Review: Can we identify how programmes aimed at promoting self‐management in musculoskeletal pain work and who benefits? A systematic review of sub‐group analysis within RCTs

Background: There are now several systematic reviews of RCTs testing self‐management for those with chronic musculoskeletal pain. Evidence for the effectiveness of self‐management interventions in chronic musculoskeletal pain is equivocal and it is not clear for which sub‐groups of patients SM is optimally effective. Aims: To systematically review randomized controlled trials of self‐management for chronic musculoskeletal pain that reported predictors, i.e., ‘baseline factors that predict outcome independent of any treatment effect’; moderators, i.e., ‘baseline factors which predict benefit from a particular treatment’; or mediators i.e., ‘factors measured during treatment that impact on outcome’ of outcome. Method: We searched relevant electronic databases. We assessed the evidence according to the methodological strengths of the studies. We did meta‐regression analyses for age and gender, as potential moderators. Results: Although the methodological quality of primary trials was good, there were few relevant studies; most were compromised by lack of power for moderator and mediator analyses. We found strong evidence that self‐efficacy and depression at baseline predict outcome and strong evidence that pain catastrophizing and physical activity can mediate outcome from self‐management. There was insufficient data on moderators of treatment. Conclusions: The current evidence suggests four factors that relate to outcome as predictors/mediators, but there is no evidence for effect moderators. Future studies of mediation and moderation should be designed with ‘a priori’ hypotheses and adequate statistical power.     

Clinical predictors of steroid-induced exacerbation in myasthenia gravis

Although oral corticosteroids are effective for the treatment of myasthenia gravis (MG), the possibility of steroid-induced exacerbation of symptoms, especially during the initial course of steroid therapy, has limited their use patients with severe MG. However, the factors influencing or predicting in exacerbation are not well understood. The purpose of this study was to identify the clinical factors that predict the initial paradoxical exacerbation of MG in response to steroid therapy. Fifty-five consecutive patients who were administered for the first time high doses of prednisone (40-80 mg) in a tertiary medical centre in Seoul, were included. Prednisone-induced exacerbation was defined as a significant reduction in a patient's Myasthenia Gravis Severity Scale (MSS) score within 4 weeks of prednisone administration. We divided the patients into two groups on the basis of whether or not they experienced prednisone-induced exacerbation, and investigated the differences between the two groups with respect to clinical, laboratory and electrophysiological features. Twenty-three patients (42%) experienced definite exacerbation after prednisone therapy. Older age, predominantly severe bulbar symptoms, and low MSS score were found to be significant clinical predictors of exacerbation by multivariate logistic regression analysis. A high daily dosage of prednisone relative to body weight was found to be neither a predictor of exacerbation nor a predictor of early improvement in bivariate correlation analysis. Steroid-induced exacerbation in MG is a frequently encountered and challenging problem. Clinicians should be aware of the possibility of exacerbation of MG when prescribing prednisone, especially when treating elderly, bulbar dominant, or severely myasthenic patients.     

胸部放化疗后完全缓解的局限期小细胞肺癌脑转移风险

目的 评价影响胸部放化疗后完全缓解的Ⅱ_B-Ⅲ_B期小细胞肺癌患者发生脑转移的临床因素。方法 回顾性分析191例于2009年1月至2016年4月在浙江省肿瘤医院接受胸部放化疗达到完全缓解的Ⅱ_B-Ⅲ_B期小细胞肺癌患者。对脑转移预后相关的因素,如性别、年龄、胸部放疗剂量、放化疗模式、治疗前血清神经元特异性烯醇化酶（NSE）和乳酸脱氢酶（LDH）、是否行预防性全脑照射（PCI）、TMN分期、体力状态评分（PS）等进行分析。使用log-rank法进行单因素分析,使用COX回归法进行多因素分析,使用Kaplan-Meier法绘制生存曲线。结果 单因素分析提示治疗前LDH≥240 IU、治疗前NSE≥17 ng/ml、未行PCI和脑转移风险正相关（P<0.05）。多因素分析提示脑转移风险只和治疗前LDH≥240 IU（HR=1.90,95%CI为1.07~3.37,P=0.029）、未行PCI（HR=2.08,95%CI为1.17~3.72）,P=0.013）正相关。结论 治疗前血清LDH水平可为预测胸部放化疗后达到完全缓解的Ⅱ_B-Ⅲ_B期小细胞肺癌患者的脑转移风险提供重要价值。     

