Using a targeted metabolomics approach to explore differences in ARDS associated with COVID-19 compared to ARDS caused by H1N1 influenza and bacterial pneumonia.

RATIONALE: Acute respiratory distress syndrome (ARDS) is a life-threatening critical care syndrome commonly associated with infections such as COVID-19, influenza, and bacterial pneumonia. Ongoing research aims to improve our understanding of ARDS, including its molecular mechanisms, individualized treatment options, and potential interventions to reduce inflammation and promote lung repair. OBJECTIVE: To map and compare metabolic phenotypes of different infectious causes of ARDS to better understand the metabolic pathways involved in the underlying pathogenesis. METHODS: We analyzed metabolic phenotypes of 3 ARDS cohorts caused by COVID-19, H1N1 influenza, and bacterial pneumonia compared to non-ARDS COVID-19-infected patients and ICU-ventilated controls. Targeted metabolomics was performed on plasma samples from a total of 150 patients using quantitative LC-MS/MS and DI-MS/MS analytical platforms. RESULTS: Distinct metabolic phenotypes were detected between different infectious causes of ARDS. There were metabolomics differences between ARDSs associated with COVID-19 and H1N1, which include metabolic pathways involving taurine and hypotaurine, pyruvate, TCA cycle metabolites, lysine, and glycerophospholipids. ARDSs associated with bacterial pneumonia and COVID-19 differed in the metabolism of D-glutamine and D-glutamate, arginine, proline, histidine, and pyruvate. The metabolic profile of COVID-19 ARDS (C19/A) patients admitted to the ICU differed from COVID-19 pneumonia (C19/P) patients who were not admitted to the ICU in metabolisms of phenylalanine, tryptophan, lysine, and tyrosine. Metabolomics analysis revealed significant differences between C19/A, H1N1/A, and PNA/A vs ICU-ventilated controls, reflecting potentially different disease mechanisms. CONCLUSION: Different metabolic phenotypes characterize ARDS associated with different viral and bacterial infections.

Summative Evaluation of Vaginal Surgery Skills: Setting A Pass-Fail Score.

INTRODUCTION AND HYPOTHESIS: We developed a summative assessment tool to evaluate competent performance on three procedure-specific low fidelity simulation models for vaginal surgery. Our purpose was to determine a pass-fail score for each model. METHODS: We enrolled participants (2011-2023, three Canadian academic centers) and grouped them according to operative competency in vaginal procedures. Novice operators were medical students recruited through targeted advertisement to clerkship level medical students. Proficient operators consisted of gynecology residents from the intervention arm of a randomized controlled trial, trained to competence in the use of the models; urogynecology fellows and attending gynecologic surgeons recruited through departmental rounds. All participants were asked to perform the three procedures on the models, were videotaped, and their performance assessed by evaluators familiar with the procedure and the scoring system, blinded to operator identity. A total performance score (range 0-400) assessed timing and errors. Basic skill deductions were set a priori. We calculated sensitivity and specificity scores and obtained an optimal cutoff based on Youden's J statistic. RESULTS: For anterior repair, we rated 46 novice and 16 proficient videos. The pass-fail score was 170/400. For posterior repair, we rated 54 novice and 14 proficient videos. The pass-fail score was 140/400. For vaginal hysterectomy, we rated 47 novice and 12 proficient videos. The pass-fail score was 180/400. Scores of proficient operators were significantly better than those of novice participants (p < 0.001 for all). CONCLUSIONS: A pass-fail score can distinguish between novice and proficient operators and can be used for summative assessment of surgical skill.

Procedure-specific simulation for vaginal surgery training: A randomized controlled trial.

INTRODUCTION: Vaginal surgery has a superior outcome profile compared with other surgical routes, yet skills are declining because of low case volumes. Graduating residents' confidence and preparedness for vaginal surgery has plummeted in the past decade. The objective of the present study was to investigate whether procedure-specific simulation skills, vs usual training, result in improved operative competence. MATERIAL AND METHODS: We completed a randomized controlled trial of didactic and procedural training via low fidelity vaginal surgery models for anterior repair, posterior repair (PR), vaginal hysterectomy (VH), recruiting novice gynecology residents at three academic centers. We evaluated performance via global rating scale (GRS) in the real operating room and for corresponding procedures by attending surgeon blinded to group. Prespecified secondary outcomes included procedural steps knowledge, overall performance, satisfaction, self-confidence and intraoperative parameters. A priori sample size estimated 50 residents (20% absolute difference in GRS score, 25% SD, 80% power, alpha 0.05). CLINICALTRIALS: gov: Registration no. NCT05887570. RESULTS: We randomized 83 residents to intervention or control and 55 completed the trial (2011-23). Baseline characteristics were similar, except for more fourth-year control residents. After adjustment of confounders (age, level, baseline knowledge), GRS scores showed significant differences overall (mean difference 8.2; 95% confidence interval [CI]: 0.2-16.1; p = 0.044) and for VH (mean difference 12.0; 95% CI: 1.8-22.3; p = 0.02). The intervention group had significantly higher procedural steps knowledge and self-confidence for VH and/or PR (p < 0.05, adjusted analysis). Estimated blood loss, operative time and complications were similar between groups. CONCLUSIONS: Compared to usual training, procedure-specific didactic and low fidelity simulation modules for vaginal surgery resulted in significant improvements in operative performance and several other skill parameters.

