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Record W2066008483 · doi:10.1186/1752-1947-3-109

Tenecteplase for ST-elevation myocardial infarction in a patient treated with drotrecogin alfa (activated) for severe sepsis: a case report

2009· article· en· W2066008483 on OpenAlexaff
Lillian Barra, Jeffrey Shum, J. Geoffrey Pickering, Raymond Kao

Bibliographic record

VenueJournal of Medical Case Reports · 2009
Typearticle
Languageen
FieldMedicine
TopicBlood Coagulation and Thrombosis Mechanisms
Canadian institutionsWestern University
Fundersnot available
KeywordsMedicineDrotrecogin alfaTenecteplaseSeptic shockMyocardial infarctionThrombolysisSepsisInternal medicineCardiologyPneumoniaIntensive care medicineSevere sepsis

Abstract

fetched live from OpenAlex

INTRODUCTION: Drotrecogin alfa (activated) (DrotAA), an activated protein C, promotes fibrinolysis in patients with severe sepsis. There are no reported cases or studies that address the diagnosis and treatment of myocardial infarction in septic patients treated with DrotAA. CASE PRESENTATION: A 59-year-old Caucasian man with septic shock secondary to community-acquired pneumonia treated with DrotAA, subsequently developed an ST-elevation myocardial infarction 12 hours after starting DrotAA. DrotAA was stopped and the patient was given tenecteplase thrombolysis resulting in complete resolution of ST-elevation and no adverse bleeding events. DrotAA was restarted to complete the 96-hour course. The sepsis resolved and the patient was discharged from hospital. CONCLUSION: In patients with severe sepsis or septic shock complicated by myocardial infarction, it is difficult to determine if the myocardial infarction is an isolated event or caused by the sepsis process. The efficacy and safety of tenecteplase thrombolysis in septic patients treated with DrotAA need further study.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0020.001
Science and technology studies0.0030.002
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0080.004
Insufficient payload (model declined to judge)0.0030.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.024
GPT teacher head0.305
Teacher spread0.281 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designCase report
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2009
Admission routes1
Has abstractyes

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