{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,15]],"date-time":"2026-09-15T23:31:10Z","timestamp":1789515070255,"version":"build-2803163510"},"reference-count":49,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2025,10,24]],"date-time":"2025-10-24T00:00:00Z","timestamp":1761264000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2025,10,24]],"date-time":"2025-10-24T00:00:00Z","timestamp":1761264000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"DOI":"10.13039\/100008191","name":"Wings for Life","doi-asserted-by":"publisher","award":["2017_044"],"award-info":[{"award-number":["2017_044"]}],"id":[{"id":"10.13039\/100008191","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100008191","name":"Wings for Life","doi-asserted-by":"publisher","award":["2024_301"],"award-info":[{"award-number":["2024_301"]}],"id":[{"id":"10.13039\/100008191","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001711","name":"Schweizerischer Nationalfonds zur F\u00f6rderung der Wissenschaftlichen Forschung","doi-asserted-by":"publisher","award":["PZ00P3_186101"],"award-info":[{"award-number":["PZ00P3_186101"]}],"id":[{"id":"10.13039\/501100001711","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001711","name":"Schweizerischer Nationalfonds zur F\u00f6rderung der Wissenschaftlichen Forschung","doi-asserted-by":"publisher","award":["TMSGI3_225913"],"award-info":[{"award-number":["TMSGI3_225913"]}],"id":[{"id":"10.13039\/501100001711","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001708","name":"International Foundation for Research in Paraplegia","doi-asserted-by":"publisher","award":["P192"],"award-info":[{"award-number":["P192"]}],"id":[{"id":"10.13039\/501100001708","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100022242","name":"Botnar Research Centre for Child Health, University of Basel","doi-asserted-by":"publisher","award":["PEP-2021-1008"],"award-info":[{"award-number":["PEP-2021-1008"]}],"id":[{"id":"10.13039\/501100022242","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["BMC Med"],"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Successfully completing clinical trials for rare and heterogeneous disorders, like spinal cord injuries (SCI), remains challenging, thereby reducing the ability to test and translate promising preclinical findings. We propose synthetic controls, derived from data-driven predictions of recovery in patients undergoing standard treatments, to mitigate these challenges, in particular related to patient recruitment.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>Based on data from the European Multicenter Study about Spinal Cord Injury (EMSCI) and the Sygen trial, we construct synthetic controls from personalized predictions of neurological recovery of sequences of segmental motor scores. A total of six architectures (linear, tree, and deep learning models) are compared. We demonstrate the applicability of synthetic controls through a simulation framework modeling the randomization process in a clinical trial and a case study that re-evaluates the recently completed Nogo Inhibition in SCI (NISCI) trial as a single-arm trial post hoc.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>The primary dataset included 4196 patients from EMSCI and 587 patients from the Sygen trial for external validation. We identified a convolutional neural network as the best-performing architecture to predict segmental motor score sequences, achieving a median root mean squared error below the neurological level of injury of 0.55. Our trial simulations demonstrate that synthetic controls are a viable alternative to randomization, as the proposed solution reduces intercohort heterogeneity and leads to no significant differences with randomized controls in our case study reassessing a clinical trial.