ObjectiveTo compare the disinfection effect of peracetic acid versus glutaraldehyde in disinfection of flexible endoscope, and provide suggestions for choosing endoscopic disinfectant.MethodsWe searched literatures in PubMed, Embase, Cochrane Central Library, China National Knowledge Infrastructure, Wanfang database and VIP database, with the retrieval time from the establishment of each database to July 2017, screening and comparing the disinfection qualification rate of peroxyacetic acid versus glutaraldehyde in immersion disinfection of flexible endoscope. The number of flexible endoscopies after disinfection was the main effect index, and a fixed effect model analysis was performed.ResultsSix comparative studies were enrolled in this Meta-analysis, with a total of 786 flexible endoscopes. The result of Meta-analysis showed that the qualification rate of disinfection of peracetic acid was higher than that of glutaraldehyde with the same disinfection time [relative risk=1.09, 95% confidence interval (1.06, 1.13), P<0.000 01].ConclusionThe disinfection effect of peroxyacetic acid immersion method is better than that of glutaraldehyde.
ObjectiveTo find out the influencing factors of electrocardiogram (ECG) monitor configuration decision in surgical nursing units and form a scientific configuration standard, so as to provide a basis for the reasonable configuration of ECG monitors.MethodsFrom May to June 2018, the indexes and weights affecting the configuration of ECG monitors in surgical nursing units of a large public hospital were determined by interview survey method and analytic hierarchy process.ResultsThe influencing factors for configuration of ECG monitors in surgical nursing units were the number of operations, number of rescues, number of emergencies, number of deaths, and number of patients transferred to and out of intensive care unit, and the weights were 0.459 7, 0.224 9, 0.155 3, 0.111 2, and 0.049 0, respectively. The classification of nursing units was taken as plan, and the configuration standard of ECG monitors was established.ConclusionThe configuration model of ECG monitors in surgical nursing units based on analytic hierarchy process realizes the combination of qualitative and quantitative analysis, which provides scientific and reasonable reference for the configuration of ECG monitors.
ObjectiveTo understand the current status of healthcare human resources (HHR) in a large public hospital, predict the HHR demand aligned with the development of the hospital, and provide reference basis and feasible solutions for HHR planning for high-quality development of the large public hospital. MethodsBased on grey model and auto regressive integrated moving average model, a variance reciprocal method for weight allocation was applied to set up the combination forecasting model. Different types of HHR demand of the large public hospital from 2024 to 2026 were predicted and the accuracies of the three different model predictions were compared. ResultsThe numbers of total personnel, health technical personnel, physicians, nurses, and technicians predicted by the combination forecasting model for 2026 were 17654, 13041, 4389, 6198, and 2264, respectively. The corresponding average annual growth rates from 2024 to 2026 were 5.54%, 5.55%, 5.37%, 4.27%, and 5.60%, respectively. Compared with the two single forecasting models, the combination forecasting model had the smallest average absolute errors, mean squared errors, and mean absolute percentage errors for predicting the numbers of total personnel, nurses, and technicians. It also had the smallest average absolute error and mean absolute percentage error for predicting the number of health technical personnel, and the smallest average absolute error for predicting the number of physicians. ConclusionsCompared with the single forecasting model, the combination forecasting model shows fewer system errors and better predictive results. The demand for total personnel, health technical personnel, physicians, nurses, and technicians of this large public hospital will continue to increase, so planning and reserving staff in advance is a key to high-quality development of the hospital.
ObjectiveTo study the distributions of virulence genes of Klebsiella pneumoniae (KP) and the distribution of hypervirulent KP (HvKP), and assess the performance of a single gene to predict HvKP.MethodsPolymerase chain reaction (PCR) method was used to analyze 12 virulence-related genes (entB, irp2, iroN, iucA, mrkD, fimH, c-rmpA, p-rmpA2, p-rmpA, wzy-K1, allS and peg-344) and drug-resistance gene blaKPC among 376 clinical KP strains collected from January 2016 to December 2018. Sequence types (ST) of KP were determined after sequencing and comparison, following the detection of 7 house-keeping genes (gapA, infB, mdh, pgi, phoE, rpoB and tonB) by PCR method. Statistical analyses were made for the distributions of virulence genes of KP and the distribution of HvKP with GraphPad Prism 8 software.ResultsAmong the 376 KP strains, the positive rates of entB, irp2, iroN, iucA, mrkD, fimH, c-rmpA, p-rmpA2, p-rmpA, wzy-K1, allS and peg-344 were 100.0%, 76.9%, 22.1%, 28.2%, 97.6%, 97.1%, 1.6%, 24.5%, 21.0%, 7.4%, 4.8% and 31.6%, respectively. The positive rates of the aforementioned virulence genes in the blaKPC-positive group (n=167) were 100.0%, 94.0%, 7.2%, 16.8%, 97.0%, 96.4%, 0.0%, 15.0%, 6.6%, 0.0%, 0.0% and 21.0%, respectively, and those in the blaKPC-negative group (n=209) were 100.0%, 63.2%, 34.0%, 37.3%, 98.1%, 97.6%, 2.9%, 32.1%, 32.5%, 13.4%, 8.6% and 40.2%, respectively; there was no statistically significant difference in entB, mrkD or fimH between the two groups (P>0.05), the positive rate of irp2 was higher in the blaKPC-positive group than that in the blaKPC-negative group (P<0.05), and the positive rates of the rest virulence-related genes were lower in the blaKPC-positive group than those in the blaKPC-negative group (P<0.05). The rate of HvKP in the blaKPC-negative group was higher than that in the blaKPC-positive group (38.3% vs. 18.0%, P<0.05). As a marker of HvKP, iucA showed high sensitivity and specificity (90.9% and 97.7%), followed by p-rmpA2 (83.6% and 100.0%) and iroN (73.6% and 99.2%). ST11 accounted for 87.4% in the blaKPC-positive group, while ST23, ST20, ST54 and ST29 were the four primary types in the blaKPC-negative group, accounting for 23.4% totally.ConclusionsDifferent virulence genes mean different distributions in KP. blaKPC-negative KP is more virulent than blaKPC-positive KP. iucA and p-rmpA2 could serve as good predicators of HvKP. Armed with extreme virulence and drug-resistance, blaKPC-positive HvKP is of great clinical concern.