105 - Malaria / Ecstasy for PTSD / Statin Overprescription
Bibliographic record
Abstract
What does the body of evidence say on malaria? Your favourite travel destination may be a malaria hot zone: we discuss how to prepare. Plus: a strange FDA application to use MDMA to treat PTSD, and have statins been overprescribed? A Block: Malaria(0:58) History; the parasite's life cycle; how many people are affected by malaria; symptoms; how to diagnose it; how to treat it; prevention.B Block: Ecstasy for PTSD(35:46) An advisory committee for the FDA has raised many concerns about a company's application to use MDMA (ecstasy, molly) as part of psychotherapy for post-traumatic stress disorder.C Block: Statin Overprescription(46:08) A new risk calculator is classifying fewer people as needing statins.* Theme music: \"Fall of the Ocean Queen\" by Joseph Hackl* Assistant researcher: Aigul ZaripovaTo contribute to The Body of Evidence, go to our Patreon page at: http://www.patreon.com/thebodyofevidence/.To make a one-time donation to our show, you can now use PayPal! https://www.paypal.com/donate?hosted_button_id=9QZET78JZWCZEPatrons get a bonus show on Patreon called \"Digressions\"! Check it out!Chris' book, Does Coffee Cause Cancer?: https://ecwpress.com/products/does-coffee-cause-cancer References:1) WHO fact sheet on malaria: https://www.who.int/news-room/fact-sheets/detail/malariaHistory of malaria:2) https://doi.org/10.3390/ijerph70206753) https://doi.org/10.1007/s11230-004-6354-64) DOI: 10.1111/j.1365-2141.2008.07085.x5) https://doi.org/10.1179/1351000032250029526) https://doi.org/10.1038/hdy.2011.167) doi: 10.1038/s41598-018-19554-0 8) https://www.ncbi.nlm.nih.gov/books/NBK215638/ 9) Plasmodium parasite life cycle: https://www.cdc.gov/dpdx/malaria/index.html Malaria epidemiology:10) https://www.canada.ca/en/public-health/services/catmat/canadian-recommendations-prevention-treatment-malaria/chapter-1-introduction.html 11) https://www.who.int/news-room/fact-sheets/detail/malaria 12) https://apps.who.int/malaria/maps/threats/#13) https://www.who.int/publications/i/item/9789240086173 14) DOI: 10.15585/mmwr.mm7236a1 15) https://emergency.cdc.gov/han/2023/han00496.asp 16) https://www.canada.ca/en/public-health/services/catmat/appendix-1-malaria-risk-recommended-chemoprophylaxis-geographic-area.html How to diagnose malaria:17) https://www.cdc.gov/dpdx/resources/pdf/benchAids/malaria/Pfalciparum_benchaidV2.pdf 18) https://www.cdc.gov/dpdx/resources/pdf/benchAids/malaria/Pvivax_benchaidV2.pdf 19) https://www.cdc.gov/dpdx/resources/pdf/benchAids/malaria/Povale_benchaidV2.pdf 20) https://www.cdc.gov/dpdx/resources/pdf/benchAids/malaria/Pmalariae_benchaidV2.pdf How to prevent malaria:21) https://www.who.int/groups/vector-control-advisory-group/summary-of-new-interventions-for-vector-control/lethal-house-lures 22) DOI: 10.1016/S0140-6736(24)00004-723) https://www.bbc.com/news/world-africa-6803700824) DOI: 10.1056/NEJMoa202633025) DOI: 10.1016/S1473-3099(23)00368-726) DOI: https://doi.org/10.1016/S1473-3099(22)00442-X 27) Dr. Andrea Love's article about DEET and insect repellents for Immunologic: https://immunologic.substack.com/p/essential-oils-are-not-chemical-free?publication_id=2109759&post_id=145493032&isFreemail=true&r=5o22t28) Ada McVean's article about insect repellents for the McGill OSS: https://www.mcgill.ca/oss/article/health-technology/why-mosquitos-bite-you-and-how-make-them-stop29) FDA advisers vote against medical use of ecstasy: https://www.science.org/content/article/fda-advisory-panel-rejects-mdma-ptsd-treatment30) Elizabeth Conney's STAT article on new cardiovascular risk calculator for statin prescriptions: https://www.statnews.com/2024/06/10/cardiovascular-disease-statins-aha-guidelines/ It's Not Twitter But It'll Do:1) Jonathan's interview on the Rethinking Wellness podcast: https://rethinkingwellness.substack.com/p/why-you-probably-dont-have-a-leaky
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
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; both teacher heads agree on what is shown here.
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".