Multimodal assessment improves neuroprognosis performance in clinically unresponsive critical-care patients with brain injury
Open accessAbstract
Accurately predicting functional outcomes for unresponsive patients with acute brain injury is a medical, scientific and ethical challenge. This prospective study assesses how a multimodal approach combining various numbers of behavioral, neuroimaging and electrophysiological markers affects the performance of outcome predictions. We analyzed data from 349 patients admitted to a tertiary neurointensive care unit between 2009 and 2021, categorizing prognoses as good, uncertain or poor, and compared these predictions with observed outcomes using the Glasgow Outcome Scale–Extended (GOS-E, levels ranging from 1 to 8, with higher levels indicating better outcomes). After excluding cases with life-sustaining therapy withdrawal to mitigate the self-fulfilling prophecy bias, our findings reveal that a good prognosis, compared with a poor or uncertain one, is associated with better one-year functional outcomes (common odds ratio (95% CI) for higher GOS-E: OR = 14.57 (5.70–40.32), P < 0.001; and 2.9 (1.56–5.45), P < 0.001, respectively). Moreover, increasing the number of assessment modalities decreased uncertainty (OR = 0.35 (0.21–0.59), P < 0.001) and improved prognostic accuracy (OR = 2.72 (1.18–6.47), P = 0.011). Our results underscore the value of multimodal assessment in refining neuroprognostic precision, thereby offering a robust foundation for clinical decision-making processes for acutely brain-injured patients. ClinicalTrials.gov registration: NCT04534777 .
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Machine learning models that integrate task-relevant multimodal EHR yield superior performance compared to those relying on a single modality.
“Machine learning models that integrate task-relevant multimodal EHR have been shown to yield superior performance compared to those relying on a single modality2–6.”
From MoMA: a mixture-of-multimodal-agents architecture for enhancing clinical prediction modelling (2025) · cites this paper as [2]
The Results (‘Multimodal assessment improves neuroprognosis performance’) report that the multivariable classifier trained on multimodal markers performed similarly to individual prognostic markers, not better. The reported accuracy gain with more modalities concerns the specialist team’s prognosis, rather than superior performance by a machine-learning model. (LLM, conf=0.88)
Checked by a reasoning model — may be wrong.
Experimental — accuracy not yet measured
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
von Elm, E., Altman, D. G., Egger, M., Pocock, S. J., Gøtzsche, P. C., Vandenbroucke, J. P., & Initiative, F. T. S. (2007) · PLoS Medicine · doi:10.1371/journal.pmed.0040296 · Cited by 23,020 · cited 1× · see citing works
“The results are reported in accordance with the Strengthening the Reporting of Observational Studies in Epidemiology guidelines for reporting observational studies 29 .”
von Elm, E., Altman, D. G., Egger, M., Pocock, S. J., Gøtzsche, P. C., Vandenbroucke, J. P., & Initiative, F. T. S. (2007) · Annals of Internal Medicine · doi:10.7326/0003-4819-147-8-200710160-00010 · Cited by 17,796 · see citing works
mixOmics: An R package for ‘omics feature selection and multiple data integration
Rohart, F., Gautier, B., Singh, A., & Lê Cao, K.-A. (2017) · PLOS Computational Biology · doi:10.1371/journal.pcbi.1005752 · Cited by 4,056 · see citing works
Some Methods for Strengthening the Common χ 2 Tests
Cochran, W. G. (1954) · Biometrics · doi:10.2307/3001616 · Cited by 3,718 · cited 1× · see citing works
“Trend analysis of uncertainty and accuracy according to the number of modalities included in the MMA was conducted using the Cochran–Armitage test 47,48 .”
Tests for Linear Trends in Proportions and Frequencies
Armitage, P. (1955) · Biometrics · doi:10.2307/3001775 · Cited by 2,092 · see citing works
Disability after severe head injury: observations on the use of the Glasgow Outcome Scale.
