The burden of urological disease in Zomba, Malawi: A needs assessment in a sub-Saharan tertiary care center
Bibliographic record
Abstract
INTRODUCTION: A large part of the developing world continues to lack access to surgical care. Urology remains one of the least represented surgical subspecialties in global health. To begin understanding the burden of urological illness in sub-Saharan Africa, we sought to characterize all patients presenting to a tertiary care hospital in Malawi with a urological diagnosis or related complaint in the past year. METHODS: Retrospective review of the surgical clinic and surgical theater record books at Zomba Central Hospital (ZCH) was performed over a one-year time span. Patients presenting with urological diagnoses or undergoing a urological procedure under local or general anesthetic in the operating theater were identified and entered into a database. RESULTS: We reviewed 440 clinical patients. The most common clinical presentations were for urinary retention (34.7%) and lower urinary tract symptoms (15.5%). A total of 182 surgical cases were reviewed. The most common diagnoses for surgical patients were urethral stricture disease (22%), bladder masses (17%), and benign prostatic hyperplasia (BPH) symptoms (14.8%). Urethral stricture-related procedures, including direct visual internal urethrotomy and urethral dilatation, were the most common (14.2% and 7.7%, respectively). BPH-related procedures, including simple prostatectomy and transurethral resection of the prostate were the second most common (6.7% and 8.2%, respectively). CONCLUSIONS: Urethral stricture disease, BPH, and urinary retention represent the clinical diagnoses with the highest burden of visits. Despite these numbers, few definitive procedures are performed annually. Further focus on urological training in sub-Saharan Africa should focus on these conditions and their surgical management.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".