The impact of goggle-associated harms to health and working status of nurses during management of COVID-19

BackgroundTo investigate the impact of goggles on their health and clinical practice during management of patients with COVID-19. Methods231 nurse practitioners were enrolled who worked in isolation region in designated hospitals to admit patients with COVID-19 in China. Demographic data, goggle-associated symptoms and underlying reasons, incidence of medical errors or exposures, the effects of fog in goggles on practice were all collected. Data were stratified and analyzed by age or working experience. Risk factors of goggle-associated medical errors were analyzed by multivariable logistical regression analysis. FindingsGoggle-associated symptoms and foggy goggles widely presented in nurses. The most common symptoms were headache, skin pressure injury and dizziness. Headache, vomit and nausea were significantly fewer reported in nurses with longer working experience while rash occurred higher in this group. The underlying reasons included tightness of goggles, unsuitable design and uncomfortable materials. The working status of nurses with more working experience was less impacted by goggles. 11.3% nurses occurred medical exposures in clinical practice while 19.5% nurses made medical errors on patients. The risk factors for medical errors were time interval before adapting to goggle-associated discomforts, adjusting goggles and headache. InterpretationGoggle-associated symptoms and fog can highly impact the working status and contribute to medical errors during management of COVID-19. Increased the experience with working in PPE through adequate training and psychological education may benefit for relieving some symptoms and improving working status. Improvement of goggle design during productive process was strongly suggested to reduce incidence of discomforts and medical errors.

Validation of reported risk factors for disease classification and prognosis in COVID-19: a descriptive and retrospective study

Risk indicators viral load (ORF1ab Ct), lymphocyte percentage (LYM%), C-reactive protein (CRP), interleukin-6 (IL-6), procalcitonin (PCT) and lactic acid (LA) in COVID-19 patients have been proposed in recent studies. However, the predictive effects of those indicators on disease classification and prognosis remains largely unknown. We dynamically measured those reported indicators in 132 cases of COVID-19 patients including the moderate-cured (moderated and cured), severe-cured (severe and cured) and critically ill (died). Our data showed that CRP, PCT, IL-6, LYM%, lactic acid and viral load could predict prognosis and guide classification of COVID-19 patients in different degrees. CRP, IL-6 and LYM% were more effective than other three factors in predicting prognosis. For disease classification, CRP and LYM% were sensitive in identifying the types between critically ill and severe (or moderate). Notably, among the investigated factors, LYM% was the only one that could distinguish between the severe and moderate types. Collectively, we concluded that LYM% was the most sensitive and reliable predictor for disease typing and prognosis. During the COVID-19 pandemic, the precise classification and prognosis prediction are critical for saving the insufficient medical resources, stratified treatment and improving the survival rate of critically ill patients. We recommend that LYM% be used independently or in combination with other indicators in the management of COVID-19.

A special case of COVID-19 with long duration of viral shedding for 49 days

Prolonged viral shedding is associated with severe status and poor prognosis of COVID-19 patients. Unexpectedly, here we report a non-severe patient with the longest duration of viral shedding. According to the investigation on the clinical and epidemiological information of this case, we concluded that this type of virus might have a low toxicity and transmissibility, but have a prolonged infective ability and was hardly to be eliminated in the body with regular therapy. However, infusion of plasma from recovered patients showed high efficiency in elimination of this virus. Our findings might shed light on the management of COVID-19.

Lymphopenia predicts disease severity of COVID-19: a descriptive and predictive study

BackgroundCoronavirus disease-2019 (COVID-19) is a rapidly escalating epidemic caused by SARS-CoV-2. Identification of a simple and effective indicator to assess disease severity and prognosis is urgently needed. MethodsDynamic changes of blood lymphocyte percentage (LYM%) in 15 death cases, 15 severe cases as well as 40 moderate cases of COVID-19 patients were retrospectively analyzed. A Time-LYM% model (TLM) was established according to the descriptive studies and was validated in 92 hospitalized cases. ResultsResults from death and severe cases showed that LYM% in blood tests were inversely associated with the severity and prognosis of COVID-19. LYM% in moderate type of patients with COVID-19 remained higher than 20% 10-12 days after symptom onset. In contrast, LYM% was lower than 20% in severe cases. However, LYM% in severe cases was higher than 5% 17-19 days after the onset of the disease, while it fell below 5% in death cases. Accordingly, we established a Time-LYM% model (TLM), which was validated as an independent criterion of disease classification in another 92 hospitalized patients with COVID-19. ConclusionLymphopenia can be used as an indicator of disease severity and prognosis of COVID-19 patients. TLM is worth of application in the clinical practice.