Associations between post-traumatic stress symptoms and quality of life among psychiatric healthcare personnel in China during the COVID-19 pandemic: A network approach

Background Post-traumatic stress symptoms (PTSS) are commonly reported by psychiatric healthcare personnel during the coronavirus disease 2019 (COVID-19) pandemic and negatively affect quality of life (QOL). However, associations between PTSS and QOL at symptom level are not clear. This study examined the network structure of PTSS and its connection with QOL in psychiatric healthcare personnel during the COVID-19 pandemic. Methods This cross-sectional study was carried out between March 15 and March 20, 2020 based on convenience sampling. Self-report measures including the 17-item Post-Traumatic Stress Disorder Checklist – Civilian version (PCL-C) and World Health Organization Quality of Life Questionnaire - Brief Version (WHOQOL-BREF) were used to measure PTSS and global QOL, respectively. Network analysis was used to investigate the central symptoms of PTSS and pattern of connections between PTSS and QOL. An undirected network was constructed using an extended Bayesian Information Criterion (EBIC) model, while a directed network was established based on the Triangulated Maximally Filtered Graph (TMFG) method. Results Altogether, 10,516 psychiatric healthcare personnel completed the assessment. "Avoidance of thoughts” (PTSS-6), "Avoidance of reminders” (PTSS-7), and "emotionally numb” (PTSS-11) were the most central symptoms in the PTSS community, all of which were in the Avoidance and Numbing domain. Key bridge symptoms connecting PTSS and QOL were "Sleep disturbances” (PTSS-13), "Irritability” (PTSS-14) and "Difficulty concentrating” (PTSS-15), all of which were within the Hyperarousal domain. Conclusion In this sample, the most prominent PTSS symptoms reflected avoidance while symptoms of hyper-arousal had the strongest links with QOL. As such, these symptom clusters are potentially useful targets for interventions to improve PTSS and QOL among healthcare personnel at work under pandemic conditions.

Associations between post-traumatic stress symptoms and quality of life among psychiatric healthcare personnel in China during the COVID-19 pandemic: A network approach.

Background: Post-traumatic stress symptoms (PTSS) are commonly reported by psychiatric healthcare personnel during the coronavirus disease 2019 (COVID-19) pandemic and negatively affect quality of life (QOL). However, associations between PTSS and QOL at symptom level are not clear. This study examined the network structure of PTSS and its connection with QOL in psychiatric healthcare personnel during the COVID-19 pandemic. Methods: This cross-sectional study was carried out between March 15 and March 20, 2020 based on convenience sampling. Self-report measures including the 17-item Post-Traumatic Stress Disorder Checklist - Civilian version (PCL-C) and World Health Organization Quality of Life Questionnaire - Brief Version (WHOQOL-BREF) were used to measure PTSS and global QOL, respectively. Network analysis was used to investigate the central symptoms of PTSS and pattern of connections between PTSS and QOL. An undirected network was constructed using an extended Bayesian Information Criterion (EBIC) model, while a directed network was established based on the Triangulated Maximally Filtered Graph (TMFG) method. Results: Altogether, 10,516 psychiatric healthcare personnel completed the assessment. "Avoidance of thoughts" (PTSS-6), "Avoidance of reminders" (PTSS-7), and "emotionally numb" (PTSS-11) were the most central symptoms in the PTSS community, all of which were in the Avoidance and Numbing domain. Key bridge symptoms connecting PTSS and QOL were "Sleep disturbances" (PTSS-13), "Irritability" (PTSS-14) and "Difficulty concentrating" (PTSS-15), all of which were within the Hyperarousal domain. Conclusion: In this sample, the most prominent PTSS symptoms reflected avoidance while symptoms of hyper-arousal had the strongest links with QOL. As such, these symptom clusters are potentially useful targets for interventions to improve PTSS and QOL among healthcare personnel at work under pandemic conditions.

Protective Effect of Inactivated COVID-19 Vaccines against Omicron BA.2 Infection in Guangzhou: A Test-Negative Case-Control Real-World Study.

This study aims to explore the relationship between the doses of inactivated COVID-19 vaccines received and SARS-CoV-2 Omicron infection in the real-world setting, so as to preliminarily evaluate the protective effect induced by COVID-19 vaccination. We conducted a test-negative case-control study and recruited the test-positive cases and test-negative controls in the outbreak caused by Omicron BA.2 in April 2022 in Guangzhou, China. All the participants were 3 years and older. The vaccination status between the case group and the control group was compared in the vaccinated and all participants, respectively, to estimate the immune protection of inactivated COVID-19 vaccines. After adjusting for sex and age, compared with a mere single dose, full vaccination of inactivated COVID-19 vaccines (OR = 0.191, 95% CI: 0.050 to 0.727) and booster vaccination (OR = 0.091, 95% CI: 0.011 to 0.727) had a more superior protective effect. Compared with one dose, the second dose was more effective in males (OR = 0.090), as well as two doses (OR = 0.089) and three doses (OR = 0.090) among individuals aged 18-59. Whereas, when compared with the unvaccinated, one dose (OR = 7.715, 95% CI: 1.904 to 31.254) and three doses (OR = 2.055, 95% CI: 1.162 to 3.635) could contribute to the increased risk of Omicron infection after adjusting for sex and age. Meanwhile, by contrast with unvaccinated individuals, the result of increased risk was also manifested in the first dose in males (OR = 12.400) and one dose (OR = 21.500), two doses (OR = 1.890), and a booster dose (OR = 1.945) in people aged 18-59. In conclusion, the protective effect of full and booster vaccination with inactivated COVID-19 vaccines exceeded the incomplete vaccination, of which three doses were more effective. Nevertheless, vaccination may increase the risk of Omicron infection compared with unvaccinated people. This may result from the transmission traits of BA.2, the particularity and stronger protection awareness of the unvaccinated population, as well as the ADE effect induced by the decrease of antibody titers after a long time of vaccination. It is crucial to explore this issue in depth for the formulation of future COVID-19 vaccination strategies.

