Classification of subtask types and skill levels in robot-assisted surgery using EEG, eye-tracking, and machine learning.

BACKGROUND: Objective and standardized evaluation of surgical skills in robot-assisted surgery (RAS) holds critical importance for both surgical education and patient safety. This study introduces machine learning (ML) techniques using features derived from electroencephalogram (EEG) and eye-tracking data to identify surgical subtasks and classify skill levels. METHOD: The efficacy of this approach was assessed using a comprehensive dataset encompassing nine distinct classes, each representing a unique combination of three surgical subtasks executed by surgeons while performing operations on pigs. Four ML models, logistic regression, random forest, gradient boosting, and extreme gradient boosting (XGB) were used for multi-class classification. To develop the models, 20% of data samples were randomly allocated to a test set, with the remaining 80% used for training and validation. Hyperparameters were optimized through grid search, using fivefold stratified cross-validation repeated five times. Model reliability was ensured by performing train-test split over 30 iterations, with average measurements reported. RESULTS: The findings revealed that the proposed approach outperformed existing methods for classifying RAS subtasks and skills; the XGB and random forest models yielded high accuracy rates (88.49% and 88.56%, respectively) that were not significantly different (two-sample t-test; P-value = 0.9). CONCLUSION: These results underscore the potential of ML models to augment the objectivity and precision of RAS subtask and skill evaluation. Future research should consider exploring ways to optimize these models, particularly focusing on the classes identified as challenging in this study. Ultimately, this study marks a significant step towards a more refined, objective, and standardized approach to RAS training and competency assessment.

Performance evaluation in cataract surgery with an ensemble of 2D-3D convolutional neural networks.

An important part of surgical training in ophthalmology is understanding how to proficiently perform cataract surgery. Operating skill in cataract surgery is typically assessed by real-time or video-based expert review using a rating scale. This is time-consuming, subjective and labour-intensive. A typical trainee graduates with over 100 complete surgeries, each of which requires review by the surgical educators. Due to the consistently repetitive nature of this task, it lends itself well to machine learning-based evaluation. Recent studies utilize deep learning models trained on tool motion trajectories obtained using additional equipment or robotic systems. However, the process of tool recognition by extracting frames from the videos to perform phase recognition followed by skill assessment is exhaustive. This project proposes a deep learning model for skill evaluation using raw surgery videos that is cost-effective and end-to-end trainable. An advanced ensemble of convolutional neural network models is leveraged to model technical skills in cataract surgeries and is evaluated using a large dataset comprising almost 200 surgical trials. The highest accuracy of 0.8494 is observed on the phacoemulsification step data. Our model yielded an average accuracy of 0.8200 and an average AUC score of 0.8800 for all four phase datasets of cataract surgery proving its robustness against different data. The proposed ensemble model with 2D and 3D convolutional neural networks demonstrated a promising result without using tool motion trajectories to evaluate surgery expertise.

Cost-benefit analysis of ecosystem modeling to support fisheries management.

Mathematical and statistical models underlie many of the world's most important fisheries management decisions. Since the 19th century, difficulty calibrating and fitting such models has been used to justify the selection of simple, stationary, single-species models to aid tactical fisheries management decisions. Whereas these justifications are reasonable, it is imperative that we quantify the value of different levels of model complexity for supporting fisheries management, especially given a changing climate, where old methodologies may no longer perform as well as in the past. Here we argue that cost-benefit analysis is an ideal lens to assess the value of model complexity in fisheries management. While some studies have reported the benefits of model complexity in fisheries, modeling costs are rarely considered. In the absence of cost data in the literature, we report, as a starting point, relative costs of single-species stock assessment and marine ecosystem models from two Australian organizations. We found that costs varied by two orders of magnitude, and that ecosystem model costs increased with model complexity. Using these costs, we walk through a hypothetical example of cost-benefit analysis. The demonstration is intended to catalyze the reporting of modeling costs and benefits.

Consideration of within-patient diversity highlights transmission pathways and antimicrobial resistance gene variability in vancomycin-resistant Enterococcus faecium.