Jennett, B., Snoek, J. W., Bond, M., & Brooks, N. H. (1981) · Journal of Neurology Neurosurgery & Psychiatry · doi:10.1136/jnnp.44.4.285 · Cited by 1,271 · see citing works
Collaborators, M. C. T. (2008) · BMJ · doi:10.1136/bmj.39461.643438.25 · Cited by 1,238 · see citing works
Cao, K. L., Boitard, S., & Besse, P. C. (2011) · BMC Bioinformatics · doi:10.1186/1471-2105-12-253 · Cited by 998 · see citing works
Path Models with Latent Variables: The NIPALS Approach
Wold, H. (1975) · Elsevier eBooks · doi:10.1016/b978-0-12-103950-9.50017-4 · Cited by 842 · see citing works
Practice guideline update recommendations summary: Disorders of consciousness
Giacino, J. T., Katz, D. I., Schiff, N. D., Whyte, J., Ashman, E. J., Ashwal, S., Barbano, R. L., Hammond, F. M., Laureys, S., Ling, G. S. F., et al. (2018) · Neurology · doi:10.1212/wnl.0000000000005926 · Cited by 785 · see citing works
Recovery from disorders of consciousness: mechanisms, prognosis and emerging therapies
Edlow, B. L., Claassen, J., Schiff, N. D., & Greer, D. M. (2020) · Nature Reviews Neurology · doi:10.1038/s41582-020-00428-x · Cited by 744 · see citing works
Neural signature of the conscious processing of auditory regularities
Bekinschtein, T. A., Dehaene, S., Rohaut, B., Tadel, F., Cohen, L., & Naccache, L. (2009) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0809667106 · Cited by 738 · see citing works
Self-citationKondziella, D., Bender, A., Diserens, K., van Erp, W. S., Estraneo, A., Formisano, R., Laureys, S., Naccache, L., Öztürk, Ş., Rohaut, B., et al. (2020) · European Journal of Neurology · doi:10.1111/ene.14151 · Cited by 735 · see citing works
Self-citationSitt, J. D., King, J.-R., El Karoui, I., Rohaut, B., Faugeras, F., Gramfort, A., Cohen, L., Sigman, M., Dehaene, S., & Naccache, L. (2014) · Brain · doi:10.1093/brain/awu141 · Cited by 608 · see citing works
Self-citationStender, J., Gosseries, O., Bruno, M.-A., Charland-Verville, V., Vanhaudenhuyse, A., Demertzi, A., Chatelle, C., Thonnard, M., Thibaut, A., Heine, L., et al. (2014) · The Lancet · doi:10.1016/s0140-6736(14)60042-8 · Cited by 550 · see citing works
Self-citationDetection of Brain Activation in Unresponsive Patients with Acute Brain Injury
Claassen, J., Doyle, K. W., Matory, A., Couch, C., Burger, K. M., Velazquez, A. G., Okonkwo, J. U., King, J.-R., Park, S., Agarwal, S., et al. (2019) · New England Journal of Medicine · doi:10.1056/nejmoa1812757 · Cited by 521 · see citing works
Self-citationElmer, J., Torres, C. D., Aufderheide, T. P., Austin, M., Callaway, C. W., Golan, E., Herren, H., Jasti, J., Kudenchuk, P. J., Scales, D. C., et al. (2016) · Resuscitation · doi:10.1016/j.resuscitation.2016.01.016 · Cited by 437 · see citing works
Comprehensive systematic review update summary: Disorders of consciousness