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>We provide a comprehensive benchmark of data-driven prediction architectures for neurological recovery after SCI. Apart from offering individual patients a specific recovery prediction, these models constitute the basis for synthetic controls. Using real-world data from a completed trial in SCI, we show that synthetic controls could mitigate the challenges of small cohorts and patient recruitment in rare disorders, offering the opportunity to maximize the number of patients receiving an investigative treatment.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>GitHub repository<\/jats:title>\n                    <jats:p>\n                      <jats:ext-link xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\" xlink:href=\"https:\/\/gitlab.ethz.ch\/BMDSlab\/publications\/sci\/sci-in-silico-trials\" ext-link-type=\"uri\">https:\/\/gitlab.ethz.ch\/BMDSlab\/publications\/sci\/sci-in-silico-trials<\/jats:ext-link>\n                      .\n                    <\/jats:p>\n                  <\/jats:sec>","DOI":"10.1186\/s12916-025-04405-3","type":"journal-article","created":{"date-parts":[[2025,10,24]],"date-time":"2025-10-24T10:04:16Z","timestamp":1761300256000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Exploring synthetic controls in rare diseases with a proof of concept in spinal cord injury"],"prefix":"10.1186","volume":"23","author":[{"given":"Louis P.","family":"Lukas","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Samuel","family":"H\u00e5kansson","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Miklovana","family":"Tuci","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Abel","family":"Torres-Esp\u00edn","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"R\u00fcdiger","family":"Rupp","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Olga","family":"Taran","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Norbert","family":"Weidner","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fred","family":"Geisler","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Martin","family":"Schubert","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Frank","family":"R\u00f6hrich","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yorck B.","family":"Kalke","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rainer","family":"Abel","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Doris","family":"Maier","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Harvinder S.","family":"Chhabra","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Thomas","family":"Liebscher","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"name":"EMSCI study group","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"John L. K.","family":"Kramer","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Marc","family":"Bolliger","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Armin","family":"Curt","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Catherine R.","family":"Jutzeler","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sarah C.","family":"Br\u00fcningk","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2025,10,24]]},"reference":[{"key":"4405_CR1","doi-asserted-by":"publisher","first-page":"407","DOI":"10.1111\/j.1750-3639.1995.tb00619.x","volume":"5","author":"CH Tator","year":"1995","unstructured":"Tator CH. Update on the pathophysiology and pathology of acute spinal cord injury. Brain Pathol. 1995;5:407\u201313.","journal-title":"Brain Pathol"},{"key":"4405_CR2","doi-asserted-by":"publisher","first-page":"24","DOI":"10.1016\/S1474-4422(18)30444-7","volume":"18","author":"JH Badhiwala","year":"2019","unstructured":"Badhiwala JH, Wilson JR, Fehlings MG. Global burden of traumatic brain and spinal cord injury. Lancet Neurol. 