Target, Application, and Interpretation of Scores and Alternative Methods for Risk Assessment in Cardiac Surgery
The more popular the use of different methods for risk adjustment becomes, the more often data are applied without any regard about the primary target and/or about important assumptions. Furthermore, risk adjustment is no longer restricted for quality assurance purposes, but became a "tool"...
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Veröffentlicht in: | The Thoracic and cardiovascular surgeon 2000-04, Vol.48 (2), p.72-78 |
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container_title | The Thoracic and cardiovascular surgeon |
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creator | Osswald, B. R. Tochtermann, U. Schweiger, P. Thomas, G. Göhring, D. Vahl, C. F. Hagl, S. |
description | The more popular the use of different methods for risk adjustment becomes, the more often data are applied without any regard about the primary target and/or about important assumptions. Furthermore, risk adjustment is no longer restricted for quality assurance purposes, but became a "tool" of health policy. Few working groups currently use risk adjustment for the development of new therapeutic concepts. The aim of our study is to clarify possibilities and limitations of popular risk adjustment methods.
4985 Patients underwent isolated CABG. Statistics was performed by calculating descriptive statistics, Parsonnet, and Higginsscores. Furthermore, the parametric, time-adjusted hazard function by Blackstone was used.
Descriptive statistics allows intra-, and interinstitutional comparisons of single items to identify "outlying" results. Risk scores aim to predict preoperatively the risk category of the patient who undergoes cardiac surgery. However, since different scores are based on a score-specific combination of variables, and different definitions of the investigation interval, different results may occur, when different scores are calculated for a single patient. However, the use for example, of scores in patient groups allows description of changing risk structures. Most of the scores derive from univariate analyses and monophasic functions. However, survival curves are predominantly multiphasic and require a consideration of the time-dependency of "risk factors".
An increasing number of patients with severe comorbidity undergoes cardiac surgery. To evaluate reliably present and futurous therapeutic options, risk adjustment is necessary. Since various tools for risk-adjustment are available, a serious discussion about reliability and application is necessary. |
doi_str_mv | 10.1055/s-2000-9869 |
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4985 Patients underwent isolated CABG. Statistics was performed by calculating descriptive statistics, Parsonnet, and Higginsscores. Furthermore, the parametric, time-adjusted hazard function by Blackstone was used.
Descriptive statistics allows intra-, and interinstitutional comparisons of single items to identify "outlying" results. Risk scores aim to predict preoperatively the risk category of the patient who undergoes cardiac surgery. However, since different scores are based on a score-specific combination of variables, and different definitions of the investigation interval, different results may occur, when different scores are calculated for a single patient. However, the use for example, of scores in patient groups allows description of changing risk structures. Most of the scores derive from univariate analyses and monophasic functions. However, survival curves are predominantly multiphasic and require a consideration of the time-dependency of "risk factors".
