Objective To examine the effect of surgeon sex on postoperative outcomes of patients undergoing common surgical procedures.Design Population based, retrospective, matched cohort study from 2007 to ...2015.Setting Population based cohort of all patients treated in Ontario, Canada.Participants Patients undergoing one of 25 surgical procedures performed by a female surgeon were matched by patient age, patient sex, comorbidity, surgeon volume, surgeon age, and hospital to patients undergoing the same operation by a male surgeon.Interventions Sex of treating surgeon.Main outcome measure The primary outcome was a composite of death, readmission, and complications. We compared outcomes between groups using generalised estimating equations.Results 104 630 patients were treated by 3314 surgeons, 774 female and 2540 male. Before matching, patients treated by female doctors were more likely to be female and younger but had similar comorbidity, income, rurality, and year of surgery. After matching, the groups were comparable. Fewer patients treated by female surgeons died, were readmitted to hospital, or had complications within 30 days (5810 of 52 315, 11.1%, 95% confidence interval 10.9% to 11.4%) than those treated by male surgeons (6046 of 52 315, 11.6%, 11.3% to 11.8%; adjusted odds ratio 0.96, 0.92 to 0.99, P=0.02). Patients treated by female surgeons were less likely to die within 30 days (adjusted odds ratio 0.88; 0.79 to 0.99, P=0.04), but there was no significant difference in readmissions or complications. Stratified analyses by patient, physician, and hospital characteristics did not significant modify the effect of surgeon sex on outcome. A retrospective analysis showed no difference in outcomes by surgeon sex in patients who had emergency surgery, where patients do not usually choose their surgeon.Conclusions After accounting for patient, surgeon, and hospital characteristics, patients treated by female surgeons had a small but statistically significant decrease in 30 day mortality and similar surgical outcomes (length of stay, complications, and readmission), compared with those treated by male surgeons. These findings support the need for further examination of the surgical outcomes and mechanisms related to physicians and the underlying processes and patterns of care to improve mortality, complications, and readmissions for all patients.
Increased interest in the opportunities provided by artificial intelligence and machine learning has spawned a new field of health-care research. The new tools under development are targeting many ...aspects of medical practice, including changes to the practice of pathology and laboratory medicine. Optimal design in these powerful tools requires cross-disciplinary literacy, including basic knowledge and understanding of critical concepts that have traditionally been unfamiliar to pathologists and laboratorians. This review provides definitions and basic knowledge of machine learning categories (supervised, unsupervised, and reinforcement learning), introduces the underlying concept of the bias-variance trade-off as an important foundation in supervised machine learning, and discusses approaches to the supervised machine learning study design along with an overview and description of common supervised machine learning algorithms (linear regression, logistic regression, Naive Bayes, k-nearest neighbor, support vector machine, random forest, convolutional neural networks).
Novel second-line treatments are needed for patients with advanced urothelial cancer (UC). Interim analysis of the phase III KEYNOTE-045 study showed a superior overall survival (OS) benefit of ...pembrolizumab, a programmed death 1 inhibitor, versus chemotherapy in patients with advanced UC that progressed on platinum-based chemotherapy. Here we report the long-term safety and efficacy outcomes of KEYNOTE-045.
Adult patients with histologically/cytologically confirmed UC whose disease progressed after first-line, platinum-containing chemotherapy were enrolled. Patients were randomly assigned 1 : 1 to receive pembrolizumab 200mg every 3weeks (Q3W) or investigator’s choice of paclitaxel (175mg/m2 Q3W), docetaxel (75mg/m2 Q3W), or vinflunine (320mg/m2 Q3W). Primary end points were OS and progression-free survival (PFS) per Response Evaluation Criteria in Solid Tumors, version 1.1 (RECIST v1.1) by blinded independent central radiology review (BICR). A key secondary end point was objective response rate per RECIST v1.1 by BICR.
A total of 542 patients were enrolled (pembrolizumab, n=270; chemotherapy, n=272). Median follow-up as of 26 October 2017 was 27.7months. Median 1- and 2-year OS rates were higher with pembrolizumab (44.2% and 26.9%, respectively) than chemotherapy (29.8% and 14.3%, respectively). PFS rates did not differ between treatment arms; however, 1- and 2-year PFS rates were higher with pembrolizumab. The objective response rate was also higher with pembrolizumab (21.1% versus 11.0%). Median duration of response to pembrolizumab was not reached (range 1.6+ to 30.0+ months) versus chemotherapy (4.4months; range 1.4+ to 29.9+ months). Pembrolizumab had lower rates of any grade (62.0% versus 90.6%) and grade ≥3 (16.5% versus 50.2%) treatment-related adverse events than chemotherapy.
Long-term results (>2 years’ follow-up) were consistent with those of previously reported analyses, demonstrating continued clinical benefit of pembrolizumab over chemotherapy for efficacy and safety for treatment of locally advanced/metastatic, platinum-refractory UC.
