Internal and emergency medicine
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Review Observational Study
Renal function-adapted D-dimer cutoffs in combination with a clinical prediction rule to exclude pulmonary embolism in patients presenting to the emergency department.
D-dimer levels significantly increase with declining renal function and hence, renal function-adjusted D-dimer cutoffs to rule out pulmonary embolism were suggested. Aim of this study was to "post hoc" validate previously defined renal function-adjusted D-dimer levels to safely rule out pulmonary embolism in patients presenting to the emergency department. In this retrospective, observational analysis, all patients with low to intermediate pre-test probability receiving D-dimer measurement and computed tomography angiography (CTA) to rule out pulmonary embolism between January 2017 and December 2020 were included. ⋯ The findings of this study underline that application of renal function-adapted D-dimer levels in combination with a clinical prediction rule appears feasible to rule out pulmonary embolism. Out of the current dataset, renal function-adjusted D-dimer cutoffs to rule out pulmonary embolism were slightly different compared to previously defined cutoffs. Further studies on a larger scale are needed to validate possible renal function-adjusted D-dimer cutoffs.
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Randomized Controlled Trial
Real-time machine learning-assisted sepsis alert enhances the timeliness of antibiotic administration and diagnostic accuracy in emergency department patients with sepsis: a cluster-randomized trial.
Machine learning (ML) has been applied in sepsis recognition across different healthcare settings with outstanding diagnostic accuracy. However, the advantage of ML-assisted sepsis alert in expediting clinical decisions leading to enhanced quality for emergency department (ED) patients remains unclear. A cluster-randomized trial was conducted in a tertiary-care hospital. ⋯ The diagnostic performance of ML in prompt sepsis detection was superior to that of the rule-based system. Trial registration Thai Clinical Trials Registry TCTR20230120001. Registered 16 January 2023-Retrospectively registered, https://www.thaiclinicaltrials.org/show/TCTR20230120001 .
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This study aims to apply machine learning models to identify new biomarkers associated with the early diagnosis and prognosis of SARS-CoV-2 infection. Plasma and serum samples from COVID-19 patients (mild, moderate, and severe), patients with other pneumonia (but with negative COVID-19 RT-PCR), and healthy volunteers (control) from hospitals in four different countries (China, Spain, France, and Italy) were analyzed by GC-MS, LC-MS, and NMR. Machine learning models (PCA and PLS-DA) were developed to predict the diagnosis and prognosis of COVID-19 and identify biomarkers associated with these outcomes. ⋯ The PLS-DA model was able to predict the diagnosis and prognosis of COVID-19 around 95%. Additionally, our investigation pinpointed five novel potential biomarkers linked to the diagnosis and prognosis of COVID-19: N-Acetyl-4-O-acetylneuraminic acid, N-Acetyl-L-Alanine, N-Acetyltriptophan, palmitoylcarnitine, and glycerol 1-myristate. These biomarkers exhibited heightened levels in severe COVID-19 patients compared to those with mild COVID-19 or healthy volunteers.
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Observational Study
Site and duration of abdominal pain discriminate symptomatic uncomplicated diverticular disease from previous diverticulitis patients.
Abdominal pain in patients with diverticular disease (DD) can be challenging in clinical practice. Patients with symptomatic uncomplicated diverticular disease (SUDD) and patients with a previous acute diverticulitis (PD) may share a similar clinical pattern, difficult to differentiate from irritable bowel syndrome (IBS). We used standardized questionnaires for DD (short and long lasting abdominal pain) and IBS (following Rome III Criteria) to assess clinical features of abdominal pain, in terms of presence, severity and length, in SUDD and PD patients. ⋯ SUDD and PD patients presented different pattern of abdominal pain (length, number of long lasting episodes, site and associated features), with a third reporting overlap with IBS. Further observational studies are needed to better characterize abdominal symptoms in DD patients, especially in those not fulfilling IBS criteria. Trial registration: The REMAD Registry is registered as an observational study in ClinicalTrial.gov (ID: NCT03325829).
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The effect of digoxin and beta-blockers on cardiovascular outcomes and mortality remains unclear. The study aimed to determine differences in cardiovascular (CV) outcomes and death rates among patients with atrial fibrillation (AF) who were prescribed with beta-blockers, digoxin or combination therapy. Data from phase II/III of the prospective Global Registry on Long-Term Oral Anti-thrombotic Treatment in Patients with Atrial Fibrillation (GLORIA-AF) were analysed. ⋯ The incidence rate (IR) of MACE was 22.4 (95%CI 21.0-24.0) per 1000 person-years, while the IR of all-cause death was 25.4 (95%CI 23.8-27.0) per 1000 person-years. After multivariate adjustment with Cox regression, the risk of MACE (HR 1.35, 95% CI 1.09-1.68) and the risk of all-cause death (HR 1.28, 95%CI 1.04-1.57) were significantly higher in the combination therapy group, compared to the beta-blockers alone group. The risks of MACE and all-cause death remained significant in both PS matched and PS weighted cohort Among AF patients, combination therapy of beta-blockers and digoxin was associated with higher risks of MACE and all-cause death compared to beta-blockers alone.