97例急性心肌梗死患者的葡萄糖代谢状态分析

目的:研究无糖尿病史的急性心肌梗死(AMI)患者的葡萄糖代谢状态.方法:选择无糖尿病史的AMI患者97例,入院时测HbA1c、血脂、简易OGTT(0及120 min),同步测定胰岛素水平,病程第4周及出院后3月进行正规OGTT及IRT,并复查上述指标,记录患者的临床特征及血糖变化情况.结果:依出院后3月OGTT结果,按WHO标准将其分为3组:NGT组(33例),IGT组(34例),DM组(30例).发生葡萄糖代谢异常的比例为68.0%;不同葡萄糖代谢状况的3组患者间比较,入院时FPG、HbA1c、血甘油三酯差异有显著性.3月内,AMI患者葡萄糖代谢状况可在NGT、IGT、DM间互相转化,但OGTT(PG-60')保持相对稳定,可预测将来的葡萄糖代谢状况.结论:无糖尿病史的AMI患者中,普遍存在葡萄糖代谢异常,发病3个月内,AMI急性期所伴随的葡萄糖代谢状况可在NGT、IGT、DM之间转化,也可保持不变;病程第4周OGTT单次血糖(PG-60')是预测其后葡萄糖代谢状况的有用指标,切点值为9.1 mmol/L.     

影响减重术后2型糖尿病缓解的相关因素

2型糖尿病是胰岛素抵抗及β细胞功能衰竭共同作用的结果,传统药物治疗糖尿病的方式无法阻止β细胞功能的进行性下降,而减重手术作为治疗糖尿病的有效措施已获得共识。然而,现行的主要基于体重指数的筛选标准已不能满足提高缓解率的要求,预测术后糖尿病缓解还需考虑缓解终点的设定、2型糖尿病状态、生化指标、术式等其他因素,联合相关因素有望使更多糖尿病患者获益。     

Predictors of participation change in various areas for preschool children with cerebral palsy: A longitudinal study

This study identifies potential predictors of participation changes in various areas for preschool children with cerebral palsy (CP). Eighty children with CP (2–6 years) were enrolled. Seven potential predictors were identified: age; sex; socioeconomic status, CP subtype; cognitive function, Function Independence Measure for Children (WeeFIM), and motor composite variable from 5 motor factors (gross motor function classification system (GMFCS) level; bimanual fine motor function level; selective motor control score; Modified Ashworth Scale score; and Spinal Alignment and Range of Motion Measure). Outcome was assessed at baseline and at 6-month follow-up using the Assessment of Preschool Children's Participation (APCP) including diversity and intensity scores in the areas of play (PA), skill development (SD), active physical recreation, social activities (SA), and total areas. Dependent variables were change scores of APCP scores at baseline and 6-month follow-up. Regression analyses shows age and sex together predicted for APCP-total, APCP-SD diversity and APCP-total intensity changes (r² = 0.13–0.25, p < 0.001); cognitive function and WeeFIM were negative predictors for APCP-SA and APCP-PA diversity changes, respectively. CP subtype, motor composite variable, and socioeconomic status predicted for APCP changes in some areas. Findings suggest that young boys with poor cognitive function and daily activity predicted most on participation changes.     

A rest-activity biomarker to predict response to SSRIs in major depressive disorder

Most adults with Major Depressive Disorder (MDD) will not experience a remission with the first antidepressant trial. No practical biomarkers presently exist to predict responsiveness to antidepressants. Herein we report pilot data for a rest-activity biomarker of antidepressant response.Fifty-eight medication-free adults with MDD underwent a week-long collection of actigraphic data before beginning a 9 week open label trial of fluoxetine, coupled with blinded randomized assignment to eszopiclone/placebo. Depression severity was repeatedly measured with the Hamilton Rating Scale for Depression (HRSD). Baseline actigraphic data was analyzed with functional data analysis to create smoothed 24-h curves of activity. The time of the lowest point of activity (the bathyphase) was calculated for each patient, as well the mean difference between bedtime and the bathyphase (BBD). At the end of treatment, patients were characterized as treatment responders (50% reduction in HRSD) or non-responders, and receiver operating curves were calculated to find the optimal cut point of the BBD for prediction of treatment response.The best cut point for BBD was at 260.2 min, resulting in an effect size of 1.45, and with a positive predictive value of 0.75 and a negative predictive value of 0.88.We conclude that actigraphically-determined measures of rest-activity patterns show promise as potential biomarker predictors of antidepressant response. However, this conclusion is based upon a small number of patients who received only one choice of antidepressant, for a single trial. Replication with a larger sample is needed.     

