Objective: To investigate the prevalence, characteristics, and preventive status of skin injuries caused by personal protective equipment (PPE) in medical staff. Approach: A cross-sectional survey was conducted online for understanding skin injuries among medical staff fighting COVID-19 in February 8-22, 2020. Participants voluntarily answered and submitted the questionnaire with cell phone. The questionnaire items included demographic data, grade of PPE and daily wearing time, skin injury types, anatomical sites, and preventive measures. Univariable analyses and logistic regression analyses were used to explore the risk factors associated with skin injuries. Results: A total of 4,308 respondents were collected from 161 hospitals and 4,306 respondents were valid. The overall prevalence of skin injuries was 42.8% (95% confidence interval [CI] 41.30-44.30) with three types of devicerelated pressure injuries, moist-associated skin damage, and skin tear. Co-skin injuries and multiple location injuries were 27.4% and 76.8%, respectively. The logistic regression analysis indicated that sweating (95% CI for odds ratio [OR] 87.52-163.11), daily wearing time (95% CI for OR 1.61-3.21), male (95% CI for OR 1.11-2.13), and grade 3 PPE (95% CI for OR 1.08-2.01) were associated with skin injuries. Only 17.7% of respondents took prevention and 45.0% of skin injuries were treated. Innovation: This is the first cross-sectional survey to understand skin injuries in medical staff caused by PPE, which is expected to be a benchmark. Conclusion: The skin injuries among medical staff are serious, with insufficient prevention and treatment. A comprehensive program should be taken in the future.

Since December 2019, the medical staff fighting against COVID-19 frequently reported the device-related pressure injury (DRPI) caused by personal protective equipment (PPE). We conducted a cross-sectional survey online to investigate the prevalence and characteristics of DRPI among medical staff.Univariate and multivariate logistic regression analyses were employed to explore the risk factors associated with DRPI. A total of 4308 participants were collected and 4306 participants were valid from 161 hospitals in China. The overall prevalence of DRPI caused by PPE among medical staff was 30.03% Int Wound J. 2020;1-10.wileyonlinelibrary.com/journal/iwj (95% CI 28.69%-31.41%). The prevalence of male was more than that of female (42.25%, 95% CI 37.99-46.51% vs 26.36%, 95% CI 26.93-29.80%, P < .001).The categories were mainly stages 1 and 2, and the common anatomical locations were nose bridge, cheeks, ears, and forehead. Logistic regression analysis revealed that the risk factors were sweating (OR = 43.99, 95% CI 34.46-56.17), male (OR = 1.50, 95% CI 1.12-1.99), level 3 PPE (OR = 1.44, 95% CI 1.14-1.83), and longer wearing time (OR = 1.28, 95% CI 0.97-1.68). The prevalence of DRPI was high among medical staff wearing PPE against COVID-19, and the risk factors were sweating, male, wearing level 3 PPE, and longer wearing time.Comprehensive preventive interventions should be taken.

Background Coronavirus disease (COVID-19) has become a pandemic. The knowledge, attitudes, and practices (KAP) of the public play a major role in the prevention and control of infectious diseases. The objective of the present study was to evaluate the KAP of the Chinese public and to assess potential influencing factors related to practices. Methods A cross-sectional online survey was conducted in China in February 2020 via a self-designed questionnaire comprising 33 questions assessing KAP. Results For the 2136 respondents from 30 provinces or municipalities in China, the accurate response rate for the knowledge section ranged from 72.7 to 99.5%, and the average was 91.2%. Regarding attitude section, the percentage of positive attitudes (“strongly agree” and “agree”) ranged from 94.7 to 99.7%, and the average value was 98.0%. The good practices (“always” and “often”) results ranged from 76.1 to 99.5%, and the average value was 96.8%. The independent samples t-test revealed that gender and ethnic differences had no effect on knowledge, attitude or behaviour (P > 0.05). However, knowledge was associated with age (t = 4.842, p < 0.001), marital status (t = − 5.323, p < 0.001), education level (t = 8.441, p < 0.001), occupation (t = − 10.858, p < 0.001), and place of residence (t = 7.929, p < 0.001). Similarly, attitude was associated with marital status (t = − 2.383, p = 0.017), education level (t = 2.106, p = 0.035), occupation (t = − 4.834, p < 0.001), and place of residence (t = 4.242, p < 0.001). The multiple linear regression analysis results showed that the factors influencing practices were knowledge (t = − 3.281, p = 0.001), attitude (t = 18.756, p < 0.001), occupation (t = − 3.860, p < 0.001), education level (t = 3.136, p = 0.002), and place of residence (t = 3.257, p = 0.001). Conclusions The Chinese public exhibited a good level of knowledge of COVID-19, a positive attitude, and high adherence to good practices. COVID-19-related knowledge, attitudes and practices were affected by age, marital status, education level, occupation, and place of residence to varying degrees. In addition, practices were affected by knowledge and attitudes towards COVID-19.

