Benefits of fracture liaison services (FLS) in four Latin American countries: Brazil, Mexico, Colombia, and Argentina
Bibliographic record
Abstract
AIMS: Fracture liaison services (FLS) use a multidisciplinary approach to treat patients who have experienced an osteoporotic fracture to reduce the risk of subsequent fractures. To date, there has been minimal FLS implementation in Latin America where fractures continue to be undertreated. This study aims to estimate the number of fractures averted, bed days avoided, and costs saved resulting from universal FLS implementation in Brazil, Mexico, Colombia, and Argentina. MATERIALS AND METHODS: A calculator was developed to estimate the annual benefits of FLS programs in Brazil, Mexico, Colombia, and Argentina from a public hospital perspective. It was assumed all patients with a hip, vertebral, or wrist fracture were referred to an FLS program. Country-specific data were obtained from a previous systematic review and interviews with osteoporosis experts. Hospitalization and post-hospitalization costs were expressed in 2019 USD without discounting. Costs of FLS implementation were not considered. RESULTS: In 2019, the number of FLS patients prevented from having a subsequent hip, vertebral, or wrist fracture was estimated as 15,607 in Brazil, 8,168 in Mexico, 5,190 in Argentina, and 2,435 in Colombia with total bed days saved of 142,378 in Brazil, 75,877 in Mexico, 52,301 in Argentina, and 21,725 in Colombia. The annual cost savings in 2019 were highest in Argentina (28.1 million USD), followed by Mexico (19.6 million USD), Brazil (7.64 million USD) and Colombia (3.04 million USD). Over five years (2019-2023) the cumulative cost savings were 145 million USD in Argentina, 106 million USD in Mexico, 40.5 million USD in Brazil, and 16.1 million USD in Colombia. CONCLUSION: Universal FLS implementation in Brazil, Mexico, Colombia, and Argentina was predicted to prevent 31,400 fractures, avoid 292,281 bed days, and save 58.4 million USD in 2019, though caution is warranted in the interpretation of these results due to high uncertainty. Increased implementation of FLS programs in Latin American countries may help to realize these benefits.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".