BACKGROUND: WGS is increasingly being applied to healthcare-associated vancomycin-resistant Enterococcus faecium (VREfm) outbreaks. Within-patient diversity could complicate transmission resolution if single colonies are sequenced from identified cases. OBJECTIVES: Determine the impact of within-patient diversity on transmission resolution of VREfm. MATERIALS AND METHODS: Fourteen colonies were collected from VREfm positive rectal screens, single colonies were collected from clinical samples and Illumina WGS was performed. Two isolates were selected for Oxford Nanopore sequencing and hybrid genome assembly to generate lineage-specific reference genomes. Mapping to closely related references was used to identify genetic variations and closely related genomes. A transmission network was inferred for the entire genome set using Phyloscanner. RESULTS AND DISCUSSION: In total, 229 isolates from 11 patients were sequenced. Carriage of two or three sequence types was detected in 27% of patients. Presence of antimicrobial resistance genes and plasmids was variable within genomes from the same patient and sequence type. We identified two dominant sequence types (ST80 and ST1424), with two putative transmission clusters of two patients within ST80, and a single cluster of six patients within ST1424. We found transmission resolution was impaired using fewer than 14 colonies. CONCLUSIONS: Patients can carry multiple sequence types of VREfm, and even within related lineages the presence of mobile genetic elements and antimicrobial resistance genes can vary. VREfm within-patient diversity could be considered in future to aid accurate resolution of transmission networks.

Unravelling the complex interplay between antibiotic consumption and adaptive changes in methicillin-resistant Staphylococcus aureus.

OBJECTIVES: This study aims to elucidate the genomic dynamics driving the emergence of antimicrobial resistance (AMR), with a specific focus on the interplay between AMR and antimicrobial usage. METHODS: We conducted a comprehensive analysis using a ST239 methicillin-resistant Staphylococcus aureus (MRSA) dataset over a continuous 12-year period from a single hospital. Genomic analyses were performed tracking the changes in MRSA populations, particularly the emergence of reduced vancomycin susceptibility, and assessing the impact of glycopeptide use on these emergence events. RESULTS: Our findings reveal a significant correlation between hospital glycopeptide usage and the selection of MRSA strains with reduced vancomycin susceptibility. Genomic analyses provided insights into the molecular mechanisms driving resistance emergence, including the slowing of the molecular clock rate in response to heightened antimicrobial consumption. CONCLUSIONS: In conclusion, this study the highlights the complex dynamics between AMR and antimicrobial use at the hospital level. The observed correlation between antimicrobial consumption and the development of less susceptible MRSA strains underscores the importance of antimicrobial stewardship programmes and the establishment of optimal consumption thresholds for mitigating AMR effectively.

Treatment seeking behaviours, antibiotic use and relationships to multi-drug resistance: A study of urinary tract infection patients in Kenya, Tanzania and Uganda.

Antibacterial resistance (ABR) is a major public health threat. An important accelerating factor is treatment-seeking behaviour, including inappropriate antibiotic (AB) use. In many low- and middle-income countries (LMICs) this includes taking ABs with and without prescription sourced from various providers, including health facilities and community drug sellers. However, investigations of complex treatment-seeking, AB use and drug resistance in LMICs are scarce. The Holistic Approach to Unravel Antibacterial Resistance in East Africa (HATUA) Consortium collected questionnaire and microbiological data from adult outpatients with urinary tract infection (UTI)-like symptoms presenting at healthcare facilities in Kenya, Tanzania and Uganda. Using data from 6,388 patients, we analysed patterns of self-reported treatment seeking behaviours ('patient pathways') using process mining and single-channel sequence analysis. Among those with microbiologically confirmed UTI (n = 1,946), we used logistic regression to assess the relationship between treatment seeking behaviour, AB use, and the likelihood of having a multi-drug resistant (MDR) UTI. The most common treatment pathway for UTI-like symptoms in this sample involved attending health facilities, rather than other providers like drug sellers. Patients from sites in Tanzania and Uganda, where over 50% of patients had an MDR UTI, were more likely to report treatment failures, and have repeat visits to providers than those from Kenyan sites, where MDR UTI proportions were lower (33%). There was no strong or consistent relationship between individual AB use and likelihood of MDR UTI, after accounting for country context. The results highlight the hurdles East African patients face in accessing effective UTI care. These challenges are exacerbated by high rates of MDR UTI, suggesting a vicious cycle of failed treatment attempts and sustained selection for drug resistance. Whilst individual AB use may contribute to the risk of MDR UTI, our data show that factors related to context are stronger drivers of variations in ABR.

Predominance of multidrug-resistant bacteria causing urinary tract infections among symptomatic patients in East Africa: a call for action.

