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Record W2804508505 · doi:10.1093/ndt/gfy104.fp671

FP671FRAILTY, COMORBIDITY INDEXES AND THE ANNUAL FREQUENCY OF VISITS TO HOSPITAL EMERGENCY SERVICE IN PATIENTS ON HEMODIALYSIS

2018· article· en· W2804508505 on OpenAlexaboutno aff
César García-Cantón, Ana Rodenas-Galvez, Celia Lopez-Aperador, Yaiza Rivero, Tania Monzón, Gloria Antón, Fátima Batista, I. Auyanet, Germán Calle Pérez, Noemí Esparza

Bibliographic record

VenueNephrology Dialysis Transplantation · 2018
Typearticle
Languageen
FieldMedicine
TopicEmergency and Acute Care Studies
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineComorbidityHemodialysisEmergency medicineMedical emergencyIntensive care medicineService (business)Internal medicine

Abstract

fetched live from OpenAlex

INTRODUCTION AND AIMS: Frailty has been defined as a syndrome or a state of increased vulnerability resulting from a decline in biological functional reserves, such that the ability to cope with stressors is compromised, and leading to higher risk of poor health outcomes, disability, hospitalization and death. Our objective was to relate frailty, as measured by the Fried Phenotype Frail Index (FPFI) and the Edmonton Frail Scale (EFS), and the Charlson comorbidity index (CCI) with the annual frequency of visits to hospital emergency service in a cohort of hemodialysis patients. METHODS: To that end, frailty, according to the FPFI and EFS and CCI were measured and the number of visits to the hospital emergency service for any cause was recorded for the hemodialysis prevalent patients managed in our sanitary area. the study included 375 hemodialysis patients, 61.5% of them were men, 57.5% suffered from diabetes mellitus, their median age was 65 years and the mean time in hemodialysis was 50.4 (3-318) months. The mean follow-up time was 10.84 months; 215 patients completed the 12.month follow-up; 42 patients died before completing it, 16 received kidney transplantation and 2 were transfered. RESULTS: The proportion of frail patients was 41.1% as measured with the FPFI and 29.5% as measured with the EFS; 65% of patients presented CCI higher than 5, which is high or very high. During the follow-up period, 507 visits to the emergency services were recorded. According to the FPFI, the annual rate of visits to the emergency services was 1.61±2.7 for non-frail patients and 3.28±4.2 for frail ones (P<0.001). Also according to the FPFI, 45.6% of non-frail and 22.1% of frail patients did not visit the emergency services during a year. According to the EFS, the annual rate of visits to the emergency services was 1.70±2.8 for non-frail patients and 3.72±4.5 for frail ones (P<0.001). Also according to the FPFI, 45.3% of non-frail and 13.5% of frail patients did not visit the emergency services during a year. The annual rate of visits to the emergency services was 1.87±3.3 for patients with CCI equal to or lower than 5 and 2.53±3.6 for those with CCI higher than 5 (P<0.05); 44.7% of patients with CCI≤5 and 31.4% of those with CCI>5 did not visit the emergency services during a year (n.s.). CONCLUSIONS: In conclusion, the frequency of visits to the hospital emergency services was significantly higher for hemodialysis patients classified as frail by both indexes. Frailty indexes seemed to be better predictors of higher frequency of visits to the emergency services than the Charlson comorbidity index.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.008
GPT teacher head0.259
Teacher spread0.250 · 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 source (direct Gemma or distilled Codex), 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".

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Citations0
Published2018
Admission routes1
Has abstractyes

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