A narrative review of protocols for the management of respiratory illness on short-term medical missions (STMMs) in Latin America and the Caribbean
Bibliographic record
Abstract
# Background Respiratory illnesses are prevalent on short-term medical missions (STMMs) in Latin America and the Caribbean, and commonly include upper respiratory infections, asthma, and allergic rhinitis. There have been no previous attempts to describe protocols that international volunteer clinicians use in managing these patients. The purpose of this study was to collect North American clinical protocols used by sending organizations in their volunteer operations in Latin America and the Caribbean, summarize the most common pharmacologic and non-pharmacologic management strategies, and compare these to published international practice recommendations. # Methods A systematic web search was used to identify North American medical service trip sending organizations. Clinical protocols were downloaded from their websites, and organizations were directed contacted to request protocols that were not published online. The protocols obtained were summarized, analyzed thematically, and compared to existing international guidelines. # Results Of 225 organizations contacted, 112 (49.8%) responded, and 31 of these (27.7%) claimed to possess protocols for their trips, of which 20 were obtained and analyzed. Four (20%) protocols discussed asthma, six (30%) discussed upper respiratory infections, and three (15%) discussed lower respiratory infections. The protocols discussed clinical assessment, pharmacologic and non-pharmacologic management with variable degrees of accuracy and thoroughness, and with important omissions when compared to international guidelines. None were the product of systematic literature searches, and most were not referenced. # Conclusions To avoid ineffective treatment and related harms, context-specific clinical guidelines are needed for volunteer clinicians practicing in remote international settings, and such guidelines should be based on best evidence and stakeholder consensus.
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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 | 0.042 | 0.188 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.016 | 0.017 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".