Derivation, external and clinical validation of a deep learning approach for detecting intracranial hypertension

Increased intracranial pressure (ICP) ≥15 mmHg is associated with adverse neurological outcomes, but needs invasive intracranial monitoring. Using the publicly available MIMIC-III Waveform Database (2000-2013) from Boston, we developed an artificial intelligence-derived biomarker for elevated ICP (aICP) for adult patients. aICP uses routinely collected extracranial waveform data as input, reducing the need for invasive monitoring. We externally validated aICP with an independent dataset from the Mount Sinai Hospital (2020-2022) in New York City. The AUROC, accuracy, sensitivity, and specificity on the external validation dataset were 0.80 (95% CI, 0.80-0.80), 73.8% (95% CI, 72.0-75.6%), 73.5% (95% CI 72.5-74.5%), and 73.0% (95% CI, 72.0-74.0%), respectively. We also present an exploratory analysis showing aICP predictions are associated with clinical phenotypes. A ten-percentile increment was associated with brain malignancy (OR = 1.68; 95% CI, 1.09-2.60), intracerebral hemorrhage (OR = 1.18; 95% CI, 1.07-1.32), and craniotomy (OR = 1.43; 95% CI, 1.12-1.84; P < 0.05 for all).

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Publication Details

Journal
npj Digital Medicine
Published
2024-09-05
DOI
https://doi.org/10.1038/s41746-024-01227-0
Citations
7
Primary Topic
Traumatic Brain Injury and Neurovascular Disturbances
Type
article
Field-Weighted Citation Impact
2.58

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Derivation, external and clinical validation of a deep learning approach for detecting intracranial hypertension

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7 citations
npj Digital Medicine
Traumatic Brain Injury and Neurovascular Disturbances
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article

Derivation, external and clinical validation of a deep learning approach for detecting intracranial hypertension

Faris F. Gulamali, Alexandra S. Reynolds, Son Q. Duong, Patricia Kovatch, Ashwin Sawant, Jacob Desman, Annette Chang, Akhil Vaid, Girish N. Nadkarni, Brian Y. Soong, Neha Dangayach, Robert Freeman, Ankit Sakhuja, Ira S. Hofer, Alexander W. Charney, Pushkala Jayaraman, Benjamin Fox, Naveen Arivazagan, David S. Reich
article en
7 citations

Abstract

Increased intracranial pressure (ICP) ≥15 mmHg is associated with adverse neurological outcomes, but needs invasive intracranial monitoring. Using the publicly available MIMIC-III Waveform Database (2000-2013) from Boston, we developed an artificial intelligence-derived biomarker for elevated ICP (aICP) for adult patients. aICP uses routinely collected extracranial waveform data as input, reducing the need for invasive monitoring. We externally validated aICP with an independent dataset from the Mount Sinai Hospital (2020-2022) in New York City. The AUROC, accuracy, sensitivity, and specificity on the external validation dataset were 0.80 (95% CI, 0.80-0.80), 73.8% (95% CI, 72.0-75.6%), 73.5% (95% CI 72.5-74.5%), and 73.0% (95% CI, 72.0-74.0%), respectively. We also present an exploratory analysis showing aICP predictions are associated with clinical phenotypes. A ten-percentile increment was associated with brain malignancy (OR = 1.68; 95% CI, 1.09-2.60), intracerebral hemorrhage (OR = 1.18; 95% CI, 1.07-1.32), and craniotomy (OR = 1.43; 95% CI, 1.12-1.84; P < 0.05 for all).

npj Digital MedicineVol. 7(1)
Icahn School of Medicine at Mount Sinai (US)
Georgia Clinical and Translational Science Alliance, National Institutes of Health, National Center for Advancing Translational Sciences
Openalex Percentile: Top 10%
Traumatic Brain Injury and Neurovascular Disturbances
2.58
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