Background: In low- and middle-income countries, antibiotics are often prescribed for patients with symptoms of urinary tract infections (UTIs) without microbiological confirmation. Inappropriate antibiotic use can contribute to antimicrobial resistance (AMR) and the selection of MDR bacteria. Data on antibiotic susceptibility of cultured bacteria are important in drafting empirical treatment guidelines and monitoring resistance trends, which can prevent the spread of AMR. In East Africa, antibiotic susceptibility data are sparse. To fill the gap, this study reports common microorganisms and their susceptibility patterns isolated from patients with UTI-like symptoms in Kenya, Tanzania and Uganda. Within each country, patients were recruited from three sites that were sociodemographically distinct and representative of different populations. Methods: UTI was defined by the presence of >104 cfu/mL of one or two uropathogens in mid-stream urine samples. Identification of microorganisms was done using biochemical methods. Antimicrobial susceptibility testing was performed by the Kirby-Bauer disc diffusion assay. MDR bacteria were defined as isolates resistant to at least one agent in three or more classes of antimicrobial agents. Results: Microbiologically confirmed UTI was observed in 2653 (35.0%) of the 7583 patients studied. The predominant bacteria were Escherichia coli (37.0%), Staphylococcus spp. (26.3%), Klebsiella spp. (5.8%) and Enterococcus spp. (5.5%). E. coli contributed 982 of the isolates, with an MDR proportion of 52.2%. Staphylococcus spp. contributed 697 of the isolates, with an MDR rate of 60.3%. The overall proportion of MDR bacteria (n = 1153) was 50.9%. Conclusions: MDR bacteria are common causes of UTI in patients attending healthcare centres in East African countries, which emphasizes the need for investment in laboratory culture capacity and diagnostic algorithms to improve accuracy of diagnosis that will lead to appropriate antibiotic use to prevent and control AMR.

Treatment seeking and antibiotic use for urinary tract infection symptoms in the time of COVID-19 in Tanzania and Uganda.

Background: There is still little empirical evidence on how the outbreak of coronavirus disease 2019 (COVID-19) and associated regulations may have disrupted care-seeking for non-COVID-19 conditions or affected antibiotic behaviours in low- and middle-income countries (LMICs). We aimed to investigate the differences in treatment-seeking behaviours and antibiotic use for urinary tract infection (UTI)-like symptoms before and during the pandemic at recruitment sites in two East African countries with different COVID-19 control policies: Mbarara, Uganda and Mwanza, Tanzania. Methods: In this repeated cross-sectional study, we used data from outpatients (pregnant adolescents aged >14 and adults aged >18) with UTI-like symptoms who visited health facilities in Mwanza, Tanzania and Mbarara, Uganda. We assessed the prevalence of self-reported behaviours (delays in care-seeking, providers visited, antibiotics taken) at three different time points, labelled as 'pre-COVID-19 phase' (February 2019 to February 2020), 'COVID-19 phase 1' (March 2020 to April 2020), and 'COVID-19 phase 2' (July 2021 to February 2022). Results: In both study sites, delays in care-seeking were less common during the pandemic than they were in the pre-COVID phase. Patients in Mwanza, Tanzania had shorter care-seeking pathways during the pandemic compared to before it, but this difference was not observed in Mbarara, Uganda. Health centres were the dominant sources of antibiotics in both settings. Over time, reported antibiotic use for UTI-like symptoms became more common in both settings. During the COVID-19 phases, there was a significant increase in self-reported use of antibiotics like metronidazole (<30% in the pre-COVID-19 phase to 40% in COVID phase 2) and doxycycline (30% in the pre-COVID-19 phase to 55% in COVID phase 2) that were not recommended for treating UTI-like symptoms in the National Treatment Guidelines in Mbarara, Uganda. Conclusions: There was no clear evidence that patients with UTI-like symptoms attending health care facilities had longer or more complex treatment pathways despite strict government-led interventions related to COVID-19. However, antibiotic use increased over time, including some antibiotics not recommended for treating UTI, which has implications for future antimicrobial resistance.

Change in economy of ultrasound probe motion among general medicine trainees.

