Regional anaesthesia practice in public hospitals in Botswana: A cross-sectional study
Bibliographic record
Abstract
INTRODUCTION: Little is known about the regional anesthesia practice in low resources settings (LRS). The aim of this study was to describe the regional anesthesia capacity, characteristics of regional anesthesia practice, and challenges and solutions of practicing safe regional anesthesia in public hospitals in Botswana. METHODS: This was a cross-sectional survey of anesthesia providers working in public hospitals in Botswana. A purposive sampling method of public hospitals was used to achieve representation of different hospital levels across Botswana. Paper-based questionnaires were sent to anesthesia providers from selected hospitals. Descriptive statistics were used for analysis. RESULTS: Questionnaires were distributed to 47 selected anesthesia providers from selected hospitals; 38 (80.9%) were returned. Most participants were nurse anesthetists and medical officers (57.8%). All hospitals perform spinal anesthesia; however, other regional techniques were performed by a small number of participants in one referral hospital. Most hospitals had adequate regional anesthesia drugs and sedation medications, however, most hospitals (except one referral hospital) lacked ultrasound machine and the regional anesthesia kit. The common challenges reported were lack of knowledge and skills, lack of equipment and supplies, and lack of hospital engagement and support. Some solutions were proposed such as regional anesthesia training and engaging the hospital management to get resources. CONCLUSIONS: The results of this study suggest that spinal anesthesia is the most common regional anesthesia technique performed by anesthesia providers working in public hospitals in Botswana followed by few upper limb blocks. However, most public hospitals lack enough training capacity, equipment, and supplies for regional anesthesia. More engagement of the hospital management, investment in regional anesthesia resources, and training are needed in order to improve the regional anesthesia capacity and provide safe surgery and anesthesia in Botswana.
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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 | 0.001 | 0.001 |
| 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 | 0.001 |
| 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".