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Pneumonia is the Leading Cause of Death from Respiratory Diseases at High Altitude In La Paz, Bolivia

2024· article· en· W4391917280 on OpenAlexfundno aff
Gonzales Marcelino, Casto Navia, Carlos Tamayo, Martin Villarroel, Aïda Bairam, Lida Sanchez, Christian Arias‐Reyes, Jorge Soliz

Bibliographic record

VenueInternational Journal of Innovative Research in Medical Science · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicHigh Altitude and Hypoxia
Canadian institutionsnot available
FundersCanadian Institutes of Health Research
KeywordsPneumoniaRespiratory systemAltitude (triangle)MedicineIntensive care medicineCause of deathInternal medicineMathematicsDisease

Abstract

fetched live from OpenAlex

Chronic obstructive pulmonary disease (COPD) and asthma are major contributors to mortality resulting from respiratory diseases among sea-level populations. In high altitude environments, located between 2500 and 3600 meters, where oxygen availability decreases (hypoxia), pulmonary edema has been identified as the main cause of mortality among transient visitors to such high regions. However, despite the existence of physiological adaptations among permanent residents of high altitudes (characterized by increased ventilation, increased red blood cell counts, vasodilation, and an increased muscle contraction pump), extensive research on fatal respiratory diseases that prevalence in this demographic remains low. In this research effort, we analyzed 1,214 mortality records from 2017 in La Paz, Bolivia (located at 3,600 meters). Our results indicate that pneumonia is the leading cause of death in these high-altitude Bolivian cities. This is in stark contrast to pneumonia's position as the fourth leading cause of death at sea level, accentuating the distinctive health challenges faced by populations residing at high altitudes.

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 imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.522
Threshold uncertainty score0.388

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.063
GPT teacher head0.446
Teacher spread0.383 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2024
Admission routes1
Has abstractyes

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