Beaumont Health

BackgroundHeart failure (HF) is a major global cause of death. Early risk prediction and intervention could mitigate disease progression. We aimed to improve HF prediction by integrating genome-wide association studies (GWAS)- and electronic health records (EHR)-derived risk scores.MethodsWe previously performed a large HF GWAS within the Global Biobank Meta-analysis Initiative to create a polygenic risk score (PRS). Three Michigan Medicine (MM) cohorts were used to develop the clinical risk score (ClinRS): 1) Primary Care Provider cohort (MM-PCP; N = 61,849), 2) Heart Failure cohort (MM-HF; N = 53,272), and 3) Michigan Genomics Initiative cohort (MM-MGI; N = 60,215). To extract information from high-dimensional EHR data, we leveraged natural language processing to generate 350 latent phenotypes representing EHR codes and used coefficients from LASSO regression on these phenotypes in a training set as weights to calculate ClinRS in a validation set. Using logistic regression, model performances were compared between baseline model and models with risk scores added: 1) PRS, 2) ClinRS, and 3) ClinRS+PRS. We further compared the proposed models with Atherosclerosis Risk in Communities (ARIC) HF risk score.ResultsPRS and ClinRS each predict HF outcomes significantly better than the baseline model, up to eight years prior to HF diagnosis. Including both PRS and ClinRS further improves prediction performance up to ten years prior to diagnosis, two years earlier than either score alone. Additionally, ClinRS significantly outperforms the ARIC model one year prior.ConclusionsWe demonstrate the additive power of integrating GWAS- and EHR-derived risk scores to predict HF cases prior to diagnosis. This standardizable and scalable risk predictor may enable physicians to provide earlier interventions to improve patient outcomes.

A 32-year-old male with Lynch Syndrome and a history of colon cancer status post total proctocolectomy was found to have invasive high-grade carcinoma with signet ring cell morphology on tissue sampling of the bladder neck following transurethral resection of a bladder tumor (TURBT). The patient subsequently underwent an open cystoprostatectomy and completion proctectomy. Final pathology of the prostate, bladder, and bladder augment confirmed the diagnosis of signet ring cell adenocarcinoma (SRCC) of the bladder. Given its rarity, this case illustrates the challenges of managing an aggressive bladder cancer and underscores the importance of considering appropriate screening strategies in high-risk populations.

BackgroundGenomic sequences of E. marmotae and E. coli differ by 10%. Discovered as an environmental “cryptic clade” of Escherichia, E. marmotae also occurs in human infections. Microbiological and MALDI-TOF-MS methods frequently misidentify E. marmotae as E.coli. Our goal was to develop methods that reliably distinguish E. marmotae from E. coli to improve therapeutic decisions and treatments.MethodsA Taqman PCR method was developed to distinguish E. marmotae from E. coli based on genomic sequences of uidA, uidB, and a positive control targeting adk in E. marmotae and E. coli. MALDI-TOF-MS spectra were obtained for environmental and clinical isolates using a bioMérieux VITEK MALDI-TOF-MS system.ResultsUidA- and uidB species-specific PCR amplified DNA from E. marmotae with 100% specificity, and not from E. coli or other Escherichia species. The Biomérieux VITEK MALDI-TOF-MS consistently misidentified E. marmotae as E. coli, with median IVD confidence scores for both E. marmotae and E. coli of 99.9%; however, RUO scores for E. marmotae (median 0%) were significantly lower (P < 0.0001) than for E. coli (median = 87.4%). The spectral peak between m/z 7,250 to 7,280 consistently occurred between 7,260 and 7,268 in E. marmotae and only between 7,268 and 7,280 in E. coli, with no overlap (p < 0.001). Application of these spectral criteria to 176 clinical isolates revealed the first identification of a E. marmotae isolate from a human infection in North America. The isolate had originally been diagnosed as E. coli based on a 99.1% IVD confidence score. This first North American clinical isolate was confirmed as E. marmotae by Taqman-PCR and whole genome sequencing. This isolate had numerous antibiotic resistance gene markers and unlike most clinical E. coli, this E. marmotae isolate lacked motility at 37°C.ConclusionClinical tests based on these methods of differentiating E. marmotae and E. coli may assist in determining the prevalence of this emerging pathogen and making therapeutic decisions.

