Surgical Screening Protocol for Craniocervical Instability Secondary to Ehlers-Danlos Syndrome and other Connective Tissue Disorders: Analysis of a 347 Patient Case Series

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Bloom, John B. Biggins, Andrew Brodbelt, Misao Nishikawa, and 12 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7675903/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 12 Mar, 2026 Read the published version in Neurosurgical Review → Version 1 posted 14 You are reading this latest preprint version Abstract Background Evaluation of craniocervical instability (CCI) in individuals with connective tissue disorders (CTDs) remains controversial. We present a surgical screening protocol created and implemented at our institution for these individuals. Methods We reviewed patients referred to our institution for CCI secondary to CTDs, between May 2018 and April 2022 using our two-stage protocol. Stage 1 included: history, clinical questionnaire, physical examination, non-invasive provocative testing, neuroimaging with morphometric analysis, Karnofsky Performance Scale. Items 1–5 were each scored on a scale from 0 to 2. Individuals with a KPS ≤ 70 and an aggregate score ≥6 were recommended for Stage 2, which included additional neuroimaging, psychiatric evaluation, and a trial of intraoperative craniocervical traction (ICT) with clinical and morphometric scores. Individuals meeting criteria in both stages were considered surgical candidates. Postoperative outcomes were assessed. Results Of the 347 individuals who entered Stage 1, 190 progressed through Stage 2. Following advanced evaluation, 115 patients met full surgical qualification criteria, with 95 proceeding to craniocervical fusion (CCF), and 86.4% reporting satisfaction on the NASS satisfaction index. An additional 12 patients were offered surgery due to marked clinical improvement during ICT despite borderline morphometric findings, with 70% reporting satisfaction on the NASS index postoperatively. Conclusions We present a two-stage surgical evaluation protocol for CCI secondary to CTDs. ICT served as a critical diagnostic and prognostic tool, clarifying the biomechanical contribution of CCI to symptomatology and aiding in the identification of appropriate surgical candidates. Further multicenter studies are warranted to validate this approach. Craniocervical Instability Craniocervical Fusion Intraoperative Craniocervical Traction Connective Tissue Disorders Ehlers-Danlos Syndrome Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Introduction The functional mobility of the craniocervical junction (CCJ) depends on its ligamentous structures [8,26]. Craniocervical Instability (CCI) may be congenital or acquired secondary to various pathologies, including trauma, neoplasms (e.g., chordoma), inflammatory diseases (e.g., rheumatoid arthritis, systemic lupus erythematosus), infection (e.g., Grisel’s syndrome), and connective tissue disorders (CTDs) [7-9]. CCI in individuals with CTDs presents unique diagnostic and surgical challenges [1-3,5,6,10,27], often manifesting with debilitating symptoms that appear disproportionate to findings on conventional neuroimaging and neurological examination—unlike other etiologies such as rheumatoid arthritis. A range of non-invasive diagnostic tools have been proposed to address these challenges, including morphometric analysis, dynamic imaging, trials of cervical collars or traction, cervicothoracic orthoses, and halo jackets [3,10]. Prior work underscores the need for a tailored protocol that reflects the distinct pathophysiology of CCI in individuals with CTDs. In response, we developed and evaluated a structured protocol designed to support clinical decision-making and guide management in this complex population. Materials & Methods Patient Selection and Study Design From May 2018 to April 2022, we evaluated individuals with a genetic and/or clinical diagnosis of CTDs who were referred to our institution for assessment and management of suspected CCI. Individuals with radiologically obvious CCI pathologies on prior neuroanatomic imaging were excluded from this study. Evaluation for CCI and potential surgical intervention was conducted using a two-stage protocol, as outlined below. Stage 1 (Initial Screening) consisted of six components: (1) a detailed history focused on features suggestive of CCI [10]; (2) a standardized questionnaire assessing signs and symptoms of CCI, as well as comorbidities commonly associated with CTDs [5,10];(3) a physical examination; (4) non-invasive provocative testing; (5) initial neuroanatomic imaging of the CCJ with morphometric analysis based on previously validated criteria in this population [12,15];and (6) assessment of functional status using the Karnofsky Performance Scale (KPS) [11]. With the exception of the KPS, each component was scored on a scale of 0 to 2, with 0 indicating no suspicion for CCI, 1 indicating intermediate suspicion, and 2 indicating strong suspicion. Individuals with a KPS score of 70 (i.e., patient cares for self, but unable to carry on normal activity or to do active work) or less (related to their chief complaints) and an aggregate screening score of 6 or greater were recommended to proceed to Stage 2 (Advanced Evaluation). In contrast, those with a score below 6 and/or a KPS greater than 70 were advised to pursue conservative management. Stage 2 (Advanced Evaluation) involved a comprehensive diagnostic workup to evaluate surgical candidacy. This included CT angiogram of the CCJ, medical and cardiac clearances and double psychiatric evaluation and clearance as described below. Following completion of the above screening steps, candidates underwent a trial of ICT, which was evaluated using a defined scoring system (outlined below). Individuals who met criteria in both Stage 1 and Stage 2 and demonstrated positive scores on both components of the ICT assessment were deemed surgical candidates for craniocervical fusion (CCF). Diagnostic Intake Tool As part of Stage 1 screening, individuals completed a diagnostic intake tool developed internally for patients with CTDs. (Supplementary Material 1) Psychiatric Clearance All individuals underwent psychiatric evaluation by two independent trained professionals —an outside mental health specialist local to the individual and a neuropsychologist at our institution. These evaluations were essential not only to identify established psychiatric comorbidities that can be associated with CTDs—such as anxiety disorders, depression, personality disorder, obsessive-compulsive disorder, and mood disorders—but also to further assess the patient’s subjective symptom burden. These evaluations aimed to distinguish between symptoms arising from underlying pathophysiology and those potentially influenced or amplified by psychological factors. Particular attention was given to evaluating how psychological factors may influence the perception of pain and other symptoms, as well as the patient’s ability to cope with the postoperative recovery process. Findings from both evaluations were integrated into the multidisciplinary surgical planning to ensure appropriate support and risk stratification. Additional details can be found in Supplementary Material 2 Imaging All imaging studies were reviewed using a commercial electronic platform ( OsiriX; Pixmeo, Switzerland) [20]. ICT Protocol Following informed consent, Gardner-Wells tongs were applied in the operating room, and the patient was placed in a sitting position after a baseline neurological exam. Lateral-view digital fluoroscopic imaging of the CCJ was obtained in neutral, flexion, and extension positions. After baseline documentation of signs and symptoms, the tongs were connected to a rope-and-pulley system and an initial vertical traction force of 20 pounds was applied. Traction was gradually increased every 10 minutes as tolerated, up to a maximum of 35 pounds (or 40 pounds in individuals with a strong athletic build). At each increment, patients were asked to report any change—positive, negative, or none—in each of their pre-identified symptoms and/or signs, expressed subjectively as a percentage relative to baseline (e.g., “10% worse,” “90% better,” or “no change”). Fifteen minutes after reaching the final traction level, follow-up digital fluoroscopic images of the CCJ were obtained, along with a repeat neurological examination. An example of the clinical and morphometric data obtained during ICT is presented (Table 1). The ICT set-up and testing are illustrated (Figure 1). Further technical details are provided in Supplementary Material 3. Table 1. Example of Data Collected During Intraoperative Craniocervical Traction (ICT). Illustrative patient case showing percentage improvement in pre-identified signs and symptoms at incremental traction weights, as reported by the patient, alongside changes in neurological examination findings. Corresponding morphometric measurements of the craniocervical junction are shown for both pre-traction and peak-traction states. Morphometric Measurements Biomechanical assessment of CCI was performed using four established morphometric parameters: the basion-dens interval (BDI), basion-axial interval (BAI), Grabb-Oakes measurement (pB-C2 distance), and the clivo-axial angle (CXA) [18,19]. Technical details are provided in Supplementary Material 4. Static measurements were obtained from MRI during Stage 1 and compared against established normative values. Dynamic measurements—acquired both at pre-traction and at peak traction—were obtained during ICT using calibrated digital fluoroscopy ( Iso-C, Siemens, Germany). Calibration was performed against a known object placed in the midsagittal plane. The difference between each morphometric value at peak traction and its corresponding pre-traction measurement was defined as the translational value. These translational changes were evaluated against established normal reference ranges and predefined surgical