Perioperative Anticoagulant Use for Surgery Evaluation (PAUSE) Study: A Perioperative Management Plan for Patients with Atrial Fibrillation Who Are Receiving a Direct Oral Anticoagulant
Bibliographic record
Abstract
Abstract Introduction: The perioperative management of patients who are taking a direct oral anticoagulant (DOAC) for atrial fibrillation (AF) and require an elective surgery/procedure is uncertain. No studies have addressed the timing of perioperative DOAC interruption and resumption, and if perioperative heparin bridging and coagulation function testing are needed. The Perioperative Anticoagulant Use for Surgery Evaluation (PAUSE) Study hypothesized that a simple, standardized perioperative management strategy, based on DOAC-specific interruption and resumption intervals, that foregoes perioperative heparin bridging and coagulation function testing, is safe for patient care, with associated low rates of major bleeding (1%) and arterial thromboembolism (0.5%). We postulated that this management yields a high proportion of patients (>90%) with a minimal to no DOAC level at surgery/procedure. Methods: PAUSE is a prospective study with 3 parallel DOAC cohorts of patients with AF taking apixaban, dabigatran or rivaroxaban and requiring anticoagulant interruption for an elective surgery/procedure. Patients were managed using a standardized protocol based on DOAC pharmacokinetic properties, procedure-associated bleeding risk (Appendix 1) and creatinine clearance (CrCl). DOACs were interrupted for 1 day before and after surgery for a low bleed risk surgery and 2 days before and after a high bleed surgery; longer interruption was done in patients on dabigatran with a CrCl<50 mL/min (Figure 1). A blood sample was obtained just before the procedure to measure residual DOAC levels (Appendix 2). Heparin bridging and preoperative coagulation testing were not used to manage patients. Patient follow-up occurred weekly for 30 days post-procedure for the primary clinical outcomes of major bleeding and arterial thromboembolism (Appendix 3). The incidence (95% confidence interval [CI]) of clinical outcomes was determined for each DOAC cohort using an intention-to-treat (ITT) analysis (interrupted at least 1 DOAC dose) and per-protocol analysis (adhering to DOAC interruption and resumption protocol). Results: We enrolled 3007 patients from 23 sites in Canada, the U.S. and Europe (Appendix 4). The patient characteristics were (Figure 2): mean age 72.5 years; 66.1% male; 33.5% high bleeding risk surgery/procedure, with 1257 patients in the apixaban cohort, 668 in the dabigatran cohort and 1082 in the rivaroxaban cohort (Table 1). DOAC interruption and resumption intervals are shown in Table 2. The 30-day postoperative rate (95% CI) of major bleeding was 1.35% (0-2.00) in the apixaban cohort, 0.90% (0-1.73) in the dabigatran cohort and 1.85% (0-2.65) in the rivaroxaban cohort; the rate (95% CI) of arterial thromboembolism was 0.16% (0-0.48) in the apixaban cohort, 0.6% (0-1.33) in the dabigatran cohort and 0.37% (0-0.82) in the rivaroxaban cohort (Table 3). There were 2541 (84.5%) patients with preoperative DOAC levels measured: a level <50 ng/ml occurred in 90.5% of patients in the apixaban cohort, in 95.1% of the dabigatran cohort and in 96.8% of the rivaroxaban cohort. Of 1007 patients having a high bleeding risk procedure, 832 (82.6%) had DOAC levels measured: 98.8% had a level <50 ng/mL (Table 4). Rates of major bleeding and arterial thromboembolism in the per protocol analysis were comparable to those of the ITT analysis (Table 5). Conclusions: In patients with AF who were taking a DOAC (apixaban, dabigatran, rivaroxaban) and required anticoagulant interruption for an elective surgery/procedure, using a standardized DOAC-specific perioperative management strategy was safe for patient care, with associated low rates of perioperative MB (<2%) and ATE (<1%). Further, a high proportion of patients (>90% overall; 98.8% at high bleeding risk) had a minimal or no residual DOAC level at the time of the surgery/procedure. PAUSE is the largest study, to date, that addresses how to manage the common problem of perioperative DOAC management. It is likely to have a practice-changing impact and will inform future practice guidelines in perioperative care. Study Funding: CIHR (313156) and the H&S Foundation of Canada (G-14-0006136). Aniara-Hyphen Biomed (assays). Acknowledgments: We thank Drs. Walter Ageno, David Garcia, Lehana Thabane, Wendt Lim, Lori Linkins, William Ristevski, and Demetrios J. Sahlas. Also, Kayla Lucier, Grace Wang, Tara McDougall, and HRLMP and CRLB. Supported by CanVector and REDCap. Disclosures Douketis: Bayer: Other: Advisory Board; Janssen: Consultancy; BMS: Other: Advisory Board; Biotie: Other: Advisory Board; Daiichi-Sankyo: Other: Advisory Board; Boehringer-Ingelheim: Consultancy, Other: Advisory Board, Research Funding; The Medicines Company: Other: Advisory Board; Sanofi: Consultancy, Other: Advisory Board; Astra-Zeneca: Other: Advisory Board; Portola: Other: Advisory Board; Pfizer: Other: Advisory Board. Spyropoulos:Janssen Scientific Affairs, LLC: Consultancy. Carrier:Bayer: Honoraria; Leo Pharma: Research Funding; Pfizer: Honoraria; BMS: Honoraria, Research Funding. Vanassche:Bayer: Consultancy; Boehringer Ingelheim: Consultancy; BMS/Pfizer: Consultancy. Verhamme:Bayer: Honoraria, Research Funding; Medtronic: Honoraria; Portola: Honoraria; Boehringer Ingelheim: Honoraria; Leo Pharma: Honoraria, Research Funding; BMS: Honoraria, Research Funding; Daiichi-Sankyo: Honoraria, Research Funding; Pfizer: Honoraria, Research Funding. Shivakumar:Pfizer: Honoraria; Servier: Honoraria; Bayer: Honoraria; LEO Pharma: Honoraria. Gross:Pfizer: Honoraria; Bayer: Honoraria; LEO Pharma: Honoraria; Servier: Honoraria. Lee:Pfizer: Consultancy, Research Funding; BMS: Research Funding; Servier: Honoraria; LEO Pharma: Consultancy, Research Funding; Bayer: Consultancy, Honoraria. Le Templier:BMS-pfizer: Honoraria. Wu:Leo Pharma: Honoraria; Pfizer: Honoraria; BMS-Pfizer: Honoraria. Coppens:Bayer: Honoraria, Other: Non-financial support, Research Funding; CSL Behring: Honoraria, Other: non-financial support, Research Funding; Uniqure BV: Research Funding. Arnold:Bristol Myers Squibb: Research Funding; UCB: Consultancy; Amgen: Consultancy, Research Funding; UCB: Consultancy; Amgen: Consultancy, Research Funding; Novartis: Consultancy, Research Funding; Bristol Myers Squibb: Research Funding; Novartis: Consultancy, Research Funding. Caprini:Alexion Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees; Recovery Force: Consultancy; BMS: Membership on an entity's Board of Directors or advisory committees; Pfizor: Membership on an entity's Board of Directors or advisory committees; Janssen R&D: Membership on an entity's Board of Directors or advisory committees. Summer:Octapharma: Honoraria. Schulman:Daiichi-Sankyo: Honoraria; Bayer: Honoraria; Sanofi: Honoraria; Boehringer-Ingelheim: Honoraria, Research Funding.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".