ClinicalTrials.gov: NCT02256436.
The E. coli chromosome is condensed into insulated regions termed macrodomains (MDs), which are essential for genomic packaging. How chromosomal MDs are specifically organized and compacted is ...unknown. Here, we report studies revealing the molecular basis for Terminus-containing (Ter) chromosome condensation by the Ter-specific factor MatP. MatP contains a tripartite fold with a four-helix bundle DNA-binding motif, ribbon-helix-helix and C-terminal coiled-coil. Strikingly, MatP-matS structures show that the MatP coiled-coils form bridged tetramers that flexibly link distant matS sites. Atomic force microscopy and electron microscopy studies demonstrate that MatP alone loops DNA. Mutation of key coiled-coil residues destroys looping and causes a loss of Ter condensation in vivo. Thus, these data reveal the molecular basis for a protein-mediated DNA-bridging mechanism that mediates condensation of a large chromosomal domain in enterobacteria.
► MatP is a specific DNA-binding protein that compacts enterobacteria chromosomal DNA ► MatP contains a modular fold with a four-helix bundle DNA-binding motif ► MatP coiled-coils form tetramers that link distant DNA sites ► Tetramerization is required for MatP-mediated in vivo chromosomal condensation
Nanostructured thin plastic foils have been used to enhance the mechanism of laser-driven proton beam acceleration. In particular, the presence of a monolayer of polystyrene nanospheres on the target ...front side has drastically enhanced the absorption of the incident 100 TW laser beam, leading to a consequent increase in the maximum proton energy and beam charge. The cutoff energy increased by about 60% for the optimal spheres' diameter of 535 nm in comparison to the planar foil. The total number of protons with energies higher than 1 MeV was increased approximately 5 times. To our knowledge this is the first experimental demonstration of such advanced target geometry. Experimental results are interpreted and discussed by means of 2(1/2)-dimensional particle-in-cell simulations.
Abstract
Background
Artificial intelligence (AI) and machine learning (ML) are poised to transform infectious disease testing. Uniquely, infectious disease testing is technologically diverse spaces ...in laboratory medicine, where multiple platforms and approaches may be required to support clinical decision-making. Despite advances in laboratory informatics, the vast array of infectious disease data is constrained by human analytical limitations. Machine learning can exploit multiple data streams, including but not limited to laboratory information and overcome human limitations to provide physicians with predictive and actionable results. As a quickly evolving area of computer science, laboratory professionals should become aware of AI/ML applications for infectious disease testing as more platforms are become commercially available.
Content
In this review we: (a) define both AI/ML, (b) provide an overview of common ML approaches used in laboratory medicine, (c) describe the current AI/ML landscape as it relates infectious disease testing, and (d) discuss the future evolution AI/ML for infectious disease testing in both laboratory and point-of-care applications.
Summary
The review provides an important educational overview of AI/ML technique in the context of infectious disease testing. This includes supervised ML approaches, which are frequently used in laboratory medicine applications including infectious diseases, such as COVID-19, sepsis, hepatitis, malaria, meningitis, Lyme disease, and tuberculosis. We also apply the concept of “data fusion” describing the future of laboratory testing where multiple data streams are integrated by AI/ML to provide actionable clinical knowledge.
The 2019 novel coronavirus infectious disease (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has created an unsustainable need for molecular diagnostic ...testing. Molecular approaches such as reverse transcription (RT) polymerase chain reaction (PCR) offers highly sensitive and specific means to detect SARS-CoV-2 RNA, however, despite it being the accepted "gold standard", molecular platforms often require a tradeoff between speed versus throughput. Matrix assisted laser desorption ionization (MALDI)-time of flight (TOF)-mass spectrometry (MS) has been proposed as a potential solution for COVID-19 testing and finding a balance between analytical performance, speed, and throughput, without relying on impacted supply chains. Combined with machine learning (ML), this MALDI-TOF-MS approach could overcome logistical barriers encountered by current testing paradigms. We evaluated the analytical performance of an ML-enhanced MALDI-TOF-MS method for screening COVID-19. Residual nasal swab samples from adult volunteers were used for testing and compared against RT-PCR. Two optimized ML models were identified, exhibiting accuracy of 98.3%, positive percent agreement (PPA) of 100%, negative percent agreement (NPA) of 96%, and accuracy of 96.6%, PPA of 98.5%, and NPA of 94% respectively. Machine learning enhanced MALDI-TOF-MS for COVID-19 testing exhibited performance comparable to existing commercial SARS-CoV-2 tests.
The role of children in the spread of the SARS-CoV-2 coronavirus has become a matter of urgent debate as societies in the US and abroad consider how to safely reopen schools. Small studies have ...suggested higher viral loads in young children. Here we present a multicenter investigation on over five thousand SARS-CoV-2 cases confirmed by real-time reverse transcription (RT) PCR assay. Notably, we found no discernable difference in amount of viral nucleic acid among young children and adults.
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