Awareness and knowledge of cardiovascular disease and their associations with the lifestyles of 8-16-year-old girls: a perspective from Saudi Arabia.

BACKGROUND: There has been an increased focus on children as a target for primordial prevention of cardiovascular disease (CVD). In particular, girls should receive attention to combat the burden of CVD in women, because women have higher CVD mortality and morbidity rates than men do. As health literacy is paramount, the evaluation of awareness, and knowledge of CVD and its risk factors and their associations with the lifestyles of girls forms the basis for planning cardiovascular health promotion programs aiming to improve girls' immediate health and reduce the future burden of CVD among women. METHODS: A prospective cross-sectional study was conducted on a random sample of girls attending elementary and intermediate schools in Riyadh, Saudi Arabia. The girls completed a newly validated 24-item questionnaire that assessed their demographic data, lifestyles, and awareness and knowledge of CVD and its risk factors. Anthropometric and blood pressure measurements were obtained. Knowledge scores were calculated on the basis of correct responses and compared between subgroups via analysis of variance to determine associated factors. RESULTS: In total, 469 girls (mean age of 12.5 years) were included. Approximately 41.4% of them did not exercise or only exercised once a week. The dietary intake of important food groups was below or just at the minimal recommended servings for most. Overall, 44.1% were overweight/obese, and almost half were identified as hypertensive on the basis of a single resting measurement. Awareness of CVD as a dangerous disease in adults was 50.3%, whereas, cancer was identified by 61% of participants. Individual risk factors were identified by ≈ 25%, and 16.6% were not aware of any risk factors. The overall knowledge score of the participants was 2.6 (± 1.6) out of a total possible score of 8 representing 32.5% (± 20%). Knowledge levels were positively influenced by increasing school grade (P = 0.001) and family history of CVD (P < 0.001). There was no significant favorable association between improved knowledge level and lifestyle factors. CONCLUSION: The awareness and knowledge of CVD among girls aged 8-16 years are poor and are largely dissociated from their lifestyle. Improved knowledge scores with increasing school grade and family history of CVD confirm a role for schools and families in improving girls' knowledge. Our findings mirror those obtained in older women, showing that misinformation among women starts in childhood and should be targeted early in life.

Risk Factors for Worsening Morphology and Visual Acuity in Eyes with Adult-Onset Foveomacular Vitelliform Dystrophy.

PURPOSE: To explore clinical risk factors and OCT features associated with worse visual acuity (VA), progression of disease, choroidal neovascularization (CNV), and atrophy in eyes with adult-onset foveomacular vitelliform dystrophy (AOFVD). DESIGN: Single-center, retrospective, observational cohort study. PARTICIPANTS: Patients seen at Duke Eye Center between January 2012 and May 2023 with a diagnosis of AOFVD confirmed via OCT and fundus autofluorescence. METHODS: Baseline and final-visit images from eyes with AOFVD were examined. Disease stage was assigned, and presence of atrophy or CNV was determined. Clinical and OCT features associated with progression to atrophy and CNV were determined using t tests and chi-square analysis. Correlation with lower VA was determined using linear regression. MAIN OUTCOME MEASURES: Association of clinical characteristics and OCT features with worse VA, progression of disease, CNV, and atrophy as determined by independent t tests, chi-square analysis, and linear regression (P < 0.05). RESULTS: One hundred one eyes (63 patients) met inclusion criteria for this study, with mean follow-up duration of 48 months (standard deviation, 31 months). Fifty-one percent of eyes progressed beyond baseline staging during follow-up; among baseline stage 1 eyes, incidence of atrophy was 0.068/person-year; incidence of CNV was 0.022/person-year. Risk factors for worse final VA were baseline presence of vitreomacular traction ([VMT], P = 0.006), ellipsoid zone attenuation (P = 0.02), and increased lesion height and width (P < 0.001). Predictors of progression include diabetes mellitus (P = 0.01), statin use (P = 0.03), presence of hyperreflective foci (P = 0.01), and increased lesion width and volume (P = 0.03 and P = 0.04, respectively). Predictors of atrophy include the baseline presence of VMT (P = 0.02), decreased choroidal thickness (P = 0.03), and greater maximal height, width, and volume of the lesion (P = 0.03, P = 0.02, and P = 0.009, respectively). Lower baseline VA (P = 0.03) and increased lesion volume (P = 0.04) were associated with CNV. CONCLUSIONS: Clinical and OCT imaging features at baseline may prove useful in stratifying patient risk for progression, atrophy, CNV, and worse VA. Features such as statin use, diabetes, baseline VA, and laterality should be accounted for. OCT features, such as lesion size, VMT, ellipsoid zone attenuation, choroidal thickness, and hyperreflective foci, may impart greater risk of poor outcomes. Future prospective analysis accounting for the time to development of atrophy and CNV is needed. FINANCIAL DISCLOSURES: Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

