Complex patterns of functional change among TBI survivors from discharge to 6-month follow-up: Findings from a registry-based cohort study

Hosein Kouchaki; Sina Bazmi; Saman Rabiei; Parnia Kamyab; Mohammadreza Khosravi; Reza Taheri; Hosseinali Khalili; Reza Tabrizi

doi:10.1371/journal.pone.0353189

Peer Review History

Original SubmissionFebruary 17, 2026
23 Mar 2026 Decision Letter - Chinh Quoc Luong, Editor -->PONE-D-26-08416-->-->Complex patterns of functional change among TBI survivors from discharge to 6-month follow-up: findings from a registry-based cohort study-->-->PLOS One Dear Dr. Tabrizi, Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process. Please submit your revised manuscript by May 07 2026 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file. Please include the following items when submitting your revised manuscript:--> A letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'. A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'. An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'. If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter. If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: https://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols. Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols. We look forward to receiving your revised manuscript. Kind regards, Chinh Quoc Luong, MD., PhD. Academic Editor PLOS One Journal Requirements: -->1. When submitting your revision, we need you to address these additional requirements.-->--> -->-->Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found at -->-->https://journals.plos.org/plosone/s/file?id=wjVg/PLOSOne_formatting_sample_main_body.pdf and -->-->https://journals.plos.org/plosone/s/file?id=ba62/PLOSOne_formatting_sample_title_authors_affiliations.pdf-->--> -->-->2. We note that you have indicated that there are restrictions to data sharing for this study. For studies involving human research participant data or other sensitive data, we encourage authors to share de-identified or anonymized data. However, when data cannot be publicly shared for ethical reasons, we allow authors to make their data sets available upon request. For information on unacceptable data access restrictions, please see http://journals.plos.org/plosone/s/data-availability#loc-unacceptable-data-access-restrictions. -->--> -->-->Before we proceed with your manuscript, please address the following prompts:-->--> -->-->a) If there are ethical or legal restrictions on sharing a de-identified data set, please explain them in detail (e.g., data contain potentially identifying or sensitive patient information, data are owned by a third-party organization, etc.) and who has imposed them (e.g., a Research Ethics Committee or Institutional Review Board, etc.). Please also provide contact information for a data access committee, ethics committee, or other institutional body to which data requests may be sent.-->--> -->-->b) If there are no restrictions, please upload the minimal anonymized data set necessary to replicate your study findings to a stable, public repository and provide us with the relevant URLs, DOIs, or accession numbers. Please see http://www.bmj.com/content/340/bmj.c181.long for guidelines on how to de-identify and prepare clinical data for publication. For a list of recommended repositories, please see https://journals.plos.org/plosone/s/recommended-repositories. You also have the option of uploading the data as Supporting Information files, but we would recommend depositing data directly to a data repository if possible.-->--> -->-->Please update your Data Availability statement in the submission form accordingly.-->--> -->-->3. If the reviewer comments include a recommendation to cite specific previously published works, please review and evaluate these publications to determine whether they are relevant and should be cited. There is no requirement to cite these works unless the editor has indicated otherwise. Additional Editor Comments: Thank you for submitting your manuscript “Complex patterns of functional change among TBI survivors from discharge to 6-month follow-up” (PONE-D-26-08416) to PLOS ONE. Your manuscript was reviewed by an expert, who found the topic timely and clinically relevant. To continue the review process, please submit a major revision that fully addresses all reviewer comments, provides a detailed response to each comment, and clearly indicates changes in the manuscript. -->--> -->-->[Note: HTML markup is below. Please do not edit.] Reviewers' comments: Reviewer's Responses to Questions--> -->Comments to the Author 1. Is the manuscript technically sound, and do the data support the conclusions? The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented. --> Reviewer #1: No ******** -->2. Has the statistical analysis been performed appropriately and rigorously? --> Reviewer #1: No ****** -->3. Have the authors made all data underlying the findings in their manuscript fully available? The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.