Dynamic changes of functional fitness, antibodies to SARS-CoV-2 and immunological indicators within 1 year after discharge in Chinese health care workers with severe COVID-19: a cohort study.

BACKGROUND: Few studies had described the health consequences of patients with coronavirus disease 2019 (COVID-19) especially in those with severe infections after discharge from hospital. Moreover, no research had reported the health consequences in health care workers (HCWs) with COVID-19 after discharge. We aimed to investigate the health consequences in HCWs with severe COVID-19 after discharge from hospital in Hubei Province, China. METHODS: We conducted an ambidirectional cohort study in "Rehabilitation Care Project for Medical Staff Infected with COVID-19" in China. The participants were asked to complete three physical examinations (including the tests of functional fitness, antibodies to SARS-CoV-2 and immunological indicators) at 153.4 (143.3, 164.8), 244.3 (232.4, 259.1), and 329.4 (319.4, 339.3) days after discharge, respectively. Mann-Whitney U test, Kruskal-Wallis test, t test, one-way ANOVA, χ2, and Fisher's exact test were used to assess the variance between two or more groups where appropriate. RESULTS: Of 333 HCWs with severe COVID-19, the HCWs' median age was 36.0 (31.0, 43.0) years, 257 (77%) were female, and 191 (57%) were nurses. Our research found that 70.4% (114/162), 48.9% (67/137), and 29.6% (37/125) of the HCWs with severe COVID-19 were considered to have not recovered their functional fitness in the first, second, and third functional fitness tests, respectively. The HCWs showed improvement in muscle strength, flexibility, and agility/dynamic balance after discharge in follow-up visits. The seropositivity of IgM (17.0% vs. 6.6%) and median titres of IgM (3.0 vs. 1.4) and IgG (60.3 vs. 45.3) in the third physical examination was higher than that in the first physical examination. In the third physical examination, there still were 42.1% and 45.9% of the HCWs had elevated levels of IL-6 and TNF-α, and 11.9% and 6.3% of the HCWs had decreased relative numbers of CD3+ T cells and CD4+ T cells. CONCLUSION: The HCWs with severe COVID-19 showed improvement in functional fitness within 1 year after discharge, active intervention should be applied to help their recovery if necessary. It is of vital significance to continue monitoring the functional fitness, antibodies to SARS-CoV-2 and immunological indicators after 1 year of discharge from hospital in HCWs with severe COVID-19.

Comparing the Effects of Two Culture Methods to Determine the Total Heterotrophic Bacterial Colony Count in Hospital Purified Water.

BACKGROUND: Accurately detecting the quantity of microorganisms in hospital purified water is of significant importance for early identification of microbial contamination and reducing the occurrence of water-borne hospital infections. The choice of detection method is a prerequisite for ensuring accurate results. Traditional Plate Count Agar (PCA) belongs to a high-nutrient medium, and there may be limitations in terms of accuracy or sensitivity in detecting microorganisms in hospital purified water. On the other hand, Reasoner's 2A agar (R2A) has characteristics, such as low-nutrient levels, low cultivation temperature, and extended incubation time, providing advantages in promoting the growth of aquatic microorganisms. This study, through comparing the differences in total colony counts between two detection methods, aims to select the method more suitable for the growth of aquatic microorganisms, offering new practical insights for accurately detecting the total count of heterotrophic bacteria in hospital purified water. METHODS: The most commonly used plate count agar (PCA) method, and the R2A agar culture were adopted to detect microorganisms and determine the total number of bacterial colonies in the water for oral diagnosis and treatment water and terminal rinse water for endoscopes in medical institutions. The two water samples were inoculated by pour plate and membrane filtration methods, respectively. Using statistical methods including Spearman and Pearson correlation, Wilcoxon signed-rank sum test, paired-Chi-square test, and linear regression, we analyze the differences and associations in the bacterial counts cultivated through two different methods. RESULTS: In 142 specimens of the water, the median and interquartile range of the heterotrophic bacterial colony number under the R2A culture method and under the PCA culture method were 200 (Q1-Q3: 25-18,000) and 6 (Q1-Q3: 0-3700). The total number of heterotrophic bacteria colonies cultured in R2A medium for 7 days was more than that cultured in PCA medium for 2 days (P < 0.05). The linear regression results showed a relatively strong linear correlation between the number of colonies cultured by the R2A method and that cultured by the PCA method (R2 = 0.7264). The number of bacterial species detected on R2A agar medium is greater than that on PCA agar medium. CONCLUSION: The R2A culture method can better reflect the actual number of heterotrophic bacterial colonies in hospital purified water. After logarithmic transformation, the number of colonies cultured by the two methods showed a linear correlation.

Age at SARS-CoV-2 infection and psychological and physical recovery among Chinese health care workers with severe COVID-19 at 28 months after discharge: A cohort study.