thresholds (Table 2). Table 2. Normal Values for Morphometric Measurements. Normal reference ranges and predefined surgical thresholds for morphometric parameters used in the biomechanical assessment of craniocervical instability (CCI), including the basion-dens interval (BDI), basion-axial interval (BAI), Grabb-Oakes measurement (pB–C2 distance), and clivo-axial angle (CXA). Scoring of the ICT Test The ICT Clinical Score was considered positive if most or all of the patient’s chief CCI-related signs and symptoms improved by ≥75% at peak traction compared with the pre-traction baseline. The ICT Morphometric Score was considered positive when one or more of the following criteria were met: (1) a ≥2 mm increase in the translational BDI, and/or (2) a ≥4 mm change in the BAI or pB–C2, observed on flexion/extension images or during traction. Patients with both a positive ICT Clinical Score and a positive ICT Morphometric Score met our criteria for CCF surgery. CCF Procedure Instead of a traditional barplate construct, our CCF technique utilized condylar screws at C0, lateral mass screws at C1, and pedicle screws at C2, connected by two short rods and overlaid with a bone fusion matrix [25]. Postoperative Monitoring and Outcome Questionnaire Patients were routinely evaluated at 6 and 12 months postoperatively, with additional follow-up conducted on a PRN basis thereafter. A custom-designed postoperative outcome questionnaire was distributed as a one-time, simultaneous mailing in March 2023 to all individuals who had undergone CCF. The complete questionnaire is provided in Supplementary Material 5. For the purposes of this study, analyses were limited to sign and symptom changes and the North American Spine Surgery (NASS) Patient Satisfaction Index [16]. Comprehensive evaluation of the full dataset will be presented in a subsequent publication focused on long-term CCF outcomes. Statistical Analysis We retrospectively collected data from the electronic medical record and performed analyses using Microsoft Excel and GraphPad Prism. Individuals with incomplete medical records were excluded. Morphometric variables measured at pre- and peak-traction were compared using two-tailed t -tests. Changes in patient-reported signs and symptoms between pre-traction, peak-traction, and post-surgical states were evaluated using McNemar’s test, with calculations performed in R (RStudio, Posit PBC). Statistical significance was defined as a p -value < 0.05. Research Reporting Guidelines This retrospective study was approved by the Institutional Review Board and the Intramural Protocol Review Committee for Clinical Research at Mount Sinai South Nassau Hospital. The study was conducted in accordance with institutional ethical standards, the Declaration of Helsinki, and the STROBE-PROCESS 2023 reporting guidelines [14,28]. No AI-assisted copy editing was used in this manuscript. Results Enrollment in Stage 1 From May 2018 to April 2022, 347 individuals with a clinical and/or genetic diagnosis of a CTD were referred to our institution for evaluation of CCI (mean age 37 ± 12 years; 87.3% female). All individuals were enrolled in Stage 1 of the protocol (Figure 2a). Chiari I malformation was present as a comorbidity in 33.2% of patients. Ehlers–Danlos Syndrome (EDS) was the most common CTD diagnosis (75.3%), although many individuals exhibited mixed CTD phenotypes. Regardless of the specific CTD subtype, CCI emerged as a final common pathway. Enrollment in Stage 2 Of the individuals who entered Stage 1, 254 met criteria to proceed to Stage 2, and 190 completed the advanced evaluation. Surgical Qualification The 190 individuals who completed Stage 2 were categorized into four subgroups based on whether they met surgical criteria and elected to proceed with CCF surgery. Subgroup 1 (n = 63) did not meet criteria for CCF surgery. Subgroup 2 (n = 12) had borderline morphometric scores on ICT but were offered surgery based on remarkable improvements in signs and/or symptoms during ICT, and proceeded with CCF surgery at our center. Subgroup 3 (n = 95) met full surgical criteria and underwent CCF surgery. Subgroup 4 (n = 20) met surgical criteria but did not undergo surgery at our institution. (Supplementary Material 6) Stage 2 (Advanced Evaluation) procedures and subgroup allocation are summarized in the flowchart (Figure 2b). Subgroup 1 was further analyzed to identify which components of the advanced evaluation led to disqualification from surgery. (Supplementary Material 7) Exceptions to surgical qualification were made for Subgroup 2 based on specific clinical considerations. Although these 12 individuals narrowly missed the ICT morphometric threshold for BDI by a fraction of a millimeter, 6 exhibited marked improvement in neurological deficits at peak traction, while the remaining 6 experienced striking relief of their baseline chief complaints during traction. Signs and Symptoms Table 3 summarizes the most common presenting signs and symptoms reported by individuals on the diagnostic intake tool at the time of enrollment in Stage 1, limited to those who ultimately completed Stage 2. (Table 3) Figure 3 illustrates common pre-traction signs and symptoms in individuals who completed Stage 2 (Advanced Evaluation) that demonstrated the greatest improvement with peak traction, showing the number of patients who experienced more than 75% symptom relief. (Figure 3). Table 3. Common presenting signs and symptoms at Stage 1 enrollment among individuals completing Stage 2 Most common presenting signs and symptoms reported on the diagnostic intake tool at Stage 1 enrollment among individuals who completed Stage 2, (n=190) presented in decreasing order of frequency. Morphometric Analysis Key morphometric parameters—including BDI, BAI,pB–C2 distance, and CXA—were measured both pre-traction and at peak-traction. All four morphometric parameters showed statistically significant changes from pre-traction to peak traction during ICT ( p -value < 0.001 for all). (Figure 4 and Supplementary Material 8) Complications of the ICT Procedure No patients who underwent ICT experienced direct complications from the application of tongs or weights, such as skull fractures, dislocations, hemorrhages, brain injuries, or cerebrospinal fluid leaks. Two patients with previously documented severe CCI who qualified for CCF at the conclusion of the screening process developed intense and persistent rebound symptoms following completion of ICT. After a period of observation, both proceeded to CCF surgery during the same hospitalization, with resolution of rebound symptoms and their initial chief complaints postoperatively. Outcomes of CCF Of the 107 surgical patients (Subgroups 2 and 3), 98 completed the NASS Patient Satisfaction Index [16] via a one-time postoperative questionnaire, administered at a mean of 2.4 ± 1 years after surgery. Satisfaction (NASS score 1 or 2) was reported by 70.0% of Subgroup 2 and 86.4 % of Subgroup 3, indicating that surgery met expectations or provided sufficient benefit to warrant the same procedure again (Figure 5 and Supplementary Material 9) The same questionnaire also documented changes in preoperative signs and symptoms. At follow-up, a substantial proportion of patients reported ≥75% improvement in many of their preoperative symptoms (Figure 6a). Discussion We developed and implemented a two-stage surgical screening and evaluation protocol for individuals with suspected CCI secondary to CTDs. This protocol evolved over years of clinical experience with this complex patient population and was designed to integrate multiple layers of evaluation—beginning with initial screening and followed by advanced assessment. Our goal was to create a stringent, multidimensional framework that improves upon prior screening methods by synthesizing previously disparate clinical, functional, and radiographic data into a cohesive profile to guide decision-making. While no single component of the protocol is sufficient in isolation, ICT offered particularly valuable diagnostic and prognostic insight. ICT served as a dynamic adjunct to the broader assessment, revealing functional biomechanical instability that may be overlooked by static imaging modalities and routine clinical examination. Controversies of CCI in Patients with CTDs In our experience, individuals with CTDs may present across a wide clinical spectrum, ranging from high-performance athletes to individuals who are severely debilitated or bedridden [13,23]. Paradoxically, some asymptomatic individuals may exhibit marked hypermobility of the CCJ, while others with profound neurological compromise may show minimal or no abnormalities on standard neuroanatomic imaging. While CCI is increasingly recognized as a potential cause of neurological dysfunction in individuals with CTDs, variability in clinical presentation and uncertainty surrounding optimal management continue to pose challenges. Additionally, many of these individuals present with complex Chiari malformations [4,17,22,24,29], further complicating diagnosis and treatment. This heterogeneity has contributed to ongoing controversy regarding when CCJ hypermobility should be considered pathologic and when surgical intervention is appropriate. Notably, the presence of hypermobility—often misinterpreted as instability on dynamic imaging when assessed in isolation—should not be considered synonymous with pathological instability. The Problem of Surgical Screening In a recent review article, Lohkamp et al . recommended that surgical intervention for suspected CCI in individuals with CTDs should be considered only when both clear radiographic evidence of instability and concordant clinical symptoms are present [12].It was also highlighted that a 4-6 week trial of hard collar cervical immobilization may represent a valuable adjunctive strategy for surgical selection in this population. Between 1998 and 2004, in an effort to develop a reliable surgical screening protocol for this