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Analysis of Longitudinal Cardiopulmonary Data

2012년 5월 15일 업데이트: Bernard Rosner, Brigham and Women's Hospital
To define new national norms for pediatric blood pressure by adjusting the available data set of over 60,000 pediatric blood pressure readings for age, height and gender among children of normal body weight.

연구 개요

상세 설명

BACKGROUND:

Longitudinal designs are frequently encountered in epidemiologic research, particularly in the cardiopulmonary field. Many different statistical models have been proposed for the analysis of longitudinal data in the statistical literature. These include the general linear model, autoregressive models, random effects models, and simple models based on an analysis of slopes over time. Complex models are not widely used in the epidemiologic literature, due mainly to a lack of understanding of their underlying utility and the types of questions that could be answered with complex models that cannot be addressed using simple models. An additional problem is a lack of software available for fitting complex models. The study has important public health implications, since longitudinal data continue to accumulate rapidly and no guidelines are available as to the appropriate methods of analysis for specific research questions. Furthermore, it is often only through the modelling of longitudinal data that processes pertaining to change can be understood. The original aim of the study was to perform a comparative study of statistical models on datasets from nine large epidemiological studies in the cardiopulmonary field in order to develop tools for identifying appropriate classes of statistical models for use in analyzing longitudinal data.

The present study define new national norms for pediatric blood pressure by adjusting the available data set of over 60,000 pediatric blood pressure readings for age, height and gender among children of normal body weight. It has been increasingly accepted that there is a long-term correlation between blood pressure in childhood and adulthood. Hence, it is significant to monitor childhood blood pressure. The 90th and 95th percentiles of blood pressure for specific age, sex and height groups were presented in the Update for the 1987 Task Force Report on Blood Pressure control in children, arid widely distributed by the National High Blood Pressure Education Program. There has been a recent update to the Task Force Report (Pediatrics, 2004) which used more current height percentiles based on Center for Disease Control and Prevention (2000) growth charts and extends the percentiles provided to include the 50th, 90th, 95th, and 99th percentiles. However, the percentiles are based on all children including both obese and non-obese children.

DESIGN NARRATIVE:

The nine datasets used included: for pulmonary data, the Childhood Respiratory Disease Study, the Netherlands data from Vlagtwedde and Vlaardingen, the Boston Police Study, the Fletcher Study data from England; for cardiopulmonary data, the Veterans Administration Normative Aging Study; for blood pressure data, the Wales Study, the Zinner/Kass Study, the Lee/Zinner Study, and the East Boston Childhood Blood Pressure Study. For each of the nine datasets the following models were fitted and compared for adults, children, and for adults and children combined: autoregressive models both serial-correlation and state-dependence; random-effects models; regression models with intraclass correlation structure; general linear models; models based on fitting slopes to individual persons. New methods for analyzing longitudinal data were developed and included fitting of higher-order autoregressive models with unequally spaced data, nonparametric methods, familial and other clustering effects in the analysis of longitudinal pulmonary function data, robust methods, empirical Bayes methods for estimation of slopes, and hierarchial models based on old and new methods.

The study was renewed in 1996 to perform a comparative study of complex models on datasets from four large epidemiologic studies in the cardiopulmonary field. The models were compared as regards goodness of fit, ease of implementation, and interpretability. In addition, new statistical methods were developed to model phenomena which seemed poorly-fitted by existing models, including adult longitudinal bp and pulmonary function data. The overall goal was to develop tools for identifying appropriate classes of longitudinal statistical models. This has important public health implications, since longitudinal data continue to accumulate rapidly and no guidelines exist as to appropriate methods of analysis. Furthermore, it is often only through modelling of longitudinal data rather than through cross-sectional or separate two time-point analyses that underlying processes pertaining to change can be understood.

The study was renewed in February 2000 to extend and enhance several techniques in the analyses of longitudinal data frequently encountered in epidemiological studies. The techniques include: methods for control for time-dependent confounding in epidemiological studies; developing an incidence model for benign breast disease using the Nurses' Health Study; analysis of incomplete longitudinal data from the Normative Aging Study; extending the penalized likelihood procedures for quantile regression to the repeated measures setting; and development of methods to estimate correlated ROC curves to measure the predictive accuracy of GEE regression models for longitudinal data.