Background: No prior study had reported the psychological and physical recovery of patients with COVID-19 2~3 years after discharge from the hospital. Moreover, it is not clear whether there is any difference in the health status of the patients with COVID-19 of different ages after discharge from the hospital. Methods: Embedding in the "Rehabilitation Care Project for Medical Staff Infected with COVID-19" in China, this study included 271 health care workers (HCWs) with severe COVID-19. Their status of health-related quality of life, persistent symptoms, functional fitness and immune function at 28 months after discharge were followed, and compared according to tertiles of age at SARS-CoV-2 infection (group of younger (≤ 33 years); medium (34-42 years); and older (≥43 years)). Multivariate linear regression and multivariable adjusted logistic regression models were applied in investigating the associations of age at SARS-CoV-2 infection and outcomes. Results: At 28 months after discharge, 76% of the HCWs with severe COVID-19 had symptom of fatigue/weakness; 18.7% of the HCWs with severe COVID-19 did not fully recover their functional fitness; the decrease of CD3+ T cells, CD8+ T cells and the increase of natural killer cells accounted for 6.6, 6.6, and 5.5%, respectively. Compared with the HCWs with severe COVID-19 in younger group, HCWs with severe COVID-19 in older group had lower scores regarding physical functioning, role physical, bodily pain and role emotional; HCWs with severe COVID-19 in older group had higher risk of cough, joint pain, hearing loss and sleep disorder; HCWs with severe COVID-19 in older group scored lower on flexibility test. The variance of relative numbers of CD3+ T cells, CD8+ T cells and natural killer cells among HCWs with severe COVID-19 of different age groups were significant. Conclusions: This study demonstrated that older HCWs with severe COVID-19 recovered slower than those with younger age regarding health-related quality of life, persistent symptoms, functional fitness and immune function at 28 months after discharge. Effective exercise interventions regarding flexibility should be performed timely to speed their rehabilitation, especially among those with older age.

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Coronavirus disease 2019 (COVID-19) is an acute respiratory infectious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. It is highly contagious and can cause death in severe cases. As reported by the World Health Organization (WHO), as of 6:36 pm Central European Summer Time (CEST), 12 August 2022, there had been 585 950 285 confirmed cases of COVID-19, including 6 425 422 deaths (WHO, 2022).

Recovery of functional fitness, lung function, and immune function in healthcare workers with nonsevere and severe COVID-19 at 13 months after discharge from the hospital: a prospective cohort study.

OBJECTIVES: This study aimed to evaluate the recovery of functional fitness, lung function, and immune function in healthcare workers (HCWs) with nonsevere and severe COVID-19 at 13 months after discharge from the hospital. METHODS: The participants of "Rehabilitation Care Project for Medical Staff Infected with COVID-19" underwent a functional fitness test (muscle strength, flexibility, and agility/dynamic balance), lung function test, and immune function test (including cytokines and lymphocyte subsets) at 13 months after discharge. RESULTS: The project included 779 HCWs (316 nonsevere COVID-19 and 463 severe COVID-19). This study found that 29.1% (130/446) of the HCWs have not yet recovered their functional fitness. The most affected lung function indicator was lung perfusion capacity (34% with diffusion capacity for carbon monoxide-single breath <80%). The increase of interleukin-6 (64/534, 12.0%) and natural killer cells (44/534, 8.2%) and the decrease of CD3+ T cells (58/534, 10.9%) and CD4+ T cells (26/534, 4.9%) still existed at 13 months after discharge. No significant difference was found in the HCWs with nonsevere and severe COVID-19 regarding recovery of functional fitness, lung function, and immune function at 13 months after discharge. CONCLUSION: The majority of Chinese HCWs with COVID-19 had recovered their functional fitness, lung function, and immune function, and the recovery status in HCWs with severe COVID-19 is no worse than that in HCWs with nonsevere COVID-19 at 13 months after discharge from the hospital.

Long-Term Effects of COVID-19 on Health Care Workers 1-Year Post-Discharge in Wuhan.

INTRODUCTION: To assess the long-term consequences of coronavirus disease (COVID-19) among health care workers (HCWs) in China (hereafter surviving HCWs). METHODS: A total of 303 surviving HCWs were included. Lung (pulmonary function test, 6-min walk test [6MWT], chest CT), physical (St. George's Respiratory Questionnaire [SGRQ], Modified Medical Research Council dyspnea scale [mMRC], and Borg scale), and psychiatric functions (Essen Trauma Inventory) were evaluated during the 1-year follow-up. RESULTS: Surviving HCWs had an abnormal diffusion capacity 1 year post-discharge. Participants with a reduced carbon monoxide diffusing capacity (DLCO) comprised 43.48%. The proportion of HCWs with a median 6MWT distance below the lower limit of the normal was 19.4%. An abnormal CT pattern was observed in 37.5% of the HCWs. The SGRQ, mMRC, and Borg scores of surviving HCWs, especially those with critical/severe disease, were significantly higher than those in the normal population. Probable post-traumatic stress disorder (PTSD) was reported in 21.9% of the surviving HCWs. Diffusion capacity impairment was associated with women. Critical/severe illness and nurses were associated with impaired physical function. CONCLUSIONS: Most surviving HCWs, especially female HCWs, still had an abnormal diffusion capacity at 1 year. The physical and psychiatric functions of surviving HCWs were significantly worse than those of the healthy population. Long-term follow-up of pulmonary, physical, and psychiatric functions for surviving HCWs is required.