2019;18:24\u20135.","journal-title":"Lancet Neurol"},{"key":"4405_CR3","doi-asserted-by":"publisher","first-page":"139","DOI":"10.1097\/01.NPT.0000282246.08288.67","volume":"29","author":"M Post","year":"2005","unstructured":"Post M, Noreau L. Quality of life after spinal cord injury. J Neurol Phys Ther. 2005;29:139\u201346.","journal-title":"J Neurol Phys Ther"},{"key":"4405_CR4","doi-asserted-by":"publisher","first-page":"1235","DOI":"10.1038\/s41393-020-00547-8","volume":"58","author":"MJ Mulcahey","year":"2020","unstructured":"Mulcahey MJ, Jones LAT, Rockhold F, Rupp R, Kramer JLK, Kirshblum S, et al. Adaptive trial designs for spinal cord injury clinical trials directed to the central nervous system. Spinal Cord. 2020;58:1235\u201348.","journal-title":"Spinal Cord"},{"key":"4405_CR5","doi-asserted-by":"publisher","first-page":"799","DOI":"10.1002\/cpt.2528","volume":"111","author":"D Stephenson","year":"2022","unstructured":"Stephenson D, Ollivier C, Brinton R, Barrett J. Can innovative trial designs in orphan diseases drive advancement of treatments for common neurological diseases? Clin Pharmacol Ther. 2022;111:799\u2013806.","journal-title":"Clin Pharmacol Ther"},{"key":"4405_CR6","doi-asserted-by":"publisher","first-page":"42","DOI":"10.1016\/S1474-4422(24)00447-2","volume":"24","author":"N Weidner","year":"2025","unstructured":"Weidner N, Abel R, Maier D, R\u00f6hl K, R\u00f6hrich F, Baumberger M, et al. Safety and efficacy of intrathecal antibodies to Nogo-A in patients with acute cervical spinal cord injury: a randomised, double-blind, multicentre, placebo-controlled, phase 2b trial. Lancet Neurol. 2025;24:42\u201353.","journal-title":"Lancet Neurol"},{"key":"4405_CR7","doi-asserted-by":"publisher","first-page":"457","DOI":"10.2147\/CLEP.S242097","volume":"12","author":"K Thorlund","year":"2020","unstructured":"Thorlund K, Dron L, Park JJH, Mills EJ. Synthetic and external controls in clinical trials\u2013 a primer for researchers. Clin Epidemiol. 2020;12:457\u201367.","journal-title":"Clin Epidemiol"},{"key":"4405_CR8","doi-asserted-by":"publisher","first-page":"255","DOI":"10.1126\/science.aaa8415","volume":"349","author":"MI Jordan","year":"2015","unstructured":"Jordan MI, Mitchell TM. Machine learning: trends, perspectives, and prospects. Science. 2015;349:255\u201360.","journal-title":"Science"},{"key":"4405_CR9","doi-asserted-by":"publisher","DOI":"10.1136\/bmjopen-2020-043497","volume":"11","author":"Z Azizi","year":"2021","unstructured":"Azizi Z, Zheng C, Mosquera L, Pilote L, El Emam K, GOING-FWD Collaborators. Can synthetic data be a proxy for real clinical trial data? A validation study. BMJ Open. 2021;11:e043497.","journal-title":"BMJ Open"},{"key":"4405_CR10","doi-asserted-by":"publisher","first-page":"911","DOI":"10.1109\/72.392253","volume":"6","author":"T Chen","year":"1995","unstructured":"Chen T, Chen H. Universal approximation to nonlinear operators by neural networks with arbitrary activation functions and its application to dynamical systems. IEEE Trans Neural Netw. 1995;6:911\u20137.","journal-title":"IEEE Trans Neural Netw"},{"key":"4405_CR11","doi-asserted-by":"crossref","unstructured":"H\u00e5kansson S, Tuci M, Bolliger M, Curt A, Jutzeler CR, Br\u00fcningk S. Data-driven prediction of spinal cord injury recovery: an exploration of current status and future perspectives. medRxiv. 2024;:2024.05.03.24306807.","DOI":"10.1101\/2024.05.03.24306807"},{"issue":"1 Suppl","key":"4405_CR12","doi-asserted-by":"publisher","first-page":"11","DOI":"10.3171\/2012.4.AOSPINE1245","volume":"17","author":"JR Wilson","year":"2012","unstructured":"Wilson JR, Cadotte DW, Fehlings MG. Clinical predictors of neurological outcome, functional status, and survival after traumatic spinal cord injury: a systematic review. J Neurosurg Spine. 2012;17(1 Suppl):11\u201326.","journal-title":"J Neurosurg Spine"},{"key":"4405_CR13","doi-asserted-by":"publisher","first-page":"723","DOI":"10.1038\/s41467-023-36390-7","volume":"14","author":"G Balbinot","year":"2023","unstructured":"Balbinot G, Li G, Kalsi-Ryan S, Abel R, Maier D, Kalke Y-B, et al. Segmental motor recovery after cervical spinal cord injury relates to density and integrity of corticospinal tract projections. Nat Commun. 