Preoperative assessments by trained nurses were equal in quality to assessments by preregistration house officers
Bibliographic record
Abstract
Kinley H, Czoski-Murray C, George S, et al. Effectiveness of appropriately trained nurses in preoperative assessment: randomised controlled equivalence/non-inferiority trial. BMJ2002 ; 325 : 1323 –6 [OpenUrl][1][Abstract/FREE Full Text][2] QUESTION: Are preoperative assessments by trained nurses equal in quality to those done by preregistration house officers? Randomised (allocation concealed), unblinded, controlled equivalence/non-inferiority trial. 4 hospital sites in 3 UK National Health Service Trusts. 1907 patients who required assessment before general anaesthesia for general, vascular, urological, or breast surgery. 1874 patients (98%) were included in the analysis (mean age 57 y, 49% women). 954 patients were allocated to preoperative assessment by a nurse who had completed master’s level courses in advanced practice or equivalent. 953 patients were allocated to assessment by a preregistration house officer. 1 of 2 specialist registrars in anaesthesia examined each patient … [1]: {openurl}?query=rft.jtitle%253DBMJ%26rft.stitle%253DBMJ%26rft.aulast%253DKinley%26rft.auinit1%253DH.%26rft.volume%253D325%26rft.issue%253D7376%26rft.spage%253D1323%26rft.epage%253D1323%26rft.atitle%253DEffectiveness%2Bof%2Bappropriately%2Btrained%2Bnurses%2Bin%2Bpreoperative%2Bassessment%253A%2Brandomised%2Bcontrolled%2Bequivalence%252Fnon-inferiority%2Btrial%26rft_id%253Dinfo%253Adoi%252F10.1136%252Fbmj.325.7376.1323%26rft_id%253Dinfo%253Apmid%252F12468478%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [2]: /lookup/ijlink?linkType=ABST&journalCode=bmj&resid=325/7376/1323&atom=%2Febnurs%2F6%2F4%2F122.atom
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".