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Record W4391541287 · doi:10.7759/cureus.53620

The Significance of Equipment Availability and Anesthesia Educational Conferences to Decision-Making for EKG Lead V5 Abnormalities

2024· article· en· W4391541287 on OpenAlexaboutno aff
Kimberly L. Skidmore, Joseph Drinkard, Henson M Randall, Giustino Varrassi, Sahar Shekoohi, Alan D. Kaye

Bibliographic record

VenueCureus · 2024
Typearticle
Languageen
FieldMedicine
TopicCardiac, Anesthesia and Surgical Outcomes
Canadian institutionsnot available
Fundersnot available
KeywordsMedicinePerioperativeMyocardial infarctionTroponinLead (geology)CardiologyInternal medicineOdds ratioEmergency medicineAnesthesia

Abstract

fetched live from OpenAlex

Introduction To predict postoperative myocardial infarction rates in patients who undergo noncardiac surgery, the Canadian Cardiovascular Society Guidelines on Perioperative Cardiac Risk Assessment and Management recommends assessment of brain natriuretic peptide (BNP) in certain patients. Serial troponins are measured if the BNP level is elevated. In certain cases, Revised Cardiac Risk Index (RCRI) alone does not perform well, for example, during vascular surgery. Cardiac events occur in 20% of all vascular surgery patients. The odds ratio for such events is 9.2 if ST segments were depressed by 1 mm intraoperatively (relative to the PR interval) within the first 48 hours postoperatively. Increasing the number of cables and pads from three to five for electrocardiogram (EKG) increases the sensitivity from around 30% to over 80% for ischemic events relative to a formal EKG stress test, and then the monitor continuously displays not only lead II but also lead V5. Methods Our hypothesis was that raising awareness about diagnostic and therapeutic options to reduce the risk of postoperative myocardial infarction would increase the use of five pads. We conducted open-ended surveys at six hospitals to assess the reasons for choosing three pads. In our university hospital practice, we measured a cross-sectional incidence of using three pads before and, once again, a month after an intervention during a single morning. Several resident conferences encouraged the use of five pads. Education included weekly lectures and informal discussions with other staff during surgery, demonstrating that using five pads allows interrogation of an entire 12-lead EKG. In comparison, three pads only allow viewing three leads. Results At baseline, only three pads were available in 96% of our 23 operating rooms. Five cables were available in eight of those surgeries, but two were taped off to the side. Surveys unveiled scarcity of equipment and, more importantly, disempowerment (i.e., knowing how to diagnose or when to treat ischemia). After several conferences, the prevalence of equipment availability of only three pads fell to 47%. Conclusions Education enumerated details of recognizing ischemic configurations of ST depression. Next, education revealed methods to interrupt the progression of ischemia to infarction such as elevated blood pressure and hematocrit, reducing heart rate, and calling a cardiology consultant if the anesthesiologist wishes to draw serial troponins. Barriers to implementing an enhanced recovery after surgery (ERAS) pathway began with a need for more access to manage stress tests or optimize blood pressure medications after a preoperative anesthesia evaluation. The intraoperative barrier was knowing what to do if ST depression occurs. Therefore, we began raising awareness by encouraging the addition of an element of a future ERAS pathway, adding a cost of only $1 to monitor lead V5. Future ERAS pathways can include preoperative stress tests and consults, as found in published guidelines.

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)0.004
metaresearch head score (Gemma)0.046
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.046
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.026
GPT teacher head0.335
Teacher spread0.309 · 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 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

Citations0
Published2024
Admission routes1
Has abstractyes

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