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Record W7132320609

KT indikacijų politraumos atveju ir išgyvenamumo vertinimas

2024· dissertation· en· W7132320609 on OpenAlexaboutno aff
Kristina Jakuseva

Bibliographic record

VenueLithuanian University of Health Sciences · 2024
Typedissertation
Languageen
FieldMedicine
TopicAbdominal Trauma and Injuries
Canadian institutionsnot available
Fundersnot available
KeywordsPolytraumaGuidelineComputed tomographyGold standard (test)CancerMajor trauma
DOInot available

Abstract

fetched live from OpenAlex

Title of the thesis Polytrauma Computed Tomography Indications and Survival Advantage Aim This master thesis aims to assess the indications for the utilization of polytrauma computed tomography (CT) and the repercussions CT might have on trauma patients’ survival advantage. Objectives To determine the patient selection for polytrauma CT; To assess the controversial routine use of whole-body CT (WBCT) in trauma patients; To evaluate the impact of WBCT on the survival of acutely injured patients; To assess the effectiveness of a possible dose reduction of 13% via low-dose multi-phase trauma CT protocols. Research methodology This study assesses the selection of trauma patients for WBCT and the method’s potential impact on the survival advantage for acutely injured patients. Articles published to PubMed and Springer Link were selected using search terms related to the objectives. The included articles were written in English, were published after 2013, and contained information relevant for this study. Scientific literature is cited according to the Vancouver system. Results and their discussion The trauma team leader decides, according to the S3 guideline recommendations, whether a WBCT scan is required. This decision is based on a clinical examination and the severity of the mechanism of action. The mean ED of 16.3 mSv used in WBCT is associated with an estimated cancer risk of ≥1/1,000. However, WBCT also has important benefits, such as being less time-consuming than selective CT (SCT). For this reason, the former method has become the gold standard for the initial diagnosis of polytrauma patients. On the other hand, despite its association with a reduced mortality rate, WBCT also increases multiple organ dysfunction syndrome (MODS), multiple organ failure (MOF), or the time span of mechanical ventilation due to prolonged survival, intensive care management, and trauma-related complications. Furthermore, a low-dose multi-phase CT protocol enhances the diagnostic precision and image quality at a markedly reduced radiation dose of 13%. Conclusions 1. The S3 guideline first guarantees the quality and consistency of patient selection. The trauma team leader bases their decisions on the severity of the mechanism of action and a clinical assessment. 2. The predicted cancer risk is mitigated by a substantially quicker and potentially life-saving WBCT-assisted diagnosis. 3. WBCT has the drawbacks of MODS, MOF, and an extended period of mechanical ventilation even if it lowers the overall mortality rate in patients who are hemodynamically stable and unstable. 4. The use of CT techniques reduces radiation exposure while greatly improving diagnostic accuracy and image quality.

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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.039
Threshold uncertainty score0.132

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0040.001
Open science0.0000.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0390.007

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 head0.030
GPT teacher head0.323
Teacher spread0.293 · 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
Published2024
Admission routes1
Has abstractyes

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