Hospital Mortality Due to Pulmonary Embolism (PE) and an Evaluation of the Usefulness of Preventative Interventions.
Notice bibliographique
Résumé
Abstract Background: Many hospitalized patients with PE die. A large registry study described a mortality rate of 17.4% in patients with PE and suggested 45% of these deaths were due to the PE. Data on death and PE is usually derived retrospectively from hospital databases without chart confirmation and to our knowledge no study has attempted to determine the accuracy of coding for PE deaths. Furthermore, it is unclear how often deaths caused by PE could have been prevented. Methods: A retrospective chart review of PE cases hospitalized at a tertiary care center. Charts over an 8 year period ending in 2004 were reviewed if the hospital database record identified PE as a diagnosis by the ICD-10 coding system. Charts of those who died were independently reviewed by two thrombosis experts with discrepancies resolved by consensus or a third reviewer. Prior to chart review definitions were agreed upon. The coding as PE was considered correct (confirmed PE) if there was supportive imaging, an autopsy, or in the case of death without imaging or autopsy, the clinical scenario was such that PE could have occurred. The degree of certainty that PE contributed to the death was classified as certain (unexplained hypotension, hypoxia, cardiac arrest with no other explanation other than PE and autopsy confirmation or radiographic confirmation), highly probable (same as certain but no autopsy confirmation), probable (criteria for highly probable but another disease could have caused the death). We considered these cases to be death due to PE. Deaths were also classified as possible (other cause suspected based on clinical evidence but 100% certainty not available), or unlikely due to PE (all other cases). In cases defined as death due to PE we determined whether any further intervention could have prevented death. Results: 612 cases were identified of whom 68 had radiographic or autopsy data that ruled out the diagnosis and in 46 the coding was clearly an error. 498 cases of PE were identified, 111 of whom died during hospitalization; the mortality rate in those the hospital coded as PE was 18% vs 22% of those with confirmed PE. Death due to PE was diagnosed in 70 patients (14% of patients with confirmed PE and 11% of all patients coded as PE). In the remaining 41 deaths, PE was possible in 24 and unlikely in 17. Disagreement was uncommon. There was no difference between the likelihood of death from PE in the group diagnosed by imaging and autopsy compared with the group where PE death was confirmed by an appropriate clinical scenario. 38 deaths due to PE may have been prevented with an additional intervention: prophylaxis (55%), earlier diagnosis (45%), inferior vena cava filter (IVCF) (32%), anticoagulation (18%), embolectomy 5%, thrombolytics (3%). The remaining deaths due to PE were not preventable since 15 patients were palliative and did not receive active treatment, 9 died before a diagnosis was made and in 8 another disease prevented treatment. Conclusions: Using hospital database records is a reasonable means to evaluate PE mortality and our death due to PE rates are similar to those in registry publications. Surprisingly imaging and autopsy results do not increase the probability of reaching the conclusion that death is due to PE. Over half of preventable PE deaths may have been prevented by prophylaxis and one third with an IVCF.
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 machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,012 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,003 | 0,002 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».