Diagnose All Patients

Applies all available diagnostic algorithms for probable Parkinson’s disease dementia (PDD) across the full dataset. The set of criteria is generated internally via the specify_algorithms function. Each patient is assessed using each specification, and the corresponding diagnoses and supporting information are recorded.

Usage

diagnose_pdd_sample(d0)

Arguments

d0

A tibble containing the dataset prepared using prepare_data.

Value

A list with two tibbles:

algorithms

A tibble containing the full specification of all algorithms used.

diagnoses

A tibble containing:

• Patient ID

• Criterion label (linked to the specification)

• PDD diagnosis (TRUE/FALSE)

• Individual diagnostic flags corresponding to Table 2 in Dubois et al. (2007)

• Impairment labels across cognitive domains (per Level I criteria)

References

Dubois, B., Burn, D., Goetz, C., Aarsland, D., Brown, R. G., Broe, G. A., ... & Emre, M. (2007). Diagnostic procedures for Parkinson's disease dementia: recommendations from the movement disorder society task force. Movement disorders, 22(16), 2314-2324. doi:10.1002/mds.21844

See also

• prepare_data() prepares d0.

• specify_algorithms() runs internally to prepare a set of algorithms to be used.

• diagnose_pdd_case() runs internally to diagnose patients using a single algorithm.

Examples

if (FALSE) { # \dontrun{
p <- data_paths("data-raw")
data <- prepare_data(p)
pdd  <- diagnose_pdd_sample(data)
} # }