Giacino, J. T., Katz, D. I., Schiff, N. D., Whyte, J., Ashman, E. J., Ashwal, S., Barbano, R. L., Hammond, F. M., Laureys, S., Ling, G. S. F., et al. (2018) · Neurology · doi:10.1212/wnl.0000000000005928 · Cited by 432 · see citing works
Intrinsic functional connectivity differentiates minimally conscious from unresponsive patients
Athena Demertzi, A., Antonopoulos, G., Heine, L., Voss, H. U., Crone, J. S., Angeles, C. D. L., Bahri, M. A., Perri, C. D., Vanhaudenhuyse, A., Charland‐Verville, V., et al. (2015) · Brain · doi:10.1093/brain/awv169 · Cited by 384 · see citing works
Long-term outcomes of chronic minimally conscious and vegetative states
Luauté, J., Maucort‐Boulch, D., Tell, L., Quelard, F., Sarraf, T., Iwaz, J., Dominique Boisson, A., & Fischer, C. (2010) · Neurology · doi:10.1212/wnl.0b013e3181e8e8df · Cited by 384 · see citing works
Prediction of poor neurological outcome in comatose survivors of cardiac arrest: a systematic review
Sandroni, C., D’Arrigo, S., Cacciola, S., Hoedemaekers, C., Kamps, M. J. A., Oddo, M., Taccone, F. S., Rocco, A. D., Meijer, F. J. A., Westhall, E., et al. (2020) · Intensive Care Medicine · doi:10.1007/s00134-020-06198-w · Cited by 362 · see citing works
The JFK coma recovery scale—revised
Kalmar, K., & Giacino, J. T. (2005) · Neuropsychological Rehabilitation · doi:10.1080/09602010443000425 · Cited by 301 · see citing works
Practice Guideline Update Recommendations Summary: Disorders of Consciousness
Giacino, J. T., Katz, D. I., Schiff, N. D., Whyte, J., Ashman, E. J., Ashwal, S., Barbano, R. L., Hammond, F. M., Laureys, S., Ling, G. S. F., et al. (2018) · Archives of Physical Medicine and Rehabilitation · doi:10.1016/j.apmr.2018.07.001 · Cited by 272 · see citing works
Comanducci, A., Boly, M., Claassen, J., Marzia De Lucia, E., Gibson, R. M., Juan, E., Laureys, S., Naccache, L., Owen, A. M., Rosanova, M., et al. (2020) · Clinical Neurophysiology · doi:10.1016/j.clinph.2020.07.015 · Cited by 203 · see citing works
Self-citationBoosting medical diagnostics by pooling independent judgments
Kurvers, R. H. J. M., Herzog, S. M., Hertwig, R., Krause, J., Carney, P. A., Bogart, A., Argenziano, G., Zalaudek, I., & Wolf, M. (2016) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1601827113 · Cited by 198 · see citing works
Probing consciousness with event-related potentials in the vegetative state
Faugeras, F., Rohaut, B., Weiss, N., Bekinschtein, T. A., Damien Galanaud, E., Puybasset, L., Bolgert, F., Sergent, C., Cohen, L., Dehaene, S., et al. (2011) · Neurology · doi:10.1212/wnl.0b013e3182217ee8 · Cited by 195 · see citing works
Self-citationThe added value of ordinal analysis in clinical trials: an example in traumatic brain injury
Roozenbeek, B., Lingsma, H. F., Perel, P., Edwards, P. J., Roberts, I., Murray, G. D., Maas, A. I. R., & Steyerberg, E. W. (2011) · Critical Care · doi:10.1186/cc10240 · Cited by 191 · see citing works
Minimally conscious state or cortically mediated state?