2023;14:723.","journal-title":"Nat Commun"},{"key":"4405_CR14","doi-asserted-by":"publisher","DOI":"10.1016\/j.expneurol.2024.114905","volume":"380","author":"SC Br\u00fcningk","year":"2024","unstructured":"Br\u00fcningk SC, Bourguignon L, Lukas LP, EMSCI Study Group, Maier D, Abel R, et al. Prediction of segmental motor outcomes in traumatic spinal cord injury: advances beyond sum scores. Exp Neurol. 2024;380:114905.","journal-title":"Exp Neurol"},{"key":"4405_CR15","doi-asserted-by":"publisher","first-page":"266","DOI":"10.1089\/neu.2020.7407","volume":"39","author":"M Buri","year":"2022","unstructured":"Buri M, Tanadini LG, Hothorn T, Curt A. Unbiased recursive partitioning enables robust and reliable outcome prediction in acute spinal cord injury. J Neurotrauma. 2022;39:266\u201376.","journal-title":"J Neurotrauma"},{"key":"4405_CR16","unstructured":"Single-arm trials as pivotal evidence for the authorisation of medicines in the EU. https:\/\/www.ema.europa.eu\/en\/news\/single-arm-trials-pivotal-evidence-authorisation-medicines-eu. Accessed 17 May 2024."},{"key":"4405_CR17","doi-asserted-by":"publisher","first-page":"1","DOI":"10.46292\/sci2702-1","volume":"27","author":"R Rupp","year":"2021","unstructured":"Rupp R, Biering-S\u00f8rensen F, Burns SP, Graves DE, Guest J, Jones L, et al. International standards for neurological classification of spinal cord injury: revised 2019. Top Spinal Cord Inj Rehabil. 2021;27:1\u201322.","journal-title":"Top Spinal Cord Inj Rehabil"},{"key":"4405_CR18","doi-asserted-by":"publisher","first-page":"120","DOI":"10.1179\/2045772314Y.0000000196","volume":"37","author":"SC Kirshblum","year":"2014","unstructured":"Kirshblum SC, Biering-Sorensen F, Betz R, Burns S, Donovan W, Graves DE, et al. International standards for neurological classification of spinal cord injury: cases with classification challenges. J Spinal Cord Med. 2014;37:120\u20137.","journal-title":"J Spinal Cord Med"},{"key":"4405_CR19","doi-asserted-by":"crossref","unstructured":"Geisler FH, Coleman WP, Grieco G, Poonian D, Sygen Study Group. The Sygen multicenter acute spinal cord injury study. Spine. 2001;26(24) Suppl:S87\u201398.","DOI":"10.1097\/00007632-200112151-00015"},{"key":"4405_CR20","doi-asserted-by":"publisher","first-page":"206","DOI":"10.1038\/sj.sc.3102008","volume":"45","author":"JD Steeves","year":"2007","unstructured":"Steeves JD, Lammertse D, Curt A, Fawcett JW, Tuszynski MH, Ditunno JF, et al. Guidelines for the conduct of clinical trials for spinal cord injury (SCI) as developed by the ICCP panel: clinical trial outcome measures. Spinal Cord. 2007;45:206\u201321.","journal-title":"Spinal Cord"},{"key":"4405_CR21","doi-asserted-by":"publisher","first-page":"369","DOI":"10.1016\/j.apmr.2010.09.027","volume":"92","author":"RJ Marino","year":"2011","unstructured":"Marino RJ, Burns S, Graves DE, Leiby BE, Kirshblum S, Lammertse DP. Upper- and lower-extremity motor recovery after traumatic cervical spinal cord injury: an update from the national spinal cord injury database. Arch Phys Med Rehabil. 2011;92:369\u201375.","journal-title":"Arch Phys Med Rehabil"},{"key":"4405_CR22","unstructured":"Pedregosa F, Varoquaux G, Gramfort A, Michel V, Thirion B, Grisel O, et al. Scikit-learn: machine learning in Python. J Mach Learn Res. 2011;abs\/1201.0490:2825\u201330."},{"key":"4405_CR23","unstructured":"Lundberg SM, Lee S-I. A unified approach to interpreting model predictions. In: Proceedings of the 31st International Conference on Neural Information Processing Systems. Red Hook: Curran Associates Inc.; 2017. p. 4768\u201377."