{"title":"Response","authors":"John M. Esdaile, Ralph I. Horwitz","doi":"10.1016/0021-9681(87)90122-6","DOIUrl":"https://doi.org/10.1016/0021-9681(87)90122-6","url":null,"abstract":"","PeriodicalId":15427,"journal":{"name":"Journal of chronic diseases","volume":"40 11","pages":""},"PeriodicalIF":0.0,"publicationDate":"1987-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/0021-9681(87)90122-6","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72212655","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Mary E. Charlson , Frederic L. Sax , C.Ronald Mackenzie, Robert L. Braham, Suzanne D. Fields , R.G. Douglas Jr
{"title":"Morbidity during hospitalization: Can we predict it?","authors":"Mary E. Charlson , Frederic L. Sax , C.Ronald Mackenzie, Robert L. Braham, Suzanne D. Fields , R.G. Douglas Jr","doi":"10.1016/0021-9681(87)90107-X","DOIUrl":"10.1016/0021-9681(87)90107-X","url":null,"abstract":"<div><p>Physicians use the concept of stability to estimate the likelihood that a patient will deteriorate during a hospitalization. To determine whether physicians can accurately predict a patient's risk of morbidity, 603 patients admitted to the medical service during a one month period were rated prospectively as to how stable they were.</p><p>Overall, 15% of patients had deterioration of already compromised systems, while 17% had new complications, such as sepsis. Eight percent of patients had both. Twelve percent of stable patients experienced morbidity; 39% of the somewhat unstable and 61% of the most unstable. When all of the demographic and clinical variables were taken into account including the reason for admission and comorbid diseases, the residents' estimates of the patient's stability was the most significant predictor of morbidity (<em>p</em> < 0.001).</p><p>The judgment that a patient was stable had an 87% negative predictive accuracy, while the judgment unstable had a 46% positive predictive accuracy.</p></div>","PeriodicalId":15427,"journal":{"name":"Journal of chronic diseases","volume":"40 7","pages":"Pages 705-712"},"PeriodicalIF":0.0,"publicationDate":"1987-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/0021-9681(87)90107-X","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"14242548","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
William M. Vollmer , Larry R. Johnson , Lynn E. McCamant , A.Sonia Buist
{"title":"Methodologic issues in the analysis of lung function data","authors":"William M. Vollmer , Larry R. Johnson , Lynn E. McCamant , A.Sonia Buist","doi":"10.1016/0021-9681(87)90115-9","DOIUrl":"10.1016/0021-9681(87)90115-9","url":null,"abstract":"<div><p>The forced expiratory volume in one second (FEV<sub>1</sub>) is routinely used in epidemiologic studies of lung function to assess the presence and severity of obstructive airways disease. Normative prediction equations developed using data from healthy, asymptomatic individuals may then be used both in a clinical setting and to adjust comparisons among risk subgroups for known demographic differences. Unfortunately no concensus has yet developed as to how best to model lung function data. This paper addresses this issue in a systematic manner using data derived from two cohorts followed over a period of 9–11 years. We compare a variety of cross-sectional and longitudinal models for FEV<sub>1</sub>, show how they may be expressed as members of a larger class of general linear models, and discuss goodness-of-fit procedures for comparing them. We found little objective evidence for discriminating among these models; only those fit to FEV<sub>1</sub>/ht<sup>3</sup> performed poorly. We argue on subjective grounds for the use of models based on FEV<sub>1</sub>, as a function of age, height and their interactions.</p></div>","PeriodicalId":15427,"journal":{"name":"Journal of chronic diseases","volume":"40 11","pages":"Pages 1013-1023"},"PeriodicalIF":0.0,"publicationDate":"1987-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/0021-9681(87)90115-9","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"14622684","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Marilyn Bergner , Robert M. Kaplan , John E. Ware Jr
{"title":"Evaluating health measures. Commentary: Measuring overall health: An evaluation of three important approaches","authors":"Marilyn Bergner , Robert M. Kaplan , John E. Ware Jr","doi":"10.1016/S0021-9681(87)80028-0","DOIUrl":"https://doi.org/10.1016/S0021-9681(87)80028-0","url":null,"abstract":"","PeriodicalId":15427,"journal":{"name":"Journal of chronic diseases","volume":"40 ","pages":"Pages 23S-26S"},"PeriodicalIF":0.0,"publicationDate":"1987-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/S0021-9681(87)80028-0","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72220249","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"“Rainbow Reviews” III: Recent publications of the National Center for Health Statistics","authors":"James F. Jekel","doi":"10.1016/0021-9681(87)90177-9","DOIUrl":"https://doi.org/10.1016/0021-9681(87)90177-9","url":null,"abstract":"","PeriodicalId":15427,"journal":{"name":"Journal of chronic diseases","volume":"40 5","pages":"Pages 439-443"},"PeriodicalIF":0.0,"publicationDate":"1987-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/0021-9681(87)90177-9","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72220513","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Interpreting time-related trends in effect estimates","authors":"Sander Greenland","doi":"10.1016/S0021-9681(87)80005-X","DOIUrl":"10.1016/S0021-9681(87)80005-X","url":null,"abstract":"<div><p>This paper reviews the sources of apparent time trends in effect. Apparent changes in effect may arise from changes in covariate distributions, background rates, exposure distribution, measurement