Relationship Between Poor Olfaction and Mortality
Bibliographic record
Abstract
Letters1 October 2019Relationship Between Poor Olfaction and MortalityEsme R. Fuller-Thomson, PhD and Elysia G. Fuller-ThomsonEsme R. Fuller-Thomson, PhDInstitute for Life Course & Aging, University of Toronto, Toronto, Ontario, Canada (E.R.F., E.G.F.)Search for more papers by this author and Elysia G. Fuller-ThomsonInstitute for Life Course & Aging, University of Toronto, Toronto, Ontario, Canada (E.R.F., E.G.F.)Search for more papers by this authorAuthor, Article, and Disclosure Informationhttps://doi.org/10.7326/L19-0467 SectionsAboutFull TextPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinkedInRedditEmail TO THE EDITOR:Liu and colleagues' article (1) indicates that poor olfaction was associated with higher long-term mortality from both neurodegenerative and cardiovascular diseases. We hypothesize that lifetime exposure to airborne lead pollution may be a common underlying cause that is associated with both poor olfaction and mortality from these conditions. We have previously noted (2) that blood lead levels (BLLs) in the late 1970s (before tetraethyl lead additives in gasoline were phased out) were extremely high; at that time, persons in the United States had an average BLL of 13 µg/dL (2). Among U.S. children younger than 6 years, ...References1. Liu B, Luo Z, Pinto JM, et al. Relationship between poor olfaction and mortality among community-dwelling older adults. A cohort study. Ann Intern Med. 2019;170:673-81. [PMID: 31035288]. doi:10.7326/M18-0775 LinkGoogle Scholar2. Fuller-Thomson E. Might lifetime exposure to lead confound the association between hearing impairment and incident dementia? [Letter]. J Gerontol A Biol Sci Med Sci. 2018;73:991-2. [PMID: 29529129] doi:10.1093/gerona/glx238 CrossrefMedlineGoogle Scholar3. Grashow R, Sparrow D, Hu H, et al. Cumulative lead exposure is associated with reduced olfactory recognition performance in elderly men: the Normative Aging Study. Neurotoxicology. 2015;49:158-64. [PMID: 26121922] doi:10.1016/j.neuro.2015.06.006 CrossrefMedlineGoogle Scholar4. Bakulski KM, Rozek LS, Dolinoy DC, et al. Alzheimer's disease and environmental exposure to lead: the epidemiologic evidence and potential role of epigenetics. Curr Alzheimer Res. 2012;9:563-73. [PMID: 22272628] CrossrefMedlineGoogle Scholar5. Lanphear BP, Rauch S, Auinger P, et al. Low-level lead exposure and mortality in US adults: a population-based cohort study. Lancet Public Health. 2018;3:e177-84. [PMID: 29544878] doi:10.1016/S2468-2667(18)30025-2 CrossrefMedlineGoogle Scholar Author, Article, and Disclosure InformationAffiliations: Institute for Life Course & Aging, University of Toronto, Toronto, Ontario, Canada (E.R.F., E.G.F.)Disclosures: Authors have disclosed no conflicts of interest. Forms can be viewed at www.acponline.org/authors/icmje/ConflictOfInterestForms.do?msNum=L19-0467. PreviousarticleNextarticle Advertisement FiguresReferencesRelatedDetailsSee AlsoRelationship Between Poor Olfaction and Mortality Among Community-Dwelling Older Adults Bojing Liu , Zhehui Luo , Jayant M. Pinto , Eric J. Shiroma , Gregory J. Tranah , Karin Wirdefeldt , Fang Fang , Tamara B. Harris , and Honglei Chen Relationship Between Poor Olfaction and Mortality Bojing Liu , Zhehui Luo , and Honglei Chen Metrics Cited byOlfactory loss is a predisposing factor for depression, while olfactory enrichment is an effective treatment for depressionMechanisms Linking Olfactory Impairment and Risk of Mortality 1 October 2019Volume 171, Issue 7Page: 525-526KeywordsCardiovascular diseasesChildrenForecastingHealth surveysMini mental state examinationMortalityNutritionPathology and laboratory medicinePollutionProspective studies ePublished: 1 October 2019 Issue Published: 1 October 2019 Copyright & PermissionsCopyright © 2019 by American College of Physicians. All Rights Reserved.PDF downloadLoading ...
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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 | 0.019 |
| 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 | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.022 | 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; 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".