population, we tested a variety of dynamic non-invasive diagnostic tools (ranging from cervical collar trials to dynamic imaging and intermittent traction) [3,10]to evaluate CCI in CTD patients. However, we found these methods to be limited by significant technical, anatomic, and mechanical constraints, as well as an inability to objectively assess vertical instability. These shortcomings ultimately led us to incorporate ICT as a dynamic diagnostic modality, which has since become a cornerstone of our surgical screening protocol by providing real-time insight into functional instability and symptom reversibility under controlled conditions. The Role of ICT In 2004, we incorporated the ICT technique, commonly used in trauma settings, into our surgical screening protocol and paired it with morphometric analysis. This adaptation combined the provocative diagnostic utility of ICT with objective, real-time measurements, allowing us to correlate morphometric changes with both patient-reported symptomatic improvements and neurologic examination findings. This approach enabled us to distinguish non-pathologic CCJ hypermobility (i.e., hypermobility without symptom provocation or relief during controlled traction) from clinically significant, pathologic CCI. It also provided objective criteria to guide surgical qualification. Importantly, morphometric data obtained at peak traction informed intraoperative positioning during CCF, improving surgical precision (Figure 6b). Additionally, this protocol enhanced our understanding of vertical instability—aka. cranial settling—as a critical component of CCI in this patient population. Biomechanics of the CCJ and Cranial Settling Cranial settling has been described in pathologies which disrupt the anatomic integrity of the bony elements of the CCJ, such as neoplasms, trauma, rheumatoid arthritis, and infections [21]. Historically, CTDs have not been considered causes of cranial settling. However, our study using ICT demonstrates that ligamentous compromise of the CCJ in CTDs, typically in the absence of overt bony pathology, can indeed result in vertical instability or cranial settling. Importantly, surgical correction of this instability was associated with improvement and/or resolution of related neurological signs and symptoms. Moreover, our data suggest that dynamic cranial settling and brainstem or neurovascular compression may underlie the frequent discordance between static neuroanatomic imaging and the severity of clinical presentation in this patient population. The intrinsic validity of the morphometric component of the ICT score in the surgical qualification process was supported by the significant difference in postoperative NASS satisfaction scores observed between Subgroups 2 and 3 (70.0% vs. 86.4%, respectively). Limitations of this Study This study reflects the experience of a single surgeon at a single institution specializing in the evaluation and treatment of patients with CTDs and CCI. As such, inter- and intra-observer variability may arise if this protocol is implemented at other centers. While the morphometric measurements and neurological examination findings assessed during the ICT procedure are objective, patient-reported symptoms and perceived symptom improvement are inherently subjective. To mitigate this potential source of bias, patients underwent two independent psychiatric evaluations and were asked to quantify their perceived improvement as a percentage change from baseline. Conclusions The evaluation and management of CCI secondary to CTDs remains a subject of ongoing controversy, with debate surrounding diagnostic protocols and surgical selection criteria fueling understandable skepticism. In this study, we present our institutional experience using a structured surgical screening protocol specifically developed to assess CCI in individuals with CTDs, with the goal of introducing greater diagnostic clarity and rigor to clinical decision-making. Among all components of the protocol, ICT proved to be the most revealing, offering unique biomechanical insights not captured by static imaging or conventional assessments. While this represents a preliminary, single-surgeon, single-center experience, we strongly believe that further multicenter studies are warranted. We are encouraged that the initial CCF outcome data reported here support the clinical utility of our screening protocol. Looking ahead, we anticipate that future studies—particularly those evaluating surgical outcomes in patients selected using this protocol—will help resolve ongoing controversies in the field. In addition, we are currently initiating a randomized crossover study at our institution comparing surgical and conservative treatment strategies in this population, which we believe will offer critical insight into optimal care pathways moving forward. ABBREVIATIONS BAI = Basion Axial Interval ; BDI = Basion Dens Interval ; CXA = Clivo Axial Angle ; CCF = Craniocervical Fusion ; CCI = Craniocervical Instability ; CCJ = Craniocervical Junction ; CTA = Computed Tomography Angiography ; CTD = Connective Tissue Disorders ; EDS = Ehlers-Danlos Syndrome ; ICT = Intraoperative Craniocervical Traction; KPS = Karnofsky Performance Scale ; pB–C2 = Perpendicular to the Basion to C2 Line (Grabb-Oakes measurement); NASS = North American Spine Surgery Satisfaction Index Declarations Funding This work was supported by a generous Gift provided by the Canerector Foundation. Acknowledgements: We would like to acknowledge the patients who trusted us with their care. We would also like to acknowledge Dr. Thomas H. Milhorat for his mentorship and Dr. Roger W. Kula for his example. Competing Interests The authors have no relevant financial or non-financial interests to disclose. Authors Contributions Paolo A Bolognese—conceptualization, drafting original manuscript, writing, revising the manuscript, data collection, data analysis/interpretation, patient care, supervision, resources Allison R Bloom—conceptualization, revising the manuscript John B Biggins—conceptualization, data collection, data analysis/interpretation, revising the manuscript Andrew Brodbelt—conceptualization, data analysis/interpretation, revising the manuscript Misao Nishikawa—conceptualization, data analysis/interpretation, revising manuscript Mansoor Foroughi—conceptualization, revising the manuscript Ilene S Ruhoy—conceptualization, drafting the original manuscript, data analysis/interpretation, data collection, revising the manuscript Randall Dass—conceptualization, data analysis/interpretation, revising the manuscript Kamil Rohana—conceptualization, data collection, data analysis/interpretation, revising the manuscript Jeffrey D Wood--data collection, data analysis/interpretation, drafting original manuscript, revising the manuscript David Putrino—resources and supervision, revising the manuscript Veit Rohde—revising the manuscript Christoph Bettag—revising the manuscript Shawn Belverud—revising the manuscript Travis Caton—conceptualization, data analysis/interpretation, revising the manuscript Tanvir Choudhri—supervision, revising the manuscript Ethics approval Research Reporting Guidelines This study was conducted in accordance with the Declaration of Helsinki and adhered to the STROBE and PROCESS 2023 reporting guidelines. IRB approval The retrospective record review pertinent to this study was approved by the Internal Review Board of the two Institutions where the procedures took place: (IRB #13-655B: North Shore University Hospital – Northwell, Manhasset, NY; WIRB #1276110 and WIRB #1262008: Mount Sinai South Nassau – Oceanside, NY). Consent to participate Standard informed consent was given by the patients for all surgical procedures. Clinical Trial Number: Not applicable Consent to publish The authors affirm that human research participants provided informed consent for publication of the images in Figures 1a, and 1b. References Beighton P, de Paepe A, Danks D, Finidori G, Gedde-Dahl T, Goodman R, Hall JG, Hollister DW, Horton W, McKusick VA, et al. (1988) International Nosology of Heritable Disorders of Connective Tissue, Berlin, 1986. 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J Neurosurg Spine 14:697-709. doi:10.3171/2011.1.SPINE10612 Veatch OJ, Steinle J, Hossain WA, Butler MG (2022) Clinical genetics evaluation and testing of connective tissue disorders: a cross-sectional study. BMC Med Genomics 15:169. doi:10.1186/s12920-022-01321-w von Elm E, Altman DG, Egger M, Pocock SJ, Gotzsche PC, Vandenbroucke JP, Initiative S (2008) The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies. J Clin Epidemiol 61:344-349. doi:10.1016/j.jclinepi.2007.11.008 Zhao DY, Rock MB, Sandhu FA (2022) Craniocervical Stabilization After Failed Chiari Decompression: A Case Series of a Population with High Prevalence of Ehlers-Danlos Syndrome. World Neurosurg 161:e546-e552. doi:10.1016/j.wneu.2022.02.068 Additional Declarations No competing interests reported. Supplementary Files SUPPLEMENTARYMATERIAL1ClinicalIntaketool.dotx SUPPLEMENTARYMATERIAL2Psychiatricclearancequestions.docx SUPPLEMENTARYMATERIAL3ICTprotocoltechnicaldetails.docx SUPPLEMENTARYMATERIAL4Morphometricshowtodoit.docx SupplementaryMaterial4aRaw.tif SupplementaryMaterial4bContour.tif SupplementaryMaterial4cBDI.tif SupplementaryMaterial4dBAI.tif SupplementaryMaterial4epBC2.tif SupplementaryMaterial4fCXA.tif SupplementaryMaterial4gCompleteMorphometrics.tif SUPPLEMENTARYMATERIAL5Postopoutcometool.docx SUPPLEMENTARYMATERIAL6Subgroup4andtheiroutcomes.docx SUPPLEMENTARYMATERIAL7Subgroup1failures.docx SupplementaryMaterial8Boxplotmorphosbysubgroups.tif SUPPLEMENTARYMATERIAL9NASSdatabyindividualpatients.docx SUPPLEMENTARYMATERIAL10RawdataoftheICTpatients.xlsx Cite Share Download PDF Status: Published Journal Publication published 12 Mar, 2026 Read the published version in Neurosurgical Review → Version 1 posted Editorial decision: Revision requested 21 Dec, 2025 Reviews received at journal 21 Dec, 2025 Reviewers agreed at journal 21 Dec, 2025 Reviewers agreed at journal 15 Dec, 2025 Reviewers agreed at journal 15 Dec, 2025 Reviews received at journal 14 Dec, 2025 Reviewers agreed at journal 13 Dec, 2025 Reviews received at journal 08 Dec, 2025 Reviewers agreed at journal 03 Dec, 2025 Reviewers agreed at journal 02 Dec, 2025 Reviewers invited by journal 01 Dec, 2025 Editor assigned by journal 01 Dec, 2025 Submission checks completed at journal 25 Sep, 2025 First submitted to journal 22 Sep, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7675903","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Method Article","associatedPublications":[],"authors":[{"id":554177535,"identity":"efb60de3-5b59-466e-8718-d6e0e93e0335","order_by":0,"name":"Allison R. 