OBJECTIVES: To observe change in economy of 9 ultrasound probe movement metrics among internal medicine trainees during a 5-day training course in cardiac point of care ultrasound (POCUS). METHODS: We used a novel probe tracking device to record nine features of ultrasound probe movement, while trainees and experts optimized ultrasound clips on the same volunteer patients. These features included translational movements, gyroscopic movements (titling, rocking, and rotation), smoothness, total path length, and scanning time. We determined the adjusted difference between each trainee's movements and the mean value of the experts' movements for each patient. We then used a mixed effects model to trend average the adjusted differences between trainees and experts throughout the 5 days of the course. RESULTS: Fifteen trainees were enrolled. Three echocardiographer technicians and the course director served as experts. Across 16 unique patients, 294 ultrasound clips were acquired. For all 9 movements, the adjusted difference between trainees and experts narrowed day-to-day (p value < 0.05), suggesting ongoing improvement during training. By the last day of the course, there were no statistically significant differences between trainees and experts in translational movement, gyroscopic movement, smoothness, or total path length; yet on average trainees took 28 s (95% CI [14.7-40.3] seconds) more to acquire a clip. CONCLUSIONS: We detected improved ultrasound probe motion economy among internal medicine trainees during a 5-day training course in cardiac POCUS using an inexpensive probe tracking device. Objectively quantifying probe motion economy may help assess a trainee's level of proficiency in this skill and individualize their POCUS training.

Overcoming the impossibility of age-balanced harvest.

In many countries, sustainability targets for managed fisheries are often expressed in terms of a fixed percentage of the carrying capacity. Despite the appeal of such a simple quantitative target, an unintended consequence may be a significant tilting of the proportions of biomass across different ages, from what they would have been under harvest-free conditions. Within the framework of a widely used age-structured model, we propose a novel quantitative definition of "age-balanced harvest" that considers the age-class composition relative to that of the unfished population. We show that achieving a perfectly age-balanced policy is impossible if we harvest any fish whatsoever. However, every non-trivial harvest policy has a special structure that favours the young. To quantify the degree of age-imbalance, we propose a cross-entropy function. We formulate an optimisation problem that aims to attain an "age-balanced steady state", subject to adequate yield. We demonstrate that near balanced harvest policies are achievable by sacrificing a small amount of yield. These findings have important implications for sustainable fisheries management by providing insights into trade-offs and harvest policy recommendations.

FAST skill assessment from kinematics data using convolutional neural networks.

PURPOSE: FAST is a point of care ultrasound study that evaluates for the presence of free fluid, typically hemoperitoneum in trauma patients. FAST is an essential skill for Emergency Physicians. Thus, it requires objective evaluation tools that can reduce the necessity of direct observation for proficiency assessment. In this work, we use deep neural networks to automatically assess operators' FAST skills. METHODS: We propose a deep convolutional neural network for FAST proficiency assessment based on motion data. Prior work has shown that operators demonstrate different domain-specific dexterity metrics that can distinguish novices, intermediates, and experts. Therefore, we augment our dataset with this domain knowledge and employ fine-tuning to improve the model's classification capabilities. Our model, however, does not require specific points of interest (POIs) to be defined for scanning. RESULTS: The results show that the proposed deep convolutional neural network can classify FAST proficiency with 87.5% accuracy and 0.884, 0.886, 0.247 sensitivity for novices, intermediates, and experts, respectively. It demonstrates the potential of using kinematics data as an input in FAST skill assessment tasks. We also show that the proposed domain-specific features and region fine-tuning increase the model's classification accuracy and sensitivity. CONCLUSIONS: Variations in probe motion at different learning stages can be derived from kinematics data. These variations can be used for automatic and objective skill assessment without prior identification of clinical POIs. The proposed approach can improve the quality and objectivity of FAST proficiency evaluation. Furthermore, skill assessment combining ultrasound images and kinematics data can provide a more rigorous and diversified evaluation than using ultrasound images alone.

Is Mushy Tuna Syndrome a Growing Problem for the Tuna Industry?

Reducing food loss and waste is crucial for a sustainable global food system and an efficient use of natural resources. Fast-growing tuna provides a key contribution to global nutrition targets; however, reports suggest that an appreciable proportion of the catch is lost from its value chain due to flesh quality issues, one of which is Mushy Tuna Syndrome (MTS). MTS-affected tuna flesh becomes soft and pasty, unfit for canning or human consumption, resulting in high wastage of partially processed material. We investigated the prevalence of MTS globally by surveying the tuna industry using a questionnaire. Of the responses from 32 companies across 14 nations, 97% acknowledged MTS as an issue that predominantly affects skipjack (Katsuwonus pelamis) tuna. The cost of rejects reported by participants from 2017 to 2019 varied greatly, from less than 1000 USD per year to over 1 million USD. The median cost was over 60,000 USD and the average rejection rate was 1.8%. The occurrence of MTS was noted to be seasonal, mainly in the summer months. More than half of the respondents who experience MTS reported an increasing trend of occurrence. Industry perceptions suggest MTS causes are associated with environmental, physiological, and biological factors. The survey results highlight that MTS is prevalent in the industry and demonstrate the need to identify amelioration strategies for the fishers and processors to minimise loss and maximise resource efficiency.