Multimodal Retinal Imaging Classification for Parkinson's Disease Using a Convolutional Neural Network.

Purpose: Changes in retinal structure and microvasculature are connected to parallel changes in the brain. Two recent studies described machine learning algorithms trained on retinal images and quantitative data that identified Alzheimer's dementia and mild cognitive impairment with high accuracy. Prior studies also demonstrated retinal differences in individuals with PD. Herein, we developed a convolutional neural network (CNN) to classify multimodal retinal imaging from either a Parkinson's disease (PD) or control group. Methods: We trained a CNN to receive retinal image inputs of optical coherence tomography (OCT) ganglion cell-inner plexiform layer (GC-IPL) thickness color maps, OCT angiography 6 × 6-mm en face macular images of the superficial capillary plexus, and ultra-widefield (UWF) fundus color and autofluorescence photographs to classify the retinal imaging as PD or control. The model consists of a shared pretrained VGG19 feature extractor and image-specific feature transformations which converge to a single output. Model results were assessed using receiver operating characteristic (ROC) curves and bootstrapped 95% confidence intervals for area under the ROC curve (AUC) values. Results: In total, 371 eyes of 249 control subjects and 75 eyes of 52 PD subjects were used for training, validation, and testing. Our best CNN variant achieved an AUC of 0.918. UWF color photographs were the most effective imaging input, and GC-IPL thickness maps were the least contributory. Conclusions: Using retinal images, our pilot CNN was able to identify individuals with PD and serves as a proof of concept to spur the collection of larger imaging datasets needed for clinical-grade algorithms. Translational Relevance: Developing machine learning models for automated detection of Parkinson's disease from retinal imaging could lead to earlier and more widespread diagnoses.

Correlates of Breakthrough SARS-CoV-2 Infections in People with HIV: Results from the CIHR CTN 328 Study.

COVID-19 breakthrough infection (BTI) can occur despite vaccination. Using a multi-centre, prospective, observational Canadian cohort of people with HIV (PWH) receiving ≥2 COVID-19 vaccines, we compared the SARS-CoV-2 spike (S) and receptor-binding domain (RBD)-specific IgG levels 3 and 6 months post second dose, as well as 1 month post third dose, in PWH with and without BTI. BTI was defined as positivity based on self-report measures (data up to last study visit) or IgG data (up to 1 month post dose 3). The self-report measures were based on their symptoms and either a positive PCR or rapid antigen test. The analysis was restricted to persons without previous COVID-19 infection. Persons without BTI remained COVID-19-naïve until ≥3 months following the third dose. Of 289 participants, 92 developed BTI (31.5 infections per 100 person-years). The median days between last vaccination and BTI was 128 (IQR 67, 176), with the most cases occurring between the third and fourth dose (n = 59), corresponding to the Omicron wave. In analyses adjusted for age, sex, race, multimorbidity, hypertension, chronic kidney disease, diabetes and obesity, a lower IgG S/RBD (log10 BAU/mL) at 1 month post dose 3 was significantly associated with BTI, suggesting that a lower IgG level at this time point may predict BTI in this cohort of PWH.

Adult-onset foveomacular vitelliform dystrophy: epidemiology, pathophysiology, imaging, and prognosis.

Adult-onset foveomacular dystrophy (AOFVD) is a retinal pattern dystrophy that may affect up to 1 in 7,400 individuals. There is much that is unknown regarding this disease's epidemiology, risk factors for development, and rate of progression through its four stages. Advancements in retinal imaging over the past 15 years have enabled improved characterization of the different stages of AOFVD. These imaging advancements also offer new ways of differentiating AOFVD from phenotypically similar retinal diseases like age-related macular degeneration and Best disease. This review synthesizes the most recent discoveries regarding imaging correlates within AOFVD as well as risk factors for the development of AOFVD, complications of AOFVD, and treatment options. Our aim is to provide ophthalmologists a succinct resource so that they may offer clarity, guidance, and appropriate monitoring and treatments for their patients with suspected AOFVD.