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Record W2995027241 · doi:10.3171/2019.9.spine19820

Characteristics and management of pain in patients with Klippel-Feil syndrome: analysis of a global patient-reported registry

2019· article· en· W2995027241 on OpenAlexaff
Kishan Patel, Hardy Evans, Samuel Sommaruga, Pia Vayssière, Tariq Qureshi, Luis Kolb, Michael G. Fehlings, Joseph Cheng, Enrico Tessitore, Karl Schaller, Aria Nouri

Bibliographic record

VenueJournal of Neurosurgery Spine · 2019
Typearticle
Languageen
FieldMedicine
TopicSpinal Fractures and Fixation Techniques
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMedicineKlippel–Feil syndromeShouldersMigraineNeck painSurgeryAnesthesia

Abstract

fetched live from OpenAlex

OBJECTIVE: Klippel-Feil syndrome (KFS) is characterized by congenital fusion of the cervical vertebrae. Due to its rarity, minimal research has been done to assess the quality and management of pain associated with this disorder. Using a large global database, the authors report a detailed analysis of the type, location, and treatment of pain in patients with KFS. METHODS: Data were obtained from the Coordination of Rare Diseases at Stanford registry and Klippel-Feil Syndrome Freedom registry. The cervical fusions were categorized into Samartzis type I, II, or III. The independent-sample t-test, Wilcoxon rank-sum test, and Friedman test were conducted, with significance set at p < 0.05. RESULTS: Seventy-five patients (60 female, 14 male, and 1 unknown) were identified and classified as having the following types of Samartzis fusion: type I, n = 21 (28%); type II, n = 15 (20%); type III, n = 39 (52%). Seventy participants (93.3%) experienced pain associated with their KFS. The median age of patients at pain onset was 16.0 years (IQR 6.75-24.0 years), and the median age when pain worsened was 28.0 years (IQR 15.25-41.5 years). Muscle, joint, and nerve pain was primarily located in the shoulders/upper back (76%), neck (72%), and back of head (50.7%) and was characterized as tightness (73%), dull/aching (67%), and tingling/pins and needles (49%). Type III fusions were significantly associated with greater nerve pain (p = 0.02), headache/migraine pain (p = 0.02), and joint pain (p = 0.03) compared to other types of fusion. Patients with cervical fusions in the middle region (C2-6) tended to report greater muscle, joint, and nerve pain (p = 0.06). Participants rated the effectiveness of oral over-the-counter medications as 3 of 5 (IQR 1-3), oral prescribed medications as 3 of 5 (IQR 2-4), injections as 2 of 5 (IQR 1-4), and surgery as 3 of 5 (IQR 1-4), with 0 indicating the least pain relief and 5 the most pain relief. Participants who pursued surgical treatment reported significantly more comorbidities (p = 0.02) and neurological symptoms (p = 0.01) than nonsurgically treated participants and were significantly older when pain worsened (p = 0.03), but there was no difference in levels of muscle, joint, or nerve pain (p = 0.32); headache/migraine pain (p = 0.35); total number of cervical fusions (p = 0.77); location of fusions; or age at pain onset (p = 0.16). CONCLUSIONS: More than 90% of participants experienced pain. Participants with an increased number of overall cervical fusions or multilevel, contiguous fusions reported greater levels of muscle, joint, and nerve pain. Participants who pursued surgery had more comorbidities and neurological symptoms, such as balance and gait disturbances, but did not report more significant pain than nonsurgically treated participants.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.349

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.007
GPT teacher head0.241
Teacher spread0.234 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations10
Published2019
Admission routes1
Has abstractyes

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