Costs of COVID-19 Cases and Their Associated Factors in Guangdong, China: A Cross-Sectional Study.

Background: The ongoing COVID-19 pandemic has brought significant challenges to health system and consumed a lot of health resources. However, evidence on the hospitalization costs and their associated factors in COVID-19 cases is scarce. Objectives: To describe the total and components of hospitalization costs of COVID-19 cases, and investigate the associated factors of costs. Methods: We included 876 confirmed COVID-19 cases admitted to 33 designated hospitals from January 15th to April 27th, 2020 in Guangdong, China, and collected their demographic and clinical information. A multiple linear regression model was performed to estimate the associations of hospitalization costs with potential associated factors. Results: The median of total hospitalization costs of COVID-19 cases was $2,869.4 (IQR: $3,916.8). We found higher total costs in male (% difference: 29.7, 95% CI: 15.5, 45.6) than in female cases, in older cases than in younger ones, in severe cases (% difference: 344.8, 95% CI: 222.5, 513.6) than in mild ones, in cases with clinical aggravation than those without, in cases with clinical symptoms (% difference: 47.7, 95% CI: 26.2, 72.9) than those without, and in cases with comorbidities (% difference: 21.1%, 21.1, 95% CI: 4.4, 40.6) than those without. We also found lower non-pharmacologic therapy costs in cases treated with traditional Chinese medicine (TCM) therapy (% difference: -47.4, 95% CI: -64.5 to -22.0) than cases without. Conclusion: The hospitalization costs of COVID-19 cases in Guangdong were comparable to the national level. Factors associated with higher hospitalization costs included sex, older age, clinical severity and aggravation, clinical symptoms and comorbidities at admission. TCM therapy was found to be associated with lower costs for some non-pharmacologic therapies.

Reduction of air pollutants and associated mortality during and after the COVID-19 lockdown in China: Impacts and implications.

Although strict lockdown measurements implemented during the COVID-19 pandemic have dramatically reduced the anthropogenic-based emissions, changes in air quality and its health impacts remain unclear in China. We comprehensively described air pollution during and after the lockdown periods in 2020 compared with 2018-2019, and estimated the mortality burden indicated by the number of deaths and years of life lost (YLL) related to the air pollution changes. The mean air quality index (AQI), PM10, PM2.5, NO2, SO2 and CO concentrations during the lockdown across China declined by 18.2 (21.2%), 27.0 µg/m3 (28.9%), 10.5 µg/m3 (18.3%), 8.4 µg/m3 (44.2%), 13.1 µg/m3 (38.8%), and 0.3 mg/m3 (27.3%) respectively, when compared to the same periods during 2018-2019. We observed an increase in O3 concentration during the lockdown by 5.5 µg/m3 (10.4%), and a slight decrease after the lockdown by 3.4 µg/m3 (4.4%). As a result, there were 51.3 (95%CI: 32.2, 70.1) thousand fewer premature deaths (16.2 thousand during and 35.1 thousand after the lockdown), and 1066.8 (95%CI: 668.7, 1456.8) thousand fewer YLLs (343.3 thousand during and 723.5 thousand after the lockdown) than these in 2018-2019. Our findings suggest that the COVID-19 lockdown has caused substantial decreases in air pollutants except for O3, and that substantial human health benefits can be achieved when strict control measures for air pollution are taken to reduce emissions from vehicles and industries. Stricter tailored policy solutions of air pollution are urgently needed in China and other countries, especially in well-developed industrial regions, such as upgrading industry structure and promoting green transportation.

A SARS-CoV-2 neutralizing antibody with extensive Spike binding coverage and modified for optimal therapeutic outcomes.

COVID-19 pandemic caused by SARS-CoV-2 constitutes a global public health crisis with enormous economic consequences. Monoclonal antibodies against SARS-CoV-2 can provide an important treatment option to fight COVID-19, especially for the most vulnerable populations. In this work, potent antibodies binding to SARS-CoV-2 Spike protein were identified from COVID-19 convalescent patients. Among them, P4A1 interacts directly with and covers majority of the Receptor Binding Motif of the Spike Receptor-Binding Domain, shown by high-resolution complex structure analysis. We further demonstrate the binding and neutralizing activities of P4A1 against wild type and mutant Spike proteins or pseudoviruses. P4A1 was subsequently engineered to reduce the potential risk for Antibody-Dependent Enhancement of infection and to extend its half-life. The engineered antibody exhibits an optimized pharmacokinetic and safety profile, and it results in complete viral clearance in a rhesus monkey model of COVID-19 following a single injection. These data suggest its potential against SARS-CoV-2 related diseases.

Harnessing digital health to objectively assess cancer-related fatigue: The impact of fatigue on mobility performance.

OBJECTIVE: Cancer-related fatigue (CRF) is highly prevalent among cancer survivors, which may have long-term effects on physical activity and quality of life. CRF is assessed by self-report or clinical observation, which may limit timely diagnosis and management. In this study, we examined the effect of CRF on mobility performance measured by a wearable pendant sensor. METHODS: This is a secondary analysis of a clinical trial evaluating the benefit of exercise in cancer survivors with chemotherapy-induced peripheral neuropathy (CIPN). CRF status was classified based on a Functional Assessment of Chronic Illness Therapy-Fatigue (FACIT-F) score ≤ 33. Among 28 patients (age = 65.7±9.8 years old, BMI = 26.9±4.1kg/m2, sex = 32.9%female) with database variables of interest, twenty-one subjects (75.9%) were classified as non-CRF. Mobility performance, including behavior (sedentary, light, and moderate to vigorous activity (MtV)), postures (sitting, standing, lying, and walking), and locomotion (e.g., steps, postural transitions) were measured using a validated pendant-sensor over 24-hours. Baseline psychosocial, Functional Assessment of Cancer Therapy-General (FACT-G), Falls Efficacy Scale-International (FES-I), and motor-capacity assessments including gait (habitual speed, fast speed, and dual-task speed) and static balance were also performed. RESULTS: Both groups had similar baseline clinical and psychosocial characteristics, except for body-mass index (BMI), FACT-G, FACIT-F, and FES-I (p<0.050). The groups did not differ on motor-capacity. However, the majority of mobility performance parameters were different between groups with large to very large effect size, Cohen's d ranging from 0.91 to 1.59. Among assessed mobility performance, the largest effect sizes were observed for sedentary-behavior (d = 1.59, p = 0.006), light-activity (d = 1.48, p = 0.009), and duration of sitting+lying (d = 1.46, p = 0.016). The largest correlations between mobility performance and FACIT-F were observed for sitting+lying (rho = -0.67, p<0.001) and the number of steps per day (rho = 0.60, p = 0.001). CONCLUSION: The results of this study suggest that sensor-based mobility performance monitoring could be considered as a potential digital biomarker for CRF assessment. Future studies warrant evaluating utilization of mobility performance to track changes in CRF over time, response to CRF-related interventions, and earlier detection of CRF.