quality, or selection factors. As with time trends in rates, time trends in effect must have at least one of these sources, since time itself has no effect. If background incidence is changing, however, time trends in effect become dependent on choice of effect measure, and interpretation must take this into account. Evidence that a trend arises from age-, cohort-, or period-related phenomena can indicate the relative plausibility of different explanations of the trend. Conversely, the relative plausibility of each explanation may indicate whether the trend is most appropriately viewed over the axis of age, birth cohort, or calendar time. Nevertheless, studies of short duration relative to an apparent trend (such as most case-control studies) must invoke strong assumptions to justify focusing on a particular axis. Illustrations are given from studies of electronic fetal monitoring and of smoking and lung cancer.</p></div>","PeriodicalId":15427,"journal":{"name":"Journal of chronic diseases","volume":"40 ","pages":"Pages 17S-24S"},"PeriodicalIF":0.0,"publicationDate":"1987-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/S0021-9681(87)80005-X","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"14787759","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Some problems of inference in cohort studies","authors":"Edward D. Lustbader , Suresh H. Moolgavkar","doi":"10.1016/S0021-9681(87)80017-6","DOIUrl":"10.1016/S0021-9681(87)80017-6","url":null,"abstract":"<div><p>This paper uses a detailed example to illustrate how to detect individual observations that disproportionately influence the results of hypothesis testing with relative risk regression models.</p></div>","PeriodicalId":15427,"journal":{"name":"Journal of chronic diseases","volume":"40 ","pages":"Pages 133S-137S"},"PeriodicalIF":0.0,"publicationDate":"1987-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/S0021-9681(87)80017-6","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"14788535","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Pitfalls in the analysis of exposure-time-response relationships","authors":"Duncan C. Thomas","doi":"10.1016/S0021-9681(87)80010-3","DOIUrl":"10.1016/S0021-9681(87)80010-3","url":null,"abstract":"","PeriodicalId":15427,"journal":{"name":"Journal of chronic diseases","volume":"40 ","pages":"Pages 71S-78S"},"PeriodicalIF":0.0,"publicationDate":"1987-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/S0021-9681(87)80010-3","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"14438383","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
James J. Schlesselman , Bruce V. Stadel , Pamela Murray , Phyllis A. Wingo , George L. Rubin
{"title":"Consistency and plausibility in epidemiologic analysis: Application to breast cancer in relation to use of oral contraceptives","authors":"James J. Schlesselman , Bruce V. Stadel , Pamela Murray , Phyllis A. Wingo , George L. Rubin","doi":"10.1016/0021-9681(87)90117-2","DOIUrl":"10.1016/0021-9681(87)90117-2","url":null,"abstract":"<div><p>Consistency and plausibility are fundamental criteria for judging cause and effect from observational studies. They are applied here to the interpretation of data from a population-based case-control study of oral contraceptives and breast cancer. A preliminary analysis of oral contraceptive use in young nulliparous women, who had no family history of either breast cancer or benign breast disease, showed a statistically significant dose-response, with long-term users (49 months or more) having an apparent 4-fold elevation in risk of early breast cancer. Further analyses, however, revealed striking inconsistencies which were biologically implausible. These effectively undermine cause and effect as an explanation for the initial finding.</p></div>","PeriodicalId":15427,"journal":{"name":"Journal of chronic diseases","volume":"40 11","pages":"Pages 1033-1039"},"PeriodicalIF":0.0,"publicationDate":"1987-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/0021-9681(87)90117-2","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"14775052","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"The functional status of ESRD patients as measured by the sickness impact profile","authors":"L. Gary Hart , Roger W. Evans","doi":"10.1016/S0021-9681(87)80041-3","DOIUrl":"10.1016/S0021-9681(87)80041-3","url":null,"abstract":"<div><p>This study describes and compares the perceived sickness-related behavioral dysfunction of 859 end-stage renal disease (ESRD) patients from 11 centers according to treatment modality via the Sickness Impact Profile (SIP). The unadjusted functional status of ESRD patients differed significantly by treatment modality. Transplantation patients were least functionally limited followed in order by home dialysis, continuous peritoneal dialysis, and in-center dialysis patients. The largest overall differences were for the sleep and rest, work, recreation and pastimes, and home management SIP categories. Regression analysis revealed that many of the large observed intermodality differences in functional status may have resulted from casemix variations (e.g. age and comorbidity differences). Only SIP score differences between transplantation and other treatment modality patients remained significant following the introduction of casemix controls. Results do not justify choosing one dialysis modality over another because of differences in perceived dysfunction.</p></div>","PeriodicalId":15427,"journal":{"name":"Journal of chronic diseases","volume":"40 ","pages":"Pages 117S-130S"},"PeriodicalIF":0.0,"publicationDate":"1987-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/S0021-9681(87)80041-3","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"14425013","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}