Naccache, L. (2018) · Brain · doi:10.1093/brain/awx324 · Cited by 181 · see citing works
Self-citationPrediction of good neurological outcome in comatose survivors of cardiac arrest: a systematic review
Sandroni, C., D’Arrigo, S., Cacciola, S., Hoedemaekers, C., Westhall, E., Kamps, M. J. A., Taccone, F. S., Poole, D., Meijer, F. J. A., Antonelli, M. M., et al. (2022) · Intensive Care Medicine · doi:10.1007/s00134-022-06618-z · Cited by 177 · see citing works
Velly, L. J., Perlbarg, V., Boulier, T., Adam, N., Delphine, S., Luyt, C. E., Battisti, V., Torkomian, G., Arbelot, C., Chabanne, R., et al. (2018) · The Lancet Neurology · doi:10.1016/s1474-4422(18)30027-9 · Cited by 175 · see citing works
Self-citationFaugeras, F., Rohaut, B., Weiss, N., Bekinschtein, T., Galanaud, D., Puybasset, L., Bolgert, F., Sergent, C., Cohen, L., Dehaene, S., et al. (2012) · Neuropsychologia · doi:10.1016/j.neuropsychologia.2011.12.015 · Cited by 174 · see citing works
Self-citationAssessment of White Matter Injury and Outcome in Severe Brain Trauma
Damien Galanaud, E., Perlbarg, V., Gupta, R., Stevens, R. D., Sanchez-Peña, P., Tollard, É., de Champfleur, N. M., Dinkel, J., Faivre, S., Ares, G. S., et al. (2012) · Anesthesiology · doi:10.1097/aln.0b013e3182755558 · Cited by 155 · see citing works
Self-citationBarnett, M. L., Boddupalli, D., Nundy, S., & Bates, D. W. (2019) · JAMA Network Open · doi:10.1001/jamanetworkopen.2019.0096 · Cited by 154 · cited 1× · see citing works
“Finally, to optimize group decision-making and mitigate potential biases, we adhere to basic principles 13,30,31 .”
The Minimal Energetic Requirement of Sustained Awareness after Brain Injury
Stender, J., Mortensen, K. N., Thibaut, A., Darkner, S., Laureys, S., Gjedde, A., & Kupers, R. (2016) · Current Biology · doi:10.1016/j.cub.2016.04.024 · Cited by 131 · cited 1× · see citing works
“Functional brain-imaging techniques, such as fMRI-resting state 41 and [ 8 F]fluorodeoxyglucose-positron emission tomography metabolic index 42,43 , assessing the preservation of the default mode network to differentiate patients in a VS/UWS and those in a MCS were implemented in 2013 and 2016,…”
May, T. L., Ruthazer, R., Riker, R. R., et al. (2019) · Resuscitation · doi:10.1016/j.resuscitation.2019.02.031 · Cited by 130 · see citing works
Diffusion Tensor Imaging to Predict Long-term Outcome after Cardiac Arrest
Luyt, C. E., Galanaud, D., Perlbarg, V., Vanhaudenhuyse, A., Stevens, R. D., Gupta, R., Besancenot, H., Krainik, A., Audibert, G., Combes, A., et al. (2012) · Anesthesiology · doi:10.1097/aln.0b013e318275148c · Cited by 113 · see citing works
Self-citationBrain–heart interactions reveal consciousness in noncommunicating patients
Raimondo, F., Rohaut, B., Demertzi, A., Valente, M., Engemann, D. A., Salti, M., Fernandez Slezak, D., Naccache, L., & Sitt, J. D. (2017) · Annals of Neurology · doi:10.1002/ana.25045 · Cited by 106 · see citing works
Self-citationFaugeras, F., Rohaut, B., Denis-Valente, M., Sitt, J. D., Demeret, S., Bolgert, F., Weiss, N., Grinea, A., Marois, C., Quirins, M., et al. (2017) · Brain Injury · doi:10.1080/02699052.2017.1364421 · Cited by 103 · see citing works
Self-citationComa Prognostication After Acute Brain Injury
Fischer, D. B., & Edlow, B. L. (2024) · JAMA Neurology · doi:10.1001/jamaneurol.2023.5634 · Cited by 72 · see citing works
Neuroprognostication: a conceptual framework
Fischer, D. B., Edlow, B. L., Giacino, J. T., & Greer, D. M. (2022) · Nature Reviews Neurology · doi:10.1038/s41582-022-00644-7 · Cited by 70 · see citing works
Olfactory sniffing signals consciousness in unresponsive patients with brain injuries
