Urinary Retention in Patients in a Geriatric Rehabilitation Unit: Prevalence, Risk Factors, and Validity of Bladder Scan Evaluation
Classification
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".
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The purpose of this study was to identify risk factors for urinary retention (UR) in frail, elderly patients, to determine its prevalence, and to assess the validity of the use of the BladderScan BVI 2500+ ultrasound scanner to measure postvoid residual urine volumes of > or = 150 ml. Probable UR was defined as two consecutive ultrasound scans with postvoid residual urine estimations of > or = 150 ml. The estimates were confirmed by in- and out-catheterization of actual postvoid residual urine (PVR). Risk factors for UR were the independent variables used in the regression analysis. Nineteen of the 167 people (11%) had UR. The risk of UR was greatest among patients who were older, or who were on anticholinergic medication, or who had diabetes of long standing, or who had fecal impaction. The correlation between paired scans and catheter volumes of > or = 150 ml was 0.87. The results suggest that the BladderScan BVI 2500+ ultrasound scanner, when used by trained nursing staff, provides conservative and valid estimates of PVR of > or = 150 ml in people undergoing geriatric rehabilitation.
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 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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it