An increasing number of patients with severe comorbidity undergoes cardiac surgery. To evaluate reliably present and futurous therapeutic options, risk adjustment is necessary. Since various tools for risk-adjustment are available, a serious discussion about reliability and application is necessary.</description><identifier>ISSN: 0171-6425</identifier><identifier>EISSN: 1439-1902</identifier><identifier>DOI: 10.1055/s-2000-9869</identifier><identifier>PMID: 11028707</identifier><language>eng</language><publisher>Germany</publisher><subject>Aged ; Cardiovascular Surgical Procedures ; Coronary Artery Bypass - mortality ; Coronary Artery Bypass - statistics & numerical data ; Coronary Disease - complications ; Coronary Disease - mortality ; Coronary Disease - physiopathology ; Coronary Disease - surgery ; Diabetes Complications ; Female ; Hospital Mortality ; Humans ; Male ; Models, Theoretical ; Original Cardiovascular ; Quality of Health Care ; Regression Analysis ; Risk Assessment - methods ; Survival Analysis ; Time Factors</subject><ispartof>The Thoracic and cardiovascular surgeon, 2000-04, Vol.48 (2), p.72-78</ispartof><rights>Georg Thieme Verlag Stuttgart · New York</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.thieme-connect.de/products/ejournals/pdf/10.1055/s-2000-9869.pdf$$EPDF$$P50$$Gthieme$$H</linktopdf><linktohtml>$$Uhttps://www.thieme-connect.de/products/ejournals/html/10.1055/s-2000-9869$$EHTML$$P50$$Gthieme$$H</linktohtml><link.rule.ids>314,780,784,3018,27924,27925,54559,54560</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/11028707$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Osswald, B. R.</creatorcontrib><creatorcontrib>Tochtermann, U.</creatorcontrib><creatorcontrib>Schweiger, P.</creatorcontrib><creatorcontrib>Thomas, G.</creatorcontrib><creatorcontrib>Göhring, D.</creatorcontrib><creatorcontrib>Vahl, C. F.</creatorcontrib><creatorcontrib>Hagl, S.</creatorcontrib><title>Target, Application, and Interpretation of Scores and Alternative Methods for Risk Assessment in Cardiac Surgery</title><title>The Thoracic and cardiovascular surgeon</title><addtitle>Thorac cardiovasc Surg</addtitle><description>The more popular the use of different methods for risk adjustment becomes, the more often data are applied without any regard about the primary target and/or about important assumptions. Furthermore, risk adjustment is no longer restricted for quality assurance purposes, but became a "tool" of health policy. Few working groups currently use risk adjustment for the development of new therapeutic concepts. The aim of our study is to clarify possibilities and limitations of popular risk adjustment methods.
4985 Patients underwent isolated CABG. Statistics was performed by calculating descriptive statistics, Parsonnet, and Higginsscores. Furthermore, the parametric, time-adjusted hazard function by Blackstone was used.
Descriptive statistics allows intra-, and interinstitutional comparisons of single items to identify "outlying" results. Risk scores aim to predict preoperatively the risk category of the patient who undergoes cardiac surgery. However, since different scores are based on a score-specific combination of variables, and different definitions of the investigation interval, different results may occur, when different scores are calculated for a single patient. However, the use for example, of scores in patient groups allows description of changing risk structures. Most of the scores derive from univariate analyses and monophasic functions. However, survival curves are predominantly multiphasic and require a consideration of the time-dependency of "risk factors".
An increasing number of patients with severe comorbidity undergoes cardiac surgery. To evaluate reliably present and futurous therapeutic options, risk adjustment is necessary. Since various tools for risk-adjustment are available, a serious discussion about reliability and application is necessary.