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Record W4378234222 · doi:10.1093/europace/euad122.721

Logistics of safe and stress-free epicardial access in the electrophysiology lab: creative percutaneous subxiphoid pericardiostomy

2023· article· en· W4378234222 on OpenAlexaffabout
M Burg, Hanney Gonna, R. David Anderson, Sirish Chandra Srinath Patloori, J. Velez, Abhishek Bhaskaran, K. Nair, Danna Spears, Vishal Chauhan, Andrew C.T. Ha, Robert J. Cusimano, K. Nanthakumar

Bibliographic record

VenueEP Europace · 2023
Typearticle
Languageen
FieldMedicine
TopicPericarditis and Cardiac Tamponade
Canadian institutionsHamilton Health SciencesToronto General HospitalHealth Sciences CentreUniversity Health Network
Fundersnot available
KeywordsMedicineCoronary arteriesVentricleSurgeryAnesthesiaCardiologyArtery

Abstract

fetched live from OpenAlex

Abstract Funding Acknowledgements Type of funding sources: Foundation. Main funding source(s): Professor Nanthakumar is a recipient of the mid-career investigator award from the Heart & Stroke Foundation of Ontario. Introduction Dry epicardial access (EA) into the virtual pericardial space carries a 6-25% risk of collateral damage to important adjacent structures including the right ventricle and the coronary and internal thoracic arteries.1 This renders conventional dry EA a potentially daunting and stressful undertaking. Separation of the parietal and visceral pericardial layers by CO2 insufflation has been described and may mitigate some risk , however even in experienced tertiary centres, injury to superior epigastric arteries, liver, stomach, and transverse colon, has been reported. Furthermore, insufflating the pericardial space may cause unwanted haemodynamic changes . There is thus the need for an approach that separates the pericardial layers and avoids injury to right ventricle and coronary arteries while also avoiding abdominal and thoracic structures by direct visualisation. Purpose We describe the logistics of a creative technique that combines percutaneous EA with a minimally-invasive subxiphoid pericardiostomy that can be done with a surgeon in the electrophysiology (EP) lab for the initial 20 minutes of the procedure. Methods We performed the procedure with a surgeon in 4 patients in a single tertiary centre. The procedure was done in the EP lab under general anaesthesia with standard surgical asepsis and IV cefazolin administered pre-operatively. The subxiphoid area is infiltrated with local anaesthesia. Following a limited 5cm midline incision, the linea alba is dissected exposing the preperitoneal fat but the peritoneal space is not entered. The lower sternum is retracted anteriorly to expose the diaphragm and cardiophrenic fat pad. The diaphragm is progressively sutured to the skin to bring the pericardium into view. A 0-silk suture is then used to tent the pericardium at which point an incision is made in the pericardium to create the window. The steerable sheath and pericardial drain are inserted in the standard over-the-wire percutaneous technique through separate adjacent punctures with direct pathway visualisation through the window. Following this, the surgical incision is closed, allowing the surgeon to leave, and mapping to ensue. Results The time from skin incision to pericardial drain insertion was 18±5 minutes. None of our patients had acute or delayed bleeding or adjacent organ injury peri-procedurally. The pericardial drain was removed within 12-24 hours. One patient had mild pericarditis that resolved after a short course of non-steroidal anti-inflammatory agents. The subxiphoid wound healed well in all patients. Conclusions Percutaneous EA with easy entry into the pericardial space under direct visualisation and realtime monitoring via a pericardiostomy can be readily attained with surgical collaboration. We propose this as an alternative approach to EA, particularly in situations in which the percutaneous access will be challenging (e.g. obesity, or in presence of adhesions).

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.680
Threshold uncertainty score0.540

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.019
GPT teacher head0.297
Teacher spread0.278 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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
Published2023
Admission routes2
Has abstractyes

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