"clinical decision making"

OBJECTIVE: The role of interbodies in lumbar arthrodesis has been insufficiently supported by evidence, impacting clinical decision-making and occasionally insurance coverage. This study aimed to compare clinical and radiological outcomes between lumbar arthrodesis with a synthetic interbody spacer (cage) versus structural bone graft alone (autograft or allograft) in patients with degenerative spine disease. METHODS: A systematic review of the literature was performed to identify studies directly comparing outcomes of lumbar interbody arthrodesis with and without interbody cage use...

AbstractCochlear implants can restore hearing in people with severe hearing loss and have a significant impact on communication, social integration, self-esteem, and quality of life. However, whether and how much clinical benefit is derived from cochlear implants varies significantly by patient and is influenced by the etiology and extent of hearing loss, medical comorbidities, and preexisting behavioral and psychosocial issues. In patients with underlying psychosis, concerns have been raised that the introduction of auditory stimuli could trigger hallucinations, worsen existing delusions, or exacerbate erratic behavior...

BACKGROUND: Artificial intelligence (AI), more specifically large language models (LLMs), holds significant potential in revolutionizing emergency care delivery by optimizing clinical workflows and enhancing the quality of decision-making. Although enthusiasm for integrating LLMs into emergency medicine (EM) is growing, the existing literature is characterized by a disparate collection of individual studies, conceptual analyses, and preliminary implementations. Given these complexities and gaps in understanding, a cohesive framework is needed to comprehend the existing body of knowledge on the application of LLMs in EM...

B-cell maturation antigen (BCMA)-targeting therapeutics have dramatically improved outcomes in relapsed/refractory multiple myeloma (RRMM). However, whether the mechanisms of resistance between these therapies are shared and how the identification of such mechanisms before therapy initiation could refine clinical decision-making remains undefined. We analyzed outcomes for 72 RRMM patients treated with teclistamab, a CD3 x BCMA bispecific antibody (BsAb), 42% (30/72) of whom had prior BCMA-directed therapy exposure...

BACKGROUND: Accurately predicting kidney outcomes in IgA nephropathy is crucial for clinical decision making. Insufficient use of longitudinal data in previous studies has limited the accuracy and interpretability of prediction models for failing to reflect the chronic nature of IgA nephropathy. This study aimed at establishing a multivariable dynamic deep learning model using comprehensive longitudinal data for the prediction of kidney outcomes in IgA nephropathy. METHODS: In this retrospective cohort study of 2,056 IgA nephropathy patients at 18 kidney centers, a total of 28,317 data points were collected by the sliding window method...

This study reviews and appraises the methodological and reporting quality of prediction models for tooth loss in periodontitis patients, including the use of regression and machine learning models. Studies involving prediction modeling for tooth loss in periodontitis patients were screened. A search was performed in MEDLINE via PubMed, Embase, and CENTRAL up to 12 February 2022, with citation chasing. Studies exploring model development or external validation studies for models assessing tooth loss in periodontitis patients for clinical use at any time point, with all prediction horizons in English, were considered...

Single tooth orange discoloration secondary to root canal calcification occurs as a consequence of dental trauma, orthodontic treatment, or for unknown rea- sons. A correct case history must be compiled and a CBCT study carried out in order to establish the diag- nosis and define the best treatment plan in each case. The aim of the present study was to offer a therapeutic protocol involving a clinical decision-making tree dia- gram based on the presence or absence of apical dis- ease and the degree of canal calcification...

PURPOSE OF REVIEW: This review explores the role of circulating tumor (ct)DNA as a biomarker for clinical decision-making and monitoring purposes in metastatic gastrointestinal stromal tumor (GIST) patients. We discuss key insights from recent clinical trials and anticipate the future perspectives of ctDNA profiling within the clinical landscape of GIST. RECENT FINDINGS: The identification and molecular characterization of KIT/platelet-derived growth factor receptor alpha (PDGFRA) mutations from ctDNA in metastatic GIST is feasible and reliable...

<span style="font-size:12pt"><span style="font-family:Aptos,sans-serif">The identification and management of patients at high bleeding risk (HBR) undergoing transcatheter aortic valve implantation (TAVI) are of major importance, but the lack of standardised definitions is challenging for trial design, data interpretation, and clinical decision-making. The Valve Academic Research Consortium for High Bleeding Risk (VARC-HBR) is a collaboration among leading research organisations, regulatory authorities, and physician-scientists from Europe, the USA, and Asia, with a major focus on TAVI-related bleeding...

