[Pain perception in the vegetative state: current status and critical reflections].
Bibliographic record
Abstract
INTRODUCTION: According to experts, vegetative state (VS) patients are unable to perceive pain. BACKGROUND: Still, a large portion of nurses believe that VS patients can perceive pain and are uncomfortable when pain is not treated. AIM: To identify the criteria used in clinical practice and in research to detect the presence or the absence of conscious perception of pain in VS patients. PROCEDURE: An integrative review exploring MEDLINE, CINAHL and Cochrane's data bank was conducted. RESULTS: A total of 4 clinical articles and 7 empirical studies were included. According to them, patients in VS may exhibit reflexes (ex : closing fists) when exposed to an external stimulation such as a painful stimuli or a verbal command. However, no voluntary reaction such as localisation of the painful stimuli should be observed in VS patients otherwise the diagnosis should be questioned. When exposed to an external stimulation, use of functional neuroimaging techniques (fMRI or PET scan) in VS patients can be used to detect brain activation in the primary cortical areas, the associative cortical areas, and also in the connections between the two. Those techniques may allow the identification of objective signs of consciousness that were not detected at the bedside. DISCUSSION: Assessment of behavioural reactions is complex and greatly subjective in VS patients. The role of the associative areas in the process of pain perception is still poorly understood. CONCLUSION: Because of this incomplete picture of pain perception in VS patients, many experts recommend the prophylactic treatment on pain in this population.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.004 | 0.007 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".