Whole Genome Sequencing and Molecular Epidemiology of Clinical Isolates of Staphylococcus aureus from Algeria.

Staphylococcus aureus is an important pathogen responsible for various healthcare- and community-acquired infections. In this study, whole genome sequencing (WGS) was used to genotype S. aureus clinical isolates from two hospitals in Algeria and to characterize their genetic determinants of antimicrobial resistance. Seventeen S. aureus isolates were included in this study. WGS, single-nucleotide polymorphism (SNP)-based phylogenetic analysis, in silico multilocus sequence typing (MLST), spa and staphylococcal cassette chromosome mec (SCCmec) typing and in silico antimicrobial resistance profiling were performed. Phenotypic antibiotic susceptibility testing was performed using the Vitek 2 system and the disk diffusion method. The isolates were separated into sequence types (STs), with ST80 being predominant; five clonal complexes (CCs); four spa types (t044, t127, t368, t386); and two SCCmec types (IVc and IVa). Whole genome analysis revealed the presence of the resistance genes mecA, blaZ, ermC, fusB, fusC, tetK, aph(3')-IIIa and aad(6) and mutations conferring resistance in the genes parC and fusA. The rate of multidrug resistance (MDR) was 64%. This work provides a high-resolution characterization of methicillin-resistant S. aureus (MRSA) and methicillin-susceptible S. aureus (MSSA) isolates and emphasizes the importance of continuous surveillance to monitor the spread of S. aureus in healthcare settings in the country.

Practices and motives behind antibiotics provision in drug outlets in Tanzania: A qualitative study.

Dispensing antibiotics without prescription is among the major factors leading to antimicrobial resistance. Dispensing of antibiotics without prescription has negative impact at the individual and societal level leading to poor patient outcomes, and increased risks of resistant bacteria facilitated by inappropriate choice of antibiotics doses/courses. Antimicrobial resistance is a global public health threat which is projected to cause 10 million deaths by 2050 if no significant actions are taken to address this problem This study explored the practices and motives behind dispensing of antibiotics without prescription among community drug outlets in Tanzania. Finding of this study provides more strategies to antibiotics stewardship intervention. In-depth interviews with 28 drug dispensers were conducted for three months consecutively between November 2019 and January 2020 in 12 community pharmacies and 16 Accredited Drug Dispensing Outlets (ADDOs) in the Mwanza, Kilimanjaro and Mbeya regions of Tanzania. Transcripts were coded and analyzed thematically using NVivo12 software. Majority of dispensers admitted to providing antibiotics without prescriptions, selling incomplete courses of antibiotics and not giving detailed instructions to customers on how to use the drugs. These practices were motivated by several factors including customers' pressure/customers' demands, business orientation-financial gain of drug dispensers, and low purchasing power of patients/customers. It is important to address the motives behind the unauthorized dispensing antibiotics. On top of the existing regulation and enforcement, we recommend the government to empower customers with education and purchasing power of drugs which can enhance the dispensers adherence to the dispensing regulations. Furthermore, we recommend ethnographic research to inform antibiotic stewardship interventions going beyond awareness raising, education and advocacy campaigns. This will address structural drivers of AMR such as poverty and inadequate government health services, and the disconnect between public messaging and/or policy and the public itself.

Evaluation of the diagnostic performance of the urine dipstick test for the detection of urinary tract infections in patients treated in Kenyan hospitals.

