Global prevalence of potentially pathogenic free-living amoebae in sewage and sewage-related environments-systematic review with meta-analysis.

Free-living amoebae (FLA) include amphizoic microorganisms important in public health, widely isolated from air, water, and soil. However, its occurrence in sewage-related environments still needs to be systematically documented. This study summarizes the occurrence of FLA in sewage-related environments through a systematic review with meta-analysis. A total of 1983 scientific article were retrieved from different databases, of which 35 were selected and analyzed using a random effects forest plot model with a 95% confidence interval (IC). The pooled overall prevalence of FLA in sewage across 12 countries was 68.96% (95% IC = 58.5-79.42). Subgroup analysis indicates high prevalence in all environments analyzed, including sewage water from the sewage treatment plant (81.19%), treated sewage water (75.57%), sewage-contaminated water (67.70%), sediment contaminated by sewage (48.91%), and sewage water (47.84%). Prevalence values of Acanthamoeba spp., Hartmanella/Vermamoeba spp., and Naegleria spp. are 47.48%, 28.24%, and 16.69%, respectively. Analyzing the species level, the distribution is as follows: Acanthamoeba palestinensis (88%), A. castellanii (23.74%), A. astronyxis (19.18%), A. polyphaga (13.59%), A. culbertsoni (12.5%), A. stevensoni (8.33%), A. tubiashi (4.35%) and A. hatchetti (1.1%), Naegleria fowleri (28.4%), N. gruberi (25%), N. clarki (8.33%), N. australiensis (4.89%) and N. italica (4.29%), Hartmannella/Vermamoeba exundans (40%) and H.V. vermiform (32.61%). Overall, our findings indicate a high risk associated with sewage-related environments, as the prevalence of FLA, including pathogenic strains, is high, even in treated sewage water. The findings of this study may be valuable both for risk remediation actions against amoebic infections and for future research endeavors.

Global prevalence of free-living amoebae in solid matrices - A systematic review with meta-analysis.

The ubiquitous free-living amoebae (FLA) are microorganisms of significant medical, sanitary, and ecological importance. However, their characterization within solid matrices such as soil, dust, sediment, mud, sludge, and compost remain to be systematized. In this study, we conducted a systematic review with meta-analysis to explore the global distribution of FLA in solid matrices. From the analysis of 104 out of 4,414 scientific articles retrieved from different databases, it was found that the general global prevalence of FLA in solid matrices was of 55.13% (95% confidence interval (CI) 49.32-60.94). Specifically, FLA prevalence was high in soil (72.40%, 95% CI 69.08-75.73), sediment (57.91%, 95% CI 50.01-65.81), mud (52.90%, 95% CI 24.01-81.78), dust (48.60%, 95% CI 43.00-54.19), and sewage sludge (40.19%, 95% CI 30.68-49.70). In aerosols it was comparatively lower (17.21%, 95% CI 12.76-21.66). Acanthamoeba spp. (52.23%) and Hartmanella/Vermamoeba spp. (36.06%) were found to be more prevalent, whereas Naegleria spp. (34.98%) and Balamuthia spp. (27.32%) were less prevalent. The distribution of the highest global prevalence values for species of Acanthamoeba spp., considering different publication periods of the studies, is as follows: A. hatchetti (51.46%), A. rhysodes (47.49%), A. polyphaga (36.37%), A. culbertsoni (34.31%), A. castellanii (34.21%), and A. lenticulata (32.82%). For other FLA species, the distribution is: Hartmannella/Vermamoeba vermiformis (91.57%), Naegleria fowleri (42.32%), Naegleria gruberi (32.39%), and Balamuthia mandrillaris (25%). The most prevalent Acanthamoeba genotypes were T4 (33.38%) and T3 (23.94%). Overall, the global prevalence of FLA in solid matrices is as high as or greater than that reported in water by previous systematic reviews. Thus, actions aimed at reducing exposure to FLA or exploring their ecological dynamics should consider not only water but also the various solid matrices. The finding outlined here can provide valuable insights for such actions, e.g., informing on the level of exposure to FLA, or on the microbial biodiversity of specific environmental compartments.

Productivity evaluation of radiologists interpreting computed tomography scans using statistical process control charts.

Radiology service managers search for efficient ways to monitor productivity and improve capacity. One way to assess radiologists' productivity is by measuring their time to complete reports. Radiology reporting times (RRTs) may be monitored using statistical tools, such as process control charts (CCs). This study was carried out in the radiology sector of a University-based general hospital with 850 inward beds. Productivity was monitored using CCs. The selected control variable was RRTs, and process capability was calculated using Cp and Cpk indices. Only chest computed tomography scans were analyzed, totaling 2862 exams over a 6-month period. Our objective was to develop a simple tool to monitor radiologist performance, as given by RRT, over time. For that, we constructed CCs using data from 10 radiologists to monitor the stability of their RRTs. Only 3 radiologists presented mean times below the group average; 6 displayed a trend in RRTs that characterized performance improvement, while 4 displayed the opposite trend. Capability measures for the group indicated a process that is not capable. We demonstrate that CCs may be a useful tool for monitoring radiologists' performances in CT scans interpretation. Results demonstrated that in the individual CT reporting process, common cause variability is the type of variability most frequently observed, being most likely related to natural variations in features of the images analyzed. Lastly, CCs may also assist in decision making in the sector, such as establishing minimum productivity goals based on historical performance.

Systematic Layout Planning of a Radiology Reporting Area to Optimize Radiologists' Performance.

Optimizing radiologists' performance is a major priority for managers of health services/systems, since the radiologists' reporting activity imposes a severe constraint on radiology productivity. Despite that, methods to optimize radiologists' reporting workplace layout are scarce in the literature. This study was performed in the Radiology Division (RD) of an 850-bed University-based general hospital. The analysis of the reporting workplace layout was carried out using the systematic layout planning (SLP) method, in association with cluster analysis as a complementary tool in early stages of SLP. Radiologists, architects, and hospital managers were the stakeholders consulted for the completion of different stages of the layout planning process. A step-by-step description of the proposed methodology to plan an RD reporting layout is presented. Clusters of radiologists were defined using types of exams reported and their frequency of occurrence as clustering variables. Sectors with high degree of interaction were placed in proximity in the new RD layout, with separation of noisy and quiet areas. Four reporting cells were positioned in the quiet area, grouping radiologists by subspecialty, as follows: cluster 1-abdomen; cluster 2-musculoskeletal; cluster 3-neurological, vascular and head & neck; cluster 4-thoracic and cardiac. The creation of reporting cells has the potential to limit unplanned interruptions and enhance the exchange of knowledge and information within cells, joining radiologists with the same expertise. That should lead to improvements in productivity, allowing managers to more easily monitor radiologists' performance.