Identifying symptom etiologies using syntactic patterns and large language models.

Differential diagnosis is a crucial aspect of medical practice, as it guides clinicians to accurate diagnoses and effective treatment plans. Traditional resources, such as medical books and services like UpToDate, are constrained by manual curation, potentially missing out on novel or less common findings. This paper introduces and analyzes two novel methods to mine etiologies from scientific literature. The first method employs a traditional Natural Language Processing (NLP) approach based on syntactic patterns. By using a novel application of human-guided pattern bootstrapping patterns are derived quickly, and symptom etiologies are extracted with significant coverage. The second method utilizes generative models, specifically GPT-4, coupled with a fact verification pipeline, marking a pioneering application of generative techniques in etiology extraction. Analyzing this second method shows that while it is highly precise, it offers lesser coverage compared to the syntactic approach. Importantly, combining both methodologies yields synergistic outcomes, enhancing the depth and reliability of etiology mining.

Inherent Bias in Electronic Health Records: A Scoping Review of Sources of Bias.

Objectives: 1.1Biases inherent in electronic health records (EHRs), and therefore in medical artificial intelligence (AI) models may significantly exacerbate health inequities and challenge the adoption of ethical and responsible AI in healthcare. Biases arise from multiple sources, some of which are not as documented in the literature. Biases are encoded in how the data has been collected and labeled, by implicit and unconscious biases of clinicians, or by the tools used for data processing. These biases and their encoding in healthcare records undermine the reliability of such data and bias clinical judgments and medical outcomes. Moreover, when healthcare records are used to build data-driven solutions, the biases are further exacerbated, resulting in systems that perpetuate biases and induce healthcare disparities. This literature scoping review aims to categorize the main sources of biases inherent in EHRs. Methods: 1.2We queried PubMed and Web of Science on January 19th, 2023, for peer-reviewed sources in English, published between 2016 and 2023, using the PRISMA approach to stepwise scoping of the literature. To select the papers that empirically analyze bias in EHR, from the initial yield of 430 papers, 27 duplicates were removed, and 403 studies were screened for eligibility. 196 articles were removed after the title and abstract screening, and 96 articles were excluded after the full-text review resulting in a final selection of 116 articles. Results: 1.3Systematic categorizations of diverse sources of bias are scarce in the literature, while the effects of separate studies are often convoluted and methodologically contestable. Our categorization of published empirical evidence identified the six main sources of bias: a) bias arising from past clinical trials; b) data-related biases arising from missing, incomplete information or poor labeling of data; human-related bias induced by c) implicit clinician bias, d) referral and admission bias; e) diagnosis or risk disparities bias and finally, (f) biases in machinery and algorithms. Conclusions: 1.4Machine learning and data-driven solutions can potentially transform healthcare delivery, but not without limitations. The core inputs in the systems (data and human factors) currently contain several sources of bias that are poorly documented and analyzed for remedies. The current evidence heavily focuses on data-related biases, while other sources are less often analyzed or anecdotal. However, these different sources of biases add to one another exponentially. Therefore, to understand the issues holistically we need to explore these diverse sources of bias. While racial biases in EHR have been often documented, other sources of biases have been less frequently investigated and documented (e.g. gender-related biases, sexual orientation discrimination, socially induced biases, and implicit, often unconscious, human-related cognitive biases). Moreover, some existing studies lack causal evidence, illustrating the different prevalences of disease across groups, which does not per se prove the causality. Our review shows that data-, human- and machine biases are prevalent in healthcare and they significantly impact healthcare outcomes and judgments and exacerbate disparities and differential treatment. Understanding how diverse biases affect AI systems and recommendations is critical. We suggest that researchers and medical personnel should develop safeguards and adopt data-driven solutions with a "bias-in-mind" approach. More empirical evidence is needed to tease out the effects of different sources of bias on health outcomes.

Incidence and Predictors of New-Onset Atrial Fibrillation After Transcatheter Edge-to-Edge Repair of the Mitral Valve (from the Nationwide Readmissions Database).