Introduction: Culture is the gold-standard diagnosis for urinary tract infections (UTIs). However, most hospitals in low-resource countries lack adequately equipped laboratories and relevant expertise to perform culture and, therefore, rely heavily on dipstick tests for UTI diagnosis. Research gap: In many Kenyan hospitals, routine evaluations are rarely done to assess the accuracy of popular screening tests such as the dipstick test. As such, there is a substantial risk of misdiagnosis emanating from inaccuracy in proxy screening tests. This may result in misuse, under-use or over-use of antimicrobials. Aim: The present study aimed to assess the accuracy of the urine dipstick test as a proxy for the diagnosis of UTIs in selected Kenyan hospitals. Methods: A hospital-based cross-sectional method was used. The utility of dipstick in the diagnosis of UTIs was assessed using midstream urine against culture as the gold standard. Results: The dipstick test predicted 1416 positive UTIs, but only 1027 were confirmed positive by culture, translating to a prevalence of 54.1 %. The sensitivity of the dipstick test was better when leucocytes and nitrite tests were combined (63.1 %) than when the two tests were separate (62.6 and 50.7 %, respectively). Similarly, the two tests combined had a better positive predictive value (87.0 %) than either test alone. The nitrite test had the best specificity (89.8 %) and negative predictive value (97.4 %) than leucocytes esterase (L.E) or both tests combined. In addition, sensitivity in samples from inpatients (69.2 %) was higher than from outpatients (62.7 %). Furthermore, the dipstick test had a better sensitivity and positive predictive value among female (66.0 and 88.6 %) than male patients (44.3 and 73.9 %). Among the various patient age groups, the dipstick test's sensitivity and positive predictive value were exceptionally high in patients ≥75 years old (87.5 and 93.3 %). Conclusion: Discrepancies in prevalence from the urine dipstick test and culture, the gold standard, indicate dipstick test inadequacy for accurate UTI diagnosis. The finding also demonstrates the need for urine culture for accurate UTI diagnosis. However, considering it is not always possible to perform a culture, especially in low-resource settings, future studies are needed to combine specific UTI symptoms and dipstick results to assess possible increases in the test's sensitivity. There is also a need to develop readily available and affordable algorithms that can detect UTIs where culture is not available.

Unravelling patient pathways in the context of antibacterial resistance in East Africa.

BACKGROUND: A key factor driving the development and maintenance of antibacterial resistance (ABR) is individuals' use of antibiotics (ABs) to treat illness. To better understand motivations and context for antibiotic use we use the concept of a patient treatment-seeking pathway: a treatment journey encompassing where patients go when they are unwell, what motivates their choices, and how they obtain antibiotics. This paper investigates patterns and determinants of patient treatment-seeking pathways, and how they intersect with AB use in East Africa, a region where ABR-attributable deaths are exceptionally high. METHODS: The Holistic Approach to Unravelling Antibacterial Resistance (HATUA) Consortium collected quantitative data from 6,827 adult outpatients presenting with urinary tract infection (UTI) symptoms in Kenya, Tanzania, and Uganda between February 2019- September 2020, and conducted qualitative in-depth patient interviews with a subset (n = 116). We described patterns of treatment-seeking visually using Sankey plots and explored explanations and motivations using mixed-methods. Using Bayesian hierarchical regression modelling, we investigated the associations between socio-demographic, economic, healthcare, and attitudinal factors and three factors related to ABR: self-treatment as a first step, having a multi-step treatment pathway, and consuming ABs. RESULTS: Although most patients (86%) sought help from medical facilities in the first instance, many (56%) described multi-step, repetitive treatment-seeking pathways, which further increased the likelihood of consuming ABs. Higher socio-economic status patients were more likely to consume ABs and have multi-step pathways. Reasons for choosing providers (e.g., cost, location, time) were conditioned by wider structural factors such as hybrid healthcare systems and AB availability. CONCLUSION: There is likely to be a reinforcing cycle between complex, repetitive treatment pathways, AB consumption and ABR. A focus on individual antibiotic use as the key intervention point in this cycle ignores the contextual challenges patients face when treatment seeking, which include inadequate access to diagnostics, perceived inefficient public healthcare and ease of purchasing antibiotics without prescription. Pluralistic healthcare landscapes may promote more complex treatment seeking and therefore inappropriate AB use. We recommend further attention to healthcare system factors, focussing on medical facilities (e.g., accessible diagnostics, patient-doctor interactions, information flows), and community AB access points (e.g., drug sellers).

Directions of change in intrinsic case severity across successive SARS-CoV-2 variant waves have been inconsistent.