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The left panel shows the number of patients reporting each sign or symptom at pre-traction. The right panel shows the number of patients with each sign or symptom who experienced ≥75% improvement at peak-traction.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-7675903/v1/0e4983f454dd1fc40e020596.png"},{"id":97344494,"identity":"437d5288-9275-45f7-b3cd-42161ad110de","added_by":"auto","created_at":"2025-12-03 11:40:44","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":91374,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eMorphometric Changes During ICT\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eGraphical representation of morphometric data obtained during ICT in the cohort that underwent the procedure (n = 190). Comparisons are shown between pre-traction (Pre) and peak-traction (Peak) values for each morphometric parameter. Each boxplot displays the interquartile range (25th–75th percentile) with the median indicated by a horizontal line; whiskers represent the minimum and maximum values. (A) Basion–axial interval (BAI), measured in millimeters; (B\u003cstrong\u003e)\u003c/strong\u003e Basion–dens interval (BDI), measured in millimeters; (C) Grabb–Oakes measurement (pB–C2 distance), measured in millimeters; (D) Clivo–axial angle (CXA), measured in degrees. All comparisons between pre-traction and peak-traction values were statistically significant (\u003cem\u003ep\u003c/em\u003e-value \u0026lt; 0.001).\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-7675903/v1/636b6de38f030fb7359c6909.png"},{"id":97370533,"identity":"ca11339b-b322-4939-b77c-d75e49af6269","added_by":"auto","created_at":"2025-12-03 16:27:33","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":90847,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eNASS Patient Satisfaction Index Following CCF Surgery.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eGraphic illustration of the distribution of surgical outcome scores among patients who underwent CCF surgery. Of the 107 patients who completed surgery, 98 completed the postoperative survey (Subgroup 2: n = 10, 2 non-respondents; Subgroup 3: n = 88, 7 non-respondents). Patients rated their postoperative quality of life using the four-point NASS scale: (1) “Surgery met my expectations”; (2) “I did not improve as much as I had hoped, but I would undergo the same operation for the same results”; (3) “Surgery helped, but I \u003cem\u003ewould not\u003c/em\u003e undergo the same operation for the same results”; and (4) “I am the same or worse than before surgery.” Panels show Subgroup 2 shows Subgroup 3, respectively.\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-7675903/v1/df759d94eb386202495d516c.png"},{"id":97344503,"identity":"7d47af8e-6b19-4dad-9be0-18c120f94ff6","added_by":"auto","created_at":"2025-12-03 11:40:45","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":320861,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eClinical and Radiological Postoperative Results\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ea. \u003c/strong\u003eHistogram depicting the preoperative prevalence and postoperative improvement of common signs and symptoms in the CCF surgery cohort\u003cstrong\u003e. \u003c/strong\u003eDark bars indicate the percentage of individuals reporting each symptom preoperatively (107 patients completed surgery; 98 completed the postoperative survey). Light grey bars represent the percentage of those same individuals who experienced a ≥75% reduction in the corresponding symptom postoperatively. Data were obtained via a structured, symptom-based outcome questionnaire at a mean of 2.4 years after surgery (\u003cem\u003eSD\u003c/em\u003e ±1.0 year).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eb. \u003c/strong\u003eLateral x-ray view of one of our CCF constructs, with condylar screws, C1 lateral mass screws, and C2 pedicle screws.\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-7675903/v1/3355567e23ddeae18432500d.png"},{"id":104739324,"identity":"8b12c7d6-b555-4693-82cc-e1f12f2bb845","added_by":"auto","created_at":"2026-03-16 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11:40:45","extension":"docx","order_by":16,"title":"","display":"","copyAsset":false,"role":"supplement","size":24075,"visible":true,"origin":"","legend":"","description":"","filename":"SUPPLEMENTARYMATERIAL9NASSdatabyindividualpatients.docx","url":"https://assets-eu.researchsquare.com/files/rs-7675903/v1/8cd0b0576c742ff195bc885d.docx"},{"id":97344505,"identity":"7d03e7d6-a255-4787-9500-5e97215e40db","added_by":"auto","created_at":"2025-12-03 11:40:45","extension":"xlsx","order_by":17,"title":"","display":"","copyAsset":false,"role":"supplement","size":201348,"visible":true,"origin":"","legend":"","description":"","filename":"SUPPLEMENTARYMATERIAL10RawdataoftheICTpatients.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7675903/v1/4b70b3475af33e97e614f81f.xlsx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Surgical Screening Protocol for Craniocervical Instability Secondary to Ehlers-Danlos Syndrome and other Connective Tissue Disorders: Analysis of a 347 Patient Case Series","fulltext":[{"header":"Introduction ","content":"\u003cp\u003eThe functional mobility of the craniocervical junction (CCJ) depends on its ligamentous structures [8,26]. Craniocervical Instability (CCI) may be congenital or acquired secondary to various pathologies, including trauma, neoplasms (e.g., chordoma), inflammatory diseases (e.g., rheumatoid arthritis, systemic lupus erythematosus), infection (e.g., Grisel\u0026rsquo;s syndrome), and connective tissue disorders (CTDs) [7-9].\u003c/p\u003e\n\u003cp\u003eCCI in individuals with CTDs presents unique diagnostic and surgical challenges [1-3,5,6,10,27], often manifesting with debilitating symptoms that appear disproportionate to findings on conventional neuroimaging and neurological examination\u0026mdash;unlike other etiologies such as rheumatoid arthritis.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eA range of non-invasive diagnostic tools have been proposed to address these challenges, including morphometric analysis, dynamic imaging, trials of cervical collars or traction, cervicothoracic orthoses, and halo jackets [3,10]. Prior work underscores the need for a tailored protocol that reflects the distinct pathophysiology of CCI in individuals with CTDs. In response, we developed and evaluated a structured protocol designed to support clinical decision-making and guide management in this complex population.\u003c/p\u003e"},{"header":"Materials \u0026 Methods","content":"\u003cp\u003e\u003cem\u003ePatient Selection and Study Design\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eFrom May 2018 to April 2022, we evaluated individuals with a genetic and/or clinical diagnosis of CTDs who were referred to our institution for assessment and management of suspected CCI. Individuals with radiologically obvious CCI pathologies on prior neuroanatomic imaging were excluded from this study. Evaluation for CCI and potential surgical intervention was conducted using a two-stage protocol, as outlined below.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Stage 1 (Initial Screening) consisted of six components: (1) a detailed history focused on features suggestive of CCI [10]; (2) a standardized questionnaire assessing signs and symptoms of CCI, as well as comorbidities commonly associated with CTDs [5,10];(3) a physical examination; (4) non-invasive provocative testing; (5) initial neuroanatomic imaging of the CCJ with morphometric analysis based on previously validated criteria in this population [12,15];and (6) assessment of functional status using the Karnofsky Performance Scale (KPS) [11]. With the exception of the KPS, each component was scored on a scale of 0 to 2, with 0 indicating no suspicion for CCI, 1 indicating intermediate suspicion, and 2 indicating strong suspicion. Individuals with a KPS score of 70 (i.e., patient cares for self, but unable to carry on normal activity or to do active work) or less (related to their chief complaints) and an aggregate screening score of 6 or greater were recommended to proceed to Stage 2 (Advanced Evaluation). In contrast, those with a score below 6 and/or a KPS greater than 70 were advised to pursue conservative management.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eStage 2 (Advanced Evaluation) involved a comprehensive diagnostic workup to evaluate surgical candidacy. This included CT angiogram of the CCJ, medical and cardiac clearances and double psychiatric evaluation and clearance as described below.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFollowing completion of the above screening steps, candidates underwent a trial of ICT, which was evaluated using a defined scoring system (outlined below). Individuals who met criteria in both Stage 1 and Stage 2 and demonstrated positive scores on both components of the ICT assessment were deemed surgical candidates for craniocervical fusion (CCF).