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Seek and You Shall Find – but Then What Do You Do? Cold Agglutinins in Cardiopulmonary Bypass, and a Single Center Experience with Cold Agglutinin Screening Before Cardiac Surgery

2012· article· en· W2566600397 on OpenAlexaff
Michael D. Jain, Keyvan Karkouti, Terence M. Yau, Jacob Pendergrast, Christine Cserti‐Gazdewich

Bibliographic record

VenueBlood · 2012
Typearticle
Languageen
FieldMedicine
TopicBlood groups and transfusion
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsCold AgglutininMedicineCardiopulmonary bypassSingle CenterCohortRetrospective cohort studyCardiac surgeryAdverse effectSurgeryAnesthesiaInternal medicineAntibody

Abstract

fetched live from OpenAlex

Abstract Abstract 4372 Background: Cardiopulmonary bypass (CPB) during cardiac surgery typically involves deliberate hypothermia of the systemic (22 – 36°C) and coronary circulations (down to 8 – 12°C). Adverse sequelae of previously undiagnosed cold-active antibodies have been feared and reported under such conditions. For this reason, some centers elect to screen for cold agglutinins prior to CPB. Some groups also intervene when a positive screen is noted, by electing to modify CPB conditions to lessen hypothermia in such patients. Aim: To determine the yields and effects of cold agglutinin screening (CAS) in pre-operative cardiac surgery patients planned for CPB. Methods: Literature review and retrospective cohort study of 14,900 patients undergoing CPB and cardiac surgery over 8 years at our institution. Results: The majority of the literature consists of case reports and case series. The literature review found that patients with a positive CAS had infrequent adverse events when undergoing CPB. These included 4 cases where complications were likely attributable to cold agglutinins, 4 cases where complications were possibly due to cold agglutinins and 158 cases where no complications were noted, despite a likely bias towards case reporting adverse events. Analysis of a retrospective cohort of 14,900 patients undergoing CPB and cardiac surgery at our institution identified 47 patients (0.3%) with positive cold agglutinin screens (CAS+) over 8 years. The annual testing cost was $17,000 CAD. Compared to the cohort of CAS-negative patients, CAS+ patients had a statistically longer ICU length of stay [median 54.6 hours (IQR 24 – 166) vs. 42.8 hours (IQR 23 – 70), P = 0.021] and hospital length of stay [median 7 days (IQR 6 – 14) vs. 7 days (IQR 5 – 9), P = 0.044]. However, the composite of mortality or severe morbidity (stroke, MI, dialysis, low output, sepsis, and DVT) was not significantly different in comparing the CAS+ and CAS-negative groups (14.9% vs. 9.2%, P = 0.2). The response of the surgical team to the pre-operative discovery of a CAS+ patient was variable, with CPB modified to avoid hypothermia in approximately one-third of cases. Modification of CPB to avoid hypothermia in the CAS+ group did not lead to better outcomes. Patients undergoing unmodified (standard) CPB had an event rate of 10.3% on the composite outcome, while patients undergoing modified (less hypothermic) CPB had an event rate of 20.0% (P = 0.647). Antibody verification found that only 43% of positive CAS patients had true cold agglutinins (20 patients). Half of these patients had unmodified CPB, while the other half had modified CPB. Event rates were low, with 1 out of 10 patients reaching the composite outcome in each group. Conclusion: Based upon historical and local data, we conclude that preclinical CAS is cost-substantial, does not effectively identify true-positive patients, and does not lead to an intervention that meaningfully improves patient outcomes during surgery. We do not recommend CAS in asymptomatic cardiac surgery patients. Disclosures: No relevant conflicts of interest to declare.

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)0.007
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.017
GPT teacher head0.222
Teacher spread0.205 · 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".

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Citations3
Published2012
Admission routes1
Has abstractyes

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