The study was renewed in 2005 to define new national norms for pediatric blood pressure by adjusting the available data set of over 60,000 pediatric blood pressure readings for age, height and gender among children of normal body weight. The study will (a) broaden the percentiles presented so as to display the full range of blood pressure percentiles from the first to the 99th percentile (b) evaluate the percentiles for children of normal body weight so as to disentangle the relationship between hypertension and obesity (c) provide a algorithm using Microsoft Access for computation of a blood pressure percentile or Z-score in a user-friendly format (d) provide percentiles for both K4 and K5 diastolic blood pressure (the Task Force Report only includes percentiles for K5 DBF) and (e) compare childhood blood pressure percentiles by ethnic group. The study will also develop screening rules for detecting high blood pressure in children. Given the existence of new Task Force Norms that quantify percentile values of blood pressure in children by age, sex and height, an significant issue is how to use these norms to effectively screen children for high blood pressure, where high blood pressure is defined as having an average blood pressure > 95' percentile for a given age, sex and height based on task force percentiles over a large number of visits. The goal is to develop efficient screening rules that maximize accuracy with the fewest screening visits necessary per child. The screening rules will be assessed in simulation studies and tested in a sample of 16,000 Houston school children who were screened for high blood pressure

연구 유형

관찰

등록 (실제)

60000

참여기준

연구원은 적격성 기준이라는 특정 설명에 맞는 사람을 찾습니다. 이러한 기준의 몇 가지 예는 개인의 일반적인 건강 상태 또는 이전 치료입니다.

자격 기준

공부할 수 있는 나이

  • 어린이
  • 성인
  • 고령자

건강한 자원 봉사자를 받아들입니다

아니

연구 대상 성별

모두

샘플링 방법

비확률 샘플

연구 인구

Pediatric Task Force, combination of 11 different studies collecting pediatric blood pressure data.

설명

No eligibility criteria

공부 계획

이 섹션에서는 연구 설계 방법과 연구가 측정하는 내용을 포함하여 연구 계획에 대한 세부 정보를 제공합니다.

연구는 어떻게 설계됩니까?

디자인 세부사항

공동 작업자 및 조사자

여기에서 이 연구와 관련된 사람과 조직을 찾을 수 있습니다.

수사관

  • 수석 연구원: Bernard Rosner, PhD, Brigham and Women's Hospital

간행물 및 유용한 링크

연구에 대한 정보 입력을 담당하는 사람이 자발적으로 이러한 간행물을 제공합니다. 이것은 연구와 관련된 모든 것에 관한 것일 수 있습니다.

일반 간행물

연구 기록 날짜

이 날짜는 ClinicalTrials.gov에 대한 연구 기록 및 요약 결과 제출의 진행 상황을 추적합니다. 연구 기록 및 보고된 결과는 공개 웹사이트에 게시되기 전에 특정 품질 관리 기준을 충족하는지 확인하기 위해 국립 의학 도서관(NLM)에서 검토합니다.

연구 주요 날짜

연구 시작

1988년 4월 1일

기본 완료 (실제)

2008년 5월 1일

연구 완료 (실제)

2008년 5월 1일

연구 등록 날짜

최초 제출

2000년 5월 25일

QC 기준을 충족하는 최초 제출

2000년 5월 25일

처음 게시됨 (추정)

2000년 5월 26일

연구 기록 업데이트

마지막 업데이트 게시됨 (추정)

2012년 5월 17일

QC 기준을 충족하는 마지막 업데이트 제출

2012년 5월 15일

마지막으로 확인됨

2012년 5월 1일

추가 정보

이 연구와 관련된 용어

기타 연구 ID 번호

  • 1100
  • R01HL040619 (미국 NIH 보조금/계약)

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심장 질환에 대한 임상 시험

3
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