Clinical decision rules

Group A beta-hemolytic streptococcal pharyngitis is a common infection responsible for more than 6 million office visits in the United States annually. Only 10% of adults seeking care for a sore throat have group A beta-hemolytic streptococcal pharyngitis; however, 60% or more are prescribed antibiotics. Guidelines recommend using clinical decision rules to assess the risk of group A beta-hemolytic streptococcal infection, followed by rapid antigen testing if a diagnosis is unclear, before prescribing antibiotics...

BACKGROUND: Thus far, all the clinical models developed to predict major bleeding in patients on extended anticoagulation therapy use the baseline predictors to stratify patients into different risk groups. Therefore, these models do not account for the clinical changes and events that occur after the baseline visit, which can modify risk of bleeding. However, it is difficult to develop predictive models from the routine follow-up clinical interviews which are irregular sequences of multivariate time series data...

BACKGROUND: Hepatic artery infusion pump (HAIP) with floxuridine/dexamethasone and systemic chemotherapy is an established treatment regimen, which had been reported about converting 47% of patients with stage 4 colorectal liver metastasis from unresectable to resectable.1,2 To this effect, HAIP chemotherapy contributes to prolonged survival of many patients, which otherwise may not have other treatment options. Biliary sclerosis, however, is a known complication of the HAIP treatment, which occurs in approximately 5...

OBJECTIVE: Machine learning (ML) is increasingly employed to diagnose medical conditions, with algorithms trained to assign a single label using a black-box approach. We created an ML approach using deep learning that generates outcomes that are transparent and in line with clinical, diagnostic rules. We demonstrate our approach for autism spectrum disorders (ASD), a neurodevelopmental condition with increasing prevalence. METHODS: We use unstructured data from the Centers for Disease Control and Prevention (CDC) surveillance records labeled by a CDC-trained clinician with ASD A1-3 and B1-4 criterion labels per sentence and with ASD cases labels per record using Diagnostic and Statistical Manual of Mental Disorders (DSM5) rules...

Interpersonal communication facilitates symptom measures of autistic sociability to enhance clinical decision-making in identifying children with autism spectrum disorder (ASD). Traditional methods are carried out by clinical practitioners with assessment scales, which are subjective to quantify. Recent studies employ engineering technologies to analyze children's behaviors with quantitative indicators, but these methods only generate specific rule-driven indicators that are not adaptable to diverse interaction scenarios...

BACKGROUND: The syndemic nature of gonococcal infections and HIV provides an opportunity to develop a synergistic intervention tool that could address the need for adequate treatment for gonorrhea, screen for HIV infections, and offer pre-exposure prophylaxis (PrEP) for persons who meet the criteria. By leveraging information available on electronic health records, a clinical decision support (CDS) system tool could fulfill this need and improve adherence to Centers for Disease Control and Prevention (CDC) treatment and screening guidelines for gonorrhea, HIV, and PrEP...

In Acute Admission Wards, vital signs are commonly measured only intermittently. This may result in failure to detect early signs of patient deterioration and impede timely identification of patient stability, ultimately leading to prolonged stays and avoidable hospital admissions. Therefore, continuous vital sign monitoring may improve hospital efficacy. The objective of this randomized controlled trial was to evaluate the effect of continuous monitoring on the proportion of patients safely discharged home directly from an Acute Admission Ward...

Opioid administration is particularly challenging in the perioperative period. Computerized-based Clinical Decision Support Systems (CDSS) are a promising innovation that might improve perioperative pain control. We report the development and feasibility validation of a knowledge-based CDSS aiming at optimizing the management of perioperative pain, postoperative nausea and vomiting (PONV), and laxative medications. This novel CDSS uses patient adaptive testing through a smartphone display, literature-based rules, and individual medical prescriptions to produce direct medical advice for the patient user...

Objective: Previous research indicates positive effects of feedback based on rational or empirical decision rules in psychotherapy. The implementation of these usually session-to-session-based feedback systems into clinical practice, however, remains challenging. This study aims to evaluate decision rules based on routine outcome monitoring with reduced assessment frequency. Method: Data routinely collected every 5-20 sessions of N  = 3758 patients treated with CBT in an outpatient clinic ( M sessions  = 42...

Deep Learning models such as Convolutional Neural Networks (CNNs) are very effective at extracting complex image features from medical X-rays. However, the limited interpretability of CNNs has hampered their deployment in medical settings as they failed to gain trust among clinicians. In this work, we propose an interactive framework to allow clinicians to ask what-if questions and intervene in the decisions of a CNN, with the aim of increasing trust in the system. The framework translates a layer of a trained CNN into a measurable and compact set of symbolic rules...

