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Record W4405402788 · doi:10.1002/ajim.23685

Prevalence of Mild and Severe Cognitive Impairment in World Trade Center Exposed Fire Department of the City of New York (FDNY) and General Emergency Responders

2024· article· en· W4405402788 on OpenAlexaboutno aff
Frank D. Mann, Alexandra K. Mueller, Rachel Zeig‐Owens, Jaeun Choi, David J. Prezant, Melissa A. Carr, Alicia M. Fels, Christina M. Hennington, Megan Armstrong, Alissa Barber, Ashley Fontana, Cassandra H. Kroll, Kevin Chow, Onix A. Melendez, Abigail J. Smith, Christopher Christodoulou, Benjamin J. Luft, Charles B. Hall, Sean Clouston

Bibliographic record

VenueAmerican Journal of Industrial Medicine · 2024
Typearticle
Languageen
FieldHealth Professions
TopicOccupational Health and Performance
Canadian institutionsnot available
FundersNational Institute for Occupational Safety and HealthNational Institute on AgingCenters for Disease Control and PreventionNational Center for Advancing Translational SciencesState University of New York
KeywordsMedicineMontreal Cognitive AssessmentCohortEmergency departmentCognitive impairmentCognitionCohort studyDemographyGerontologyEmergency medicineInternal medicinePsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND: The emergency personnel who responded to the World Trade Center (WTC) attacks endured severe occupational exposures, yet the prevalence of cognitive impairment remains unknown among WTC-exposed-FDNY-responders. The present study screened for mild and severe cognitive impairment in WTC-exposed FDNY responders using objective tests, compared prevalence rates to a cohort of non-FDNY WTC-exposed responders, and descriptively to meta-analytic estimates of MCI from global, community, and clinical populations. METHODS: A sample of WTC-exposed-FDNY responders (n = 343) was recruited to complete an extensive battery of cognitive, psychological, and physical tests. The prevalences of domain-specific impairments were estimated based on the results of norm-referenced tests, and the Montreal Cognitive Assessment (MoCA), Jak/Bondi criteria, Petersen criteria, and the National Institute on Aging and Alzheimer's Association (NIA-AA) criteria were used to diagnose MCI. NIA-AA criteria were also used to diagnose severe cognitive impairment. Generalized linear models and propensity score matching were used to compare prevalence estimates of cognitive impairment to a large sample of WTC-exposed-non-FDNY responders from the General Responder Cohort (GRC; n = 7102) who completed the MoCA during a similar time frame. RESULT: Among FDNY responders under 65 years, the unadjusted prevalence of MCI varied from 52.57% to 60.32% depending on the operational definition of MCI, apart from using a conservative cut-off applied to MoCA total scores (18 < MoCA < 23), which yielded a markedly lower crude prevalence (24.31%) compared to alternative criteria. Using propensity score matching, the prevalence of MCI was significantly higher among WTC-exposed FDNY responders, compared to WTC-exposed GRC responders (adjusted RR = 1.13 (CI 95% = 1.07-1.20, p < 0.001), and descriptively higher than meta-analytic estimates from different global, community, and clinical populations. Following NIA-AA diagnostic guidelines, 4.96% of WTC-exposed-FDNY-responders met the criteria for severe impairments (95% CI = 2.91-7.82), a prevalence that remained largely unchanged after excluding responders over the age of 65 years. DISCUSSION: There is a high prevalence of mild and severe cognitive impairment among WTC-responders, highlighting the putative role of occupational, environmental, and disaster-related exposures in the etiology of accelerated cognitive decline.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.037
Threshold uncertainty score0.263

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.128
GPT teacher head0.413
Teacher spread0.285 · 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

Citations6
Published2024
Admission routes1
Has abstractyes

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