Derivation, External Validation and Clinical Implications of a deep learning approach for intracranial pressure estimation using non-cranial waveform measurements

Author:

Gulamali Faris,Jayaraman PushkalaORCID,Sawant Ashwin S.ORCID,Desman Jacob,Fox Benjamin,Chang Annie,Soong Brian Y.,Arivazaghan Naveen,Reynolds Alexandra S.,Duong Son Q,Vaid Akhil,Kovatch Patricia,Freeman Robert,Hofer Ira S.,Sakhuja Ankit,Dangayach Neha S.,Reich David S.,Charney Alexander WORCID,Nadkarni Girish N.

Abstract

AbstractImportanceIncreased intracranial pressure (ICP) is associated with adverse neurological outcomes, but needs invasive monitoring.ObjectiveDevelopment and validation of an AI approach for detecting increased ICP (aICP) using only non-invasive extracranial physiological waveform data.DesignRetrospective diagnostic study of AI-assisted detection of increased ICP. We developed an AI model using exclusively extracranial waveforms, externally validated it and assessed associations with clinical outcomes.SettingMIMIC-III Waveform Database (2000-2013), a database derived from patients admitted to an ICU in an academic Boston hospital, was used for development of the aICP model, and to report association with neurologic outcomes. Data from Mount Sinai Hospital (2020-2022) in New York City was used for external validation.ParticipantsPatients were included if they were older than 18 years, and were monitored with electrocardiograms, arterial blood pressure, respiratory impedance plethysmography and pulse oximetry. Patients who additionally had intracranial pressure monitoring were used for development (N=157) and external validation (N=56). Patients without intracranial monitors were used for association with outcomes (N=1694).ExposuresExtracranial waveforms including electrocardiogram, arterial blood pressure, plethysmography and SpO2.Main Outcomes and MeasuresIntracranial pressure > 15 mmHg. Measures were Area under receiver operating characteristic curves (AUROCs), sensitivity, specificity, and accuracy at threshold of 0.5. We calculated odds ratios and p-values for phenotype association.ResultsThe AUROC was 0.91 (95% CI, 0.90-0.91) on testing and 0.80 (95% CI, 0.80-0.80) on external validation. aICP had accuracy, sensitivity, and specificity of 73.8% (95% CI, 72.0%-75.6%), 99.5% (95% CI 99.3%-99.6%), and 76.9% (95% CI, 74.0-79.8%) on external validation. A ten-percentile increment was associated with stroke (OR=2.12; 95% CI, 1.27-3.13), brain malignancy (OR=1.68; 95% CI, 1.09-2.60), subdural hemorrhage (OR=1.66; 95% CI, 1.07-2.57), intracerebral hemorrhage (OR=1.18; 95% CI, 1.07-1.32), and procedures like percutaneous brain biopsy (OR=1.58; 95% CI, 1.15-2.18) and craniotomy (OR = 1.43; 95% CI, 1.12-1.84;P< 0.05 for all).Conclusions and RelevanceaICP provides accurate, non-invasive estimation of increased ICP, and is associated with neurological outcomes and neurosurgical procedures in patients without intracranial monitoring.

Publisher

Cold Spring Harbor Laboratory

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