Learn R Programming

cliot (version 1.0.0)

mgfa_classification: Myasthenia Gravis Foundation of America (MGFA) Clinical Classification

Description

Determines the MGFA Clinical Classification for patients with Myasthenia Gravis. This system categorizes patients based on the distribution and severity of muscle weakness (ocular vs. generalized) and the specific muscle groups primarily affected (limb/axial vs. oropharyngeal/respiratory).

Usage

mgfa_classification(intubated, ocular_weakness_only, generalized_severity,
                    predominant_symptoms)

Value

A list containing:

MGFA_Class

The determined classification (e.g., Class I, Class IIa, Class IVb, Class V).

Description

The clinical definition of the classification.

Arguments

intubated

Numeric (0 or 1). Is the patient currently intubated (excluding routine postoperative management)? (1 = Yes). This defines Class V.

ocular_weakness_only

Numeric (0 or 1). Is weakness restricted ONLY to ocular muscles (including eye closure)? (1 = Yes). This defines Class I.

generalized_severity

String. Severity of weakness affecting non-ocular muscles. Options: "mild" (Class II), "moderate" (Class III), "severe" (Class IV). Required if ocular_weakness_only is 0.

predominant_symptoms

String. The muscle groups primarily affected. "limb_axial": Predominantly limb and/or axial muscles (Subtype a). "oropharyngeal_respiratory": Predominantly oropharyngeal and/or respiratory muscles (Subtype b).

References

Jaretzki A 3rd, Barohn RJ, Ernstoff RM, et al. Myasthenia gravis: recommendations for clinical research standards. Task Force of the Medical Scientific Advisory Board of the Myasthenia Gravis Foundation of America. Neurology. 2000;55(1):16-23. doi:10.1212/wnl.55.1.16

Examples

Run this code

# Example 1: Mild Generalized, Limb Predominant
mgfa_classification(0, 0, "mild", "limb_axial")

# Example 2: Severe Bulbar Symptoms
mgfa_classification(0, 0, "severe", "oropharyngeal_respiratory")

# Example 3: Ocular Myasthenia
mgfa_classification(0, 1, "none", "none")

Run the code above in your browser using DataLab