--> Reviewer #1: No ****** -->4. Is the manuscript presented in an intelligible fashion and written in standard English? PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.--> Reviewer #1: Yes ****** -->5. Review Comments to the Author Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)--> Reviewer #1: Thank you for the opportunity to review the paper by Kouchaki et al entitled “Complex patterns of functional change among TBI survivors from discharge to 6-month follow up: findings from a registry-based cohort study. This is a retrospective single-centre registry analysis of TBI patients who survived until discharge, aiming to understand which baseline variables are associated with change in GOSE between discharge and 6-month follow up. Most TBI prognostic studies to date have looked at the association between baseline variables and 6-month GOSE, rather than the change in GOSE between discharge and 6-month. This different perspective is welcome as it will be useful to the discharging clinician when counselling families at that point. MAJOR POINTS 1. The potential to improve between discharge and 6-month will heavily depend on how much recovery has already occurred (i.e. GOSE at discharge) and how much more time remains to recover (i.e. length of stay in hospital). In fact the degree of recovery may directly influence the decision as to whether the patient is ready for discharge. Therefore all models must be adjusted for GOSE0 and LOS by including them as predictors, which is currently missing. GOSE0 should also be shown in Table 1. 2. The statistical method for variable selection is flawed. Authors use univariate analysis and include all variables with p<0.20 for the multivariate analysis. This approach will lead to missing potentially important variables if they are confounded by others and should be included regardless of p-value. I would suggest the authors use existing literature (e.g. CRASH and IMPACT models) and their knowledge of the subject matter to inform selection. In addition they could consider stepwise inclusion/exclusion of covariates guided by AIC/BIC or penalised regression. MINOR POINTS 1. In the introduction the authors say that TBI affects younger adults, citing a reference from 2007. The demographic in Western countries has now shifted to include predominantly older adults. This does not take away from the importance of the paper but a more balanced statement and newer epidemiological reference should be provided (e.g. Maas, Lancet Neurology 2022). 2. The introduction states the current system of classifying severity of TBI uses GCS. Actually the new current system is the CBI-M system (Manley, Lancet 2025), the traditional older methods was using GCS – reword please. 3. Patients with missing data were excluded. As the number is relatively small (n= 157) this unlikely to change results but ideally missing data would be managed at least by checking for differences between those included and excluded, plus/minus multiple imputation and/ or sensitivity analysis (see Richter, J Neurotrauma, 2019) 4. Regarding presentation of results. Usually in the literature moderate-severe TBI is grouped together and mild TBI is kept separate. For comparison with other literature, please could the authors present results (also) in these groupings. 5. This study addresses a very specific subgroup of patients: those who have been admitted (as opposed to been discharged from the emergency department) but have not died as an inpatient. So a “medium” risk group for poor outcome. This should be made a bit clearer in the discussion/limitation section so the reader can appreciate the generalisability of results. 6. Line 266 states a result is present with “lower power”. Please reword to statistically correct terminology. 