To evaluate the use of shoulder arthroscopic simulation in orthopaedic surgery trainees. A literature search was performed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, using PubMed, Medline (Ovid), and EMBASE library databases. Inclusion criteria were experimental studies reporting pre- and post-test results of shoulder arthroscopic simulation in orthopaedic trainees (studies reporting results of comparison between groups not within the groups were excluded). Participant demographics, type of simulator training, simulator tasks assessed, and performance outcome measures were systematically reviewed. Each performance outcome measure was graphically represented in a Forest plot with point estimates of the incidence of performance outcomes with corresponding 95% confidence intervals and I2. Fifteen studies met inclusion criteria with a total of 353 participants. The most common procedures simulated were diagnostic shoulder arthroscopy (n = 9 [60%]), arthroscopic Bankart repairs (n = 3 [20%]), and rotator cuff repairs (n = 2 [13%]). Simulations primarily used virtual reality (60%) and benchtop models (40%). The primary outcomes measured were time to task completion and Arthroscopic Surgical Skill Evaluation Tool scores. Time to task completion improved significantly with training (range 13-439 seconds pretest to 8-253.29 seconds post-test), with substantial heterogeneity across studies (I2 = 87%). ASSET scores improved in 60% of the studies (ranging from 14-20.9 pretest to 17.9-28.5 post-test), with low heterogeneity (I2 = 20%). In addition, both camera and probe distances decreased after simulation use, whereas the 14-point anatomic checklist showed no pre- to post-test differences. Arthroscopic simulation training benefits technical skills in shoulder arthroscopy, but the quality, assessment, and validity of these protocols vary. The translation of simulation training into the operating room has yet to be conclusively demonstrated. Level IV, systematic review of Level I-IV studies.

Abstract INTRODUCTION: Acute respiratory distress syndrome (ARDS) is a life-threatening inflammatory condition with acute-onset hypoxemia with non-cardiogenic pulmonary edema, and bilateral opacities on lung radiograph. While the definition of ARDS has changed throughout the years, the Berlin Criteria specifies an arterial to inspired oxygen ratio (PaO2/FiO2) of &amp;lt;300. ARDS is often complicated by thrombocytopenia and dysregulated hemostasis. This study aimed to investigate the association of triggering receptor expressed in myeloid cells-like transcript-1 positive (TLT-1+), glycoprotein (Gp) 1b, and αIIbβIIIa Microparticles (MPs) with clinical outcomes in ARDS. RATIONALE: Identify the association of triggering receptor expressed in myeloid cells-like transcript-1 positive (TLT-1+), glycoprotein (Gp) 1b, andαIIbβIIIa Microparticles (MPs) with clinical outcomes and disease severity in acute respiratory distress syndrome (ARDS). METHODS: We quantified TLT-1, glycoprotein (Gp) 1b, or αIIbβIIIa immunopositive MPs in plasma samples from patients with ARDS enrolled in the ARMA, KARMA, and LARMA ARDS Network clinical trials via flow cytometry. A total of 543 patients’ blood samples were analyzed. Apache 3 scores were calculated for all patients and the number of days the patient survived up to 28 days. RESULTS: No associations were found between Gp1b+ MPs and clinical outcomes for any of the cohorts. When stratified by quartile, associations were found for survival, ventilation-free breathing, and thrombocytopenia with αIIbβIIIa + and TLT-1+ MPs (χ2 p &amp;lt; 0.001). Notably, 63 of 64 patients in this study who failed to achieve unassisted breathing had TLT1+ PMP in the 75th percentile. In all three cohorts, patients whose TLT1+ MP counts were higher than the median had higher Acute Physiology and Chronic Health Evaluation (APACHE) III scores, were more likely to present with thrombocytopenia and were 3.7 times (p &amp;lt; 0.001) more likely to die than patients with lower TLT+ PMP after adjusting for other risk factors. The highest association with mortality was when high TLT1+ MP were divided by high platelet counts as shown in the Kaplan-Meir curve. CONCLUSIONS: Although both αIIbβIIIa + and TLT+ microparticles (αIIbβIIIa, TLT-1) were associated with mortality, TLT-1+ MPs demonstrated stronger correlations with APACHE III scores, unassisted breathing, and multiple system organ failure. These findings warrant further exploration of the mechanistic role of TLT-1+ PMP in ARDS or acute lung injury progression especially when normalized for platelet count and its potential as a therapeutic target.