To reduce delirium risk of patients in intensive care unit, nurses need to assess the risk of physical restraint and consider alternative measures, thereby to achieve the minimisation of the use of restraint.

Coronavirus disease 2019 (COVID-19) has become pandemic. Previous studies 1-3 on COVID-19 have been mainly centered on the epidemiology, clinical characteristics, radiological features, and treatment of patients with confirmed infection. Follow-up studies of discharged patients have been rarely reported. MethodsThis case series study was approved by the institutional review board of the Affiliated Hospital of Zunyi Medical University. The need for informed consent was waived because the data were entirely anonymized and the individuals could not be identified. This study follows the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guideline.We collected the clinical data of patients who had been cured and discharged from a hospital designated for patients with COVID-19 in Guizhou Province, China, between January 25, 2020, and February 26, 2020. All COVID-19 infections were classified into 4 different types-mild, moderate, severe, and critical-on the basis of the disease severity. 4 Patients could be discharged if they met discharge standards. 4 They were required to quarantine for 14 days in a designated hospital, 4 and their nasopharyngeal swabs were usually collected on the 7th and 14th days; however, swabs were collected anytime if the patients had clinical symptoms. Real-time reverse transcriptase-polymerase chain reaction (RT-PCR) was performed on nasopharyngeal swabs at the Centers for Disease Control and Prevention of Guizhou Province. The researchers performed follow-up for all the patients, and the demographic data, clinical symptoms, and radiographic and laboratory results at admission were extracted from the electronic medical records. P values were calculated with Pearson χ 2 tests, Fisher exact tests, or Wilcoxon-Mann-Whitney U tests as appropriate; all tests were 2-sided. Statistical significance was set at P < .05. Data calculations were performed with SPSS statistical software version 22.0 (IBM Corp). Data analysis was performed in April 2020. ResultsWe examined data for 69 patients in total (median age, 33 years; range, 2-78 years; 35 male patients [50.7%]). Eleven of the patients (15.9%) had positive RT-PCR results for the COVID-19 nucleic acid test but without any symptoms. Among the 11 patients (median age, 27 years; range, 4-58 years), there were 7 male patients (63.6%), and 3 patients (27.3%) had comorbidities. Most of the 11 patients had moderate (9 patients) or mild infection (1 patient); only 1 patient was classified as having critical infection. The median interval from discharge to positive RT-PCR results was 14 days (range, 9-17 days). None of the patients were medical staff. There were no substantial differences in the demographic and baseline clinical characteristics between the recurrence group and nonrecurrence group (median age, 27 years [range, 4-58 years] vs 34 years [range, 2-78 years]; number of cluster cases, 8 patients [72.7%] vs 41 patients [70.7%]; presence of comorbidities, 3 patients [27.3%] vs 14 patients [24.1%]; median duration o...

Despite increasing preventive efforts, pressure injury still occurs in intensive care patients. This study was aimed to describe pressure injury prevalence, risk factors, and prevention practices in adult intensive care patients. This was a multi‐centre, one‐day, prospective point prevalence study in which a total of 198 intensive care units from 21 provinces in China participated. Overall and ICU‐acquired prevalence in intensive care patients were 12.26% and 4.31%, respectively. Consistent with earlier reports, almost half of the ICU‐acquired pressure injuries were at stage I, one‐fourth were at stage 2, and the most common body sites for pressure injuries were sacral and heel region. Risk factors identified were consistent with prior studies. Repositioning was the most commonly used pressure injury prevention strategy, followed by alternating pressure mattresses/overlays, floating heels, and air‐filled mattresses/overlays. These reflect a good level of adherence to recommended international pressure injury prevention clinical practice guidelines. The results provide a baseline reference for overall and ICU‐acquired prevalence among adult intensive care patients in China. Future research on what contributed to the lower pressure injury incidence in China needs to be conducted to inform healthcare organisations on their future preventive strategies for pressure injury prevention.

