# Pediatric Chronic Headache and COVID-19: Use of Machine Learning and Biobehavioral Analysis to Classify Headache Mechanism and Optimize Treatment Course.

> **NIH NIH R01** · BOSTON CHILDREN'S HOSPITAL · 2024 · $523,414

## Abstract

Chronic pain experienced by children has the potential to persist into adulthood and drive drug
addiction, mental health problems and suicidal behavior. The level of pain reported by children
who experience headache is immense and likely poorly estimated based on lowered ability of
children to articulate symptoms, potential malingering or underreporting of pain symptoms, and
extensive variability in physical growth and brain development. Headache is a frequently reported
and poorly understood primary and secondary disorder in pediatric subjects. The diverse
presentation of headache underscores the potential for distinct mechanisms of headache
presentation, thus placing emphasis on tailored treatment options. There is clear need to better
define childhood headache in terms of the clinical presentation and underlying pain physiology.
Our hypothesis is that each clinical headache disorder can be defined by unique biobehavioral
characteristics. In the proposed research program, we (Aim 1) evaluate the clinical and behavioral
elements of each headache disorder and pain modulation, (Aim 2) the biobehavioral signature of
treatment refractory headache, and (Aim 3) develop machine learning classifiers to understand
the features that differentiate headache subtype and treatment resistance. This study is likely to
yield highly relevant information that will contribute towards identifying and treating headache
disorders in children, identifying unique characteristics of headache and pain processing, and (3)
outline biobehavioral targets for different headache disorders. Data from this investigation is likely
to contribute greatly towards the treatment of pediatric pain disorders.

## Key facts

- **NIH application ID:** 10851768
- **Project number:** 5R01NS125265-03
- **Recipient organization:** BOSTON CHILDREN'S HOSPITAL
- **Principal Investigator:** Scott Holmes
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $523,414
- **Award type:** 5
- **Project period:** 2022-08-18 → 2027-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10851768

## Citation

> US National Institutes of Health, RePORTER application 10851768, Pediatric Chronic Headache and COVID-19: Use of Machine Learning and Biobehavioral Analysis to Classify Headache Mechanism and Optimize Treatment Course. (5R01NS125265-03). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10851768. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*