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Record W2044793229 · doi:10.1097/pcc.0b013e3181ae5b8a

Pacemaker therapy of postoperative arrhythmias after pediatric cardiac surgery

2009· review· en· W2044793229 on OpenAlexaff
Peter Skippen, Shubhayan Sanatani, Norbert Froese, Robert M. Gow

Bibliographic record

VenuePediatric Critical Care Medicine · 2009
Typereview
Languageen
FieldMedicine
TopicCardiac pacing and defibrillation studies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMedicineIntensivistBradycardiaCardiac surgeryIntensive care medicineIntensive care unitCardiologyInternal medicineHeart rate

Abstract

fetched live from OpenAlex

OBJECTIVE: To summarize the practical operation of temporary pacemakers in common use pertinent to the intensivist caring for the postcardiac patient. Pacemaker therapy is commonly required in the postoperative period after congenital cardiac surgery. DATA SYNTHESIS: Monitoring the hemodynamic status and availability of equipment for resuscitation is always important in any patient requiring a temporary pacemaker. Two important scenarios to consider in the pediatric intensive care unit are: 1) the patient in whom pacing has been initiated to optimize cardiac function; and 2) the patient without demonstrable spontaneous electrical activity or with extreme bradycardia. A number of different models of temporary pacemaker are available. Management of the child requiring cardiac pacing requires an understanding of the indications for pacing, a thorough knowledge of the available pacemaker, and an ability to troubleshoot problems. CONCLUSIONS: As the most common arrhythmias post congenital cardiac surgery involve either rate or conduction abnormalities, temporary pacemaker systems are a common form of electrical therapy in the postoperative period.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.062
GPT teacher head0.385
Teacher spread0.323 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations5
Published2009
Admission routes1
Has abstractyes

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