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Record W7120692291

Evaluation of pain and its care process after traumatic brain injury (TBI)

2017· dissertation· pt· W7120692291 on OpenAlexaboutno aff
Tássia Lima Bomfim

Bibliographic record

VenueLA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas) · 2017
Typedissertation
Languagept
FieldMedicine
TopicTraumatic Brain Injury Research
Canadian institutionsnot available
Fundersnot available
KeywordsMcGill Pain QuestionnaireMedical recordHead injuryTraumatic brain injuryTest (biology)Pain assessmentData collectionEmergency departmentHuman factors and ergonomics
DOInot available

Abstract

fetched live from OpenAlex

Pain is a frequent symptom following Traumatic Brain Injury (TBI) and its experience should be better explored in the field of neuroscience. The aim of the study was to evaluate pain and their care process in adult patients after TBI. A cross-sectional quantitative research developed at the outpatient clinic of the Federal University of Sergipe (UFS) and emergency room of the Emergency Hospital of Sergipe (HUSE), after approval of the ethics committee.Data collection was carried out from August 2016 to May 2017, through interviews with the application form of the evaluation of pain were based on the functional health standards of Marjory Gordon, adapted by Pimenta and Cruz, which includes the McGill pain assessment questionnaire and Scales of verbal and numerical category, besides the analysis of the medical records of 40 patients with TBI. To evaluate the association between ordinal and nominal variables, the Rank-Bisserial correlation (Rrb) we used. The binomial test was applied to assess whether the proportion of cases that CTE pain affected Gordon's functional health standards. The significance level adopted was 5% and the software used was the R Core Team 2017. The results indicated that the patients were mostly young men who suffered TBI with hematoma due to the motorcycle accident and did not use equipments for individual protection.All patients evaluated with had pain ranging from moderate to unbearable or from moderate to severe on the verbal and numerical categories scales respectively. The most painful site in the body diagram was the head region. The descriptors of the most representative McGill questionnaire were the pain characterized as "Sickening", "Throbbing" and "Jumping". There was a shortage of record of the painful complaint in the medical record in the hospital, in contrast there was record of the pain in the totality of the medical records of the outpatient clinic. Most of patients with aggression, falls or other types of occurrence reported moderate pain, while victims of transport accidents presented severe or unbearable pain. Although, all patients had referred feeling pain, and daily life activities were not harmed. It is concluded that pain is a frequent symptom in the patient after the TBI, especially the headache and needs the evaluation of the health team, in order to provide a humanized and qualified care.

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)0.001
metaresearch head score (Gemma)0.004
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 score0.001
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
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 head0.059
GPT teacher head0.345
Teacher spread0.286 · 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
Published2017
Admission routes1
Has abstractyes

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