Objectives To evaluate the resuscitative effects of mechanical and manual chest compression in patients with out-of-hospital cardiac arrest (OHCA). Methods All randomized controlled and cohort studies comparing the effects of mechanical compression and manual compression on cardiopulmonary resuscitation in OHCA patients were retrieved from the Cochrane Library, PubMed, EMBASE, and Ovid databases from the date of their establishment to January 14, 2019. The included outcomes were as follows: the return of spontaneous circulation (ROSC) rate, the rate of survival to hospital admission, the rate of survival to hospital discharge, and neurological function. After evaluating the quality of the studies and summarizing the results, RevMan5.3 software was used for the meta-analysis. Results In total, 15 studies (9 randomized controlled trials and 6 cohort studies) were included. The results of the meta-analysis showed that there were no significant differences in the resuscitative effects of mechanical and manual chest compression in terms of the ROSC rate, the rate of survival to hospital admission and survival to hospital discharge, and neurological function in OHCA patients (ROSC: RCT: OR = 1.12, 95% CI (0.90, 1.39), P = 0.31; cohort study: OR = 1.08, 95% CI (0.85, 1.36), P = 0.54; survival to hospital admission: RCT: OR = 0.95, 95% CI (0.75, 1.20), P = 0.64; cohort study: OR = 0.98 95% CI (0.79, 1.20), P = 0.82; survival to hospital discharge: RCT: OR = 0.87, 95% CI (0.68, 1.10), P = 0.24; cohort study: OR = 0.78, 95% CI (0.53, 1.16), P = 0.22; Cerebral Performance Category (CPC) score: RCT: OR = 0.88, 95% CI (0.64, 1.20), P = 0.41; cohort study: OR = 0.68, 95% CI (0.34, 1.37), P = 0.28). When the mechanical compression group was divided into Lucas and Autopulse subgroups, the Lucas subgroup showed no difference from the manual compression group in ROSC, survival to admission, survival to discharge, and CPC scores; the Autopulse subgroup showed no difference from the manual compression subgroup in ROSC, survival to discharge, and CPC scores. Conclusion There were no significant differences in resuscitative effects between mechanical and manual chest compression in OHCA patients. To ensure the quality of CPR, we suggest that manual chest compression be applied in the early stage of CPR for OHCA patients, while mechanical compression can be used as part of advanced life support in the late stage.

Background : A novel coronavirus disease that emerged in China in December 2019 (COVID-19) is an ongoing pandemic all over the world, leading to 823,626 people diagnosed and 40,598 deaths globally as of April 1, 2020. Nurses are providing care to patients with COVID-19 who require hospitalization. To ensure adequate response capacity and to maintain the health of nurses, it is important to analyse the actual work hours and the nurses reported preferred work hours per shift among frontline nurses. Objective : To analyse the actual work hours and preferred work hours per shift of nurses reports among frontline nurses fighting the COVID-19 epidemic and to explore the influencing factors on the nurses reported preferred work hours. Design : Cross-sectional survey Setting(s) This study was conducted in 10 designated hospitals providing treatments to patients with COVID-19 in China. Participants Nurses providing care to patients with COVID-19 in designated hospitals in China. Methods : A questionnaire with open-ended questions was used to assess frontline nurses caring for COVID-19 cases in 10 designated hospitals. Quantitative and qualitative methods were used to analyse the actual work hours, the nurses reported preferred work hours and factors influencing nurses reported preferred work hours among the frontline nurses. Results : A total of 109 nurses responded to the survey. The shift length exceeded the nurses’ preferred work hours [Median (interquartile range): 5.00 (2.00) h vs 4.00 (2.00) h; Minimum-Maximum: 4 - 12 h vs 4 - 8 h], and 60.55% (66/109) of the nurses regarded 4 h as the preferred number of work hours per shift. Five key themes associated with the influencing factors emerged, including circumstances; personal preventable equipment; the nurses’ physical and emotional needs of nurse; and the nurses’ safety needs and work intensity. Conclusions : These findings suggest that there is a gap between the actual work hours and the nurses preferred work hours among frontline nurses in different units and different posts. The main influencing factors were circumstances, personal protective equipment, the nurses’ physical and emotional needs, and the nurses’ safety needs and work intensity.