We present the software ModInterv as an informatics tool to monitor, in an automated and user-friendly manner, the evolution and trend of COVID-19 epidemic curves, both for cases and deaths. The ModInterv software uses parametric generalized growth models, together with LOWESS regression analysis, to fit epidemic curves with multiple waves of infections for countries around the world as well as for states and cities in Brazil and the USA. The software automatically accesses publicly available COVID-19 databases maintained by the Johns Hopkins University (for countries as well as states and cities in the USA) and the Federal University of Viçosa (for states and cities in Brazil). The richness of the implemented models lies in the possibility of quantitatively and reliably detecting the distinct acceleration regimes of the disease. We describe the backend structure of software as well as its practical use. The software helps the user not only to understand the current stage of the epidemic in a chosen location but also to make short term predictions as to how the curves may evolve. The app is freely available on the internet (http://fisica.ufpr.br/modinterv), thus making a sophisticated mathematical analysis of epidemic data readily accessible to any interested user.
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http://dx.doi.org/10.1016/j.asoc.2023.110159 | DOI Listing |
Eur J Pediatr
January 2025
Pediatric Endocrinology and Diabetes Unit, Department of Pediatrics, Mansoura Faculty of Medicine, Mansoura University Children's Hospital, Mansoura University, Gomhoria Street, Mansoura, 35516, Dakhlia, Egypt.
Unlabelled: This study aims to determine the incidence, clinical course, and risk factors of hypothyroidism following cardiac catheter (CC) in infants with congenital heart diseases (CHD). This prospective study involved 115 patients with CHD, all aged 3 years or younger, who underwent CC, as well as 100 healthy age- and sex-matched controls. Baseline thyroid function tests (TFTs) were conducted for both the patients and controls.
View Article and Find Full Text PDFTunis Med
January 2025
University of Tunis El Manar, Faculty of Medicine of Tunis, Department of Cardiology, Security forces hospital, La Marsa, Tunisia.
Unlabelled: Introduction Acute heart failure (AHF) is a life-threatening condition that requires swift diagnosis and tailored management to enhance patient outcomes. In the pursuit of more precise prognostic indicators, Tricuspid Annular Plane Systolic Excursion (TAPSE) and Pulmonary Arterial Systolic Pressure (PASP) have emerged as potential significant advancements. The TAPSE/PASP ratio, a novel parameter, has recently gained attention as a promising predictor of outcomes in acute heart failure.
View Article and Find Full Text PDFJ Antimicrob Chemother
January 2025
Department of Infectious Diseases and Clinical Microbiology, Hacettepe University Faculty of Medicine, Ankara, Turkey.
Objectives: To develop a scoring system to predict resistance to ceftolozane/tazobactam in Pseudomonas aeruginosa strains isolated from respiratory specimens.
Methods: A case-control study was conducted to evaluate the risk factors associated with resistance to ceftolozane/tazobactam. Patients with P.
World J Gastroenterol
January 2025
Clinical School of the Second People's Hospital, Tianjin Medical University, Tianjin 300192, China.
Background: Colorectal polyps are commonly observed in patients with chronic liver disease (CLD) and pose a significant clinical concern because of their potential for malignancy.
Aim: To explore the clinical characteristics of colorectal polyps in patients with CLD, a nomogram was established to predict the presence of adenomatous polyps (AP).
Methods: Patients with CLD who underwent colonoscopy at Tianjin Second People's Hospital from January 2020 to May 2023 were evaluated.
Ophthalmol Sci
November 2024
Casey Eye Institute, Oregon Health & Science University, Portland, Oregon.
Purpose: The diagnosis of fungal keratitis using potassium hydroxide (KOH) smears of corneal scrapings enables initiation of the correct antimicrobial therapy at the point-of-care but requires time-consuming manual examination and expertise. This study evaluates the efficacy of a deep learning framework, dual stream multiple instance learning (DSMIL), in automating the analysis of whole slide imaging (WSI) of KOH smears for rapid and accurate detection of fungal infections.
Design: Retrospective observational study.
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