Benefits of Musculoskeletal Physical Therapy in Emergency Departments: A Systematic Review
Bibliographic record
Abstract
BACKGROUND: Over the past few decades, physical therapists have emerged as key health care providers in emergency departments (EDs), especially for patients with musculoskeletal disorders (MSKD). PURPOSE: The purpose of this review was to update the current evidence regarding physical therapist care for patients with MSKD in EDs and to update current recommendations for these models of care. DATA SOURCES: Systematic searches were conducted in 5 bibliographic databases. STUDY SELECTION: The studies selected presented quantitative data related to the care of patients with MSKD by physical therapists in an ED setting. DATA EXTRACTION: Raters reviewed studies and used the Effective Public Health Practice Project Quality Assessment Tool to assess their methodological quality. DATA SYNTHESIS: Fifteen studies were included. Two studies, 1 of weak and 1 of strong quality, demonstrated that physical therapist care in EDs was as effective as or more effective than usual medical care for pain reduction, and 6 studies of varying quality reported that physical therapist care in EDs was as effective as usual care in EDs in reducing disability. Eight studies of varying quality reported that physical therapist care could significantly reduce waiting time in EDs. Four studies of varying quality reported that physical therapists ordered no more, or even fewer, medical images than physicians. In terms of health care costs, 2 studies of moderate to high quality found no significant differences in costs between physical therapist care and usual care in EDs. Finally, 6 studies of varying quality reported that patients were as satisfied or more satisfied with physical therapist care as with usual medical care in EDs. LIMITATIONS: The roles of physical therapists in EDs vary depending on the setting, legislation, and training of providers. Only a limited number of high-quality studies were identified. CONCLUSIONS: Although the quality of the evidence is heterogeneous, physical therapist care for patients with MSKD in EDs may be beneficial.
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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 | 0.008 | 0.048 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.008 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".