Can the prediction model using regression with optimal scale improve the power to predict the Parkinson's dementia?

Table 1 Measurement of variables

Factors	Measurement	Characteristics
Demographic factors	Sex	Male or female
	Age	60-74, 75+
	Mainly used hand	Left hand or right hand
	Education level	Middle school graduate and below or high school graduate and above
Family history of the disease	Parkinson's disease; Alzheimer's disease	Yes or no; Yes or no
Health behaviors	Pack-years (smoking)	Non-smoking, 1-20, 21-40, 41-60, or ≥ 61 pack-years
	Coffee-drinking	Yes or no
	Mean coffee intake per day (cups/d)	No, ≤ 1, 2-3, or ≥ 4 cups
	Coffee drinking period (yr)	No, ≤ 5, 6-9, or ≥ 10
Disease history	Carbon monoxide poisoning	Yes or no
	Diabetes	Yes or no
	Alcoholism	Yes or no
	Hyperlipidemia	Yes or no
	Traumatic brain injury	Yes or no
	Hypertension	Yes or no
Exercise characteristics related to Parkinson's disease relatedmotor signs	Tremor	Yes or no
	Rigidity	Yes or no
	Akinesia/bradykinesia	Yes or no
	Postural instability	Yes or no
	Late motor complications	Yes or no
Neuropsychological test	K-MoCA	Continuous variable
	K-MMSE	Continuous variable
	Global CDR score	Continuous variable
	Sum of boxes in CDR	Continuous variable
	Hoehn and Yahr staging	Continuous variable
	UPDRS (Total UPDRS score)	Continuous variable
	UPDRS (Motor UPDRS score)	Continuous variable
	K-IADL	Continuous variable
	Schwab and England ADL	Continuous variable

K-MoCA: Korean version of montreal cognitive assessment; K-MMSE: Korean version of mini mental state examination; CDR: Clinical dementia rating; UPDRS: Untitled parkinson disease rating; K-IADL: Korean version of instrumental activities of daily living; Schwab and England ADL: Schwab and England avtivities of daily living scale.