Determining indications for care common to competing guidelines by using classification tree analysis: application to the prevention of venous thromboembolism in medical inpatients.

BACKGROUND: Substantial variations have been reported in the advice given by competing guidelines addressing the same clinical problem. OBJECTIVE: This study aimed to assess the usefulness of classification tree analysis in comparing competing guidelines. METHOD: The authors implemented a classifica...

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Published in:Medical Decision Making Vol. 26; no. 1; pp. 63 - 76
Main Authors: Bosson L, Labarere J
Format: research tables/charts Journal Article
Published: Sage Publications Inc. Jan/Feb2006
Online Access:View this record in EBSCOhost
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      dt: Jan/Feb2006
      vid: 26
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      pub: Sage Publications Inc.
      place: Thousand Oaks, California
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        atl: Determining indications for care common to competing guidelines by using classification tree analysis: application to the prevention of venous thromboembolism in medical inpatients.
      aug:
        au:
          Bosson L
          Labarere J
        affil: Laboratoire TIMC IMAG UMR CNRS 5525, Grenoble, France
      sug:
        subj:
          Practice Guidelines Evaluation
          Venous Thrombosis Classification
          Venous Thrombosis Prevention and Control
          Venous Thromboembolism
          Aged
          Confidence Intervals
          Data Analysis Software
          Data Analysis, Statistical
          Descriptive Statistics
          Female
          Interviews
          Male
          Record Review
          Retrospective Design
          Venous Thrombosis Risk Factors
          Human
          Aged: 65+ years
          Female
          Male
      ab: BACKGROUND: Substantial variations have been reported in the advice given by competing guidelines addressing the same clinical problem. OBJECTIVE: This study aimed to assess the usefulness of classification tree analysis in comparing competing guidelines. METHOD: The authors implemented a classification tree-growing algorithm on cross-sectional data from 818 patients to determine indications for prophylactic heparin treatment common to 4 competing guidelines disseminated between 1998 and 2000 and addressing the prophylaxis of venous thromboembolism in medical inpatients. RESULTS: The resulting classification tree involved 10 terminal nodes. Its mean accuracy estimated by performing 10-fold cross-validation was 82% (s=3). The guidelines consistently supported prophylactic heparin treatment for 5 indications: a previous episode of deep vein thrombosis or pulmonary embolism, recent paralysis of lower limb(s), congestive heart failure with one or more risk factors, recent myocardial infarction, and malignancy with one or more risk factors. These indications involved 257 patients (31.4%) and were supported by robust scientific evidence. Deep vein thrombosis was detected in 27 of these patients (10.5%). Two consistent negative indications involved 347 patients (42.4%). Deep vein thrombosis was detected in 9 of these patients (2.6%). Three indications involving 214 patients (26.2%) were discordant over the 4 guidelines. CONCLUSION: Classification tree analysis of real patient data is a useful strategy to identify indications common to competing guidelines. These indications should be considered for inclusion when updating guidelines. The findings of recently completed randomized trials have partly resolved the disagreement among the 4 guidelines. This approach may be helpful when developing new guidelines or for identifying topics warranting further complementary clinical trials.
      pubtype: Academic Journal
      doctype:
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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