【摘要】 目的 观察在腹腔镜胆囊切除术中，氯胺酮超前镇痛对瑞芬太尼麻醉后急性疼痛的影响。 方法 2009年10月-2010年1月，将择期行腹腔镜胆囊切除术患者90例，随机分为对照组（C组）、氯胺酮超前镇痛组（K组）、氯胺酮术毕镇痛组（K1组），每组30例。所有患者均采用瑞芬太尼复合丙泊酚静脉麻醉，K组在切皮前静脉给予氯胺酮0.5 mg/kg，K1组在关腹前静脉给予氯胺酮0.5 mg/kg，C组不给予任何药物。记录术毕患者麻醉恢复情况，各时间点疼痛程度。 结果 K组、K1组躁动发生率均明显低于C组（Plt;0.05）；术后2、4、8、24 h，K组VAS评分及镇痛药使用率明显低于C组和K1组（Plt;0.05）。 结论 氯胺酮超前镇痛能明显降低瑞芬太尼术后疼痛，并且不增加并发症发生率。【Abstract】 Objective To evaluate the preemptive analgesia of ketamine on remifentanil induced acute postoperative pain after laparoscopic cholecystectomy. Methods Ninty patients scheduled for laparoscopic cholecystectomy between october 2009 to Jannary 2010 were randomly assigned to three groups (n=30). Group K was administrated with 0. 5 mg/kg ketamine intravenously before skin incision, and Group K1 were administrated with 0. 5 mg/kg ketamine intravenously before abdominal closure, while Group C received nothing. The recovery and the side effects were recorded, the VAS at two, four, eight and 24 hours after surgery, and the use of anodyne were recorded. Results The incidence of restlessness in Groups K and K1 was remarkably lower than that of Group C (Plt;0. 05). The analgesic effects two, four, eight and 24 hours after surgery were obviously better in group K than those of Group C and Group K1 (Plt;0. 05). Conclusion Ketamine can produce preemptive analgesia to relieve remifentanil-induced acute pain, and it would not increase incidence of side effects.
ObjectiveTo investigate the video-electroencephalography (VEEG) characteristics of old patients with epilepsy (OPWE). MethodsBetween June 2013 and July 2014, 57 OPWE at an age over 60 years were assigned to research group and 65 adults between 16 and 60 years old with epilepsy were regarded as controls. All the subjects underwent VEEG for 24 hours covering awake state and sleep with hyperventilation test being applied. Chi square was used to compare occurrence rate of epileptic wave and abnormal response rate after hyperventilation between the two groups of patients. Additionally, ictal elcetroencephalograph (EEG) was analyzed. ResultsCommon features of waves on EEG for patients in both the two groups during the ictal period included widespread low amplitude fast wave (2 cases in the research group, 7.4%; 4 cases in the control group, 12.5%), focal low amplitude fast wave (5 cases in the research group, 18.5%; 6 cases in the control group, 18.8%), widespread spike or spike slowing complex (3 cases in the research group, 11.1%; 7 case in the control group, 21.8%), focal spike or spike slowing complex (5 cases in the research group, 14.9%; 8 cases in the control group, 25.0%), and focal rhythmic slow wave (6 cases in the research group, 18.5%; 6 cases in the control group, 18.8%). In the research group, there were two following cases:single abnormal background activity in 5 cases (18.5%), and neither abnormal background activity nor epileptic discharge in 1 case (3.7%). Ictal focal epileptic discharges were found in 16 cases in the research group and 8 in the control group (59.3% vs 25.0%), with statistical difference (P<0.05). Inter-ictal epilepsy discharges were found in 57 patients of the research group (awake, 15.8%; sleep, 52.6%), which was less than that in the control group (awake, 46.2%; sleep, 83.1%) with statistical difference (P<0.05), accompanied by focal slow wave (temporal intermittent rhythmic delta activity, TIRDA) in 9 cases. In natural sleep period, epilepsy discharge occurrences increased (65.3%). Abnormal response rate in the research group (14.0%) was lower than that in the control group (64.6%) with statistical difference (P<0.05). ConclusionEarly onset EEG of the old and the adult are similar except those with single abnormal background activity and those with neither abnormal background activity nor epileptic discharge. Focal onset on EEG is more frequently seen in OPWE than in APWE. In natural sleep, epileptic discharge increases among OPWE, and abnormal response during hyperventilation is less likely to happen in OPWE.
