Documentation of Rectal Examination Performance in the Clinical Teaching Unit of a University Hospital
Bibliographic record
Abstract
Digital rectal examination is used to evaluate the distal rectum and other organs, including the prostate gland. It may be combined with fecal screening for occult blood loss, and annual performance has been recommended for asymptomatic individuals over age 40 years for cancer screening. In this study, documentation of digital rectal examinations was assessed through a review of hospital medical records of a randomly selected group of 100 patient discharges (55 females and 45 males) from a total of 896 patients admitted through a hospital emergency room to a medical clinical teaching inpatient unit of a university hospital during a six-month period. In this group, 26% were admitted for a gastrointestinal disorder, but only 17% of all hospitalized patients had rectal examinations done by the medical resident house staff and/or attending medical staff directly responsible for the care of these patients. Occult blood testing was done in 15 patients. Pelvic and breast examinations were rarely documented. The majority of rectal examinations (ie, 13 of 17) were 'same sex' examinations, appeared to be used largely for testing or confirmation of grossly visible blood loss and were never confirmed by attending staff. The presence or absence of nursing staff during examinations was not documented. The prostate examination was normal in one patient but not documented in the other 44 males (ie, 26 patients over age 60 years). In conclusion, rectal examinations (as well as breast and pelvic examinations) were rarely documented in the medical teaching unit by medical resident house staff or their attending staff.
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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 | 0.000 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".