Arzi, A., Rozenkrantz, L., Gorodisky, L., Rozenkrantz, D., Holtzman, Y., Ravia, A., Bekinschtein, T., Galperin, T., Krimchansky, B., Cohen, G., et al. (2020) · Nature · doi:10.1038/s41586-020-2245-5 · Cited by 67 · see citing works
Rohaut, B., & Claassen, J. (2017) · British Journal of Anaesthesia · doi:10.1016/j.bja.2017.11.007 · Cited by 65 · see citing works
Self-citationA Method for Reducing Misclassification in the Extended Glasgow Outcome Score
Lu, J., Marmarou, A., Lapane, K., Turf, E., & Wilson, L. (2010) · Journal of Neurotrauma · doi:10.1089/neu.2010.1293 · Cited by 59 · see citing works
Uncovering Consciousness in Unresponsive ICU Patients: Technical, Medical and Ethical Considerations
Rohaut, B., Eliseyev, A., & Claassen, J. (2019) · Critical Care · doi:10.1186/s13054-019-2370-4 · Cited by 59 · see citing works
Self-citationWeimer, J. M., Nowacki, A. S., & Frontera, J. A. (2016) · Critical Care Medicine · doi:10.1097/ccm.0000000000001570 · Cited by 58 · see citing works
Measuring Consciousness in the Intensive Care Unit
Edlow, B. L., Fecchio, M., Bodien, Y. G., Comanducci, A., Rosanova, M., Casarotto, S., Young, M. J., Li, J., Dougherty, D. D., Koch, C., et al. (2023) · Neurocritical Care · doi:10.1007/s12028-023-01706-4 · Cited by 50 · see citing works
Habituation of auditory startle reflex is a new sign of minimally conscious state
Hermann, B., Salah, A. B., Perlbarg, V., Denis-Valente, M., Pyatigorskaya, N., Habert, M., Raimondo, F., Stender, J., Damien Galanaud, E., Kas, A., et al. (2020) · Brain · doi:10.1093/brain/awaa159 · Cited by 48 · see citing works
Self-citationLe FOUR score en français, un nouveau score d’évaluation de la profondeur du coma
Weiss, N., Mutlu, G., Essardy, F., et al. (2009) · Revue Neurologique · doi:10.1016/j.neurol.2009.01.045 · Cited by 41 · see citing works
Self-citationHermann, B., Goudard, G., Courcoux, K., Denis-Valente, M., Labat, S., Despois, L., Bourmaleau, J., Richard-Gilis, L., Faugeras, F., Demeret, S., et al. (2019) · BMJ Open · doi:10.1136/bmjopen-2018-026211 · Cited by 39 · see citing works
Self-citationLimitation of life sustaining therapy in disorders of consciousness: ethics and practice
Lissak, I. A., & Young, M. J. (2024) · Brain · doi:10.1093/brain/awae060 · Cited by 29 · see citing works
Aberrant brain–heart coupling is associated with the severity of post cardiac arrest brain injury
Hermann, B., Candia‐Rivera, D., Sharshar, T., Gavaret, M., Diehl, J., Cariou, A., & Benghanem, S. (2024) · Annals of Clinical and Translational Neurology · doi:10.1002/acn3.52000 · Cited by 24 · see citing works
Self-citationDamien Galanaud, E., Perlbarg, V., Gupta, R., et al. (2013) · Survey of Anesthesiology · doi:10.1097/01.sa.0000431217.66983.c1 · Cited by 23 · see citing works
Naccache, L., Luauté, J., Silva, S., Sitt, J. D., & Rohaut, B. (2021) · Revue Neurologique · doi:10.1016/j.neurol.2021.12.004 · Cited by 18 · see citing works
Self-citationCovert Consciousness in the Intensive Care Unit
Giacino, J. T., & Edlow, B. L. (2019) · Trends in Neurosciences · doi:10.1016/j.tins.2019.08.011 · Cited by 16 · see citing works
Lakhlifi, C., & Rohaut, B. (2023) · La Presse Médicale · doi:10.1016/j.lpm.2023.104181 · Cited by 8 · see citing works
Self-citation
Flagged first, then by citations
Cited by
Sorted by citations
MoMA: a mixture-of-multimodal-agents architecture for enhancing clinical prediction modelling
Gao, J., Rahman, M., Caskey, J., Oguss, M., O’Rourke, A., Brown, R., Stey, A., Mayampurath, A., Churpek, M. M., Chen, G., et al. (2025) · npj Digital Medicine · doi:10.1038/s41746-025-02219-4 · Cited by 2 · see citing works
“Machine learning models that integrate task-relevant multimodal EHR have been shown to yield superior performance compared to those relying on a single modality 2 – 6 .”
