Algorithm provides customized caffeine strategy for alertness

Summary: Researchers have developed a web-based caffeine optimization tool that helps determine the ideal dosage and timing for a cup of joe, based on the individual. The aim of the algorithm is to help users maximize the effects of alertness without indulging in excessive caffeine consumption.

Source: American Academy of Sleep Medicine

A web-based caffeine optimization tool successfully designs effective strategies to maximize alertness while avoiding excessive caffeine consumption, according to preliminary results from a new study.

Using multiple sleep-deprivation and shift-work scenarios, the researchers generated caffeine-consumption guidance using the open-access tool 2B-Alert Web 2.0, and then they compared the results with the U.S. Army guidelines. Their analysis found that the solutions suggested by the quantitative caffeine optimization tool either required on average 40% less caffeine or enhanced alertness by an additional 40%.

“Our 2B-Alert Web tool allows an individual, in our case our service members, to optimize the beneficial effects of caffeine while minimizing its consumption,” said principal investigator Jaques Reifman, Ph.D., a Department of the Army Senior Research Scientist for Advanced Medical Technology, serving at the U.S. Army Medical Research and Development Command at Ft. Detrick, Maryland.

According to the authors, caffeine is the most widely consumed stimulant to counter the effects of sleep deprivation on alertness. However, to be safe and most effective, the right amount must be consumed at the right time.

Last year at SLEEP 2018 in Baltimore, Reifman presented data comparing the algorithm with the caffeine dosing strategies of four previously published experimental studies of sleep loss. The current study extended his team’s previous work by incorporating the automated caffeine-guidance algorithm in an open-access tool so that users can input several factors: the desirable peak-alertness periods within a sleep/wake schedule, the minimum desirable level of alertness, and the maximum tolerable daily caffeine intake.

With this added capability, the 2B-Alert Web 2.0 tool now allows users to predict the alertness of an “average” individual as a function of his or her sleep/wake schedule and caffeine schedule. It also enables users to automatically obtain optimal caffeine timing and doses to achieve peak alertness at the desired times.

This shows a cup of coffee

According to the authors, caffeine is the most widely consumed stimulant to counter the effects of sleep deprivation on alertness. However, to be safe and most effective, the right amount must be consumed at the right time. The image is in the public domain.

This freely available tool will have practical applications that extend beyond the realms of the military and the research lab, noted Reifman.

“For example, if you pull an all-nighter, need to be at peak alertness between, say, 9 a.m. and 5 p.m., and desire to consume as little caffeine as possible, when and how much caffeine should you consume?” he said. “This is the type of question 2B-Alert was designed to answer.”

The research abstract was published recently in an online supplement of the journal Sleep and will be presented Wednesday, June 12, in San Antonio at SLEEP 2019, the 33rd annual meeting of the Associated Professional Sleep Societies LLC (APSS), which is a joint venture of the American Academy of Sleep Medicine and the Sleep Research Society.

Funding: This work was sponsored by the Military Operational Medicine Program Area Directorate of the U.S. Army Medical Research and Development Command, Ft. Detrick, Maryland.

Note: The findings will be presented at the SLEEP 2019: Associated Professional Sleep Societies Annual Meeting in San Antonio, Texas.

About this neuroscience research article

Source:
American Academy of Sleep Medicine
Media Contacts:
Corinne Lederhouse – American Academy of Sleep Medicine
Image Source:
The image is in the public domain.

Original Research: Closed access
“2B-Alert Web 2.0: An Open-access Tool to Determine Caffeine Doses That Optimize Alertness”. Kamal Kumar, Francisco Vital-Lopez, Sridhar Ramakrishnan, Tracy J Doty, Thomas J Balkin, Jaques Reifman.
Sleep. doi:10.1093/sleep/zsz067.323

Abstract

2B-Alert Web 2.0: An Open-access Tool to Determine Caffeine Doses That Optimize Alertness

Introduction
Caffeine is the most widely consumed stimulant to counter the effects of sleep deprivation on alertness. However, to be safe and most effective, the right amount must be consumed at the right time. Recently, we developed an algorithm that automatically provides guidance for optimal caffeine consumption to safely maximize alertness at the desired time of the day. However, to be useful to the research and schedule-planner communities, we made this capability freely available through a Web server, where users can compare and contrast the effects of different sleep/wake and caffeine schedules on alertness.

Methods
We extended our previously developed open-access Web tool, 2B-Alert Web, by incorporating the automated caffeine-guidance algorithm. Specifically, in this version, we allow users to input 1) desirable peak-alertness periods within a sleep/wake schedule, 2) the minimum desirable level of alertness, and 3) the maximum tolerable daily caffeine intake (≤ 1500 mg). The tool then provides the optimal caffeine doses (timing and amount) to achieve peak alertness levels at the desired times, while meeting user-defined constraints. It also displays the corresponding psychomotor vigilance test alertness predictions, which together with the caffeine guidance, can be exported to a spreadsheet.

Results
When we compared the 2B-Alert Web 2.0 caffeine-consumption guidance for multiple sleep-deprivation and shift-work scenarios with the U.S. Army guidelines, we observed an average improvement of 40%. The tool suggested solutions that either required 40% less caffeine or that enhanced alertness by an additional 40%.

Conclusion
With this added capability, the 2B-Alert Web 2.0 now allows users to 1) predict the alertness of an “average” individual as a function of sleep/wake and caffeine schedules and 2) automatically obtain optimal caffeine doses (timing and amount) to achieve peak alertness at the desired times. As such, it provides the first quantitative caffeine optimization tool for designing effective strategies to maximize alertness, while avoiding excessive caffeine consumption.

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