7. As this paper directly addresses the question of recovery trajectories, it should refer to other major works addressing this question such as papers by the TRACK-TBI group (Nelson et al; McCrea et al; Curpen et al) ****** -->6. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files. If you choose “no”, your identity will remain anonymous but your review may still be made public. Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.--> Reviewer #1: No ******** [NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.] To ensure your figures meet our technical requirements, please review our figure guidelines: https://journals.plos.org/plosone/s/figures You may also use PLOS’s free figure tool, NAAS, to help you prepare publication quality figures: https://journals.plos.org/plosone/s/figures#loc-tools-for-figure-preparation. NAAS will assess whether your figures meet our technical requirements by comparing each figure against our figure specifications. https://doi.org/10.1371/journal.pone.0353189.r001
Revision 1
11 May 2026 Author Response We are grateful to the esteemed editor for this opportunity, and we sincerely appreciate the invaluable contributions of the respected reviewers, who dedicated their precious time to improving our manuscript. We have acknowledged our shortcomings and errors, and within the short period that has passed, we have made every effort to implement all the suggestions provided by the esteemed reviewers. Their feedback has been highly valuable to us, and we have incorporated the following changes into the manuscript: Best Regards, Dr. Tabrizi Reviewer #1 Thank you for the opportunity to review the paper by Kouchaki et al entitled “Complex patterns of functional change among TBI survivors from discharge to 6-month follow up: findings from a registry-based cohort study. This is a retrospective single-centre registry analysis of TBI patients who survived until discharge, aiming to understand which baseline variables are associated with change in GOSE between discharge and 6-month follow up. MAJOR POINTS 1. The potential to improve between discharge and 6-month will heavily depend on how much recovery has already occurred (i.e. GOSE at discharge) and how much more time remains to recover (i.e. length of stay in hospital). In fact the degree of recovery may directly influence the decision as to whether the patient is ready for discharge. Therefore all models must be adjusted for GOSE0 and LOS by including them as predictors, which is currently missing. GOSE0 should also be shown in Table 1. Response: We thank the reviewer for this insightful and methodologically well-founded comment. We fully agree with the underlying rationale that both baseline functional status (GOSE₀) and hospital length of stay (LOS) are important determinants of recovery potential and post-discharge trajectories. However, in the context of our study design, there are important statistical considerations that limit the direct inclusion of these variables in the primary models: 1. GOSE₀ (baseline functional status): Our primary outcome was defined as functional change (GOSE₆ − GOSE₀). Because GOSE₀ is inherently a component of this outcome, including it as a covariate in regression models would introduce mathematical coupling and collinearity, which can bias parameter estimates and distort associations. This issue has been well described in methodological literature addressing analyses of change scores and baseline adjustment. To appropriately account for baseline functional status, we instead performed subgroup analyses stratified by GOSE₀ (Supplementary Table 10), which allow for evaluation of recovery trajectories within comparable baseline categories without introducing collinearity. We believe this represents a more statistically appropriate and clinically interpretable approach. In addition, GOSE₀ has now been explicitly included in Table 1, as suggested. 