As robotic systems become more autonomous, it gets less straightforward to determine liability when humans are harmed. This is an important emerging challenge, with legal implications, in the field of surgical robotic systems. The iRobotSurgeon survey (www.iRobotSurgeon.com) explores public opinions about questions of responsibility and liability in the area of surgical robotics.

Background The literature lacks information about the characteristics of the placebo effect following sham spine procedures for chronic low back pain. We aim to evaluate the effect using pain score data from the sham arms of published trials. Methods Relevant trials were selected and reviewed. Baseline and post-procedure pain scores were collected. Each follow up pain score was considered an episode and compared to its baseline for significance. Patients and episodes were pooled and analyzed using three parameters: patient reported outcome measures (PROMs) (Oswestry Disability Index [ODI], Visual Analog Scale [VAS], Numerical Rating Scale [NRS] and Short Form-36 [SF]), anatomical targets (disc, facet, sacroiliac joint [SIJ], ramus communicans nerve [RCN], basivertebral nerve [BVN], and caudal) and follow up periods (early: 0–2, intermediate: >2–4 and late: >4–6) in months. The percentage of pooled patients in the episodes that had significant reduction in pain scores was termed placebo effect. The outcome was defining the magnitude of the placebo effect and determining if it was influenced by the three parameters. Results Seventeen studies that reported 535 patients and 55 pain scoring episodes were considered eligible. Significant reduction in pain scores was reported in 21 episodes. The overall placebo effect among the patients during the studied period was 53.2%. The rate ranged according to PROMs from 42.4% to 72.1%, anatomical targets from 11.1% to 100% and follow up periods from 47.9% to 59%. The placebo effect differed significantly between the various domains in the three parameters. Conclusion Placebo effect was observed in nearly half of the patients during the first 6 months following a sham spine procedure. The effect was influenced by utilized PROMs, anatomical target and follow up period. The findings should be considered in the design of new sham spine procedure trials. Further research is required to delineate the effect of bias on the findings.

Clinical trials are at the top of research study designs and tend to attract high citation numbers. Glioblastoma multiforme (GBM) is a multidisciplinary disease that continues to be the subject of peak research interest. In general, the literature relating to the predictors of citation rates in clinical trials remains limited. This review aims to identify the factors that influence citation numbers in high-impact GBM clinical trials. The 100 most cited GBM trials of any phase published from 1975 to 2019 were selected and reviewed. The primary analysis correlated citation numbers of articles with various trial and publication-related predictors using the Pearson correlation coefficient. The secondary analysis compared the mean citation numbers for different subgroups using the mean difference test. The median (range) citation number for the selected 100 trials was 349 (135-16,384). The primary analysis showed a significant correlation between citation numbers of articles and the study population (P = 0.024), trial phase (I-III) (P = 0.0427), and the impact factor (IF) of the journal (P < 0.0001). The secondary analysis demonstrated significantly higher mean citation numbers in all trials with the following features: study population ≥115 (P = 0.0208), phase III (P = 0.0372), treatment protocol including radiotherapy (P = 0.0189), temozolomide (TMZ) therapy (P = 0.0343), IF of the journal ≥14.9 (P = 0.02), and general medical journals (P = 0.28). We conclude that the most significant predictors of citation rates in high-impact GBM trials were the study population, trial phase, and journal’s IF. The treatment protocol was a positive predictor when it included the currently widely accepted treatment modalities (radiotherapy and TZM). Randomization, age of publication, as well as the numbers of arms, authors, centers, countries, and references were not significant predictors. Increasing awareness of the factors that could affect citations may help researchers undertaking clinical trials to enhance the academic impact of their work.

Background Clinical trials are at the top of research study designs and tend to attract high citation numbers. Glioblastoma multiforme (GBM) is a multidisciplinary disease that continues to be the subject of peak research interest. The literature relating to predictors of citation rates in clinical trials in general remains limited. We aim to identify the factors that influence citation numbers in high impact GBM trials. Methods The 100 most cited published GBM trials were identified and reviewed. The primary analysis was correlating articles citation numbers with various trial and publication-related predictors using Pearson correlation coefficient. The secondary analysis was comparing the mean citation numbers for the different subgroups using mean difference test. Results The median (range) citation numbers for the selected 100 trials were 349 (135- 16384). The primary analysis showed significant correlation between articles citation numbers and study population (P=0.024), trial phase (P=0.0427) and journal’s IF (P<0.0001). The secondary analysis demonstrated significantly higher mean citation numbers in trials with the following features: study population ≥ 115 (P=0.0208), phase III (P=0.0372), treatment protocol that included radiotherapy (RT) (P=0.0189) and temozolomide (TMZ) (P=0.0343), journal’s IF ≥ 14.9 (P=0.02) and general medical journals (P=0.28). Conclusions The most significant predictors of citation rates in high impact GBM trials were study population, trial phase, and journal IF. The treatment protocol was a positive predictor when it included the currently widely accepted treatment modalities (RT and TZM). Randomization, age of publication as well as the numbers of arms, authors, centres, countries, and references were not significant predictors. Increasing awareness of the factors that could affect citations may be useful to researchers undertaking clinical trials.

No abstract