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eDiagnostic Intake Tool\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eAs part of Stage 1 screening, individuals completed a diagnostic intake tool developed internally for patients with CTDs. (Supplementary Material 1)\u003c/p\u003e\n\u003cp\u003e\u003cem\u003ePsychiatric Clearance\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;All individuals underwent psychiatric evaluation by two independent trained professionals\u003c/p\u003e\n\u003cp\u003e—an outside mental health specialist local to the individual and a neuropsychologist at our institution. \u0026nbsp;These evaluations were essential not only to identify established psychiatric comorbidities that can be associated with CTDs—such as anxiety disorders, depression, personality disorder, obsessive-compulsive disorder, and mood disorders—but also to further assess the patient’s subjective symptom burden. These evaluations aimed to distinguish between symptoms arising from underlying pathophysiology and those potentially influenced or amplified by psychological factors. Particular attention was given to evaluating how psychological factors may influence the perception of pain and other symptoms, as well as the patient’s ability to cope with the postoperative recovery process. Findings from both evaluations were integrated into the multidisciplinary surgical planning to ensure appropriate support and risk stratification.\u003c/p\u003e\n\u003cp\u003eAdditional details can be found in Supplementary Material 2\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eImaging\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eAll imaging studies were reviewed using a commercial electronic platform (\u003cem\u003eOsiriX;\u003c/em\u003e Pixmeo, Switzerland) [20].\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eICT Protocol\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eFollowing informed consent, Gardner-Wells tongs were applied in the operating room, and the patient was placed in a sitting position after a baseline neurological exam. \u0026nbsp;Lateral-view digital fluoroscopic imaging of the CCJ was obtained in neutral, flexion, and extension positions. After baseline documentation of signs and symptoms, the tongs were connected to a rope-and-pulley system and an initial vertical traction force of 20 pounds was applied. Traction was gradually increased every 10 minutes as tolerated, up to a maximum of 35 pounds (or 40 pounds in individuals with a strong athletic build). At each increment, patients were asked to report any change—positive, negative, or none—in each of their pre-identified symptoms and/or signs, expressed subjectively as a percentage relative to baseline (e.g., “10% worse,” “90% better,” or “no change”). Fifteen minutes after reaching the final traction level, follow-up digital fluoroscopic images of the CCJ were obtained, along with a repeat neurological examination. An example of the clinical and morphometric data obtained during ICT is presented (Table 1). \u0026nbsp;The ICT set-up and testing are illustrated (Figure 1).\u003c/p\u003e\n\u003cp\u003eFurther technical details are provided in Supplementary Material 3.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1.\u003c/strong\u003e \u003cem\u003eExample of Data Collected During Intraoperative Craniocervical Traction (ICT).\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eIllustrative patient case showing percentage improvement in pre-identified signs and symptoms at incremental traction weights, as reported by the patient, alongside changes in neurological examination findings. Corresponding morphometric measurements of the craniocervical junction are shown for both pre-traction and peak-traction states.\u003c/p\u003e\n\u003cp\u003e\u003cimg width=\"581\" height=\"621\" 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\" alt=\"image\"\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eMorphometric Measurements\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eBiomechanical assessment of CCI was performed using four established morphometric parameters: the basion-dens interval (BDI), basion-axial interval (BAI), Grabb-Oakes measurement (pB-C2 distance), and the clivo-axial angle (CXA) [18,19]. Technical details are provided in Supplementary Material 4.\u003c/p\u003e\n\u003cp\u003eStatic measurements were obtained from MRI during Stage 1 and compared against established normative values. Dynamic measurements—acquired both at pre-traction and at peak traction—were obtained during ICT using calibrated digital fluoroscopy (\u003cem\u003eIso-C,\u003c/em\u003e Siemens, Germany). Calibration was performed against a known object placed in the midsagittal plane.\u003c/p\u003e\n\u003cp\u003eThe difference between each morphometric value at peak traction and its corresponding pre-traction measurement was defined as the translational value. These translational changes were evaluated against established normal reference ranges and predefined surgical thresholds (Table 2).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2.\u0026nbsp;\u003c/strong\u003e\u003cem\u003eNormal Values for Morphometric Measurements.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eNormal reference ranges and predefined surgical thresholds for morphometric parameters used in the biomechanical assessment of craniocervical instability (CCI), including the basion-dens interval (BDI), basion-axial interval (BAI), Grabb-Oakes measurement (pB–C2 distance), and clivo-axial angle (CXA).\u003c/p\u003e\n\u003cp\u003e\u003cimg width=\"864\" height=\"317\" 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\" alt=\"image\"\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eScoring of the ICT Test\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe ICT Clinical Score was considered positive if most or all of the patient’s chief CCI-related signs and symptoms improved by ≥75% at peak traction compared with the pre-traction baseline. The ICT Morphometric Score was considered positive when one or more of the following criteria were met: (1) a ≥2 mm increase in the translational BDI, and/or (2) a ≥4 mm change in the BAI or pB–C2, observed on flexion/extension images or during traction. Patients with both a positive ICT Clinical Score and a positive ICT Morphometric Score met our criteria for CCF surgery.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eCCF Procedure\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eInstead of a traditional barplate construct, our CCF technique utilized condylar screws at C0, lateral mass screws at C1, and pedicle screws at C2, connected by two short rods and overlaid with a bone fusion matrix [25].\u003c/p\u003e\n\u003cp\u003e\u003cem\u003ePostoperative Monitoring and Outcome Questionnaire\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003ePatients were routinely evaluated at 6 and 12 months postoperatively, with additional follow-up conducted on a PRN basis thereafter. A custom-designed postoperative outcome questionnaire was distributed as a one-time, simultaneous mailing in March 2023 to all individuals who had undergone CCF. The complete questionnaire is provided in Supplementary Material 5.\u003c/p\u003e\n\u003cp\u003eFor the purposes of this study, analyses were limited to sign and symptom changes and the North American Spine Surgery (NASS) Patient Satisfaction Index [16]. Comprehensive evaluation of the full dataset will be presented in a subsequent publication focused on long-term CCF outcomes.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eStatistical Analysis\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eWe retrospectively collected data from the electronic medical record and performed analyses using Microsoft Excel and GraphPad Prism. Individuals with incomplete medical records were excluded. Morphometric variables measured at pre- and peak-traction were compared using two-tailed \u003cem\u003et\u003c/em\u003e-tests. Changes in patient-reported signs and symptoms between pre-traction, peak-traction, and post-surgical states were evaluated using McNemar’s test, with calculations performed in R (RStudio, Posit PBC). Statistical significance was defined as a \u003cem\u003ep\u003c/em\u003e-value \u0026lt; 0.05.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eResearch Reporting Guidelines\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThis retrospective study was approved by the Institutional Review Board and the Intramural Protocol Review Committee for Clinical Research at Mount Sinai South Nassau Hospital. \u0026nbsp;The study was conducted in accordance with institutional ethical standards, the Declaration of Helsinki, and the STROBE-PROCESS 2023 reporting guidelines [14,28]. \u0026nbsp;No AI-assisted copy editing was used in this manuscript.\u003c/p\u003e"},{"header":"Results ","content":"\u003cp\u003e\u003cem\u003eEnrollment in Stage 1\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eFrom May 2018 to April 2022, 347 individuals with a clinical and/or genetic diagnosis of a CTD were referred to our institution for evaluation of CCI (mean age 37 ± 12 years; 87.3% female). All individuals were enrolled in Stage 1 of the protocol (Figure 2a).\u003c/p\u003e\n\u003cp\u003eChiari I malformation was present as a comorbidity in 33.2% of patients. Ehlers–Danlos Syndrome (EDS) was the most common CTD diagnosis (75.3%), although many individuals exhibited mixed CTD phenotypes. Regardless of the specific CTD subtype, CCI emerged as a final common pathway.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eEnrollment in Stage 2\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eOf the individuals who entered Stage 1, 254 met criteria to proceed to Stage 2, and 190 completed the advanced evaluation.