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Record W2127996177 · doi:10.1016/j.jegh.2015.01.003

Fall-related injuries in a low-income setting: Results from a pilot injury surveillance system in Rawalpindi, Pakistan

2015· article· en· W2127996177 on OpenAlexaff
Junaid A. Bhatti, Umar Farooq, Mudassir Majeed, Jahangir Sarwar Khan, Junaid Razzak, Muhammad Mussadiq Khan

Bibliographic record

VenueJournal of Epidemiology and Global Health · 2015
Typearticle
Languageen
FieldMedicine
TopicInjury Epidemiology and Prevention
Canadian institutionsHealth Sciences CentreUniversity of TorontoInstitute for Clinical Evaluative SciencesSunnybrook Health Science Centre
Fundersnot available
KeywordsMedicineInjury preventionOdds ratioPsychological interventionPoison controlOccupational safety and healthEmergency departmentInjury surveillanceFall preventionSuicide preventionPediatricsEmergency medicineDemographyInternal medicine

Abstract

fetched live from OpenAlex

This study assessed the characteristics and emergency care outcomes of fall-related injuries in Pakistan. This study included all fall-related injury cases presenting to emergency departments (EDs) of the three teaching hospitals in Rawalpindi city from July 2007 to June 2008. Out of 62,530 injury cases, 43.4% (N=27,109) were due to falls. Children (0-15 years) accounted for about two out of five of all fall-related injuries. Compared with women aged 16-45 years, more men of the same age group presented with fall-related injuries (50% vs. 42%); however, compared with men aged 45 years or more, about twice as many women of the same age group presented with fall-related injuries (16% vs. 9%, P<0.001). For each reported death due to falls (n=57), 43 more were admitted (n=2443, 9%), and another 423 were discharged from the EDs (n=24,142, 91%). Factors associated with death or inpatient admission were: aged 0-15 years (adjusted odds ratio [aOR]=1.35), aged 45 years or more (aOR=1.94), male gender (aOR=1.15), falls occurring at home (aOR=3.38), in markets (aOR=1.43), on work sites (aOR=4.80), and during playing activities (aOR=1.68). This ED-based surveillance study indicated that fall prevention interventions in Pakistan should target children, older adult women, homes, and work sites.

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)0.031
metaresearch head score (Gemma)0.008
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.023
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0310.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
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 head0.036
GPT teacher head0.402
Teacher spread0.366 · 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.

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
Published2015
Admission routes1
Has abstractyes

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