},{"key":"4405_CR24","doi-asserted-by":"crossref","unstructured":"Hoerl AE, Kennard RW. Ridge regression: applications to nonorthogonal problems. Technometrics. 2012;12(1):69\u201382.","DOI":"10.1080\/00401706.1970.10488635"},{"key":"4405_CR25","doi-asserted-by":"publisher","first-page":"301","DOI":"10.1111\/j.1467-9868.2005.00503.x","volume":"67","author":"H Zou","year":"2005","unstructured":"Zou H, Hastie T. Regularization and variable selection via the elastic net. J R Stat Soc Ser B Stat Methodol. 2005;67:301\u201320.","journal-title":"J R Stat Soc Ser B Stat Methodol"},{"key":"4405_CR26","doi-asserted-by":"publisher","first-page":"5","DOI":"10.1023\/A:1010933404324","volume":"45","author":"L Breiman","year":"2001","unstructured":"Breiman L. Random forests. Mach Learn. 2001;45:5\u201332.","journal-title":"Mach Learn"},{"key":"4405_CR27","doi-asserted-by":"crossref","unstructured":"Chen T, Guestrin C. XGBoost: a scalable tree boosting system. In: Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. Association for Computing Machinery. p. 785\u201394.","DOI":"10.1145\/2939672.2939785"},{"key":"4405_CR28","first-page":"1","volume":"18","author":"L Li","year":"2018","unstructured":"Li L, Jamieson K, DeSalvo G, Rostamizadeh A, Talwalkar A. Hyperband: a novel bandit-based approach to hyperparameter optimization. J Mach Learn Res. 2018;18:1\u201352.","journal-title":"J Mach Learn Res"},{"key":"4405_CR29","unstructured":"Abadi M, Agarwal A, Barham P, Brevdo E, Chen Z, Citro C, et al. TensorFlow: large-scale machine learning on heterogeneous distributed systems. 2016."},{"key":"4405_CR30","unstructured":"Fey M, Lenssen JE. Fast graph representation learning with PyTorch geometric. arXiv [cs.LG]. 2019."},{"key":"4405_CR31","doi-asserted-by":"publisher","DOI":"10.1080\/09593985.2019.1685033","author":"E Bye","year":"2019","unstructured":"Bye E, Glinsky J, Yeomans J, Hungerford A, Patterson H, Chen L, et al. The inter-rater reliability of the 13-point manual muscle test in people with spinal cord injury. Physiother Theory Pract. 2019. https:\/\/doi.org\/10.1080\/09593985.2019.1685033.","journal-title":"Physiother Theory Pract"},{"key":"4405_CR32","doi-asserted-by":"publisher","DOI":"10.3389\/fncel.2022.977679","volume":"16","author":"VA Dietz","year":"2022","unstructured":"Dietz VA, Roberts N, Knox K, Moore S, Pitonak M, Barr C, et al. Fighting for recovery on multiple fronts: the past, present, and future of clinical trials for spinal cord injury. Front Cell Neurosci. 2022;16:977679.","journal-title":"Front Cell Neurosci"},{"key":"4405_CR33","doi-asserted-by":"publisher","first-page":"3500","DOI":"10.1038\/s41467-022-30908-1","volume":"13","author":"S Popat","year":"2022","unstructured":"Popat S, Liu SV, Scheuer N, Hsu GG, Lockhart A, Ramagopalan SV, et al. Addressing challenges with real-world synthetic control arms to demonstrate the comparative effectiveness of Pralsetinib in non-small cell lung cancer. Nat Commun. 2022;13:3500.","journal-title":"Nat Commun"},{"key":"4405_CR34","doi-asserted-by":"publisher","first-page":"39","DOI":"10.1080\/10790268.2006.11753855","volume":"29","author":"DE Graves","year":"2006","unstructured":"Graves DE, Frankiewicz RG, Donovan WH. Construct validity and dimensional structure of the ASIA motor scale. J Spinal Cord Med. 2006;29:39\u201345.","journal-title":"J Spinal Cord Med"},{"key":"4405_CR35","doi-asserted-by":"publisher","first-page":"1","DOI":"10.46292\/sci22-00036","volume":"29","author":"BA Snider","year":"2023","unstructured":"Snider BA, Eren F, Reeves RK, Rupp R, Kirshblum SC. The international standards for neurological classification of spinal cord injury: classification accuracy and challenges. Top Spinal Cord Inj Rehabil. 2023;29:1\u201315.","journal-title":"Top Spinal Cord Inj Rehabil"},{"key":"4405_CR36","unstructured":"Harrigan CF, Morgenshtern G, Goldenberg A, Chevalier F. Considerations for visualizing uncertainty in clinical machine learning models. arXiv [cs.HC]. 