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eSurgical Qualification\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe 190 individuals who completed Stage 2 were categorized into four subgroups based on whether they met surgical criteria and elected to proceed with CCF surgery. Subgroup 1 (n = 63) did not meet criteria for CCF surgery. Subgroup 2 (n = 12) had borderline morphometric scores on ICT but were offered surgery based on remarkable improvements in signs and/or symptoms during ICT, and proceeded with CCF surgery at our center. Subgroup 3 (n = 95) met full surgical criteria and underwent CCF surgery. Subgroup 4 (n = 20) met surgical criteria but did not undergo surgery at our institution. (Supplementary Material 6)\u003c/p\u003e\n\u003cp\u003eStage 2 (Advanced Evaluation) procedures and subgroup allocation are summarized in the flowchart (Figure 2b).\u003c/p\u003e\n\u003cp\u003eSubgroup 1 was further analyzed to identify which components of the advanced evaluation led to disqualification from surgery. (Supplementary Material 7)\u003c/p\u003e\n\u003cp\u003eExceptions to surgical qualification were made for Subgroup 2 based on specific clinical considerations. Although these 12 individuals narrowly missed the ICT morphometric threshold for BDI by a fraction of a millimeter, 6 exhibited marked improvement in neurological deficits at peak traction, while the remaining 6 experienced striking relief of their baseline chief complaints during traction.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eSigns and Symptoms\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eTable 3 summarizes the most common presenting signs and symptoms reported by individuals on the diagnostic intake tool at the time of enrollment in Stage 1, limited to those who ultimately completed Stage 2. (Table 3) \u0026nbsp;Figure 3 illustrates common pre-traction signs and symptoms in individuals who completed Stage 2 (Advanced Evaluation) that demonstrated the greatest improvement with peak traction, showing the number of patients who experienced more than 75% symptom relief. (Figure 3).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3.\u003c/strong\u003e Common presenting signs and symptoms at Stage 1 enrollment among individuals completing Stage 2\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eMost common presenting signs and symptoms reported on the diagnostic intake tool at Stage 1 enrollment among individuals who completed Stage 2,\u0026nbsp;(n=190) presented in decreasing order of frequency.\u003c/p\u003e\n\u003cp\u003e\u003cimg width=\"533\" height=\"696\" 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\" alt=\"image\"\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eMorphometric Analysis\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eKey morphometric parameters—including BDI, BAI,pB–C2 distance, and CXA—were measured both pre-traction and at peak-traction. All four morphometric parameters showed statistically significant changes from pre-traction to peak traction during ICT (\u003cem\u003ep\u003c/em\u003e -value \u0026lt; 0.001 for all). (Figure 4 and Supplementary Material 8)\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eComplications of the ICT Procedure\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eNo patients who underwent ICT experienced direct complications from the application of tongs or weights, such as skull fractures, dislocations, hemorrhages, brain injuries, or cerebrospinal fluid leaks. Two patients with previously documented severe CCI who qualified for CCF at the conclusion of the screening process developed intense and persistent rebound symptoms following completion of ICT. After a period of observation, both proceeded to CCF surgery during the same hospitalization, with resolution of rebound symptoms and their initial chief complaints postoperatively.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eOutcomes of CCF\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eOf the 107 surgical patients (Subgroups 2 and 3), 98 completed the NASS Patient Satisfaction Index [16] via a one-time postoperative questionnaire, administered at a mean of 2.4 ± 1 years after surgery. Satisfaction (NASS score 1 or 2) was reported by 70.0% of Subgroup 2 and 86.4 % of Subgroup 3, indicating that surgery met expectations or provided sufficient benefit to warrant the same procedure again (Figure 5 and Supplementary Material 9)\u003c/p\u003e\n\u003cp\u003eThe same questionnaire also documented changes in preoperative signs and symptoms. At follow-up, a substantial proportion of patients reported ≥75% improvement in many of their preoperative symptoms (Figure 6a).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eWe developed and implemented a two-stage surgical screening and evaluation protocol for individuals with suspected CCI secondary to CTDs. This protocol evolved over years of clinical experience with this complex patient population and was designed to integrate multiple layers of evaluation—beginning with initial screening and followed by advanced assessment.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eOur goal was to create a stringent, multidimensional framework that improves upon prior screening methods by synthesizing previously disparate clinical, functional, and radiographic data into a cohesive profile to guide decision-making. While no single component of the protocol is sufficient in isolation, ICT offered particularly valuable diagnostic and prognostic insight. ICT served as a dynamic adjunct to the broader assessment, revealing functional biomechanical instability that may be overlooked by static imaging modalities and routine clinical examination.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eControversies of CCI in Patients with CTDs\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eIn our experience, individuals with CTDs may present across a wide clinical spectrum, ranging from high-performance athletes to individuals who are severely debilitated or bedridden [13,23]. \u0026nbsp;Paradoxically, some asymptomatic individuals may exhibit marked hypermobility of the CCJ, while others with profound neurological compromise may show minimal or no abnormalities on standard neuroanatomic imaging. While CCI is increasingly recognized as a potential cause of neurological dysfunction in individuals with CTDs, variability in clinical presentation and uncertainty surrounding optimal management continue to pose challenges. Additionally, many of these individuals present with complex Chiari malformations [4,17,22,24,29], further complicating diagnosis and treatment. This heterogeneity has contributed to ongoing controversy regarding when CCJ hypermobility should be considered pathologic and when surgical intervention is appropriate. Notably, the presence of hypermobility—often misinterpreted as instability on dynamic imaging when assessed in isolation—should not be considered synonymous with pathological instability.\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eThe Problem of Surgical Screening\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eIn a recent review article, Lohkamp \u003cem\u003eet al\u003c/em\u003e. recommended that surgical intervention for suspected CCI in individuals with CTDs should be considered only when both clear radiographic evidence of instability and concordant clinical symptoms are present [12].It was also highlighted that a 4-6 week trial of hard collar cervical immobilization may represent a valuable adjunctive strategy for surgical selection in this population.\u003c/p\u003e\n\u003cp\u003eBetween 1998 and 2004, in an effort to develop a reliable surgical screening protocol for this population, we tested a variety of dynamic non-invasive diagnostic tools (ranging from cervical collar trials to dynamic imaging and intermittent traction) [3,10]to evaluate CCI in CTD patients. However, we found these methods to be limited by significant technical, anatomic, and mechanical constraints, as well as an inability to objectively assess vertical instability.\u003c/p\u003e\n\u003cp\u003eThese shortcomings ultimately led us to incorporate ICT as a dynamic diagnostic modality, which has since become a cornerstone of our surgical screening protocol by providing real-time insight into functional instability and symptom reversibility under controlled conditions.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eThe Role of ICT\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eIn 2004, we incorporated the ICT technique, commonly used in trauma settings, into our surgical screening protocol and paired it with morphometric analysis. This adaptation combined the provocative diagnostic utility of ICT with objective, real-time measurements, allowing us to correlate morphometric changes with both patient-reported symptomatic improvements and neurologic examination findings. This approach enabled us to distinguish non-pathologic CCJ hypermobility (i.e., hypermobility without symptom provocation or relief during controlled traction) from clinically significant, pathologic CCI. It also provided objective criteria to guide surgical qualification. Importantly, morphometric data obtained at peak traction informed intraoperative positioning during CCF, improving surgical precision (Figure 6b). Additionally, this protocol enhanced our understanding of vertical instability—aka. cranial settling—as a critical component of CCI in this patient population.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eBiomechanics of the CCJ and Cranial Settling\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eCranial settling has been described in pathologies which disrupt the anatomic integrity of the bony elements of the CCJ, such as neoplasms, trauma, rheumatoid arthritis, and infections [21]. \u0026nbsp;Historically, CTDs have not been considered causes of cranial settling. However, our study using ICT demonstrates that ligamentous compromise of the CCJ in CTDs, typically in the absence of overt bony pathology, can indeed result in vertical instability or cranial settling. Importantly, surgical correction of this instability was associated with improvement and/or resolution of related neurological signs and symptoms. Moreover, our data suggest that dynamic cranial settling and brainstem or neurovascular compression may underlie the frequent discordance between static neuroanatomic imaging and the severity of clinical presentation in this patient population.