Patients who underwent transcatheter edge-to-edge repair (TEER) for mitral regurgitation with atrial fibrillation (AF) at baseline have higher mortality than those without AF. Data on new-onset AF (NOAF) after TEER are limited. Using the 2016 to 2018 Nationwide Readmissions Database, we identified a cohort of patients who underwent TEER and classified them into 3 groups based on AF presence during the study period. The primary end point was the incidence and timing of NOAF up to 6 months after TEER. Logistic regression modeling identified independent predictors of NOAF at readmission. Of the 6,861patients that underwent TEER, 4,134 (59.9%) had AF at baseline, and 239 (3.5%) developed NOAF. Median time-to-NOAF admission was 47 days (interquartile range 16 to 113), and 37% of patients with NOAF presented within 30 days after TEER. Patients with NOAF experienced costlier and longer index-TEER hospitalization and had more co-morbidities. Chronic kidney disease (odds ratio [OR] 1.51, 95% confidence interval [CI] 1.03 to 2.20), fluid and electrolyte disorders (OR 1.59, 95% CI 1.01 to 2.52), and heart failure (OR 1.86, 95% CI 1.01 to 3.44) were identified as independent predictors of NOAF. Hypertensive complications and heart failure were the leading causes of readmission. In conclusion, those patients that developed NOAF after TEER tended to be an overall sicker group at baseline compared with the remainder of the study cohort. These data, obtained from a nationally representative cohort, highlight a particular group of patients subject to developing NOAF and their association with increased rehospitalization in the post-TEER setting. Predictors of NOAF can be screened for during TEER workup to identify patients at increased risk.

The inter - Test variability of growth hormone stimulation tests and factors affecting this variability.

OBJECTIVE: To evaluate the variability of growth hormone stimulation tests results and factors affecting it in short children suspected of having growth hormone deficiency. DESIGN: The cohort included patients with short stature suspected of having growth hormone deficiency, and who underwent a second stimulation test, after the first stimulation test was positive. Testing was done at a single center from May 2014 to October 2017. Patients' weight, height, age, sex, stimulating agents and test results were recorded. RESULTS: The study population comprised 200 patients, 108 males and 92 females, average age 9.2 years (2.2-16.6 years). The average peak growth hormone was 5.2 µg/L and 7.8 µg/L in the first and second tests respectively and the concordance rate was 56.5%. The probability of a second positive test was increased if the peak growth hormone level in the first test was below 5 µg/L. In the second test, Clonidine and Glucagon led to higher peak growth levels than Arginine with averages of 9.02, 9.97 and 6.88 µg/L respectively. Younger children and children with higher BMI SDS only had lower peaks of growth hormone in the second test. The effect of height SDS on peak growth hormone levels was equivocal. CONCLUSION: The reproducibility rate of GH simulation tests in our study was low. A few factors may affect the peak levels of growth hormone in the second test, the most prominent being the peak of growth hormone in the first test.

Expediting Time from Symptoms to Medical Contact Utilizing a Telemedicine Call Center.

BACKGROUND: No definitive solution has been forthcoming for the often dangerously long interval between symptom onset and seeking medical care in the prehospital setting. We examined the implementation of telemedicine technology and characterization of its utilizers for its efficacy in reducing this possibly life-threatening time lag. MATERIALS AND METHODS: A retrospective observational study was performed on the working database of an operational telemedicine facility that included all subscribers. Time-to-contact measurements throughout 2012 were retrieved from its medical files, and data on age, gender, medical history, and main complaint were analyzed. RESULTS: Throughout 2012, 22,274 of a total of 46,556 calls (47.8%) were made ≤60 min from symptom onset. It is important that 26.9% of all calls (12,522/46,556) were made in <15 min. Significantly more males (10,794/22,229 [49%]) contacted in ≤60 min compared with females (11,480/24,327 [47%], p<0.03). Subjects <60 years of age (2,889/5,717 [51%]) called earlier than those >60 years (19,386/40,839 [47%], p<0.001). Patients with prior resuscitation and/or myocardial infarction contacted significantly more rapidly than those with other cardiac diseases. Over one-half of patients with cardiac complaints contacted the call center ≤60 min from symptom onset, as did those who suffered physical trauma, but not patients with gastrointestinal symptoms or pain elsewhere. CONCLUSIONS: A telemedicine system with rapid accessibility to a professional call center and prompt triage thereafter could be an additional promising strategy for shortening the interval between symptom onset and call for medical assistance. Implementation of a widespread telemedicine infrastructure may bridge the unmet gap between occurrence of symptoms to initiation of medical treatment.

Renal impairment according to acute kidney injury network criteria among ST elevation myocardial infarction patients undergoing primary percutaneous intervention: a retrospective observational study.

