24 research outputs found
Early and delayed suture adjustments after adjustable suture strabismus surgery: a randomized controlled trial
Background: Adjustable sutures increase the success rate of strabismus surgery. However, the optimal timing of postoperative suture adjustment remains controversial. This trial was aimed at comparing the surgical outcomes and pain scores of early or 2 – 4 h and delayed or 24 h postoperative suture adjustment in adult patients undergoing strabismus surgery.
Methods: An open-label, prospective, randomized, comparative interventional study was performed in consecutive adult patients scheduled for eye muscle surgery. Patients were randomized into two groups: the early group, with suture adjustment 2 – 4 h postoperatively, and the delayed group, with suture adjustment 24 h postoperatively. Subjective pain scores during the adjustment were also analyzed. The angles of misalignment at 1 and 3 months and the success rate at 3 months postoperatively were compared.
Results: Forty-five (90%) patients completed the follow-up, including 23 (92%) in the early adjustment group and 22 (88%) in the delayed adjustment group, with a mean (standard deviation) age of 25.6 (9.5) years and a male-to-female ratio of 46.7:53.3. Thirty patients (66.7%) had exotropia, and 15 (33.3%) patients had esotropia. Both groups had comparable baseline characteristics (all P > 0.05). The mean pain scores during adjustment did not differ significantly between groups (P > 0.05). The postoperative angles of alignment were comparable between the groups before suture adjustment and at the 1- and 3-month follow-ups (all P > 0.05). The success rate in the early adjustment group was slightly higher (87.0% versus 63.6%), but the difference was not statistically significant (P > 0.05). The success rate was comparable between the groups in patients with esotropia or exotropia (both P > 0.05).
Conclusions: Although the early adjustment group had a slightly higher success rate, the difference was not significant. Both groups had comparable subjective pain scores during adjustment. Future clinical trials should be performed different time intervals for postoperative suture adjustment, and subjective and objective outcomes, such as diplopia and stereopsis, should be compared between patients with a first strabismus surgery and those who underwent reoperation. This could better resolve the persistent controversy related to the optimal time for suture adjustment
Use of production functions in assessing the profitability of shares of insurance companies
In this study the production functions (Cobb-Douglas, Zener-Rivanker, and the transcendental production function) have been used to assess the profitability of insurance companies, by reformulating these nonlinear functions based on the introduction of a set of variables that contribute to increase the explanatory capacity of the model. Then the best production function commensurate with the nature of the variable representing the profitability of insurance companies was chosen, to use it to assess the efficiency of their profitability versus the use of different factors of production and thus the possibility of using it in forecasting. It was found that the proposed model of the production function "Zener-Rivanker" is the best production functions representing the profitability of the Tawuniya and Bupa Insurance Companies. The proposed model of the Cobb-Douglas production function is suitable for the results of both Enaya and Sanad Cooperative Insurance Companies. The explanatory capacity of the production functions was also increased when the proposed variables were added (net subscribed premiums-net claims incurred)
Burnout among surgeons before and during the SARS-CoV-2 pandemic: an international survey
Background: SARS-CoV-2 pandemic has had many significant impacts within the surgical realm, and surgeons have been obligated to reconsider almost every aspect of daily clinical practice. Methods: This is a cross-sectional study reported in compliance with the CHERRIES guidelines and conducted through an online platform from June 14th to July 15th, 2020. The primary outcome was the burden of burnout during the pandemic indicated by the validated Shirom-Melamed Burnout Measure. Results: Nine hundred fifty-four surgeons completed the survey. The median length of practice was 10 years; 78.2% included were male with a median age of 37 years old, 39.5% were consultants, 68.9% were general surgeons, and 55.7% were affiliated with an academic institution. Overall, there was a significant increase in the mean burnout score during the pandemic; longer years of practice and older age were significantly associated with less burnout. There were significant reductions in the median number of outpatient visits, operated cases, on-call hours, emergency visits, and research work, so, 48.2% of respondents felt that the training resources were insufficient. The majority (81.3%) of respondents reported that their hospitals were included in the management of COVID-19, 66.5% felt their roles had been minimized; 41% were asked to assist in non-surgical medical practices, and 37.6% of respondents were included in COVID-19 management. Conclusions: There was a significant burnout among trainees. Almost all aspects of clinical and research activities were affected with a significant reduction in the volume of research, outpatient clinic visits, surgical procedures, on-call hours, and emergency cases hindering the training. Trial registration: The study was registered on clicaltrials.gov "NCT04433286" on 16/06/2020
Whole-genome sequencing reveals host factors underlying critical COVID-19
Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2–4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease
Whole-genome sequencing reveals host factors underlying critical COVID-19
Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2,3,4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease
Development of Deep Learning Methods for Real-Time Earthquake Predictions of Building Time-History Responses and Site Spectra
High Prevalence of ESBL and Plasmid-Mediated Quinolone Resistance Genes in Salmonella enterica Isolated from Retail Meats and Slaughterhouses in Egypt
The emergence and spread of multidrug-resistant Salmonella enterica (S. enterica) to humans through food of animal origin are considered a major global public health concern. Currently, little is known about the prevalence of important antimicrobial resistance genes in S. enterica from retail food in Africa. Therefore, the screening and characterization of the extended-spectrum β-lactamase (ESBL) and plasmid-mediated quinolone resistance (PMQR) genes in S. enterica isolated from retail meats and slaughterhouses in Egypt were done by using PCR and DNA sequencing techniques. Twenty-eight out of thirty-four (82.4%) non-duplicate S. enterica isolates showed multidrug-resistance phenotypes to at least three classes of antimicrobials, and fourteen (41.2%) exhibited an ESBL-resistance phenotype and harbored at least one ESBL-encoding gene. The identified β-lactamase-encoding genes included blaCTX-M-1, blaCTX-M-3, blaCTX-M-13, blaCTX-M-14, blaCTX-M-15, and blaSHV-12 (ESBL types); blaCMY-2 (AmpC type); and blaTEM-1 and blaOXA-1 (narrow-spectrum types). PMQR genes (included qnrA, qnrB, qnrS, and aac(6′)-Ib-cr) were identified in 23 (67.6%) isolates. The presence of ESBL- and PMQR-producing S. enterica with a high prevalence rate in retail meats and slaughterhouses is considered a major threat to public health as these strains with resistance genes could be transmitted to humans through the food chain