2. Hospital length of stay (LOS): As noted in the Methods section, hospital LOS reflects downstream effects of clinical management and in-hospital recovery, and its inclusion in primary models may introduce post-treatment bias. For this reason, LOS was not included in the main analyses. Nevertheless, to address the reviewer’s concern, we conducted exploratory models including LOS, and these results are presented in the Supplementary Tables. The findings were consistent with the primary analyses, suggesting that exclusion of LOS did not materially affect our conclusions. We greatly appreciate the reviewer’s comment, which highlights an important methodological consideration. While we fully agree with the conceptual importance of GOSE₀ and LOS, the statistical structure of our outcome required alternative approaches to ensure valid and interpretable results. “In addition, unfavorable discharge functional status (GOSE0 ≤ 4) was markedly more frequent among patients who subsequently regressed or recovered than among those who remained stable.” (Table 1) “Unfavorable GOSE0 was substantially more common in the regression and recovery groups than in the stable group (Table 2)” “Hospital LOS was excluded from the final model to avoid post-treatment bias; however, the results of a parallel model including hospital LOS are provided in Supplementary Table 3.” “Supplementary Table 5 provides the same model with the inclusion of hospital LOS.” Supplementary Table 3. Multivariate multinomial logistic regression of independent baseline predictors in mild to moderate TBI patients (including hospital LOS) Mild to Moderate TBI, GCS 9 – 15 (n = 1873) Variables Recovering Regressing p-value OR 95% CI p-value OR 95% CI Age (40 – 59) 0.365 0.850 0.598, 1.208  0.001 5.533 2.314, 13.232 Age (60 – 74) 0.112 1.428 0.920, 2.215  0.001 8.875 3.281, 24.008 Age (75 and older)  0.001 4.096 2.366, 7.089  0.001 40.172 14.116, 114.319 Sex (male) 0.581 0.901 0.623, 1.304 0.838 1.073 0.546, 2.110 Pupils (anisocoria) 0.261 0.674 0.339, 1.342 0.311 0.343 0.044, 2.710 Pupils (bilateral fixed) 0.440 0.631 0.196, 2.030 0.971 1.035 0.162, 6.633 Pupils (uncheckable) 0.613 1.131 0.701, 1.825 0.168 0.500 0.187, 1.338 Mechanism (motor vehicle) 0.482 1.136 0.795, 1.624 0.211 0.619 0.291, 1.314 Mechanism (pedestrian) 0.636 0.902 0.589, 1.381 0.532 0.776 0.350, 1.719 Mechanism (others) 0.064 0.549 0.292, 1.034 0.386 0.606 0.195, 1.882 HTN 0.049 0.568 0.324, 0.998 0.458 0.735 0.326, 1.657 DM 0.053 0.511 0.258, 1.009 0.539 1.354 0.515, 3.562 CVA/CVD 0.397 1.444 0.618, 3.377 0.090 2.398 0.874, 6.583 SAH 0.002 1.590 1.186, 2.131 0.036 1.888 1.044, 3.414 IVH 0.999 1.000 0.502, 1.993 0.309 1.749 0.596, 5.135 BSFx 0.742 1.051 0.782, 1.412 0.125 0.570 0.278, 1.168 Pneumocephalus 0.040 1.462 1.018, 2.100 0.659 0.808 0.314, 2.081 EDH 0.315 0.845 0.608, 1.174 0.023 0.312 0.114, 851 SDH 0.530 1.103 0.812, 1.499 0.750 1.104 0.602, 2.023 DSFx 0.163 0.684 0.402, 1.166 0.254 1.940 0.622, 6.056 Midline shift (> 5 mm) 0.127 1.443 0.901, 2.312 0.981 0.989 0.381, 2.565 Cisterns status (absent) 0.053 1.863 0.991, 3.501 0.700 1.372 0.275, 6.851 Cisterns status (compressed) 0.478 0.784 0.401, 1.535 0.822 0.868 0.253, 2.973 Hospital LOS  0.001 1.046 1.035, 1.056  0.001 1.050 1.032, 1.068 GCS  0.001 0.869 0.812, 0.930  0.001 0.683 0.591, 0.788 INR 0.411 1.153 0.821, 1.618 0.531 1.192 0.688, 2.068 Random BS, mg/dl  0.001 1.004 1.002, 1.006 0.338 0.998 0.993, 1.002 SBP, mmHg 0.582 1.002 0.995, 1.009 0.573 1.004 0.991, 1.016 Hemoglobin, g/dl 0.427 0.974 0.911, 1.040 0.149 0.909 0.797, 1.035 Platelet count 0.987 1.000 0.998, 1.002  0.001 1.005 1.002, 1.008 Multivariate multinomial logistic regression evaluating independent baseline predictors of six-month functional trajectory in patients with mild to moderate traumatic brain injury (GCS 9–15). "Stable" served as the reference category. Odds ratios (ORs), 95% confidence intervals (CIs), and p-values are shown for comparisons between Regressing and Recovering groups versus Stable. GCS = Glasgow Coma Scale; HTN = Hypertension; DM = Diabetes Mellitus; CVA/CVD = Cerebrovascular disease/Cardiovascular disease; SAH = Subarachnoid hemorrhage; IVH = Intraventricular hemorrhage; SDH = Subdural hematoma; EDH = Epidural hematoma; BSFx = Basal skull fracture; DSFx = Depressed skull fracture; LOS = Length of Stay; INR = International Normalized Ratio; SBP = Systolic Blood Pressure; BS = Blood Sugar. Significant p-values (< 0.05) are bolded. Supplementary Table 5. Multivariate multinomial logistic regression of independent baseline predictors in severe TBI patients (including hospital LOS) Severe TBI, GCS 3 – 8 (n = 1075) Variables Recovering Regressing p-value OR 95% CI p-value OR 95% CI Age (40 – 59) 0.610 1.098 0.766, 1.573  0.001 3.347 1.956, 5.727 Age (60 – 74) 0.730 0.901 