\u003c/p\u003e\n\u003cp\u003eThe intrinsic validity of the morphometric component of the ICT score in the surgical qualification process was supported by the significant difference in postoperative NASS satisfaction scores observed between Subgroups 2 and 3 (70.0% vs. 86.4%, respectively).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eLimitations of this Study\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThis study reflects the experience of a single surgeon at a single institution specializing in the evaluation and treatment of patients with CTDs and CCI. As such, inter- and intra-observer variability may arise if this protocol is implemented at other centers. While the morphometric measurements and neurological examination findings assessed during the ICT procedure are objective, patient-reported symptoms and perceived symptom improvement are inherently subjective. To mitigate this potential source of bias, patients underwent two independent psychiatric evaluations and were asked to quantify their perceived improvement as a percentage change from baseline.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThe evaluation and management of CCI secondary to CTDs remains a subject of ongoing controversy, with debate surrounding diagnostic protocols and surgical selection criteria fueling understandable skepticism. \u0026nbsp;In this study, we present our institutional experience using a structured surgical screening protocol specifically developed to assess CCI in individuals with CTDs, with the goal of introducing greater diagnostic clarity and rigor to clinical decision-making. Among all components of the protocol, ICT proved to be the most revealing, offering unique biomechanical insights not captured by static imaging or conventional assessments.\u003c/p\u003e\n\u003cp\u003eWhile this represents a preliminary, single-surgeon, single-center experience, we strongly believe that further multicenter studies are warranted. \u0026nbsp;We are encouraged that the initial CCF outcome data reported here support the clinical utility of our screening protocol. Looking ahead, we anticipate that future studies\u0026mdash;particularly those evaluating surgical outcomes in patients selected using this protocol\u0026mdash;will help resolve ongoing controversies in the field. In addition, we are currently initiating a randomized crossover study at our institution comparing surgical and conservative treatment strategies in this population, which we believe will offer critical insight into optimal care pathways moving forward.\u003c/p\u003e"},{"header":"ABBREVIATIONS","content":"\u003cp\u003eBAI = Basion Axial Interval ; BDI = Basion Dens Interval ; CXA = Clivo Axial Angle ; CCF = Craniocervical Fusion ; CCI = Craniocervical Instability ; CCJ = Craniocervical Junction ; CTA = Computed Tomography Angiography ; CTD = Connective Tissue Disorders ; EDS = Ehlers-Danlos Syndrome ; ICT = Intraoperative Craniocervical Traction; KPS = Karnofsky Performance Scale ; pB\u0026ndash;C2 = Perpendicular to the Basion to C2 Line (Grabb-Oakes measurement); NASS = North American Spine Surgery Satisfaction Index\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by a generous Gift provided by the Canerector Foundation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe would like to acknowledge the patients who trusted us with their care.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWe would also like to acknowledge Dr. Thomas H. Milhorat for his mentorship and Dr. Roger W. Kula for his example.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors have no relevant financial or non-financial interests to disclose.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePaolo A Bolognese—conceptualization, drafting original manuscript, writing, revising the manuscript, data collection, data analysis/interpretation, patient care, supervision, resources\u003c/p\u003e\n\u003cp\u003eAllison R Bloom—conceptualization, revising the manuscript\u003c/p\u003e\n\u003cp\u003eJohn B Biggins—conceptualization, data collection, data analysis/interpretation, revising the manuscript\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAndrew Brodbelt—conceptualization, data analysis/interpretation, revising the manuscript\u003c/p\u003e\n\u003cp\u003eMisao Nishikawa—conceptualization, data analysis/interpretation, revising manuscript\u003c/p\u003e\n\u003cp\u003eMansoor Foroughi—conceptualization, revising the manuscript\u003c/p\u003e\n\u003cp\u003eIlene S Ruhoy—conceptualization, drafting the original manuscript, data analysis/interpretation, data collection, revising the manuscript\u003c/p\u003e\n\u003cp\u003eRandall Dass—conceptualization, data analysis/interpretation, revising the manuscript\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eKamil Rohana—conceptualization, data collection, data analysis/interpretation, revising the manuscript\u003c/p\u003e\n\u003cp\u003eJeffrey D Wood--data collection, data analysis/interpretation, drafting original manuscript, revising the manuscript\u003c/p\u003e\n\u003cp\u003eDavid Putrino—resources and supervision, revising the manuscript\u003c/p\u003e\n\u003cp\u003eVeit Rohde—revising the manuscript\u003c/p\u003e\n\u003cp\u003eChristoph Bettag—revising the manuscript\u003c/p\u003e\n\u003cp\u003eShawn Belverud—revising the manuscript\u003c/p\u003e\n\u003cp\u003eTravis Caton—conceptualization, data analysis/interpretation, revising the manuscript\u003c/p\u003e\n\u003cp\u003eTanvir Choudhri—supervision, revising the manuscript\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eResearch Reporting Guidelines\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThis study was conducted in accordance with the Declaration of Helsinki and adhered to the STROBE and PROCESS 2023 reporting guidelines.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eIRB approval\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe retrospective record review pertinent to this study was approved by the Internal Review Board of the two Institutions where the procedures took place: (IRB #13-655B: North Shore University Hospital – Northwell, Manhasset, NY; WIRB #1276110 and WIRB #1262008: Mount Sinai South Nassau – Oceanside, NY).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eStandard informed consent was given by the patients for all surgical procedures.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical Trial Number:\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to publish\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors affirm that human research participants provided informed consent for publication of the images in Figures 1a, and 1b.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eBeighton P, de Paepe A, Danks D, Finidori G, Gedde-Dahl T, Goodman R, Hall JG, Hollister DW, Horton W, McKusick VA, et al. (1988) International Nosology of Heritable Disorders of Connective Tissue, Berlin, 1986. Am J Med Genet 29:581-594. doi:10.1002/ajmg.1320290316\u003c/li\u003e\n\u003cli\u003eBloom L, Byers P, Francomano C, Tinkle B, Malfait F, Steering Committee of The International Consortium on the Ehlers-Danlos S (2017) The international consortium on the Ehlers-Danlos syndromes. Am J Med Genet C Semin Med Genet 175:5-7. doi:10.1002/ajmg.c.31547\u003c/li\u003e\n\u003cli\u003eBrodbelt AR, Flint G (2017) Ehlers Danlos, complex Chiari and cranio-cervical fixation: how best should we treat patients with hypermobility? Br J Neurosurg 31:397-398. doi:10.1080/02688697.2017.1386282\u003c/li\u003e\n\u003cli\u003eCaetano de Barros M, Farias W, Ataide L, Lins S (1968) Basilar impression and Arnold-Chiari malformation. A study of 66 cases. J Neurol Neurosurg Psychiatry 31:596-605. doi:10.1136/jnnp.31.6.596\u003c/li\u003e\n\u003cli\u003eCastori M, Morlino S, Ghibellini G, Celletti C, Camerota F, Grammatico P (2015) Connective tissue, Ehlers-Danlos syndrome(s), and head and cervical pain. Am J Med Genet C Semin Med Genet 169C:84-96. doi:10.1002/ajmg.c.31426\u003c/li\u003e\n\u003cli\u003eCastori M, Voermans NC (2014) Neurological manifestations of Ehlers-Danlos syndrome(s): A review. Iran J Neurol 13:190-208\u003c/li\u003e\n\u003cli\u003eGhanem I, El Hage S, Rachkidi R, Kharrat K, Dagher F, Kreichati G (2008) Pediatric cervical spine instability. J Child Orthop 2:71-84. doi:10.1007/s11832-008-0092-2\u003c/li\u003e\n\u003cli\u003eHarris J, Jr. (2001) The cervicocranium: its radiographic assessment. Radiology 218:337-351. doi:10.1148/radiology.218.2.r01fe53337\u003c/li\u003e\n\u003cli\u003eHarris JH, Jr., Carson GC, Wagner LK (1994) Radiologic diagnosis of traumatic occipitovertebral dissociation: 1. Normal occipitovertebral relationships on lateral radiographs of supine subjects. AJR Am J Roentgenol 162:881-886. doi:10.2214/ajr.162.4.8141012\u003c/li\u003e\n\u003cli\u003eHenderson FC, Sr., Schubart JR, Narayanan MV, Tuchman K, Mills SE, Poppe DJ, Koby MB, Rowe PC, Francomano CA (2024) Craniocervical instability in patients with Ehlers-Danlos syndromes: outcomes analysis following occipito-cervical fusion. Neurosurg Rev 47:27. doi:10.1007/s10143-023-02249-0\u003c/li\u003e\n\u003cli\u003eKarnofsky DABJ, Burchenal JH (1949) Evaluation of chemotherpeutic agents. In: MacLeod CM (ed) Evaluation of Chemotherapeutic Agents. Columbia University Press, New York, p 196\u003c/li\u003e\n\u003cli\u003eLohkamp LN, Marathe N, Fehlings MG (2022) Craniocervical Instability in Ehlers-Danlos Syndrome-A Systematic Review of Diagnostic and Surgical Treatment Criteria. Global Spine J 12:1862-1871. doi:10.1177/21925682211068520\u003c/li\u003e\n\u003cli\u003eMalfait F, Francomano C, Byers P, Belmont J, Berglund B, Black J, Bloom L, Bowen JM, Brady AF, Burrows NP, Castori M, Cohen H, Colombi M, Demirdas S, De Backer J, De Paepe A, Fournel-Gigleux S, Frank M, Ghali N, Giunta C, Grahame R, Hakim A, Jeunemaitre X, Johnson