Predicting discharge outcomes after total knee replacement using the Risk Assessment and Predictor Tool

Objective

To explore the use of the Risk Assessment and Predictor Tool (RAPT) as a pre-operative tool to predict postoperative discharge destination and length of stay for patients undergoing total knee replacement (TKR) in Singapore.

Participants and setting

A cohort of 569 patients undergoing primary TKR at the Singapore General Hospital were recruited prospectively from November 2009 to June 2010.

Intervention

All patients completed a modified RAPT questionnaire pre-operatively, and underwent standard clinical pathway guidelines for TKR throughout the study.

Main outcome measures

Actual discharge destination (ADDest) and length of stay (LOS).

Design

Total RAPT score and preferred discharge destination (PDD) were recorded pre-operatively, while ADDest and LOS were obtained immediately after discharge. Multivariable logistic regression and multivariable regression analysis were used to determine whether the RAPT items and score could predict the discharge outcomes.

Results

Total RAPT score was a significant predictor of LOS for patients following TKR (R = 0.24, P < 0.001); the higher the RAPT score, the longer the LOS. Total RAPT score was also a significant predictor of actual discharge to home [odds ratio (OR) 2.32, 95% confidence interval (CI) 1.11 to 4.85]. PDD was a significant predictor for LOS (R = 0.22, P < 0.001) and ADDest (R = 0.33, P < 0.001). Patients who chose to be discharged home were more likely to be directly discharged home (OR 9.79, 95% CI 5.07 to 18.89, P < 0.001).

Conclusion

Total RAPT score and PDD were significant predictors of ADDest and LOS for patients following TKR in Singapore. The ability to predict discharge outcomes following TKR could assist caregivers, healthcare professionals and administrators in optimising care and resource allocations for patients.     

急诊科反复喘息婴幼儿需要住院并接受呼吸支持治疗的预测因素

目的 反复喘息患者多为2岁以下的婴幼儿。在热带国家,对该人群住院期间接受呼吸支持治疗的风险的临床预测模型研究较少。该研究旨在评估就诊于哥伦比亚急诊科的反复喘息婴幼儿需要住院并接受呼吸支持治疗的临床预测因素。方法 该研究是一项回顾性队列研究,纳入了2019年1~12月期间在哥伦比亚Rionegro的两个三级中心医院就诊的所有患有2次或2次以上喘息发作的婴幼儿（年龄均小于2岁）。主要结局指标是住院加呼吸支持治疗。采用多因素logistic回归模型确定需要住院并接受呼吸支持治疗的独立预测因素。结果 共85名婴幼儿住院并接受呼吸支持治疗,其中34名（40%）予以高流量鼻导管吸氧,2名（2%）予以无创通气,6名（7%）予以机械通气,43名（51%）予以常规氧疗。多因素logistic回归模型分析显示,早产（OR=1.79,95% CI：1.04~3.10）、喂养困难（OR=2.22,95% CI：1.25~3.94）、鼻煽和/或咕噜声（OR=4.27,95% CI：2.41~7.56）和既往有1次以上喘息发作需要住院治疗（OR=3.36,95% CI：1.86~7.08）是需要住院并接受呼吸支持治疗的预测因素。该模型特异度高（99.6%）,鉴别度中等,曲线下面积为0.70（95% CI：0.60~0.74）。结论 该研究表明,早产、喂养困难、鼻煽和/或呼噜声,以及有1次以上需要住院治疗的喘息发作史,是急诊科就诊的反复喘息婴幼儿需要住院并接受呼吸支持治疗的独立预测因素。然而,还需收集更多的其他热带国家的证据来验证这个结论。