</description><subject>Aged</subject><subject>Cardiovascular Surgical Procedures</subject><subject>Coronary Artery Bypass - mortality</subject><subject>Coronary Artery Bypass - statistics & numerical data</subject><subject>Coronary Disease - complications</subject><subject>Coronary Disease - mortality</subject><subject>Coronary Disease - physiopathology</subject><subject>Coronary Disease - surgery</subject><subject>Diabetes Complications</subject><subject>Female</subject><subject>Hospital Mortality</subject><subject>Humans</subject><subject>Male</subject><subject>Models, Theoretical</subject><subject>Original Cardiovascular</subject><subject>Quality of Health Care</subject><subject>Regression Analysis</subject><subject>Risk Assessment - methods</subject><subject>Survival Analysis</subject><subject>Time Factors</subject><issn>0171-6425</issn><issn>1439-1902</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2000</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNo1kUtPwzAQhC0EoqVw4o584oAa8COx42NV8ahUhETL2XKcDU3JC9tB6r8nLeW00s6nXc0MQteU3FOSJA8-YoSQSKVCnaAxjbmKqCLsFI0JlTQSMUtG6ML7LSE0TlN1jkaUEpZKIseoWxv3CWGKZ11XldaEsm2m2DQ5XjQBXOcgHHa4LfDKtg78QZxVg9gMyg_gVwibNve4aB1-L_0XnnkP3tfQBFw2eG5cXhqLV_3wyO0u0VlhKg9XxzlBH0-P6_lLtHx7Xsxny6hjMQtRxjMWEwFCFBmxAKYQNJPMSqpEDCKWMrW55YamYKSwUvGYJoN3liTMFEzyCbr9u9u59rsHH3RdegtVZRpoe68l44xRxQfw5gj2WQ257lxZG7fT_xkNwN0fEDYl1KC3bT9Yr7ymRO8L0F7vC9D7AvgvZ011ug</recordid><startdate>20000401</startdate><enddate>20000401</enddate><creator>Osswald, B. 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R.</creatorcontrib><creatorcontrib>Tochtermann, U.</creatorcontrib><creatorcontrib>Schweiger, P.</creatorcontrib><creatorcontrib>Thomas, G.</creatorcontrib><creatorcontrib>Göhring, D.</creatorcontrib><creatorcontrib>Vahl, C. F.</creatorcontrib><creatorcontrib>Hagl, S.</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>MEDLINE - Academic</collection><jtitle>The Thoracic and cardiovascular surgeon</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Osswald, B. R.</au><au>Tochtermann, U.</au><au>Schweiger, P.</au><au>Thomas, G.</au><au>Göhring, D.</au><au>Vahl, C. F.</au><au>Hagl, S.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Target, Application, and Interpretation of Scores and Alternative Methods for Risk Assessment in Cardiac Surgery</atitle><jtitle>The Thoracic and cardiovascular surgeon</jtitle><addtitle>Thorac cardiovasc Surg</addtitle><date>2000-04-01</date><risdate>2000</risdate><volume>48</volume><issue>2</issue><spage>72</spage><epage>78</epage><pages>72-78</pages><issn>0171-6425</issn><eissn>1439-1902</eissn><abstract>The more popular the use of different methods for risk adjustment becomes, the more often data are applied without any regard about the primary target and/or about important assumptions. Furthermore, risk adjustment is no longer restricted for quality assurance purposes, but became a "tool" of health policy. Few working groups currently use risk adjustment for the development of new therapeutic concepts. The aim of our study is to clarify possibilities and limitations of popular risk adjustment methods.
4985 Patients underwent isolated CABG. Statistics was performed by calculating descriptive statistics, Parsonnet, and Higginsscores. Furthermore, the parametric, time-adjusted hazard function by Blackstone was used.
Descriptive statistics allows intra-, and interinstitutional comparisons of single items to identify "outlying" results. Risk scores aim to predict preoperatively the risk category of the patient who undergoes cardiac surgery. However, since different scores are based on a score-specific combination of variables, and different definitions of the investigation interval, different results may occur, when different scores are calculated for a single patient. However, the use for example, of scores in patient groups allows description of changing risk structures. Most of the scores derive from univariate analyses and monophasic functions. However, survival curves are predominantly multiphasic and require a consideration of the time-dependency of "risk factors".
An increasing number of patients with severe comorbidity undergoes cardiac surgery. To evaluate reliably present and futurous therapeutic options, risk adjustment is necessary. Since various tools for risk-adjustment are available, a serious discussion about reliability and application is necessary.</abstract><cop>Germany</cop><pmid>11028707</pmid><doi>10.1055/s-2000-9869</doi><tpages>7</tpages></addata></record> |
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subjects | Aged Cardiovascular Surgical Procedures Coronary Artery Bypass - mortality Coronary Artery Bypass - statistics & numerical data Coronary Disease - complications Coronary Disease - mortality Coronary Disease - physiopathology Coronary Disease - surgery Diabetes Complications Female Hospital Mortality Humans Male Models, Theoretical Original Cardiovascular Quality of Health Care Regression Analysis Risk Assessment - methods Survival Analysis Time Factors |
title | Target, Application, and Interpretation of Scores and Alternative Methods for Risk Assessment in Cardiac Surgery |
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