Objective To investigate the prevalence of anxiety and depression in patients with epilepsy (PWE) in West China, and to explore the related risk factors. Methods The Chinese version of Generalized Anxiety Disorder (GAD)-7 and Neurological Disorders Depression Inventory for Epilepsy (NDDI-E) scales were used to evaluate the anxiety and depression in 176 PWE patients between December 2016 and February 2017. Univariate analysis was used to screen the factors that may cause anxiety and depression in PWE, and then logistic regression analysis was performed on the possible risk factors. Results In the 176 PWE, about 27.3% had anxiety, and about 28.4% had depression. Multivariate logistic regression analysis showed that seizure occurrence in the recent six months [odds ratio (OR)=3.481, 95% confidence interval (CI) (1.292, 9.380),P=0.014], seizure occurring more than once in a month [OR=3.231, 95%CI (1.468, 7.111),P=0.004], and focal seizures with conscious disorders [OR=2.416, 95%CI (1.082, 5.397),P=0.031] were risk factors for anxiety in PWE. Unmarried status [OR=0.428, 95%CI (0.195, 0.940),P=0.035], seizure occurring more than once in a month [OR=2.685, 95%CI (1.206, 5.979),P=0.016], focal seizures with conscious disorders [OR=2.541, 95%CI (1.112, 5.808),P=0.027] and seizure occurrence in the last six months [OR=7.582, 95%CI (2.416, 23.794),P=0.001] were risk factors for depression in PWE. Conclusions Anxiety and depression are common comorbidities in PWE. For patients with risk factors, early identification and intervention should be performed.
ObjectiveTo systematically evaluate the risk prediction model of knee osteoarthritis (KOA). MethodsThe CNKI, WanFang Data, VIP, PubMed, Embase, Web of Science and Cochrane Library databases were electronically searched to collect relevant studies on KOA’s risk prediction model from inception to April, 2024. After study screening and data extraction by two independent researchers, the PROBAST bias risk assessment tool was used to evaluate the bias risk and applicability of the risk prediction model. ResultsA total of 12 studies involving 21 risk prediction models for KOA were included. The number of predictors ranged from 3 to 12, and the most common predictors were age, sex, and BMI. The range of modeling AUC included in the model was 0.554-0.948, and the range of testing AUC was 0.6-0.94. The overall predictive performance of the models was mediocre and the risk of overall bias was high, and more than half of the models were not externally verified. ConclusionAt present, the overall quality and applicability of the KOA morbidity risk prediction model still have great room for improvement. Future modeling should follow the CHARMS and PROBAST to reduce the risk of bias, explore the combination of multiple modeling methods, and strengthen the external verification of the model.
Objective We aimed to evaluate the current status of the construction and practice of the stroke center in West China Hospital of Sichuan University and develope a future strategy to promote the standardized developement of inpatients care and evidence practice. Methods The current status of the Stroke Center in West China Hospital of Sichuan University was assessed. The procedure of diagnosis and treatment was inspected in detail, including triage, thrombolytic therapy, antithrombotic medication and anticoagulant, primary and secondary prevention, filter of risk factors, rehabilitation and education for patients. After that, new plans were made on the basis of the assessment and experiences acquired from practices in the Stroke Center in West China Hospital. Results The primary Stroke Center had been constructed in West China Hospital. The practice in West China Hospital showed that the Stroke Center significantly reduced the mortality and shortened the length of hospital stay of the patients with stroke. Conclusion It is proved that construction and implementation of the Stroke Center in West China Hospital are feasible.
