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Record W2280243101 · doi:10.33233/fb.v7i1.1857

Risco de trombose venosa profunda em pacientes traumato–ortopédicos hospitalizados

2018· article· pt· W2280243101 on OpenAlexaff
Luciano Pereira De Oliveira

Bibliographic record

VenueFisioterapia Brasil · 2018
Typearticle
Languagept
FieldMedicine
TopicVenous Thromboembolism Diagnosis and Management
Canadian institutionsCanadian University Music Society
Fundersnot available
KeywordsMedicineGynecology

Abstract

fetched live from OpenAlex

A trombose venosa profunda (TVP) é um transtorno comum em pacientes hospitalizados, principalmente naqueles em fase pós-operatória, restritos ao leito e imobilizados. O objetivo deste estudo foi identificar e classificar o risco para desenvolvimento de TVP nos pacientes internados na enfermaria de traumato-ortopedia do Hospital Estadual Rocha Faria (HERF) - Rio de Janeiro. Foi utilizado o delineamento de estudo epidemiológico descritivo, prospectivo, aleatório, de prevalência, por um perí­odo de quatro meses (maio/2003 a agosto/2003). A coleta de dados baseou-se no protocolo de profilaxia de TVP modificado. A amostra foi composta por 96 pacientes, 53 do sexo feminino e 43 do sexo masculino masculino, com idade variando de 04 a 97 anos; (média de 54,4 ± 24,1; p <0,05). Dos 96 pacientes, 8 (8%) foram classificados no risco baixo, 44 (46%) no risco médio e 44 (46%) no risco alto para desenvolvimento de TVP. Identificou-se alta prevalência (92%) para o risco de desenvolvimento de TVP na amostra estudada.Palavras-chave: trombose venosa profunda, prevalência, pacientes hospitalizados, traumato-ortopedia

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 score0.003
Threshold uncertainty score0.006

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 communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.018
GPT teacher head0.295
Teacher spread0.277 · 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".

Quick stats

Citations0
Published2018
Admission routes1
Has abstractyes

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