OBJECTIVES: To determine how the intrinsic severity of successively dominant SARS-CoV-2 variants changed over the course of the pandemic. METHODS: A retrospective cohort analysis in the NHS Greater Glasgow and Clyde (NHS GGC) Health Board. All sequenced non-nosocomial adult COVID-19 cases in NHS GGC with relevant SARS-CoV-2 lineages (B.1.177/Alpha, Alpha/Delta, AY.4.2 Delta/non-AY.4.2 Delta, non-AY.4.2 Delta/Omicron, and BA.1 Omicron/BA.2 Omicron) during analysis periods were included. Outcome measures were hospital admission, ICU admission, or death within 28 days of positive COVID-19 test. We report the cumulative odds ratio; the ratio of the odds that an individual experiences a severity event of a given level vs all lower severity levels for the resident and the replacement variant after adjustment. RESULTS: After adjustment for covariates, the cumulative odds ratio was 1.51 (95% CI: 1.08-2.11) for Alpha versus B.1.177, 2.09 (95% CI: 1.42-3.08) for Delta versus Alpha, 0.99 (95% CI: 0.76-1.27) for AY.4.2 Delta versus non-AY.4.2 Delta, 0.49 (95% CI: 0.22-1.06) for Omicron versus non-AY.4.2 Delta, and 0.86 (95% CI: 0.68-1.09) for BA.2 Omicron versus BA.1 Omicron. CONCLUSIONS: The direction of change in intrinsic severity between successively emerging SARS-CoV-2 variants was inconsistent, reminding us that the intrinsic severity of future SARS-CoV-2 variants remains uncertain.

Preoperative Oesophagogastroduodenoscopy and the Effect on Bariatric Surgery: a Systematic Review and Meta-Analysis.

Preoperative oesophagogastroduodenoscopy (OGD) in bariatric surgery remains a controversial topic, with a large variety in practice globally. An electronic database search of Medline, Embase and PubMed was performed in an aim to categorise the findings of preoperative endoscopies in bariatric patients. A total of 47 studies were included in this meta-analysis resulting in 23,368 patients being assessed. Of patients assessed, 40.8% were found to have no novel findings, 39.7% had novel findings which did not affect surgical planning, 19.8% had findings that affected their surgery and 0.3% were ruled to not be suitable for bariatric surgery. Preoperative OGD is altering surgical planning in one-fifth of patients; however, further comparative studies are required to determine if each patient should undergo this procedure especially if asymptomatic.

Bacterial etiology of urinary tract infections in patients treated at Kenyan health facilities and their resistance towards commonly used antibiotics.

BACKGROUND: Evidence-based empirical antibiotic prescribing requires knowledge of local antimicrobial resistance patterns. The spectrum of pathogens and their susceptibility strongly influences guidelines for empirical therapies for urinary tract infections (UTI) management. OBJECTIVE: This study aimed to determine the prevalence of UTI causative bacteria and their corresponding antibiotic resistance profiles in three counties of Kenya. Such data could be used to determine the optimal empirical therapy. METHODS: In this cross-sectional study, urine samples were collected from patients who presented with symptoms suggestive of UTI in the following healthcare facilities; Kenyatta National Hospital, Kiambu Hospital, Mbagathi, Makueni, Nanyuki, Centre for Microbiology Research, and Mukuru Health Centres. Urine cultures were done on Cystine Lactose Electrolyte Deficient (CLED) to isolate UTI bacterial etiologies, while antibiotic sensitivity testing was done using the Kirby-Bauer disk diffusion using CLSI guidelines and interpretive criteria. RESULTS: A total of 1,027(54%) uropathogens were isolated from the urine samples of 1898 participants. Staphylococcus spp. and Escherichia coli were the main uropathogens at 37.6% and 30.9%, respectively. The percentage resistance to commonly used drugs for the treatment of UTI were as follows: trimethoprim (64%), sulfamethoxazole (57%), nalidixic acid(57%), ciprofloxacin (27%), amoxicillin-clavulanic acid (5%), and nitrofurantoin (9%) and cefixime (9%). Resistance rates to broad-spectrum antimicrobials, such as ceftazidime, gentamicin, and ceftriaxone, were 15%, 14%, and 11%, respectively. Additionally, the proportion of Multidrug-resistant (MDR) bacteria was 66%. CONCLUSION: High resistance rates toward fluoroquinolones, sulfamethoxazole, and trimethoprim were reported. These antibiotics are commonly used drugs as they are inexpensive and readily available. Based on these findings, more robust standardised surveillance is needed to confirm the patterns observed while recognising the potential impact of sampling biases on observed resistance rates.