Neil Rappaport

Bio: Neil Rappaport is an academic researcher. The author has contributed to research in topics: Retrospective cohort study & Emergency medicine. The author has an hindex of 1, co-authored 1 publications receiving 694 citations.

The Effects of Nonpharmacologic Interventions on Blood Pressure of Persons With High Normal Levels: Results of the Trials of Hypertension Prevention, Phase I

Abstract: Objective. —To test the short-term feasibility and efficacy of seven nonpharmacologic interventions in persons with high normal diastolic blood pressure. Design. —Randomized control multicenter trials. Setting. —Volunteers recruited from the community, treated and followed up at special clinics. Participants. —Of 16821 screenees, 2182 men and women, aged 30 through 54 years, with diastolic blood pressure from 80 through 89 mm Hg were selected. Of these, 50 did not return for follow-up blood pressure measurements. Interventions. —Three life-style change groups (weight reduction, sodium reduction, and stress management) were each compared with unmasked nonintervention controls over 18 months. Four nutritional supplement groups (calcium, magnesium, potassium, and fish oil) were each compared singly, in double-blind fashion, with placebo controls over 6 months. Main Outcome Measures. —Primary: change in diastolic blood pressure from baseline to final follow-up, measured by blinded observers. Secondary: changes in systolic blood pressure and intervention compliance measures. Results. —Weight reduction intervention produced weight loss of 3.9 kg (P .05). Conclusions. —Weight reduction is the most effective of the strategies tested for reducing blood pressure in normotensive persons. Sodium reduction is also effective. The long-term effects of weight reduction and sodium reduction, alone and in combination, require further evaluation. (JAMA. 1992;267:1213-1220)

Risk factors for severe COVID-19 differ by age: a retrospective study of hospitalized adults

Abstract: Background: Risk stratification for hospitalized adults with COVID-19 is essential to inform decisions for individual patients and allocation of potentially scarce resources. So far, risk models for severe COVID outcomes have included age but have not been optimized to best serve the needs of either older or younger adults. Additionally, existing risk models have been limited to either small sample sizes, or modeling mortality over an entire hospital admission. Further, previous models were developed on data from early in the pandemic, before improvements in COVID-19 treatment, the SARS-CoV-2 delta variant, and vaccination. There remains a need for early, accurate identification of patients who may need invasive mechanical ventilation (IMV) or die, considering multiple time horizons. Methods: This retrospective study analyzed data from 6,906 hospitalized adults with COVID-19 from a community health system with 51 hospitals and 1085 clinics across five states in the western United States. Risk models were developed to predict mechanical ventilation illness or death across one to 56 days of hospitalization, using clinical data collected available within the first hour after either admission with COVID-19 or a first positive SARS-CoV-2 test. The relative importance of predictive risk factors features for all models was determined using Shapley additive explanations. Findings: The percentage of patients who required mechanical ventilation or died within seven days of admission to the hospital due to COVID-19 was 10.82%. For the seven-day interval, models for age [≥] 18 and < 50 years reached AUROC 0.80 (95% CI: 0.70-0.89) and models for age [≥] 50 years reached AUROC 0.83 (95% CI: 0.79-0.88). Models revealed differences in the statistical significance and relative predictive value of risk factors between older and younger patients, including age, BMI, vital signs, and laboratory results. In addition, sex and chronic comorbidities had lower predictive value than vital signs and laboratory results. Interpretation: For hospitalized adults, baseline data that is readily available within one hour after hospital admission or a first positive inpatient SARS-CoV-2 test can predict critical illness within one day, and up to 56 days later. Further, the relative importance of risk factors differs between older and younger patients.

2017 ACC/AHA/AAPA/ABC/ACPM/AGS/APhA/ASH/ASPC/NMA/PCNA Guideline for the Prevention, Detection, Evaluation, and Management of High Blood Pressure in Adults: A Report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines

Abstract: Since 1980, the American College of Cardiology (ACC) and American Heart Association (AHA) have translated scientific evidence into clinical practice guidelines (guidelines) with recommendations to improve cardiovascular health. In 2013, the National Heart, Lung, and Blood Institute (NHLBI) Advisory

Dietary pattern analysis: a new direction in nutritional epidemiology.

Abstract: Recently, dietary pattern analysis has emerged as an alternative and complementary approach to examining the relationship between diet and the risk of chronic diseases. Instead of looking at individual nutrients or foods, pattern analysis examines the effects of overall diet. Conceptually, dietary patterns represent a broader picture of food and nutrient consumption, and may thus be more predictive of disease risk than individual foods or nutrients. Several studies have suggested that dietary patterns derived from factor or cluster analysis predict disease risk or mortality. In addition, there is growing interest in using dietary quality indices to evaluate whether adherence to a certain dietary pattern (e.g. Mediterranean pattern) or current dietary guidelines lowers the risk of disease. In this review, we describe the rationale for studying dietary patterns, and discuss quantitative methods for analysing dietary patterns and their reproducibility and validity, and the available evidence regarding the relationship between major dietary patterns and the risk of cardiovascular disease.