Massage Therapy May be Safe and Reduce Pain in Critically Ill Patients with Acute Neurological Injury: a Case Control Study
Bibliographic record
Abstract
Purpose: Massage therapy is an important adjunctive treatment for physiologic and psychologic symptoms and has been shown to benefit patients among a wide variety of patient populations. Setting: Few studies have investigated the utility of massage therapy in the general ICU setting, and even fewer have done so in the neurological ICU (NeuroICU). Research Design: If massage therapy was determined to improve objective outcomes-or even subjective outcomes in the absence of harm-massage may be more readily employed as a complementary therapy, particularly in the ICU setting or in patients with acute neurological injury. Intervention: This pilot study aimed to assess the safety of massage in the neurocritical care unit and its impact on patient vital signs, subjective pain assessment, and other clinical outcomes. Participants: Twenty-one patients who received massage therapy during admission to the neurocritical care service were compared to matched controls in a retrospective case control study design. Results: We found a statistically significant reduction in pain scores among patients with acute neurological injury who received massage therapy. There was no statistical difference in hospital length of stay, discharge destination, in-hospital mortality, adverse events, or incidence/duration of delirium between patients who received massage therapy and those who did not. No adverse events were ascribed to the massage therapy when evaluated by blinded neurocritical care specialists. Conclusion: This study found that massage therapy may be safe for many patients in the NeuroICU and may offer additional subjective benefits.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
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".