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BACKGROUND: The size of artificial disc is not exactly identical to cervical vertebral endplate. However, the effect of implant size on cervical disc replacement has not yet been clearly identified. OBJECTIVE: To evaluate the effect of Bryan disc size on cervical artificial disc replacement. METHODS: Totally 71 patients with cervical degenerative disease underwent single-level Bryan disc replacement from December 2003 to December 2007 were enrolled. The average age was (45.90±8.12) years old, and all patients were followed up for more than 10 years. The artificial disc size was measured using lateral X-ray films, and expressed as (Bryan artificial disc's footprint sagittal diameter×2) / (upper endplate sagittal diameter + lower endplate's sagittal diameter)×100%. X-ray films were photographed to measure motion range of the treated segment before surgery, 3 months after surgery, and during final follow-up. Clinical outcomes, including Japanese Orthopaedic Association score, Neck Disability Index and Odom's scores, were evaluated before and after operation. Observational indexes of different disc sizes (≥95% and <95% groups) were compared and analyzed. RESULTS AND CONCLUSION: (1) There were 49 patients in the ≥95% group and 22 patients in the <95% group. (2) At 3-month follow-up, range of motion was significantly smaller in the <95% group than in the ≥95% group (P < 0.01). At the final follow-up, range of motion was significantly smaller in the <95% group than in the ≥95% group (P < 0.05). (3) At final follow-up, improvement rate of Japanese Orthopaedic Association score was (70.65±32.58)% in the <95% group and (68.83±38.85)% in the ≥95% group, and no significant difference was detected between the two groups (P > 0.05). (4) At final follow-up, Neck Disability Index decreased by (10.82±7.50)% in the <95% group, and (12.61±8.51)% in the ≥95% group, and no significant difference was detected between the two groups (P > 0.05). (5) At final follow-up, Odem's score results showed excellent in 10 cases (45%), good in 9 cases (41%) and average in 3 cases (14%) in the <95% group; and excellent in 26 cases (53%), good in 20 cases (41%) and average in 3 cases (6%) in the ≥95% group, and no significant difference was detected between the two groups (P > 0.05). (6) Results suggest that different sizes of artificial disc replacement have obtained good functional recovery, but small artificial disc may impact the range of motion. We should try to avoid placing the artificial disc smaller than 95%.
RESUMEN
<p><b>BACKGROUND</b>Differentiating intracerebral hemorrhage (ICH) from cerebral infarction as early as possible is vital for the timely initiation of different treatments. This study developed an applicable model for the ambulance system to differentiate stroke subtypes.</p><p><b>METHODS</b>From 26,163 patients initially screened over 4 years, this study comprised 1989 consecutive patients with potential first-ever acute stroke with sudden onset of the focal neurological deficit, conscious or not, and given ambulance transport for admission to two county hospitals in Yutian County of Hebei Province. All the patients underwent cranial computed tomography (CT) or magnetic resonance imaging to confirm the final diagnosis based on stroke criteria. Correlation with stroke subtype clinical features was calculated and Bayes' discriminant model was applied to discriminate stroke subtypes.</p><p><b>RESULTS</b>Among the 1989 patients, 797, 689, 109, and 394 received diagnoses of cerebral infarction, ICH, subarachnoid hemorrhage, and other forms of nonstroke, respectively. A history of atrial fibrillation, vomiting, and diabetes mellitus were associated with cerebral infarction, while vomiting, systolic blood pressure ≥180 mmHg, and age <65 years were more typical of ICH. For noncomatose stroke patients, Bayes' discriminant model for stroke subtype yielded a combination of multiple items that provided 72.3% agreement in the test model and 79.3% in the validation model; for comatose patients, corresponding agreement rates were 75.4% and 73.5%.</p><p><b>CONCLUSIONS</b>The model herein presented, with multiple parameters, can predict stroke subtypes with acceptable sensitivity and specificity before CT scanning, either in alert or comatose patients. This may facilitate prehospital management for patients with stroke.</p>