Possible posttraumatic stress disorder in Chinese frontline healthcare workers who survived COVID-19 6 months after the COVID-19 outbreak: prevalence, correlates, and symptoms.

Suffering from COVID-19 and witnessing the suffering and deaths of patients with COVID-19 may place frontline healthcare workers (HCWs) at particularly high risk for posttraumatic stress disorder (PTSD); however, few data are available on the clinical characteristics of PTSD among frontline HCWs who survived COVID-19 ("surviving HCWs" hereafter). The present study examined the prevalence, correlates, and clinical symptoms of possible PTSD in surviving HCWs 6 months after the COVID-19 outbreak in China. A total of 291 surviving HCWs and 42 age- and gender-matched COVID-19-free frontline HCWs (control group) were recruited and administered the Chinese Essen Trauma Inventory, which was used to assess the presence of possible PTSD according to DSM-IV-TR criteria. Survivors' clinical data and characteristics of exposure to COVID-19 were collected via self-report questionnaires. Surviving HCWs had significantly higher rates of possible PTSD than controls (19.9% vs. 4.8%, P = 0.017). Correlates of PTSD in survivors were ICU admission (OR = 8.73, P = 0.003), >10 respiratory symptoms during the most symptomatic period of COVID-19 (OR = 3.08, P = 0.006), the residual symptom of dizziness (OR = 2.43, P = 0.013), the residual symptom of difficult breathing (OR = 2.23, P = 0.027), life in danger due to COVID-19 (OR = 16.59, P = 0.006), and exposure to other traumatic events (OR = 2.94, P = 0.035). Less commonly seen PTSD symptoms in survivors were having nightmares about the event (34.5%), suddenly feeling like they were living through the event suddenly (25.9%), being unable to remember an important part of the event (32.8%), and overalertness (31.0%). Nearly one-fifth of the surviving HCWs had possible PTSD 6 months after the COVID-19 outbreak. Mental health services for this vulnerable population should include periodic screening for PTSD, expanded social support, and, when necessary, psychotherapy and psychopharmacological treatment.

Automated Cluster Detection of Health Care-Associated Infection Based on the Multisource Surveillance of Process Data in the Area Network: Retrospective Study of Algorithm Development and Validation.

BACKGROUND: The cluster detection of health care-associated infections (HAIs) is crucial for identifying HAI outbreaks in the early stages. OBJECTIVE: We aimed to verify whether multisource surveillance based on the process data in an area network can be effective in detecting HAI clusters. METHODS: We retrospectively analyzed the incidence of HAIs and 3 indicators of process data relative to infection, namely, antibiotic utilization rate in combination, inspection rate of bacterial specimens, and positive rate of bacterial specimens, from 4 independent high-risk units in a tertiary hospital in China. We utilized the Shewhart warning model to detect the peaks of the time-series data. Subsequently, we designed 5 surveillance strategies based on the process data for the HAI cluster detection: (1) antibiotic utilization rate in combination only, (2) inspection rate of bacterial specimens only, (3) positive rate of bacterial specimens only, (4) antibiotic utilization rate in combination + inspection rate of bacterial specimens + positive rate of bacterial specimens in parallel, and (5) antibiotic utilization rate in combination + inspection rate of bacterial specimens + positive rate of bacterial specimens in series. We used the receiver operating characteristic (ROC) curve and Youden index to evaluate the warning performance of these surveillance strategies for the detection of HAI clusters. RESULTS: The ROC curves of the 5 surveillance strategies were located above the standard line, and the area under the curve of the ROC was larger in the parallel strategy than in the series strategy and the single-indicator strategies. The optimal Youden indexes were 0.48 (95% CI 0.29-0.67) at a threshold of 1.5 in the antibiotic utilization rate in combination-only strategy, 0.49 (95% CI 0.45-0.53) at a threshold of 0.5 in the inspection rate of bacterial specimens-only strategy, 0.50 (95% CI 0.28-0.71) at a threshold of 1.1 in the positive rate of bacterial specimens-only strategy, 0.63 (95% CI 0.49-0.77) at a threshold of 2.6 in the parallel strategy, and 0.32 (95% CI 0.00-0.65) at a threshold of 0.0 in the series strategy. The warning performance of the parallel strategy was greater than that of the single-indicator strategies when the threshold exceeded 1.5. CONCLUSIONS: The multisource surveillance of process data in the area network is an effective method for the early detection of HAI clusters. The combination of multisource data and the threshold of the warning model are 2 important factors that influence the performance of the model.