R/mealtimeStatistics.R

In MRCIEU/GLU: Derives Summary Variables from Continuous Glucose Monitoring (CGM) data

# The MIT License (MIT)
# Copyright (c) 2018 Louise AC Millard, MRC Integrative Epidemiology Unit, University of Bristol
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# Derive post-mealtime (postprandial) time-to-peak, and 1hr and 2hr SG levels - the average of the SG readings in the 15 minute period 1 and 2 hrs after each mealtime event, respectively.
# Returns the average of these statistics per day, and across all days overall.
mealtimeStatistics <- function(events, raw) {

        # get rows indexes with meals
	idxMeal = which(events$event == "MEAL")

	meals = data.frame(time=c(), time_to_peak=c(), postprand_1hr=c(), postprand_2hr=c())

	if (length(idxMeal)==0) {
		print("No meals")
		return(methods::new("event", events = meals, meantimetopeak = NA_real_, meanpp1 = NA_real_, meanpp2 = NA_real_))
	}

	if (length(idxMeal)>0) {
	for (i in 1:length(idxMeal)) {

		idxThisMeal = idxMeal[i]

		# time to peak
		tTP = timeToPeak(raw, events$time[idxThisMeal])

		# 1-hr and 2-hr postprandial glucose
		pp1 = postprandial(raw, events$time[idxThisMeal], 1)
                pp2 = postprandial(raw, events$time[idxThisMeal], 2)	

		meal_sum = data.frame(time=events$time[idxThisMeal], time_to_peak=tTP, postprand_1hr=pp1, postprand_2hr=pp2)		
		meals = rbind(meals, meal_sum)

	}
	}

	# average values
	tTPsMean = mean(meals$time_to_peak, na.rm=TRUE)
	pp1sMean = mean(meals$postprand_1hr, na.rm=TRUE)
	pp2sMean = mean(meals$postprand_2hr, na.rm=TRUE)

	events = methods::new("event", events = meals, meantimetopeak = tTPsMean, meanpp1 = pp1sMean, meanpp2 = pp2sMean)

	return(events)

}