OBJECTIVE: Conflicting data exists regarding the frequency and significance of acute kidney injury (AKI) in ST segment elevation MI (STEMI) patients. The acute kidney injury network (AKIN) classification has been shown to predict mortality in various critically ill patients; however, limited information is available regarding its use and its clinical relevance among STEMI patients. STUDY DESIGN AND METHODS: We retrospectively studied 1,033 STEMI patients undergoing primary percutaneous intervention (PCI). AKI was identified on the basis of the changes in serum creatinine during hospitalization according to the AKIN criteria. Patients were assessed for in-hospital adverse outcomes as well as all-cause mortality up to 5 years. RESULTS: Overall, 100 patients (9.6 %) developed AKI: 79 patients (79 %) had stage 1, 14 patients (14 %) developed stage 2, and 7 patients (7 %) developed stage 3 AKI. Patients with AKI had more complications during hospitalization, with higher 30 days (11 vs 1 %; p < 0.001) and 5-year all-cause mortality (29 vs 6 %; p < 0.001) compared to those without AKI. The adjusted risk of death increased proportionally to AKI severity. Compared to patients with no AKI, the adjusted hazard ratio for all-cause mortality was 6.68 (95 % confidence interval: 2.1-21.6, p = 0.002) in patients with AKI. Age, hypertension, chronic kidney injury and low left ventricular ejection fraction were independent predictors of developing AKI. CONCLUSION: In STEMI patients undergoing primary PCI, AKI assessed by AKIN criteria is a frequent complication, associated with an increased risk of both short- and long-term mortality.

Predictors of improvement in diastolic function after transcatheter aortic valve implantation.

BACKGROUND: Aortic stenosis is associated with concentric left ventricle (LV) hypertrophy or remodeling resulting in impaired diastolic function and elevated left-sided filling pressure. We investigated the changes in LV geometry and LV filling hemodynamics, giving emphasis to parameters associated with changes in diastolic function after transcatheter aortic valve implantation (TAVI). METHODS: Comprehensive diastolic assessment was performed before and six months after TAVI in 70 patients with severe aortic stenosis. Patients with any degree of mitral stenosis or >mild left-sided valvular regurgitation were excluded. RESULTS: In the entire cohort six months after TAVI, LV end-diastolic diameter increased (44.1 ± 6 versus 45 ± 6 mm, P = 0.02), whereas LV mass and relative wall thickness (RWT) decreased (270.1 ± 76 versus 245.1 ± 75 g and 0.53 ± 0.15 versus 0.46 ± 0.1, respectively; P < 0.0001 for both). Lateral e' increased (5.8 ± 2 versus 6.6 ± 3 cm/s, P = 0.03) and left atrium (LA) volume, E/e' ratio, and systolic pulmonary pressure decreased (88.1 ± 30 versus 80 ± 28 cc, 18 ± 7.8 versus 16.3 ± 5.5, and 42.7 ± 14.9 versus 38.7 ± 12 mmHg, respectively; P < 0.05 for all), suggesting reduction in LA pressure. The improvement in LA volume and E/e' was almost exclusively seen in patients with LV hypertrophy before TAVI (P < 0.05 both), as opposed to patients with concentric remodeling. CONCLUSIONS: In our preliminary study, TAVI resulted in LV and LA reverse remodeling, and improved LV relaxation and LA filling pressure in patients with severe aortic stenosis and concentric hypertrophy. Patients with concentric remodeling at baseline seem to have limited improvement in LV diastolic function and filling pressure following TAVI, but larger clinical trials would be required to conclude if they have no improvement at all.

The effect of vitamin C on upper respiratory infections in adolescent swimmers: a randomized trial.

The risk of upper respiratory infections (URIs) is increased in people who are under heavy physical stress, including recreational and competitive swimmers. Additional treatment options are needed, especially in the younger age group. The aim of this study was to determine whether 1 g/day vitamin C supplementation affects the rate, length, or severity of URIs in adolescent swimmers. We carried out a randomized, double-blind, placebo-controlled trial during three winter months, among 39 competitive young swimmers (mean age 13.8 ± 1.6 years) in Jerusalem, Israel. Vitamin C had no effect on the incidence of URIs (rate ratio = 1.01; 95% confidence interval (CI) = 0.70-1.46). The duration of respiratory infections was 22% shorter in vitamin C group, but the difference was not statistically significant. However, we found a significant interaction between vitamin C effect and sex, so that vitamin C shortened the duration of infections in male swimmers by 47% (95% CI: -80% to -14%), but had no effect on female swimmers (difference in duration: +17%; 95% CI: -38% to +71%). The effect of vitamin C on the severity of URIs was also different between male and female swimmers, so that vitamin C was beneficial for males, but not for females. Our study indicates that vitamin C does not affect the rate of respiratory infections in competitive swimmers. Nevertheless, we found that vitamin C decreased the duration and severity of respiratory infections in male swimmers, but not in females. This finding warrants further research.

All-optical axial super resolving imaging using a low-frequency binary-phase mask.

In this paper we present a new approach for obtaining all-optical axial super-resolving imaging by using a non-diffractive binary phase mask inserted at the entrance pupil of an imaging lens. The designed element is tested numerically and experimentally on various practical testing benches and eventually is inserted into the lens of a cellular phone camera.