Bedside ultrasound represents a well-suited diagnostic and monitoring tool for patients on extracorporeal membrane oxygenation (ECMO) who may be too unstable for transport to other hospital areas for diagnostic tests. The role of ultrasound, however, starts even before ECMO initiation. Every patient considered for ECMO should have a thorough ultrasonographic assessment of cardiac and valvular function, as well as vascular anatomy without delaying ECMO cannulation. The role of pre-ECMO ultrasound is to confirm the indication for ECMO, identify clinical situations for which ECMO is not indicated, rule out contraindications, and inform the choice of ECMO configuration...

PURPOSE: Clinical decision support systems (CDSS) are used to identify drugs with potential need for dose modification in patients with renal impairment. ChatGPT holds the potential to be integrated in the electronic health record (EHR) system to give such dosing advices. In this study, we aim to evaluate the performance of ChatGPT in clinical rule-guided dose interventions in hospitalized patients with renal impairment. METHODS: This cross-sectional study was performed at Tergooi Medical Center, the Netherlands...

OBJECTIVES: This study aimed to explore the role of CT in septic patients presenting to the emergency department (ED). MATERIALS AND METHODS: We performed a retrospective secondary analysis of 192 septic patients from a prospective observational study, i.e., the "LIFE POC" study. Sepsis was diagnosed in accordance with the Sepsis-3 definition. Clinical and radiological data were collected from the hospital administration and radiological systems. Information on mortality and morbidity was collected...

Contingency Management (CM) is a psychological treatment that aims to change behavior with financial incentives. In substance use disorders (SUDs), deployment of CM has been enriched by longstanding discussions around the cost-effectiveness of prized-based and voucher-based approaches. In prize-based CM, participants earn draws to win prizes, including small incentives to reduce costs, and the number of draws escalates depending on the duration of maintenance of abstinence. In voucher-based CM, participants receive a predetermined voucher amount based on specific substance test results...

BACKGROUND: Measurement of cardiac troponin (cTn) by a high sensitivity method is now the recommended strategy for the detection of myocardial injury. An international survey was undertaken to assess how this has been implemented. METHODS: A questionnaire based around 14 domains on cardiac biomarkers was distributed electronically with the aid of professional societies accessed by a web link within the invitation. Results were returned electronically then extracted into a relational database for analysis...

This study aimed to develop an interpretable diagnostic model for subtyping of pulmonary adenocarcinoma, including minimally invasive adenocarcinoma (MIA), adenocarcinoma in situ (AIS), and invasive adenocarcinoma (IAC), by integrating 3D-radiomic features and clinical data. Data from multiple hospitals were collected, and 10 key features were selected from 1600 3D radiomic signatures and 11 radiological features. Diverse decision rules were extracted using ensemble learning methods (gradient boosting, random forest, and AdaBoost), fused, ranked, and selected via RuleFit and SHAP to construct a rule-based diagnostic model...

PURPOSE: With the advent of precision medicine, molecular tumor boards (MTBs) were established to interpret genomic results and guide decision making for targeted therapy in oncology patients. There are currently no universal guidelines for how MTBs should operate and thus variance can be seen depending on which MTB is reviewing the case. This study assesses the concordance of MTB recommendations when a participant case is reviewed by two different MTBs, establishes potential reasons for discordance, and advocates for the establishment of standard MTB operating guidelines...

OBJECTIVES: To analyze the performance of commonly used blood tests in febrile infants ≤90 days of age to identify patients at low risk for invasive bacterial infection (bacterial pathogen in blood or cerebrospinal fluid) by duration of fever. METHODS: We conducted a secondary analysis of a prospective single-center registry that includes all consecutive infants ≤90 days of age with fever without a source evaluated at 1 pediatric emergency department between 2008 and 2021...

BACKGROUND: Emerging evidence suggests that clinical prediction models that use repeated (time-varying) measurements within each patient may have higher predictive accuracy than models that use patient information from a single measurement. OBJECTIVE: To determine the breadth of the published literature reporting the development of clinical prediction models in children that use time-varying predictors. DATA SOURCES: MEDLINE, EMBASE and Cochrane databases...

HYPOTHESIS: The natural history of pediatric melanonychia and the necessity of biopsy for ruling out melanoma are debated in the literature. We hypothesize that there is a low rate of malignant nail pathology among pediatric patients undergoing nail bed biopsy for melanonychia. METHODS: We performed a retrospective chart review of 54 pediatric patients (age <18 years) at a single institution who presented with melanonychia and underwent nail bed biopsy from 2007 to 2022...