A machine learning model for early diagnosis of type 1 Gaucher disease using real-life data.

Objective: The diagnosis of Gaucher disease (GD) presents a major challenge due to the high variability and low specificity of its clinical characteristics, along with limited physician awareness of the disease's early symptoms. Early and accurate diagnosis is important to enable effective treatment decisions, prevent unnecessary testing, and facilitate genetic counseling. This study aimed to develop a machine learning (ML) model for GD screening and GD early diagnosis based on real-world clinical data using the Maccabi Healthcare Services electronic database, which contains 20 years of longitudinal data on approximately 2.

Assessing the diagnostic utility of the Gaucher Earlier Diagnosis Consensus (GED-C) scoring system using real-world data.

Background: Gaucher disease (GD) is a rare autosomal recessive condition associated with clinical features such as splenomegaly, hepatomegaly, anemia, thrombocytopenia, and bone abnormalities. Three clinical forms of GD have been defined based on the absence (type 1, GD1) or presence (types 2 and 3) of neurological signs. Early diagnosis can reduce the likelihood of severe, often irreversible complications.

Cancer Risk in Patients with Gaucher Disease Using Real-World Data.

The association between GD and cancer has been uncertain due to ascertainment bias in previously published studies. We analyzed cancer incidence using the Maccabi Healthcare Service (MHS) electronic health records among 264 patients with GD compared to 3440 matched controls. We ascertained cancers diagnosed before and after the index date (i.

Calcium score of the entire thoracic aorta is an independent predictor of all-cause mortality in patients referred to chest computed tomography.

Background: Thoracic arterial calcifications (TAC) are not routinely reported or quantified in chest CT scans. We aimed to evaluate the association between TAC of the entire thoracic aorta and all-cause mortality (ACM) in patients referred to standard chest CT.

Methods: A retrospective analysis of consecutive standard chest CT scans (non-gated, non-contrast) for the quantification of TAC, CAC and aortic valve calcification.

Identifying Profiles of Patients With Uncontrolled Type 2 Diabetes Who Would Benefit From Referral to an Endocrinologist.

Objective: To compare the outcomes of glycemic uncontrolled diabetes mellitus type 2 patients receiving treatment from endocrinologists with those treated by primary care physicians. Additionally, this research aims to identify patient profiles that would benefit from personalized referral-a novel medical approach that aims to match the most suitable specialist for effectively managing patient while considering the patient's profile.

Methods: This retrospective cohort study uses the Maccabi Healthcare Services diabetes registry to match 508 pairs of glycemic uncontrolled diabetes mellitus type 2 patients treated by endocrinologists (EndoG) and primary care physicians (PcPG).

The Association Between Depression and Invasive and In-situ Cervical Tumors: A Large Population Based Cohort Study.

Background: Depression has been shown to be associated with cervical tumors (CTs), an association mostly demonstrated in studies in which temporality could not have been ascertained.

Objectives: To study the association between depression and CTs and the influence of co-morbidities of this association in a large cohort study.

Methods: A retrospective computer-based cohort study was conducted.

Leveraging Comprehensive Health Records for Breast Cancer Risk Prediction: A Binational Assessment.

Breast cancer (BC) risk models based on electronic health records (EHR) can assist physicians in estimating the probability of an individual with certain risk factors to develop BC in the future. In this retrospective study, we used clinical data combined with machine learning tools to assess the utility of a personalized BC risk model on 13,786 Israeli and 1,695 American women who underwent screening mammography in the years 2012-2018 and 2008-2018, respectively. Clinical features were extracted from EHR, personal questionnaires, and past radiologists' reports.

Major cardiovascular events and subsequent risk of kidney failure with replacement therapy: a CKD Prognosis Consortium study.

Aims: Chronic kidney disease (CKD) increases risk of cardiovascular disease (CVD). Less is known about how CVD associates with future risk of kidney failure with replacement therapy (KFRT).

Methods And Results: The study included 25 903 761 individuals from the CKD Prognosis Consortium with known baseline estimated glomerular filtration rate (eGFR) and evaluated the impact of prevalent and incident coronary heart disease (CHD), stroke, heart failure (HF), and atrial fibrillation (AF) events as time-varying exposures on KFRT outcomes.

Pharmacologic Treatment of Type 2 Diabetes in the U.S., Sweden, and Israel.

Objective: To characterize and compare glucose-lowering medication use in type 2 diabetes in the U.S., Sweden, and Israel, including adoption of newer medications and prescribing patterns.

Including measures of chronic kidney disease to improve cardiovascular risk prediction by SCORE2 and SCORE2-OP.

Aims: The 2021 European Society of Cardiology (ESC) guideline on cardiovascular disease (CVD) prevention categorizes moderate and severe chronic kidney disease (CKD) as high and very-high CVD risk status regardless of other factors like age and does not include estimated glomerular filtration rate (eGFR) and albuminuria in its algorithms, systemic coronary risk estimation 2 (SCORE2) and systemic coronary risk estimation 2 in older persons (SCORE2-OP), to predict CVD risk. We developed and validated an 'Add-on' to incorporate CKD measures into these algorithms, using a validated approach.

Methods: In 3,054 840 participants from 34 datasets, we developed three Add-ons [eGFR only, eGFR + urinary albumin-to-creatinine ratio (ACR) (the primary Add-on), and eGFR + dipstick proteinuria] for SCORE2 and SCORE2-OP.

All-cause mortality prediction in T2D patients with iTirps.

Mortality in the type II diabetic elderly population can sometimes be prevented through intervention, for which risk assessment through predictive modeling is required. Since Electronic Health Records data are typically heterogeneous and sparse, the use of Temporal Abstraction and time intervals mining to discover frequent Time Intervals Related Patterns (TIRPs) is employed. While TIRPs are used as features for a predictive model, the temporal relations between them in general, and among each TIRP's instances are not represented.

