Forecasting migraine attacks
Active Project Grant Awarded Last action
- Award ID
- R01NS121233
- Recipient
-
The General Hospital Corporation UEI FLJ7DQKLL226
- Awarding agency
-
National Institute of Neurological Disorders and Stroke
National Institutes of Health, Department of Health and Human Services
- Obligated
- $4,518,840
Award facts
- Assistance listing
- 93.853 Extramural Research Programs in the Neurosciences and Neurological Disorders
- Completion date 94% complete
- Place of performance
- Boston, MA 02114, USA
Award details come from USAspending.gov.
Description
- Abstract
- For the millions of individuals who experience migraine each year, treatment typically consists of reactively treating attacks only after experiencing disruptive pain and secondary symptoms. Because individual migraine attacks are unpredictable to most sufferers, abortive medications are not used early or effectively, and strategies to preemptively stop developing attacks cannot be formulated. By formalizing the daily risk for an attack, individuals will be better prepared to use existing abortive therapies and reduce the suffering associated with any single attack. Our team has previously built and tested the headache prediction-i (hapred-i) and headache prediction-II (hapred-II) models, which are simple migraine forecasting models that are based on daily stress. Despite their promise, these models exhibit several weaknesses that would prevent them from broad clinical use. The objective of this project is to evaluate a new forecasting model that has improved predictive power. To accomplish this, several important predictors have been added to the existing model, and the parameters of the new model will be continuously updated using bayesian estimation. In the new hapred-III model (aim 1), the forecasting window is reduced from 24 to 12 hours, temporal statistical predictors have been added, and additional predictors (e.g., sleep, mood, medication use, prodromal symptoms, and self-prediction) will be tested for improved performance. To allow the model to be more easily deployed (aim 2), predictors of the model parameters will be examined. These predictors will better inform the prior probabilities of the model parameters and will reduce the need to collect weeks or months of data from each individual before generating reliable forecasts.
Transactions
| Action | Obligated | Date |
|---|---|---|
| Amendment | $419,238 | |
| Amendment | $375,325 | |
| Amendment | $29,347 | |
| Amendment | $29,347 | |
| Amendment | $377,315 | |
| Amendment | $377,315 | |
| Amendment | $377,315 | |
| Amendment | $422,001 | |
| Amendment | $422,001 | |
| Amendment | $422,001 | |
| Amendment | $422,001 | |
| Amendment | $422,817 | |
| Original award | $422,817 |
Show all 13
Subawards
| Subrecipient | Amount | Awarded |
|---|---|---|
| Nex7 LLC | $639,450 |
Quick answers
Who received award R01NS121233?
R01NS121233 was awarded to The General Hospital Corporation by National Institute of Neurological Disorders and Stroke (National Institutes of Health) on February 1, 2022.
How much is award R01NS121233 worth?
$4,518,840 has been obligated on R01NS121233.
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