BACKGROUND:The effects of posterior decompression fixation in the repair of thoracolumbar fracture are affirmative. The fixation was divided into short-segment and long-segment pedicle screw fixation according to different treatment methods. The therapeutic effects of above two methods are controversial in the clinic at present. OBJECTIVE:To compare and observe the anterior vertebral compression ratio and the changes in Cobb angle after posterior short-segment and long-segment pedicle screw placement fixation in the repair of thoracolumbar fracture. METHODS:120 patients with thoracolumbar fracture were enrol ed in this study, and assigned to two groups according to fixation methods. Study group received posterior short-segment pedicle screw fixation. Control group received posterior long-segment pedicle screw fixation. Anterior vertebral compression rate and Cobb angle were observed before fixation, immediately and 12 months after fixation in both groups. RESULTS AND CONCLUSION:There was no significant difference in anterior vertebral compression rate and Cobb angle between the two groups before fixation (P>0.05). Anterior vertebral compression rate and Cobb angle were significantly smal er in the study group than in the control group immediately and 12 months after fixation (P<0.05). Besides, surgical time and blood loss volume were less in the study group than in the control group (P<0.05). These results indicated that posterior short-segment pedicle screw fixation for treatment of thoracolumbar fracture can effectively improve kyphosis, recover vertebral compression degree, and its surgical time is short and blood loss volume during surgery is little, so it is better than posterior long-segment pedicle screw fixation.

Objective To investigate characteristics of free fatty acid (FFA) and high-sensitivity Creactive protein (hs-CRP) in patients with type 2 diabetes mellitus and metabolic syndrome (MS) compared to those with type 2 diabetes mellitus without MS.Methods Totally 120 patients with type 2 diabetes mellitus who received blood glucose control in Shaoxing People's Hospital from January to June 2013 were recruited and divided into MS group (n =56) and non-MS group (n =64).The serum FFA profile of the patients was measured by enzymatic assay, and the serum hs-CRP level measured by particle-enhanced immuno-precipitation assay.Results The level of FFA was higher in the MS group than that in the non-MS group [(0.60 ±0.25) mmoL/L vs.(0.45 ±0.21) mmol/L, P =0.033].The level of hs-CRP was higher in the MS group than that in the non-MS group [5.29 (4.69-5.82) mg/L vs.0.73 (0.42-1.26) mg/L, P =0.000].The level of hs-CRP was higher in the patients with central obesity than that in those without central obesity [4.34 (0.91-5.46) mg/L vs.1.80 (0.82-3.27) mg/L, P=0.014], also higher in hypertensive patients than in non-hypertensive patients [5.21 (3.18-5.96) mg/L vs.2.93 (0.89-4.98) mg/L, P =0.012].Conclusions Serum FFA and hs-CRP concentrations may be significantly higher in type 2 diabetes mellitus patients with MS.The increased levels of FFA and hs-CRP may play an important role in the pathogenesis of type 2 diabetes mellitus and MS.

Objective To explore the clinical efficacy of Indigo thrombus aspiration system in acute pulmonary embolism(APE).Methods Seventy APE patients were selected.All patients were treated with percutaneous mechanical thrombectomy(PMT),and the Indigo thrombus aspiration system was used during surgery.The clinical efficacy and the occurrence of complications after surgery were compared in patients.Results The total therapy effective rate after surgery for patients was 94.29％(66/70),of which 42 cases were significantly effective,24 cases were effective and 4 cases were ineffective.The occurrence rate of complications after surgery for patients was 8.57％(6/70),including bradycardia in 1 case,tachycardia in 1 case,arrhythmia in 1 case,hemorrhage in 2 cases and renal insufficiency in 1 case.Conclusion The clinical efficacy of Indigo thrombus aspiration system in APE is significant and has certain safety.

Humans ; Parkinson Disease/diagnosis* ; Machine Learning