In Response
Bibliographic record
Abstract
We read with interest the letter by Nei et al1 which was published in response to the “Society of Cardiovascular Anesthesiologists Clinical Practice Improvement Advisory for Management of Perioperative Bleeding and Hemostasis in Cardiac Surgery Patients” that was recently published in Anesthesia & Analgesia.2 The authors claim that in patients supported by extracorporeal membrane oxygenation (ECMO), if antithrombin (AT)-mediated heparin resistance occurs, an AT target level of >80%, as suggested in our publication,2 is likely unnecessary. While we agree that the level of therapeutic anticoagulation required for ECMO patients may be different than that used for cardiopulmonary bypass (CPB), we would like to remind the readers that recommendations for AT supplementation in the “Society of Cardiovascular Anesthesiologists Clinical Practice Improvement Advisory for Management of Perioperative Bleeding and Hemostasis in Cardiac Surgery Patients”2 relate only to cardiac surgical procedures requiring CPB and are not intended for patients requiring ECMO. Furthermore, the recommendations presented in the Clinical Practice Improvement Advisory are not intended to be a set of new guidelines but rather a summary of previously published societal guidelines and consensus statements for blood management during cardiac surgery. The management of anticoagulation in critically ill ECMO patients is challenging and heparin resistance may develop due to multiple causes that include AT deficiency. If low AT activity levels are confirmed, AT repletion (using either plasma or AT concentrates) may be indicated for heparin-based anticoagulation. According to the anticoagulation guidelines of the Extracorporeal Life Support Organization (ELSO; https://www.elso.org/Resources/Guidelines.aspx), a universal target threshold for AT supplementation in ECMO patients remains undetermined; however, many centers routinely administer AT replacement for AT activities <30%–80%, while others will treat low AT activity only if there is evidence of reduced heparin effect. Similarly, Esper et al3 reported that while there was no consensus on the AT target levels, levels below 60%–70% are associated with increased thrombosis. According to a recent survey published by Sniecinski et al,4 when AT-mediated heparin resistance is confirmed, >50% of practitioners administer AT concentrates as first-line therapy. Protti et al5 has recently published a worldwide survey of anticoagulation management in patients requiring venovenous ECMO. In 47% of the responding centers, patients received AT supplementation at least once while on ECMO. Furthermore, AT supplementation was routinely administered in 38% of centers when effective anticoagulation could not be achieved or when the AT level was <70%. In conclusion, managing anticoagulation for ECMO is different than that for CPB. Nonetheless, heparin resistance may develop, resulting in inability to achieve the desired level of anticoagulation due to multiple factors that include AT deficiency. While there is no consensus on the required AT level during ECMO, many centers will routinely administer AT to maintain a level between 50% and 80% as a physiologic circulating range of 80%–110%.6 We remind readers that the “Society of Cardiovascular Anesthesiologists Clinical Practice Improvement Advisory for Management of Perioperative Bleeding and Hemostasis in Cardiac Surgery Patients”2 is a summary of guidelines and consensus statements related to cardiovascular surgical procedures with CPB, and does not contain recommendations regarding the management of patients on ECMO. We would advise practitioners to use clinical judgment and not routinely extrapolate recommendations of care during CPB to patients requiring ECMO. CONTRIBUTORS Jacob Raphael, MD; C. David Mazer, MD; Sudhakar Subramani, MD; Andrew Schroeder, MD; Mohamed Abdalla, MD; Renata Ferreira, MD; Philip E. Roman, MD; Nichlesh Patel, MD; Ian Welsby, MBBS; Philip E. Greilich, MD; Reed Harvey, MD; Marco Ranucci, MD; Lori B. Heller, MD; Christa Boer, PhD; Andrew Wilkey, MD; Steven E. Hill, MD; Gregory A. Nuttall, MD; Raja R. Palvadi, MD; Prakash A. Patel, MD; Barbara Wilkey, MD; Brantley Gaitan, MD; Shanna S. Hill, MD; Jenny Kwak, MD; John Klick, MD; Bruce A. Bollen, MD; Linda Shore-Lesserson, MD; James Abernathy, MD; Nanette Schwann, MD; W. Travis Lau, MD. Jacob Raphael, MDDepartment of AnesthesiologyUniversity of Virginia Health SystemCharlottesville, Virginia[email protected]C. David Mazer, MDDepartment of AnesthesiologySt Michael’s HospitalUniversity of TorontoToronto, Ontario, CanadaLinda Shore-Lesserson, MDDepartment of AnesthesiologyZucker School of Medicine at Hofstra/NorthwellNorthshore University HospitalManhasset, New YorkBruce Bollen, MDMissoula AnesthesiologyAffiliate with International Heart Institute of Montana at Providence St Patrick Hospital, Missoula, MontanaJerrold H. Levy, MDDepartment of AnesthesiologyDuke University Medical CenterDurham, North CarolinaNanette Schwann, MDDepartment of AnesthesiologyLehigh Valley Health NetworkUniversity of South Florida Morsani College of MedicineTampa, FloridaAAA Anesthesia AssociatesPhyMed Healthcare Group, Allentown, PennsylvaniaOn behalf of the Blood Conservation Working Group and the Clinical Practice Improvement Committee of the Society of Cardiovascular Anesthesiologists
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.038 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.016 | 0.016 |
| Insufficient payload (model declined to judge) | 0.265 | 0.166 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".