- Authors
- Rohaut, B., Calligaris, C., Hermann, B., Perez, P., Faugeras, F., Raimondo, F., King, J. R., Engemann, D., Marois, C., Le Guennec, L., Di Meglio, L., Sangaré, A., Munoz Musat, E., Valente, M., Ben Salah, A., Demertzi, A., Belloli, L., Manasova, D., Jodaitis, L., Habert, M. O., Lambrecq, V., Pyatigorskaya, N., Galanaud, D., Puybasset, L., Weiss, N., Demeret, S., Lejeune, F. X., Sitt, J. D., & Naccache, L.
- Affiliations
- Centre National de la Recherche Scientifique (FR)
- Assistance Publique – Hôpitaux de Paris (FR)
- Sorbonne Université (FR)
- Corresponding author
- Rohaut, B.
- ORCID
- Rohaut, B.
- Calligaris, C.
- Hermann, B.
- Perez, P.
- Faugeras, F.
- Raimondo, F.
- King, J-.R.
- Engemann, D.
- Marois, C.
- Le Guennec, L.
- Di Meglio, L.
- Sangaré, A.
- Munoz Musat, E.
- Demertzi, A.
- Belloli, L.
- Manasova, D.
- Habert, M. O.
- Lambrecq, V.
- Pyatigorskaya, N.
- Puybasset, L.
- Weiss, N.
- Demeret, S.
- Lejeune, F. X.
- Sitt, J. D.
- Naccache, L.
- Venue
- Nature Medicine
- Published
- 2024-05-30
- Volume
- 30
- Issue
- 8
- Pages
- 2349-2355
- ISSN
- 1078-8956 (ISSN-L)
- 1546-170X
- PMC
- PMC11333287
- OpenAlex
- W4399181829
- Cited by
- 62
- References
- 55
- Citations by year
- 2026: 29 · 2025: 31 · 2024: 2
- FWCI
- 18.92
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Locations
- Nature Medicine (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Conicet (publishedVersion, cc-by)
- HAL (submittedVersion, other-oa)
- Open Repository and Bibliography (University of Liège) (submittedVersion, cc-by-nc)
- Funders
- James S. McDonnell Foundation
- Topics
- Health Sciences › Medicine › Epidemiology › Traumatic Brain Injury Research
- Health Sciences › Medicine › Neurology › Traumatic Brain Injury and Neurovascular Disturbances
- Health Sciences › Medicine › Emergency Medicine › Cardiac Arrest and Resuscitation
- Keywords
- neurological outcome prediction, acute brain injury, unresponsive patients, multimodal assessment, Glasgow Outcome Scale-Extended, functional outcome prediction, prognostic accuracy, neuroimaging biomarkers, electrophysiological markers, behavioral assessment, neurocritical care
- MeSH terms
- Adult, Aged, Brain Injuries, Critical Care, Female, Humans, Male, Middle Aged, Prognosis, Prospective Studies, Glasgow Outcome Scale, Neuroimaging
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