0.496, 1.634 0.002 3.545 1.613, 7.791 Age (75 and older) 0.383 0.505 0.109, 2.345 0.008 7.846 1.721, 35.773 Pupils (anisocoria) 0.247 1.313 0.828, 2.080 0.531 0.757 0.316, 1.811 Pupils (bilateral fixed) 0.393 1.184 0.803, 1.747 0.018 2.006 1.127, 3.572 Pupils (uncheckable) 0.418 0.803 0.472, 1.366 0.848 0.912 0.357, 2.329 Mechanism (motor vehicle) 0.386 0.816 0.516, 1.292 0.581 1.247 0.570, 2.728 Mechanism (pedestrian) 0.260 0.731 0.423, 1.262 0.819 1.107 0.465, 2.636 Mechanism (others) 0.546 0.816 0.422, 1.579 0.492 1.484 0.481, 4.575 HTN 0.574 1.329 0.493, 3.586 0.114 2.470 0.805, 7.582 DM 0.629 1.260 0.493, 3.217 0.697 1.266 0.386, 4.144 CVA/CVD 0.684 1.719 0.126, 23.417 0.304 3.901 0.291, 52.340 SAH 0.107 1.275 0.949, 1.713 0.194 1.381 0.849, 2.247 IVH 0.050 1.521 1.000, 2.312 0.016 2.142 1.149, 3.993 BSFx 0.020 1.396 1.053, 1.850 0.862 1.043 0.646, 1.684 Pneumocephalus 0.015 0.574 0.366, 0.898 0.257 1.478 0.752, 2.903 EDH 0.814 0.959 0.679, 1.355 0.054 0.518 0.265, 1.012 SDH 0.705 0.940 0.684, 1.293 0.940 1.021 0.603, 1.729 ICH 0.4007 1.125 0.852, 1.485 0.269 1.303 0.815, 2.082 Cisterns status (absent) 0.184 1.394 0.854, 2.275 0.370 1.406 0.667, 2.963 Cisterns status (compressed) 0.686 1.109 0.670, 1.837 0.875 0.935 0.407, 2.150 Hospital LOS  0.001 1.023 1.014, 1.032  0.001 1.038 1.027, 1.050 GCS 0.033 0.907 0.829, 0.992 0.038 0.858 0.743, 0.992 Random BS, mg/dl 0.130 1.002 0.999, 1.004 0.410 0.998 0.994, 1.002 PTT, seconds 0.024 1.021 1.003, 1.040 0.035 1.029 1.002, 1.056 Hemoglobin, g/dl 0.445 1.025 0.963, 1.091 0.453 0.961 0.866, 1.066 SBP, mmHg 0.345 1.003 0.997, 1.009 0.867 1.001 0.991, 1.011 Multivariate multinomial logistic regression evaluating independent baseline predictors of six-month functional trajectory in patients with severe traumatic brain injury (GCS 3–8). "Stable" served as the reference category. Odds ratios (ORs), 95% confidence intervals (CIs), and p-values are shown for comparisons between Regressing and Recovering groups versus Stable. GCS = Glasgow Coma Scale; HTN = Hypertension; DM = Diabetes Mellitus; CVA/CVD = Cerebrovascular disease/Cardiovascular disease; SAH = Subarachnoid hemorrhage; IVH = Intraventricular hemorrhage; SDH = Subdural hematoma; EDH = Epidural hematoma; ICH = Intracerebral hemorrhage; BSFx = Basal skull fracture; LOS = Length of Stay; PTT = Partial Thromboplastin Time; SBP = Systolic Blood Pressure; BS = Blood Sugar. Significant p-values (< 0.05) are bolded. 2. The statistical method for variable selection is flawed. Authors use univariate analysis and include all variables with p<0.20 for the multivariate analysis. This approach will lead to missing potentially important variables if they are confounded by others and should be included regardless of p-value. I would suggest the authors use existing literature (e.g. CRASH and IMPACT models) and their knowledge of the subject matter to inform selection. In addition they could consider stepwise inclusion/exclusion of covariates guided by AIC/BIC or penalised regression. Response: We thank the reviewer for this important methodological comment. We agree that reliance solely on univariate p-value thresholds for variable selection may risk excluding clinically relevant predictors, particularly in the presence of confounding. However, we note that the use of a liberal threshold (e.g., p<0.20) for initial variable screening is a commonly applied approach in epidemiological modeling, especially prediction models with a wide set of variables, intended to reduce the likelihood of prematurely excluding potentially important variables that may become significant in multivariable analyses. To address the reviewer’s concern more comprehensively, we have now: 1. Retained the original modeling approach using univariate screening with a liberal threshold, while clarifying its rationale in the Methods section. 2. Conducted additional sensitivity analyses in which covariate selection was based on clinical relevance and prior evidence, informed by established TBI prognostic models such as CRASH and IMPACT. 