Access Denied; Care Impaired: The Benefits of Having Online Medical Information Available at the Point-of-Care
Bibliographic record
Abstract
In Brief The availability of Internet-enabled computers in the operating room (OR) facilitates unparalleled physician access to current peer reviewed research, either in abstract or full text format, a development that provides physicians with an exciting opportunity to incorporate such findings into clinical practice at the point-of-care. In this report I describe how the availability of online peer reviewed medical literature altered, in one case a planned surgical procedure and, in the other, the interpretation by the anesthesiologist of the clinical significance of an intraoperative echocardiographic finding. In case one, a free, rather than an intact, internal mammary (IM) artery graft was placed to the left anterior descending coronary artery of a patient with renal failure and an ipsilateral upper extremity arteriovenous fistula. The change occurred after the full text results of a study indicating that steal could well occur during the initiation of dialysis if an intact IM was used were made available to the surgeon. In case two, the occurrence of mild central mitral regurgitation in a Carpentier-Edwards Perimount prosthetic mitral valve was confirmed to be a benign finding after a study detailing the long term performance characteristics of this valve was accessed online in the OR. The benefits and potential pitfalls of searching and interpreting online medical information are discussed. IMPLICATIONS: Two cases are described in which immediate access to a medical information database and other Internet available resources altered physician decision making intraoperatively. The potential benefits, limitations, and difficulties encountered using such resources in the operating room are discussed.
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 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 | 0.002 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".