BACKGROUND: Vessel-level physiological data derived from pressure wire measurements are one of the important determinant factors in the optimal revascularisation strategy for patients with multivessel disease (MVD). However, these may result in complications and a prolonged procedure time. AIMS: The feasibility of using the quantitative flow ratio (QFR), an angiography-derived fractional flow reserve (FFR), in Heart Team discussions to determine the optimal revascularisation strategy for patients with MVD was investigated...

No abstract text is available yet for this article.

BACKGROUND: Osteoporosis is becoming more common worldwide, imposing a substantial burden on individuals and society. The onset of osteoporosis is subtle, early detection is challenging, and population-wide screening is infeasible. Thus, there is a need to develop a method to identify those at high risk for osteoporosis. OBJECTIVE: This study aimed to develop a machine learning algorithm to effectively identify people with low bone density, using readily available demographic and blood biochemical data...

To optimize clinical care, it is imperative for providers to recognize their own inherent cognitive biases and the impact that has on their clinical decision making, thereby minimizing complications such as prolonged hospitalization, unnecessary healthcare spending, and impaired patient satisfaction and functional outcomes.

Recently developed survival analysis methods improve upon existing approaches by predicting the probability of event occurrence in each of a number pre-specified (discrete) time intervals. By avoiding placing strong parametric assumptions on the event density, this approach tends to improve prediction performance, particularly when data are plentiful. However, in clinical settings with limited available data, it is often preferable to judiciously partition the event time space into a limited number of intervals well suited to the prediction task at hand...

BACKGROUND: The evidence base pertaining to the efficacy of monotherapies for androgenetic alopecia (AGA), the most common form of hair loss, is ever expanding-and this warrants a formal comparison therapies' effect on a frequent basis. AIMS: The objective of the current study was to determine the comparative effect of relevant monotherapies for male AGA. PATIENTS/METHODS: Our aim was achieved by conducting Bayesian network meta-analysis (NMA), under a random effects model, for two outcomes: 6-month change in (1) total and (2) terminal hair density in adult (i...

OBJECTIVE: The macrophage activation syndrome (MAS) secondary to systemic lupus erythematosus (SLE) is a severe and life-threatening complication. Early diagnosis of MAS is particularly challenging. In this study, machine learning models and diagnostic scoring card were developed to aid in clinical decision-making using clinical characteristics. METHODS: We retrospectively collected clinical data from 188 patients with either SLE or the MAS secondary to SLE. 13 significant clinical predictor variables were filtered out using the Least Absolute Shrinkage and Selection Operator (LASSO)...

BACKGROUND: This study aimed to evaluate the efficacy of radiomics signatures derived from polyenergetic images (PEIs) and virtual monoenergetic images (VMIs) obtained through dual-layer spectral detector CT (DLCT). Moreover, it sought to develop a clinical-radiomics nomogram based on DLCT for predicting cancer stage (early stage: stage I-II, advanced stage: stage III-IV) in pancreatic ductal adenocarcinoma (PDAC). METHODS: A total of 173 patients histopathologically diagnosed with PDAC and who underwent contrast-enhanced DLCT were enrolled in this study...

Precision and intelligence in evaluating the complexities of middle ear structures are required to diagnose auriculotemporal and ossicle-related diseases within otolaryngology. Due to the complexity of the anatomical details and the varied etiologies of illnesses such as trauma, chronic otitis media, and congenital anomalies, traditional diagnostic procedures may not yield accurate diagnoses. This research intends to enhance the diagnosis of diseases of the auriculotemporal region and ossicles by combining High-Resolution Spiral Computed Tomography (HRSCT) scanning with Deep Learning Techniques (DLT)...

PURPOSE: The aim of this study was to develop and validate a machine learning (ML) model for predicting the risk of new osteoporotic vertebral compression fracture (OVCF) in patients who underwent percutaneous vertebroplasty (PVP) and to create a user-friendly web-based calculator for clinical use. METHODS: A retrospective analysis of patients undergoing percutaneous vertebroplasty: A retrospective analysis of patients treated with PVP between June 2016 and June 2018 at Liuzhou People's Hospital was performed...

Severe fever with thrombocytopenia syndrome (SFTS) is an acute infectious disease caused by a novel Bunyavirus infection with low population immunity and high mortality rate. Lacking specific therapies, the treatment measures vary with the severity of the disease, therefore, a case control study involved 394 SFTS patients was taken to determine risk factors for mortality. Comparative clinical data from the first 24 h after admission was collected through the electronic medical record system. Independent risk factors for death of SFTS were identified through univariate and multivariate binary logistic regression analyses...