Advanced-Stage Parkinson's Disease: From Identification to Characterization Using a Nationwide Database.

Background: As Parkinson's disease (PD) progresses, response to oral medications decreases and motor complications appear. Timely intervention has been demonstrated as effective in reducing symptoms. However, current instruments for the identification of these patients are often complicated and inadequate.

Long-Term Persistence and Monotherapy with Device-Aided Therapies: A Retrospective Analysis of an Israeli Cohort of Patients with Advanced Parkinson's Disease.

Introduction: Patients with advanced Parkinson's disease (PD) may require device-aided therapies (DAT) for adequate symptom control. However, long-term, real-world efficacy and safety data are limited. This study aims to describe real-world, long-term treatment persistence for patients with PD treated with levodopa-carbidopa intestinal gel (LCIG).

Burden of Endometriosis: Infertility, Comorbidities, and Healthcare Resource Utilization.

The goal of our study was to evaluate the burden of endometriosis in the community by comparing healthcare resource utilization, total direct medical costs, infertility, and comorbidity rates of women with and without a diagnosis of endometriosis. A retrospective case-control study was performed using the databases of a 2.1 million-member nationwide healthcare plan.

Minimizing treatment-induced emergence of antibiotic resistance in bacterial infections.

Treatment of bacterial infections currently focuses on choosing an antibiotic that matches a pathogen's susceptibility, with less attention paid to the risk that even susceptibility-matched treatments can fail as a result of resistance emerging in response to treatment. Combining whole-genome sequencing of 1113 pre- and posttreatment bacterial isolates with machine-learning analysis of 140,349 urinary tract infections and 7365 wound infections, we found that treatment-induced emergence of resistance could be predicted and minimized at the individual-patient level. Emergence of resistance was common and driven not by de novo resistance evolution but by rapid reinfection with a different strain resistant to the prescribed antibiotic.

Cutaneous Comorbidities Associated With Atopic Dermatitis in Israel: A Retrospective Real-World Data Analysis.

Background: Patients with atopic dermatitis (AD) are susceptible to infectious and inflammatory cutaneous comorbidities.

Objective: The aim of the study was to describe the prevalence of cutaneous comorbidities associated with AD, including their relationship with AD severity.

Methods: A retrospective cross-sectional analysis was performed using the Israeli Maccabi Healthcare Services database.

Adolescent body mass index and changes in pre-pregnancy body mass index in relation to risk of gestational diabetes.

Background: Pregestational excessive body mass index (BMI) is linked to an increased risk for gestational diabetes mellitus (GDM), but less is known on the effect of adolescent BMI on GDM occurrence. The study aimed to investigate possible associations of adolescent BMI and changes in BMI experienced before first pregnancy, with gestational diabetes risk.

Methods: This retrospective study was based on linkage of a military screening database of adolescent health status (Israel Defence Forces) including measured height and weight, with medical records (Maccabi Healthcare Services, MHS) of a state-mandated health provider.

Shifting from vitamin K antagonists to non-vitamin K antagonist oral anticoagulants in patients with atrial fibrillation: predictors, patterns and temporal trends.

Background: Non-Vitamin K antagonist oral anticoagulants (NOACs) emerged as an alternative with comparable or superior efficacy and safety to vitamin K antagonists (VKAs) for stroke prevention in patients with non-valvular atrial fibrillation (AF).

Objectives: The aim of the current study was to investigate the patterns, predictors, timelines and temporal trends of shifting from VKAs to NOACs.

Methods: In this retrospective observational study, the computerized database of a large healthcare provider in Israel, Maccabi Healthcare Services, was searched to identify patients with AF for whom either a VKA or NOAC was prescribed between 2012 and 2015.

Real-World Treatment Patterns and Outcomes of Growth Hormone Treatment Among Children in Israel Over the Past Decade (2004-2015).

To assess a decade of growth hormone (GH) treatment patterns and outcomes in a real-world setting in Israel using a state-of-the-art computerized database. This large retrospective database study included 2,379 children initiating GH treatment in Maccabi Healthcare Services (between January 2004 and December 2014). Good adherence with therapy (proportion of days covered >80%) was assessed during follow-up.

Real-world study of PD-L1 testing patterns and treatment distribution in patients with metastatic non-small-cell lung cancer in Israel.

We describe PD-L1 testing patterns and first-line treatment for patients with metastatic non-small-cell lung cancer in a 2.3 million-member state-mandated health service in Israel. Newly diagnosed stage IV non-small-cell lung cancer patients initiating systemic anticancer treatment from 1 January 2017 until 31 December 2018 were identified from the national cancer registry and Maccabi Healthcare Service database and followed until 30 June 2019.

Differences in glycated hemoglobin levels and cholesterol levels in individuals with diabetes according to Helicobacter pylori infection.

This study examined differences in glycated hemoglobin (HbA1c), fasting plasma glucose and cholesterol levels between H. pylori infected and uninfected persons with diabetes. Anonymized data of Maccabi Healthcare Services in Israel were analyzed, of 12,207 individuals (50.

Associations of Maternal Androgen-Related Conditions With Risk of Autism Spectrum Disorder in Progeny and Mediation by Cardiovascular, Metabolic, and Fertility Factors.

Fetal exposure to elevated androgens is thought to contribute to autism spectrum disorder (ASD) risk. However, data rely heavily on in utero androgens measurements, which also reflect fetal secretions. Thus, in utero hyperandrogenemia might indicate adverse autism-related neurogenesis that has already occurred affecting fetal androgen homeostasis, rather than being a cause of the disorder.