2022."},{"key":"4405_CR37","doi-asserted-by":"publisher","unstructured":"Kapoor D, Xu C. Spinal cord injury AIS predictions using machine learning. eNeuro. 2023;10.\u00a0https:\/\/doi.org\/10.1523\/ENEURO.0149-22.2022.","DOI":"10.1523\/ENEURO.0149-22.2022"},{"key":"4405_CR38","doi-asserted-by":"publisher","first-page":"533","DOI":"10.1038\/sj.sc.3101635","volume":"42","author":"M Beninato","year":"2004","unstructured":"Beninato M, O\u2019Kane KS, Sullivan PE. Relationship between motor FIM and muscle strength in lower cervical-level spinal cord injuries. Spinal Cord. 2004;42:533\u201340.","journal-title":"Spinal Cord"},{"key":"4405_CR39","doi-asserted-by":"publisher","first-page":"128","DOI":"10.1016\/j.biopha.2017.05.048","volume":"92","author":"A Saghazadeh","year":"2017","unstructured":"Saghazadeh A, Rezaei N. The role of timing in the treatment of spinal cord injury. Biomed Pharmacother. 2017;92:128\u201339.","journal-title":"Biomed Pharmacother"},{"key":"4405_CR40","doi-asserted-by":"publisher","first-page":"295","DOI":"10.1177\/1545968315593806","volume":"30","author":"I-M Velstra","year":"2016","unstructured":"Velstra I-M, Bolliger M, Krebs J, Rietman JS, Curt A. Predictive value of upper limb muscles and grasp patterns on functional outcome in cervical spinal cord injury. Neurorehabil Neural Repair. 2016;30:295\u2013306.","journal-title":"Neurorehabil Neural Repair"},{"key":"4405_CR41","doi-asserted-by":"publisher","DOI":"10.4414\/smw.2020.20291","volume":"150","author":"A Scheel-Sailer","year":"2020","unstructured":"Scheel-Sailer A, Sailer CO, Lampart P, Baumberger M, Berger M, Mueller G, et al. Examinations and assessments in patients with a newly acquired spinal cord injury\u2013 retrospective chart analysis as part of a quality improvement project. Swiss Med Wkly. 2020;150:w20291.","journal-title":"Swiss Med Wkly"},{"key":"4405_CR42","doi-asserted-by":"publisher","first-page":"232","DOI":"10.1038\/sj.sc.3102010","volume":"45","author":"D Lammertse","year":"2007","unstructured":"Lammertse D, Tuszynski MH, Steeves JD, Curt A, Fawcett JW, Rask C, et al. Guidelines for the conduct of clinical trials for spinal cord injury as developed by the ICCP panel: clinical trial design. Spinal Cord. 2007;45:232\u201342.","journal-title":"Spinal Cord"},{"key":"4405_CR43","doi-asserted-by":"publisher","first-page":"225","DOI":"10.1186\/s12916-022-02395-0","volume":"20","author":"L Bourguignon","year":"2022","unstructured":"Bourguignon L, Tong B, Geisler F, Schubert M, R\u00f6hrich F, Saur M, et al. International surveillance study in acute spinal cord injury confirms viability of multinational clinical trials. BMC Med. 2022;20:225.","journal-title":"BMC Med"},{"key":"4405_CR44","doi-asserted-by":"crossref","unstructured":"Fehlings MG, Boakye M, Ditunno JF Jr, Vaccaro AR, Rossignol S, Burns AS, editors. North American clinical trials network: building a clinical trials network for spinal cord injury. In: Essentials of spinal cord injury. Stuttgart: Georg Thieme Verlag; 2013.","DOI":"10.1055\/b-0034-83871"},{"key":"4405_CR45","doi-asserted-by":"publisher","first-page":"635","DOI":"10.1001\/jamaneurol.2017.0318","volume":"74","author":"A Curt","year":"2017","unstructured":"Curt A, Levi AD, Schwab JM. Challenges to translation and the hippocratic oath by premature termination of spinal cord stem cell-based trials. JAMA Neurol. 