METHODS: 20-Plex proteins were quantified using Human Magnetic Luminex® assay (R&D Systems, USA) from plasma and SF of OA (n = 14) and non-OA (n = 14) patients. Ingenuity Pathway Analysis (IPA) software was used to predict the relationship and possible interaction of molecules pertaining to OA.
RESULTS: There were significant differences in plasma level for matrix metalloproteinase (MMP)-3, interleukin (IL)-27, IL-8, IL-4, tumour necrosis factor-alpha, MMP-1, IL-15, IL-21, IL-10, and IL-1 beta between the groups, as well as significant differences in SF level for IL-15, IL-8, vascular endothelial growth factor (VEGF), MMP-1, and IL-18. Our predictive OA model demonstrated that toll-like receptor (TLR) 2, macrophage migration inhibitory factor (MIF), TLR4 and IL-1 were the main regulators of IL-1B, IL-4, IL-8, IL-10, IL-15, IL-21, IL-27, MMP-1 and MMP-3 in the plasma system; whilst IL-1B, TLR4, IL-1, and basigin (BSG) were the regulators of IL-4, IL-8, IL-10, IL-15, IL-18, IL-21, IL-27, MMP-1, and MMP-3 in the SF system.
CONCLUSION: The elevated plasma IL-8 and SF IL-18 may be associated with the pathogenesis of OA via the activation of MMP-3.
Method: The guidelines were developed by an appointed workgroup comprising experts in the Asia Pacific region, following reviews of previously published guidelines and recommendations relevant to each section.
Results: It recommends that healthcare facilities review specific risk factors and develop effective prevention strategies, which would be cost effective at local levels. Gaps identified are best closed using a quality improvement process. Surveillance of SSIs is recommended using accepted international methodology. The timely feedback of the data analysed would help in the monitoring of effective implementation of interventions.
Conclusions: Healthcare facilities should aim for excellence in safe surgery practices. The implementation of evidence-based practices using a quality improvement process helps towards achieving effective and sustainable results.
MATERIAL AND METHODS: A cross-sectional study was conducted using an English-language online survey. The participants were invited via a web link sent using social network platforms. It included sociodemographic- and profession-related characteristics. COVID-19-associated risks were assessed (e.g., being on the front line, doing swabs, satisfaction about protective equipment, and management protocols). Assessment of SQ was done using the Pittsburgh Sleep Quality Index (PSQI) and various medical errors were recorded.
RESULTS: A total of 217 HCWs completed the survey with mean (±standard deviation) age of 35.8 (±7.3) years; 56.2% were male, 18.43% had comorbidities, and 61.75% experienced sleep difficulties before the COVID-19 crisis. This work reports a 78.8% prevalence of poor SQ, with the mean (standard deviation) global PSQI score of 9.36 (±4.4). HCWs with poor sleep experienced more positive comorbid profile (23.64% versus 6.52%, p=0.01). Working on the front lines of COVID-19 was associated with poor sleep (69.59% versus 47.83%, p=0.006). Among the participants, 77.42% performed medical errors, particularly not checking for drug allergies (17.97%), dispensing medication with incomplete instructions (20.74%), providing incorrect doses or overdosing (14.75%), incorrectly explaining the use of medication (9.22%), and prescribing a drug to the wrong patient (10.14%).
CONCLUSION: This nationwide survey reported high prevalence of poor SQ among HCWs during the COVID-19 pandemic. Being an HCW on the front lines of COVID-19 and doing swabs with a positive comorbidity was associated with poor sleep.