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Enregistrement W2619446037 · doi:10.1001/jamacardio.2017.1460

Accuracy of Medical Claims for Identifying Cardiovascular and Bleeding Events After Myocardial Infarction

2017· article· en· W2619446037 sur OpenAlexfundno aff
Patrícia O. Guimarães, Arun Krishnamoorthy, Lisa A. Kaltenbach, Kevin J. Anstrom, Mark B. Effron, Daniel B. Mark, Patrick L. McCollam, Linda Davidson‐Ray, Eric D. Peterson, Tracy Y. Wang

Notice bibliographique

RevueJAMA Cardiology · 2017
Typearticle
Langueen
DomaineMedicine
ThématiqueAcute Myocardial Infarction Research
Établissements canadiensnon disponible
Organismes subventionnairesDuke Clinical Research InstituteNational Institutes of HealthGenentechValeant Pharmaceuticals InternationalMinistério da Ciência, Tecnologia e InovaçãoHeartWareRegeneron PharmaceuticalsBoston Scientific CorporationGilead SciencesGlaxoSmithKlineNational Heart, Lung, and Blood InstituteThoratec CorporationPfizerEli Lilly and CompanyBristol-Myers SquibbAstraZenecaDaiichi Sankyo EuropeSanofiAmerican Heart Association
Mots-clésMedicineMyocardial infarctionCardiologyInternal medicineMEDLINEIntensive care medicine

Résumé

récupéré en direct d'OpenAlex

Importance: Pragmatic clinical trial designs have proposed the use of medical claims data to ascertain clinical events; however, the accuracy of billed diagnoses in identifying potential events is unclear. Objectives: To compare the 1-year cumulative incidences of events when events were identified by medical claims vs by physician adjudication and to assess the accuracy of bill-identified events using physician adjudication as the criterion standard. Design, Setting, and Participants: This post hoc analysis of a clinical trial assessed the medical claims forms and records for all rehospitalizations at 233 US hospitals within 1 year of the index acute myocardial infarction (MI) of 12 365 patients enrolled in the Treatment With Adenosine Diphosphate Receptor Inhibitors: Longitudinal Assessment of Treatment Patterns and Events After Acute Coronary Syndrome (TRANSLATE-ACS) study between April 1, 2010, and October 31, 2012. Fourteen patients (0.1%) died during the index hospitalization and were excluded from analysis. Recurrent MI, stroke, and bleeding events were identified per the International Classification of Diseases, Ninth Revision, Clinical Modification diagnosis and procedural codes in medical bills. These events were independently adjudicated by study physicians through medical record reviews using the prespecified criteria of recurrent MI and stroke and the bleeding definition by the Global Utilization of Streptokinase and Tissue Plasminogen Activator for Occluded Coronary Arteries (GUSTO) scale. Medical claims were reported on a Uniform Bill-04 claims form; claims were collected from all hospitals visited by patients enrolled in TRANSLATE-ACS. Agreement between medical claims-identified events and physician-adjudicated events over the 12 months after discharge was assessed with the κ statistic. Data were analyzed from January 30, 2015, to March 2, 2017. Main Outcomes and Measures: Event rates within 1 year after MI. Results: Among 12 365 patients with acute MI, 8890 (71.9%) were men and mean (SD) age was 60 (11.6) years. The cumulative 1-year incidence of events identified by medical claims was 4.3% for MI, 0.9% for stroke, and 5.0% for bleeding. Incidence rates based on physician adjudication were 4.7% for MI, 0.9% for stroke, and 5.4% for bleeding. Agreement between medical claims-identified and physician-adjudicated events was modest, with a κ of 0.76 (95% CI, 0.73 to 0.79) for MI and 0.55 (95% CI, 0.41 to 0.68) for stroke events. In contrast, agreement between medical claims-identified and physician-adjudicated bleeding events was poor, with a κ of 0.24 (95% CI, 0.19 to 0.30) for any hospitalized bleeding event and 0.15 (95% CI, 0.11 to 0.20) for moderate or severe bleeding on the GUSTO scale. Conclusions and Relevance: Event rates at 1 year after MI were lower for MI, stroke, and bleeding when medical claims were used to identify events than when adjudicated by physicians. Medical claims diagnoses were only modestly accurate in identifying MI and stroke admissions but had limited accuracy for bleeding events. An alternative approach may be needed to ensure good safety surveillance in cardiovascular studies. Trial Registration: clinicaltrials.gov Identifier: NCT01088503.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,003
score de la tête « metaresearch » (Gemma)0,003
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,289
Score d'incertitude au seuil0,699

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0030,003
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0010,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,057
Tête enseignante GPT0,377
Écart entre enseignants0,321 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations61
Publié2017
Routes d'admission1
Résumé présentoui

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