Evidence map›Paper›PMID 30505567›Full record

ReviewJournal of thoracic disease2018

A review and analysis of strategies for prediction, prevention and management of post-operative atrial fibrillation after non-cardiac thoracic surgery.

Heather Smith, Ching Yeung, Stephen Gowing, Mouhannad Sadek, Donna Maziak, Sebastien Gilbert, Farid Shamji, Patrick Villeneuve, Sudhir Sundaresan, Andrew Seely

Open access · hybridAbstract readReview
In one paragraph

Review in Journal of thoracic disease, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed, 2 pooled it
2.7field-weighted citation impact, top 8% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

17 citing papers in PubMed, 2 syntheses or guidelines pooled it, 45 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Review
  4. Article
  5. Observational
  6. Article
  7. Article
  8. Article
  9. Review
  10. Review
  11. Article
  12. Review
  13. Article
  14. Article
  15. Article
  16. Article
  17. Post-operative atrial fibrillation: should we anticoagulate?Annals of translational medicine · 2019
    Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors at 2 institutions in 1 country.

Heather SmithDivision of General Surgery, The Ottawa Hospital, University of Ottawa, Ottawa, ON, Canada.
Ching YeungDivision of Thoracic Surgery, The Ottawa Hospital, University of Ottawa, Ottawa, ON, Canada.
Stephen GowingDivision of Thoracic Surgery, The Ottawa Hospital, University of Ottawa, Ottawa, ON, Canada.
Mouhannad SadekDivision of Cardiology, The Ottawa Hospital, University of Ottawa, Ottawa, ON, Canada.
Donna MaziakDivision of Thoracic Surgery, The Ottawa Hospital, University of Ottawa, Ottawa, ON, Canada.
Sebastien GilbertDivision of Thoracic Surgery, The Ottawa Hospital, University of Ottawa, Ottawa, ON, Canada.
Farid ShamjiDivision of Thoracic Surgery, The Ottawa Hospital, University of Ottawa, Ottawa, ON, Canada.
Patrick VilleneuveDivision of Thoracic Surgery, The Ottawa Hospital, University of Ottawa, Ottawa, ON, Canada.
Sudhir SundaresanDivision of Thoracic Surgery, The Ottawa Hospital, University of Ottawa, Ottawa, ON, Canada.
Andrew SeelyDivision of Thoracic Surgery, The Ottawa Hospital, University of Ottawa, Ottawa, ON, Canada.
Ottawa Hospital · CAUniversity of Ottawa · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Atrial fibrillation (AF) is the most common sustained arrhythmia after non-cardiac thoracic surgery and is associated with a significant increase in perioperative morbidity, intensive care unit (ICU) admission, and mortality. Practical guidance is needed to assist clinicians in managing this critical issue and direct further research. Here we aim to provide a synoptic review and analysis of the literature to distil practical recommendations for prediction, prevention and management of post-operative atrial fibrillation (POAF) suitable for clinical application and further evaluation. To predict POAF, risk factors including age, gender, elevated pre-operative heart rate and extent of surgical resection have been reproducibly identified and integrated into scoring systems. To prevent POAF, prophylactic therapy with beta-blockers, amiodarone, or magnesium have demonstrated to be effective, but need further trials in high-risk populations. To manage unstable POAF that precipitates hypotension and hypoperfusion, although rare, requires immediate electrocardioversion to restore cardiac output and adequate oxygen delivery. For hemodynamically stable patients, rate control and prevention of adverse events are the objectives. We propose an individualized approach aimed at rate control using initial incremental low dose beta-blocker or calcium channel blocker (CCB) therapy with close monitoring of a patient's response, and continuation of the drug that they respond to, along with simultaneous identification and reduction of triggers of AF, in order for spontaneous return to sinus rhythm. For patients who persistently fail to respond to rate control therapy, rhythm control may be considered using an agent selected based on the patient's comorbidities and the medications' side effect profile. While controversial and requiring further study, anticoagulation therapy is recommended in patients with risk factors for thromboembolic events after 48 hours of persistent AF. We recommend continuous prospective monitoring of incidence and severity of POAF to track the impact of protocols to predict, prevent and manage POAF.

Indexed as

managementPost-operative atrial fibrillation (POAF)predictionpreventionthoracic surgery

Identifiers

PMID30505567
PMCPMC6258651
OpenAlexW2901327702

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.