Investigating the Rationale for Extending CT KUB to Include the Chest for Suspected Renal Colic Patients During the COVID-19 Pandemic
Bibliographic record
Abstract
Background and Objective Following on from the Royal College of Surgeons (RCS) recommendation of 5th of April 2020 to perform computed tomography (CT) scan of the chest in patients presenting with an abdominal pain emergencies and undergoing an abdominal CT; comparison was made between a cohort of patients with a RCS-COVID recommended scan and a similar group of patients in the pre-COVID era. To evaluate the value of extending CT-KUB scan to include the chest area, in patients presenting to the emergency department with acute renal colic during the COVID-19 pandemic. Material and Methods Retrospective data included; initial presentation, COVID-19-related symptoms, dose length product (DLP), scan extension, Ground glass appearance (GGO), Wuhan corona virus swab polymerase chain reaction (PCR) test. Results A total of 100 patients underwent CT KUB in April 2020 (Group 1) with a similar number of patients from the pre-COVID-19 pandemic randomly selected from August to October 2019 (Group 2). Patients age ranged from 15 to 91 years with a median of 48 years in Group 1, whilst in Group 2 the range was 19 to 85 years with a median of 50 years. All patients in both groups initially presented with renal colic. No COVID-19-related respiratory manifestations were recorded. Nine patients from Group 1 had GGO identified in their chest CT with all of them returning with negative COVID-19 swabs. Interestingly there was almost the same number of stones diagnosed 49% (49/ 100) in Group 1 patients compared with 50% (23/5150/100) from Group 2. Conclusions Despite the RCS COVID CT scan recommendations, our study has demonstrated no significant additional value of extending the CT-KUB to include the chest area in renal colic patients with no respiratory manifestations. Further studies are recommended in order to validate these results.
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 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".