Delayed diagnosis of cervical spondylotic myelopathy by primary care physicians
Bibliographic record
Abstract
OBJECT: A retrospective study analyzing medical files of patients who had undergone surgical management for cervical spondylotic myelopathy (CSM) at a single tertiary hospital was performed to determine the time needed by community care physicians to reach a diagnosis of CSM in patients presenting with typical myelopathic signs and symptoms, and to establish the reasons for the delayed diagnosis when present. Previous studies have documented that early diagnosis and surgical treatment of CSM may improve patients' neurological as well as general outcome. However, patients complaining of symptoms compatible with CSM may undergo lengthy medical investigations and treatments by community-based physicians before a correct diagnosis is made. The authors have found no published data on the process and time frame involved in attaining a diagnosis of CSM in the community setting. METHODS: The medical records of 42 patients were retrospectively reviewed for demographic data, symptoms, time to diagnosis, physician specialty, number of visits involved in the diagnostic process, and neurological status prior to surgery. RESULTS: The mean time delay from initiation of symptoms to diagnosis of CSM was 2.2 ± 2.3 years. The majority of symptomatic patients (90.4%) initially presented to a family practitioner (69%) or an orthopedic surgeon (21.4%), with fewer patients (9.6%) referring to other disciplines (for example, the emergency department) for initial care. In contrast, the diagnosis of CSM was most often made by neurosurgeons (38.1%) and neurologists (28.6%), and less frequently by orthopedic surgeons (19%) or family physicians (4.8%). CONCLUSIONS: The diagnosis of CSM in the community is frequently delayed, leading to late referral for surgery. A higher index of suspicion for this debilitating entity is required from family practitioners and community-based orthopedic surgeons to prevent neurological sequelae.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".