2017;74:635\u20136.","journal-title":"JAMA Neurol"},{"key":"4405_CR46","doi-asserted-by":"publisher","first-page":"693","DOI":"10.1038\/s41393-020-00561-w","volume":"59","author":"AC Smith","year":"2021","unstructured":"Smith AC, Albin SR, O\u2019Dell DR, Berliner JC, Dungan D, Sevigny M, et al. Axial MRI biomarkers of spinal cord damage to predict future walking and motor function: a retrospective study. Spinal Cord. 2021;59:693\u20139.","journal-title":"Spinal Cord"},{"key":"4405_CR47","doi-asserted-by":"publisher","first-page":"1319","DOI":"10.1016\/j.spinee.2017.05.009","volume":"17","author":"A Matsushita","year":"2017","unstructured":"Matsushita A, Maeda T, Mori E, Yuge I, Kawano O, Ueta T, et al. Can the acute magnetic resonance imaging features reflect neurologic prognosis in patients with cervical spinal cord injury? Spine J. 2017;17:1319\u201324.","journal-title":"Spine J"},{"key":"4405_CR48","doi-asserted-by":"publisher","first-page":"301","DOI":"10.1089\/neu.2020.7144","volume":"38","author":"GMB Harrington","year":"2021","unstructured":"Harrington GMB, Cool P, Hulme C, Osman A, Chowdhury JR, Kumar N, et al. Routinely measured hematological markers can help to predict American Spinal Injury Association impairment scale scores after spinal cord injury. J Neurotrauma. 2021;38:301\u20138.","journal-title":"J Neurotrauma"},{"key":"4405_CR49","doi-asserted-by":"publisher","DOI":"10.1016\/j.mcpro.2021.100096","volume":"20","author":"MA Skinnider","year":"2021","unstructured":"Skinnider MA, Rogalski J, Tigchelaar S, Manouchehri N, Prudova A, Jackson AM, et al. Proteomic portraits reveal evolutionarily conserved and divergent responses to spinal cord injury. Mol Cell Proteomics. 2021;20:100096.","journal-title":"Mol Cell Proteomics"}],"container-title":["BMC Medicine"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s12916-025-04405-3.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1186\/s12916-025-04405-3\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s12916-025-04405-3.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,24]],"date-time":"2025-10-24T10:04:19Z","timestamp":1761300259000},"score":1,"resource":{"primary":{"URL":"https:\/\/bmcmedicine.biomedcentral.com\/articles\/10.1186\/s12916-025-04405-3"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,10,24]]},"references-count":49,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2025,12]]}},"alternative-id":["4405"],"URL":"https:\/\/doi.org\/10.1186\/s12916-025-04405-3","relation":{},"ISSN":["1741-7015"],"issn-type":[{"value":"1741-7015","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,10,24]]},"assertion":[{"value":"15 April 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"22 September 2025","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"24 October 2025","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The study was performed in accordance with the Declaration of Helsinki and was approved by all responsible institutional review boards (Kantonale Ethikkommission Z\u00fcrich EK-3\/2004, Heidelberg University S-188\/2003). Throughout the study duration, EMSCI followed the ethics guidelines of the participating countries and implemented changes and new policies as required (see also\n                      \n                      ). Patients gave their written informed consent before being included in the EMSCI database. Approval for the secondary analysis of the Sygen data was provided by an institutional ethical standards committee on human experimentation at the University of British Columbia (H16-03143). No further approval for the use of data from the Sygen clinical trial was required (Kantonale Ethikkommission Z\u00fcrich Req-2024-00913). The original Sygen clinical trial also received ethical approval but was conducted before clinical trials were required to be registered; hence, no clinicaltrial.gov identifier is available. All experiments were performed in accordance with relevant guidelines and regulations. Informed consent to participate was obtained from all participants as part of the original study.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval and consent to participate"}},{"value":"Not applicable.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for publication"}},{"value":"The authors declare no competing interests.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"581"}}