Effect of Vaccination Time Intervals on SARS-COV-2 Omicron Variant Strain Infection in Guangzhou: A Real-World Matched Case-Control Study.

In April 2022, a COVID-19 outbreak caused by the Omicron variant emerged in Guangzhou. A case-control study was conducted to explore the relationship between vaccination intervals and SARS-CoV-2 infection in the real world. According to the vaccination dose and age information of the cases, a 1:4 matched case-control sample was established, finally including n = 242 for the case group and n = 968 for the control group. The results indicated that among the participants who received three vaccine doses, those with an interval of more than 300 days between the receipt of the first vaccine dose and infection (or the first contact with a confirmed case) were less likely to be infected with SARS-CoV-2 than those with an interval of less than 300 days (OR = 0.67, 95% CI = 0.46-0.99). After age-stratified analysis, among participants aged 18-40 years who received two doses of vaccine, those who received the second dose more than 30 days after the first dose were less likely to be infected with SARS-CoV-2 (OR = 0.53, 95% CI = 0.30-0.96). Our findings suggest that we need to extend the interval between the first dose and the second dose and further explore the optimal interval between the first and second and between the second and third doses in order to improve vaccine efficacy.

Associations between depressive symptoms and quality of life among residents of Wuhan, China during the later stage of the COVID-19 pandemic: A network analysis.

BACKGROUND: Various populations have experienced significant increases in depression and decreased quality of life (QOL) during the coronavirus disease 2019 (COVID-19) pandemic. This network analysis study was designed to elucidate interconnections between particular depressive symptoms and different aspects of QOL and identify the most clinically important symptoms in this network among adults in Wuhan China, the initial epicenter of the COVID-19 pandemic. METHODS: This cross-sectional, convenience-sampling study (N = 2459) was conducted between May 25 to June 18, 2020, after the lockdown policy had been lifted in Wuhan. Depressive symptoms and QOL were measured with the Patient Health Questionnaire-9 (PHQ-9) and first two items of the World Health Organization Quality of Life Questionnaire - brief version (WHOQOL-BREF), respectively. A network structure was constructed from the extended Bayesian Information Criterion (EBIC) model. Network centrality strength and bridge strength were evaluated along with the stability of the derived network model. RESULTS: Loss of energy (DEP-4) and Guilt feelings (DEP-6) were the two central symptoms with the highest strength as well as the two most prominent bridge symptoms connecting the clusters of depression and quality of life (QOL) in tandem with the two nodes from the QOL cluster. Network structure and bridge strengths remained stable after randomly dropping 75 % of the sample. CONCLUSION: Interventions targeting "Loss of energy" and "Guilt feelings" should be evaluated as strategies for reducing depressive symptoms and promoting improved QOL in COVID-19-affected populations.

Semen parameters in men recovered from COVID-19.

The novel coronavirus disease (COVID-19) pandemic is emerging as a global health threat and shows a higher risk for men than women. Thus far, the studies on andrological consequences of COVID-19 are limited. To ascertain the consequences of COVID-19 on sperm parameters after recovery, we recruited 41 reproductive-aged male patients who had recovered from COVID-19, and analyzed their semen parameters and serum sex hormones at a median time of 56 days after hospital discharge. For longitudinal analysis, a second sampling was obtained from 22 of the 41 patients after a median time interval of 29 days from first sampling. Compared with controls who had not suffered from COVID-19, the total sperm count, sperm concentration, and percentages of motile and progressively motile spermatozoa in the patients were significantly lower at first sampling, while sperm vitality and morphology were not affected. The total sperm count, sperm concentration, and number of motile spermatozoa per ejaculate were significantly increased and the percentage of morphologically abnormal sperm was reduced at the second sampling compared with those at first in the 22 patients examined. Though there were higher prolactin and lower progesterone levels in patients at first sampling than those in controls, no significant alterations were detected for any sex hormones examined over time following COVID-19 recovery in the 22 patients. Although it should be interpreted carefully, these findings indicate an adverse but potentially reversible consequence of COVID-19 on sperm quality.

Operational Experiences in China and Statistical Issues on the Conduct of Clinical Trials During the COVID-19 Pandemic.

The COVID-19 outbreak is impacting clinical trials in many ways, such as patient recruitment, data collection and data analysis. To proceed in this difficult time, the adoption of new technologies and new approaches for conducting clinical trials needs to be accelerated. Simultaneously, regulatory agencies such as the US FDA and EMA have issued guidance to help the pharmaceutical industry conduct clinical trials of medical products during the COVID-19 pandemic. In this article, we will address some statistical issues and operational experiences in the conduction of clinical trials during the COVID-19 pandemic. Specifically, we will share experiences in the applications of remote clinical trials in China. Statistical issues related to protocol modifications caused by COVID-19 will be raised.