{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"institution":[{"name":"medRxiv"}],"indexed":{"date-parts":[[2026,3,8]],"date-time":"2026-03-08T04:00:02Z","timestamp":1772942402413,"version":"3.50.1"},"posted":{"date-parts":[[2026,3,4]]},"group-title":"Neurology","reference-count":52,"publisher":"openRxiv","license":[{"start":{"date-parts":[[2026,3,4]],"date-time":"2026-03-04T00:00:00Z","timestamp":1772582400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"accepted":{"date-parts":[[2026,3,4]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                <jats:sec>\n                  <jats:title>Introduction<\/jats:title>\n                  <jats:p>The eligibility of anti-amyloid disease-modifying therapies (DMTs) and their integration into clinical practice in some institutions requires a specific range of Mini-Mental State Examination (MMSE) scores. Reliance on this pencil-and-paper psychometric instrument imposes operational burdens and risks perpetuating health disparities due to the test\u2019s known educational and cultural biases. This study evaluates the efficacy of the Digital Clock and Recall (DCR\u2122) \u2013 a rapid, FDA-listed digital cognitive assessment \u2013 to crosswalk to MMSE scores using machine learning, thereby offering a faster, scalable, and equitable mechanism for patient triage.<\/jats:p>\n                <\/jats:sec>\n                <jats:sec>\n                  <jats:title>Methods<\/jats:title>\n                  <jats:p>\n                    We conducted a retrospective analysis using data from the multi-site Bio-Hermes-001 study (\n                    <jats:ext-link xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\" ext-link-type=\"clintrialgov\" xlink:href=\"NCT04733989\">NCT04733989<\/jats:ext-link>\n                    , N=945). Participants were clinically classified as cognitively unimpaired, mild cognitive Impairment, or probable Alzheimer\u2019s dementia. We trained a Poisson elastic net regression model using age and multimodal digital features derived from the DCR (including drawing kinematics and voice acoustics) to predict MMSE scores. The model was tested for generalizability using an independent external validation cohort from the Apheleia study (\n                    <jats:ext-link xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\" ext-link-type=\"clintrialgov\" xlink:href=\"NCT05364307\">NCT05364307<\/jats:ext-link>\n                    , N=238).\n                  <\/jats:p>\n                <\/jats:sec>\n                <jats:sec>\n                  <jats:title>Results<\/jats:title>\n                  <jats:p>The machine learning model predicted MMSE scores with a root mean squared error (RMSE) of 2.31 in the training cohort. This error margin falls within the established test-retest reliability range of the manual MMSE itself (2\u20134 points), suggesting the prediction is statistically non-inferior to human administration. External validation in the Apheleia cohort demonstrated robust generalizability (RMSE = 2.62). Crucially, the model exhibited demographic fairness, maintaining consistent accuracy across Race (White RMSE = 2.34; Non-White RMSE = 2.14) and Ethnicity (Hispanic RMSE = 2.26; Non-Hispanic RMSE = 2.31).<\/jats:p>\n                <\/jats:sec>\n                <jats:sec>\n                  <jats:title>Discussion<\/jats:title>\n                  <jats:p>Machine learning can leverage multimodal features from the DCR to accurately and equitably crosswalk to MMSE scores in support of current guidelines, transforming a time-intensive manual test into a rapid, automated assessment. By deploying this \u201cdigital triage\u201d engine, where traditional assessments are still used for DMT eligibility, healthcare systems can streamline the identification of DMT-eligible patients, reduce specialist referral bottlenecks, and ensure that access to life-altering therapies is determined by pathology rather than demography.<\/jats:p>\n                <\/jats:sec>","DOI":"10.64898\/2026.03.03.26347542","type":"posted-content","created":{"date-parts":[[2026,3,5]],"date-time":"2026-03-05T02:20:14Z","timestamp":1772677214000},"source":"Crossref","is-referenced-by-count":0,"title":["Streamlining Eligibility Assessment for Alzheimer\u2019s Disease-Modifying Therapies: Prediction of MMSE Scores Using the Digital Clock and Recall"],"prefix":"10.64898","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0826-1275","authenticated-orcid":false,"given":"Ali","family":"Jannati","sequence":"first","affiliation":[{"name":"Department of Neurology, Harvard Medical School, 25 Shattuck Street, Boston, MA, 02115 USA"},{"name":"Linus Health, Inc., 280 Summer Street, 10th Floor, Boston, MA, 02210 USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5273-2276","authenticated-orcid":false,"given":"Claudio","family":"Toro-Serey","sequence":"additional","affiliation":[{"name":"Linus Health, Inc., 280 Summer Street, 10th Floor, Boston, MA, 02210 USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8424-324X","authenticated-orcid":false,"given":"Marissa","family":"Ciesla","sequence":"additional","affiliation":[{"name":"Linus Health, Inc., 280 Summer Street, 10th Floor, Boston, MA, 02210 USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-2464-4713","authenticated-orcid":false,"given":"Emma","family":"Chen","sequence":"additional","affiliation":[{"name":"Linus Health, Inc., 280 Summer Street, 10th Floor, Boston, MA, 02210 USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0002-6290-9589","authenticated-orcid":false,"given":"John","family":"Showalter","sequence":"additional","affiliation":[{"name":"Linus Health, Inc., 280 Summer Street, 10th Floor, Boston, MA, 02210 USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-7339-6946","authenticated-orcid":false,"given":"David","family":"Bates","sequence":"additional","affiliation":[{"name":"Linus Health, Inc., 280 Summer Street, 10th Floor, Boston, MA, 02210 USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8975-0382","authenticated-orcid":false,"given":"Alvaro","family":"Pascual-Leone","sequence":"additional","affiliation":[{"name":"Department of Neurology, Harvard Medical School, 25 Shattuck Street, Boston, MA, 02115 USA"},{"name":"Linus Health, Inc., 280 Summer Street, 10th Floor, Boston, MA, 02210 USA"},{"name":"Hinda and Arthur Marcus Institute for Aging Research and Deanna and Sidney Wolk Center for Memory Health, Hebrew SeniorLife, 1200 Centre St, Boston, MA 02131 USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5985-7920","authenticated-orcid":false,"given":"Sean","family":"Tobyne","sequence":"additional","affiliation":[{"name":"Linus Health, Inc., 280 Summer Street, 10th Floor, Boston, MA, 02210 USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"54368","reference":[{"key":"2026030703450803000_2026.03.03.26347542v1.1","unstructured":"Food and Drug Administration (FDA). 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