Predicts recovery time, identifies compensatory muscles, and estimates
secondary injury risk based on MSK network impact analysis.
Usage
mskClinicalPredictor(injury_muscles, hg = NULL, sim = NULL, verbose = TRUE)
Arguments
- injury_muscles
Character or integer vector identifying injured muscles.
- hg
An MSKHypergraph object (NULL loads default 173-bone/270-muscle network).
- sim
An MSKSimulation object (NULL creates one with default parameters).
- verbose
Logical, print progress messages (default: TRUE).
Value
An S3 object of class "MSKClinicalPrediction" with:
- recovery
Data frame with predicted recovery weeks and CI per muscle
- compensatory
List of compensatory muscles per injured muscle
- secondary_risk
Data frame of secondary injury risk scores
- injury_muscles
Resolved muscle names
- injury_indices
Resolved integer indices
Clinical Validity
The recovery model was validated on 14 aggregate muscle groups, not individual
muscles. Patient factor adjustments are heuristic, not independently validated.
This is a research exploration tool, not a clinical diagnostic.
References
Murphy AC et al. (2018) PLOS Biology 16(1): e2002811.
Examples
if (FALSE) { # \dontrun{
pred <- mskClinicalPredictor(c("Biceps Brachii", "Deltoid"))
print(pred)
} # }