ObjectiveTo evaluate the effect of the timing of surgery on treating refractory epilepsy caused by cavernomas. Method63 patients with refractory epilepsy caused by intracranial supratentorial cavernomas were retrospectively analyzed on the duration of epilepsy, epileptogenesis sitations, and epileptic seizure types. After resection surgeries of cavernomas, the surgical outcomes were compared between the patients with shorter duration of seizures and the longer ones. ResultThe durations of epilepsy were beteen 3 months and 25 years, median 4.5 years. The temporal epilepsies were 43, frontal 12, parietal 3, occipital 1, cingulate gyrus 1, and multiple lobe 3. The overall ILAE class 1 outcome was 71.4% in 63 patients at 2-year-followup, and ILAE class 1 and 2 outcome was 81.6%. The seizure free rate in the group with epilepsy duration shorter than 5 years was 92.1%, better than the 56.0% in the group with epilepsy duration longer than 5 years. ConclusionOnce the diagnosis of medical refractory epilepsy caused by cavernoma was confirmed, the early surgical operation should be considered seriously.
ObjectiveTo analyze the changing trends in disease burden of femoral fractures in China from 1990 to 2021, evaluate the impacts of age, period, and cohort effects, and project the age-standardized prevalence rate and age-standardized incidence rates of femoral fractures from 2022 to 2036. MethodsUtilizing open data from the 2021 Global Burden of Disease (GBD) study, this research characterized the disease burden of femoral fractures in China between 1990 and 2021, including trends in incidence, prevalence, and years lived with disability (YLDs). Age-standardized rates were calculated, and Joinpoint regression models were employed to estimate annual percentage changes (APC) and average annual percentage changes (AAPC). An age-period-cohort (APC) model was applied to quantify the effects of age, period, and birth cohort on disease burden. A Bayesian age-period-cohort (BAPC) model was further utilized to project age-standardized prevalence rates and age-standardized incidence rates from 2022 to 2036, with stratified analyses by age, sex, and time period. ResultsFrom 1990 to 2021, age-standardized prevalence (AAPC=0.138 5%), incidence (AAPC=0.294 2%), and YLD rates (AAPC=0.128 3%) exhibited sustained upward trends. Unintentional injuries constituted the predominant etiology of femoral fractures, followed by transport accidents and interpersonal violence/self-harm. In 2021, disease burden escalated with advancing age, with females over 60 years demonstrating significantly higher burdens than males. Age effect coefficients showed a monotonic increase, period effects displayed a U-shaped trajectory (decline followed by rebound), and cohort effects exhibited an inverted U-shaped pattern (rise then decline). Projections indicated continued growth in age-standardized prevalence rates and age-standardized incidence rates through 2036. ConclusionAs the population aging intensifies in China, the disease burden of femoral fractures in our country remains extremely severe. Among them, the elderly female group has become the key focus for prevention and control due to the high prevalence of osteoporosis.
ObjectiveTo systematically review the research status of risk prediction models for cognitive impairment in patients with T2DM. MethodsThe CNKI, WanFang Data, VIP, CBM, PubMed, Embase, Web of Science, Cochrane Library databases and Clinical trial registration platform were electronically searched to collect relevant literature on risk prediction models for cognitive impairment in patients with T2DM from inception to February 13th 2025. Two researchers independently screened the literature, extracted data, and assessed the risk of bias of the included studies, and then qualitative description and meta-analysis was performed. ResultsA total of 20 studies were included, involving 25 risk prediction models. In terms of the risk of bias, 20 studies were considered as high risk. With regards to applicability, 20 studies were high applicability. The pooled area under the curve (AUC) for modeling set was 0.83 (95%CI 0.79 to 0.88) and for the validation set was 0.83 (95% CI 0.79 to 0.87). It suggested that the model had good discrimination ability. The most common predictors included age, education level, duration of diabetes and depression. ConclusionThe overall performance of the risk prediction model for cognitive impairment in patients with T2DM is good, but the quality of the model needs to be improved.