3. Added these results to the manuscript (Supplementary Tables 4 and 6), demonstrating that the findings were consistent across both approaches. We believe this combined approach strengthens the robustness and transparency of our analysis, and we are grateful to the reviewer for prompting this improvement. “Candidate variables for multivariable modeling were initially selected based on univariate analysis using a liberal threshold (p<0.20). This approach is commonly used in epidemiological research to avoid excluding potentially important variables that may not show strong univariate associations but could become significant in multivariable contexts due to confounding or interaction effects. Indeed, prior methodological studies recommend using higher p-value thresholds (e.g., 0.15-0.25) during initial screening to minimize the risk of omitting relevant predictors (Bursac, Gauss, Williams, & Hosmer, 2008; Chowdhury & Turin, 2020). However, recognizing the limitations of purely data-driven selection methods, we conducted additional sensitivity analyses in which covariate selection was based on clinical relevance and prior evidence, informed by established TBI prognostic models (e.g., CRASH and IMPACT).” “Additional sensitivity analyses using clinically selected covariates based on the CRASH and IMPACT prognostic models yielded broadly consistent findings (Supplementary Table 4). Recovery was independently associated with age ≥75 years (OR = 2.586, p < 0.001), SAH (OR = 1.581, p = 0.001), absent cisterns (OR = 2.668, p = 0.001), lower GCS scores (OR = 0.825, p < 0.001), higher admission BS (OR = 1.004, p < 0.001), and lower Hb levels (OR = 0.931, p = 0.020). Regression was independently associated with older age across all age categories, lower GCS scores (OR = 0.651, p < 0.001), lower Hb levels (OR = 0.863, p = 0.015), and absence of EDH, as EDH remained protective against regression (OR = 0.258, p = 0.005). SAH showed a borderline association with regression but did not reach statistical significance.” “Sensitivity analyses using clinically selected CRASH/IMPACT-based covariates also supported the primary findings in sTBI patients (Supplementary Table 6). In this model, recovery was independently associated only with lower GCS scores (OR = 0.871, p = 0.002) and higher admission BS (OR = 1.002, p = 0.047). Regression was independently associated with older age, bilateral fixed pupils (OR = 2.239, p = 0.004), and lower GCS scores (OR = 0.791, p < 0.001). SAH (p = 0.051), EDH (p = 0.067), and absent cisterns (p = 0.092) showed borderline associations but did not reach statistical significance.” Furthermore, we acknowledge that stepwise and penalised regression approaches can be useful for data-driven variable selection. However, automated stepwise procedures are not fully supported for multinomial logistic regression in SPSS, which was used in this study. Future studies using alternative statistical platforms may further explore penalised regression approaches. Supplementary Table 4. Multivariate multinomial logistic regression of independent baseline predictors in mild to moderate TBI patients (selecting variables based on CRASH and IMPACT models) Mild to Moderate TBI, GCS 9 – 15 (n = 1873) Variables Recovering Regressing p-value OR 95% CI p-value OR 95% CI Age (40 – 59) 0.304 0.841 0.605, 1.170  0.001 5.601 2.487, 12.612 Age (60 – 74) 0.318 1.222 0.824, 1.813  0.001 8.504 3.481, 20.776 Age (75 and older)  0.001 2.586 1.621, 4.126  0.001 35.185 14.625, 84.684 Pupils (anisocoria) 0.480 0.787 0.404, 1.531 0.274 0.315 0.040, 2.498 Pupils (bilateral fixed) 0.849 0.902 0.312, 2.611 0.767 1.286 0.244, 6.780 Pupils (uncheckable) 0.499 1.171 0.741, 1.853 0.186 0.529 0.206, 1.359 SAH 0.001 1.581 1.199, 2.084 0.069 1.670 0.961, 2.901 EDH 0.085 0.763 0.561, 1.038 0.005 0.258 0.100, 0.665 Midline shift (> 5 mm) 0.251 1.294 0.833, 2.012 0.811 1.114 0.461, 2.689 Cisterns status (absent) 0.001 2.668 1.463, 4.869 0.554 1.606 0.335, 7.705 Cisterns status (compressed) 0.728 0.892 0.468, 1.700 0.986 0.990 0.315, 3.106 GCS  0.001 0.825 0.774, 0.879  0.001 0.651 0.569, 0.745 Random BS, mg/dl  0.001 1.004 1.002, 1.006 0.620 1.001 0.997, 1.005 SBP, mmHg 0.669 0.999 0.992, 1.005 0.371 1.005 0.994, 1.017 Hemoglobin, g/dl 0.020 0.931 0.877, 0.989 0.015 0.863 0.767, 0.972 Multivariate multinomial logistic regression evaluating independent baseline predictors of six-month functional trajectory in patie Attachments Attachment Submitted filename: Response to the Reviewers.docx https://doi.org/10.1371/journal.pone.0353189.r002