D, Juul-Kristensen B, Kapferer-Seebacher I, Kazkaz H, Kosho T, Lavallee ME, Levy H, Mendoza-Londono R, Pepin M, Pope FM, Reinstein E, Robert L, Rohrbach M, Sanders L, Sobey GJ, Van Damme T, Vandersteen A, van Mourik C, Voermans N, Wheeldon N, Zschocke J, Tinkle B (2017) The 2017 international classification of the Ehlers-Danlos syndromes. Am J Med Genet C Semin Med Genet 175:8-26. doi:10.1002/ajmg.c.31552\u003c/li\u003e\n\u003cli\u003eMathew G, Sohrabi C, Franchi T, Nicola M, Kerwan A, Agha R, Group P (2023) Preferred Reporting Of Case Series in Surgery (PROCESS) 2023 guidelines. Int J Surg 109:3760-3769. doi:10.1097/JS9.0000000000000940\u003c/li\u003e\n\u003cli\u003eMilhorat TH, Bolognese PA, Nishikawa M, McDonnell NB, Francomano CA (2007) Syndrome of occipitoatlantoaxial hypermobility, cranial settling, and chiari malformation type I in patients with hereditary disorders of connective tissue. J Neurosurg Spine 7:601-609. doi:10.3171/SPI-07/12/601\u003c/li\u003e\n\u003cli\u003eMummaneni PV, Bydon M, Alvi MA, Chan AK, Glassman SD, Foley KT, Potts EA, Shaffrey CI, Shaffrey ME, Coric D, Knightly JJ, Park P, Wang MY, Fu KM, Slotkin JR, Asher AL, Virk MS, Kerezoudis P, Guan J, Haid RW, Bisson EF (2019) Predictive model for long-term patient satisfaction after surgery for grade I degenerative lumbar spondylolisthesis: insights from the Quality Outcomes Database. Neurosurg Focus 46:E12. doi:10.3171/2019.2.FOCUS18734\u003c/li\u003e\n\u003cli\u003eNagashima C, Tsuji R, Kubota S, Tajima K (1981) [Atlanto-axial, Atlanto-occipital dislocations, developmental cervical canal stenosis in the Ehlers-Danlos syndrome (author\u0026apos;s transl)]. No Shinkei Geka 9:601-608\u003c/li\u003e\n\u003cli\u003eNicholson LL, Rao PJ, Lee M, Wong TM, Cheng RHY, Chan C (2023) Reference values of four measures of craniocervical stability using upright dynamic magnetic resonance imaging. Radiol Med 128:330-339. doi:10.1007/s11547-023-01588-8\u003c/li\u003e\n\u003cli\u003eRojas CA, Bertozzi JC, Martinez CR, Whitlow J (2007) Reassessment of the craniocervical junction: normal values on CT. AJNR Am J Neuroradiol 28:1819-1823. doi:10.3174/ajnr.A0660\u003c/li\u003e\n\u003cli\u003eRosset A, Spadola L, Ratib O (2004) OsiriX: an open-source software for navigating in multidimensional DICOM images. J Digit Imaging 17:205-216. doi:10.1007/s10278-004-1014-6\u003c/li\u003e\n\u003cli\u003eRyken T, Menezes AH (1993) Nonrheumatoid cranial settling. Spine (Phila Pa 1976) 18:2525-2527. doi:10.1097/00007632-199312000-00025\u003c/li\u003e\n\u003cli\u003eSavasta S, Merli P, Ruggieri M, Bianchi L, Sparta MV (2011) Ehlers-Danlos syndrome and neurological features: a review. Childs Nerv Syst 27:365-371. doi:10.1007/s00381-010-1256-1\u003c/li\u003e\n\u003cli\u003eSchroeder EL, Lavallee ME (2006) Ehlers-Danlos syndrome in athletes. Curr Sports Med Rep 5:327-334. doi:10.1097/01.csmr.0000306439.59477.83\u003c/li\u003e\n\u003cli\u003eSpiessberger A, Dietz N, Gruter B, Virojanapa J (2020) Ehlers-Danlos syndrome-associated craniocervical instability with cervicomedullary syndrome: Comparing outcome of craniocervical fusion with occipital bone versus occipital condyle fixation. J Craniovertebr Junction Spine 11:287-292. doi:10.4103/jcvjs.JCVJS_166_20\u003c/li\u003e\n\u003cli\u003eTam SKP, Bolognese PA, Kula RW, Brodbelt A, Foroughi M, Avshalumov M, Mugutso D, Ruhoy I (2022) Safety analysis and complications of condylar screws in a single-surgeon series of 250 occipitocervical fusions. Acta Neurochir (Wien) 164:903-911. doi:10.1007/s00701-021-05039-z\u003c/li\u003e\n\u003cli\u003eTubbs RS, Hallock JD, Radcliff V, Naftel RP, Mortazavi M, Shoja MM, Loukas M, Cohen-Gadol AA (2011) Ligaments of the craniocervical junction. J Neurosurg Spine 14:697-709. doi:10.3171/2011.1.SPINE10612\u003c/li\u003e\n\u003cli\u003eVeatch OJ, Steinle J, Hossain WA, Butler MG (2022) Clinical genetics evaluation and testing of connective tissue disorders: a cross-sectional study. BMC Med Genomics 15:169. doi:10.1186/s12920-022-01321-w\u003c/li\u003e\n\u003cli\u003evon Elm E, Altman DG, Egger M, Pocock SJ, Gotzsche PC, Vandenbroucke JP, Initiative S (2008) The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies. J Clin Epidemiol 61:344-349. doi:10.1016/j.jclinepi.2007.11.008\u003c/li\u003e\n\u003cli\u003eZhao DY, Rock MB, Sandhu FA (2022) Craniocervical Stabilization After Failed Chiari Decompression: A Case Series of a Population with High Prevalence of Ehlers-Danlos Syndrome. World Neurosurg 161:e546-e552. doi:10.1016/j.wneu.2022.02.068\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"neurosurgical-review","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"nrev","sideBox":"Learn more about [Neurosurgical Review](https://www.springer.com/journal/10143)","snPcode":"10143","submissionUrl":"https://submission.nature.com/new-submission/10143/3","title":"Neurosurgical Review","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Craniocervical Instability, Craniocervical Fusion, Intraoperative Craniocervical Traction, Connective Tissue Disorders, Ehlers-Danlos Syndrome","lastPublishedDoi":"10.21203/rs.3.rs-7675903/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7675903/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEvaluation of craniocervical instability (CCI) in individuals with connective tissue disorders (CTDs) remains controversial. We present a surgical screening protocol created and implemented at our institution for these individuals.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe reviewed patients referred to our institution for CCI secondary to CTDs, between May 2018 and April 2022 using our two-stage protocol. Stage 1 included: history, clinical questionnaire, physical examination, non-invasive provocative testing, neuroimaging with morphometric analysis, Karnofsky Performance Scale. Items 1–5 were each scored on a scale from 0 to 2. \u003cbr\u003e\nIndividuals with a KPS ≤ 70 and an aggregate score ≥6 were recommended for Stage 2, which included additional neuroimaging, psychiatric evaluation, and a trial of intraoperative craniocervical traction (ICT) with clinical and morphometric scores. Individuals meeting criteria in both stages were considered surgical candidates. Postoperative outcomes were assessed.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOf the 347 individuals who entered Stage 1, 190 progressed through Stage 2. Following advanced evaluation, 115 patients met full surgical qualification criteria, with 95 proceeding to craniocervical fusion (CCF), and 86.4% reporting satisfaction on the NASS satisfaction index. An additional 12 patients were offered surgery due to marked clinical improvement during ICT despite borderline morphometric findings, with 70% reporting satisfaction on the NASS index postoperatively.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe present a two-stage surgical evaluation protocol for CCI secondary to CTDs. ICT served as a critical diagnostic and prognostic tool, clarifying the biomechanical contribution of CCI to symptomatology and aiding in the identification of appropriate surgical candidates. \u0026nbsp;Further multicenter studies are warranted to validate this approach.\u003c/p\u003e","manuscriptTitle":"Surgical Screening Protocol for Craniocervical Instability Secondary to Ehlers-Danlos Syndrome and other Connective Tissue Disorders: Analysis of a 347 Patient Case Series","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-03 11:40:40","doi":"10.21203/rs.3.rs-7675903/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-12-21T23:14:22+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-12-21T20:24:54+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"54047280123364982027236092659511216035","date":"2025-12-21T17:01:20+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"60267370221378451772758291446436557119","date":"2025-12-15T20:56:55+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"296842223800304687705995495283092809158","date":"2025-12-15T13:54:17+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-12-15T01:10:37+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"166910248772732686653350143805141237156","date":"2025-12-13T19:52:12+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-12-08T16:48:59+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"135296384526674223287018598476903625331","date":"2025-12-03T16:06:11+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"61459013087590724349610232383190497923","date":"2025-12-02T15:46:41+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-12-01T14:32:27+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-12-01T14:31:40+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-09-25T15:18:11+00:00","index":"","fulltext":""},{"type":"submitted","content":"Neurosurgical Review","date":"2025-09-22T10:10:04+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"neurosurgical-review","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"nrev","sideBox":"Learn more about [Neurosurgical Review](https://www.springer.com/journal/10143)","snPcode":"10143","submissionUrl":"https://submission.nature.com/new-submission/10143/3","title":"Neurosurgical Review","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"d5736d2e-18f7-4ad9-9506-5561be079014","owner":[],"postedDate":"December 3rd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2026-03-16T16:01:07+00:00","versionOfRecord":{"articleIdentity":"rs-7675903","link":"https://doi.org/10.1007/s10143-026-04195-z","journal":{"identity":"neurosurgical-review","isVorOnly":false,"title":"Neurosurgical Review"},"publishedOn":"2026-03-12 15:57:48","publishedOnDateReadable":"March 12th, 2026"},"versionCreatedAt":"2025-12-03 11:40:40","video":"","vorDoi":"10.1007/s10143-026-04195-z","vorDoiUrl":"https://doi.org/10.1007/s10143-026-04195-z","workflowStages":[]},"version":"v1","identity":"rs-7675903","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7675903","identity":"rs-7675903","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}