21 Jun 2026 Decision Letter - Chinh Quoc Luong, Editor Complex patterns of functional change among TBI survivors from discharge to 6-month follow-up: findings from a registry-based cohort study PONE-D-26-08416R1 Dear Dr. Tabrizi, We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements. Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication. An invoice will be generated when your article is formally accepted. Please note, if your institution has a publishing partnership with PLOS and your article meets the relevant criteria, all or part of your publication costs will be covered. Please make sure your user information is up-to-date by logging into Editorial Manager at Editorial Manager® and clicking the ‘Update My Information' link at the top of the page. For questions related to billing, please contact billing support. If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org. Kind regards, Chinh Quoc Luong, MD., PhD. Academic Editor PLOS One Additional Editor Comments (optional): Reviewers' comments: Reviewer's Responses to Questions -->Comments to the Author 1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.--> Reviewer #1: All comments have been addressed ******** -->2. Is the manuscript technically sound, and do the data support the conclusions? The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented. --> Reviewer #1: (No Response) ****** -->3. Has the statistical analysis been performed appropriately and rigorously? --> Reviewer #1: (No Response) ****** -->4. Have the authors made all data underlying the findings in their manuscript fully available? The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.--> Reviewer #1: (No Response) ****** -->5. Is the manuscript presented in an intelligible fashion and written in standard English? PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.--> Reviewer #1: (No Response) ****** -->6. Review Comments to the Author Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)--> Reviewer #1: (No Response) ****** -->7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files. If you choose “no”, your identity will remain anonymous but your review may still be made public. Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.--> Reviewer #1: No ******** https://doi.org/10.1371/journal.pone.0353189.r003
Formally Accepted
Acceptance Letter - Chinh Quoc Luong, Editor PONE-D-26-08416R1 PLOS One Dear Dr. Tabrizi, I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS One. Congratulations! Your manuscript is now being handed over to our production team. At this stage, our production department will prepare your paper for publication. This includes ensuring the following: * All references, tables, and figures are properly cited * All relevant supporting information is included in the manuscript submission, * There are no issues that prevent the paper from being properly typeset You will receive further instructions from the production team, including instructions on how to review your proof when it is ready. Please keep in mind that we are working through a large volume of accepted articles, so please give us a few days to review your paper and let you know the next and final steps. Lastly, if your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org. You will receive an invoice from PLOS for your publication fee after your manuscript has reached the completed accept phase. If you receive an email requesting payment before acceptance or for any other service, this may be a phishing scheme. Learn how to identify phishing emails and protect your accounts at https://explore.plos.org/phishing. If we can help with anything else, please email us at customercare@plos.org. Thank you for submitting your work to PLOS ONE and supporting open access. Kind regards, PLOS ONE Editorial Office Staff on behalf of Assoc. Prof. Chinh Quoc Luong Academic Editor PLOS One https://doi.org/10.1371/journal.pone.0353189.r004

Open letter on the publication of peer review reports

PLOS recognizes the benefits of transparency in the peer review process. Therefore, we enable the publication of all of the content of peer review and author responses alongside final, published articles. Reviewers remain anonymous, unless they choose to reveal their names.

We encourage other journals to join us in this initiative. We hope that our action inspires the community, including researchers, research funders, and research institutions, to recognize the benefits of published peer review reports for all parts of the research system.

Learn more at ASAPbio .