Laparoscopic vs robotic inguinal hernia repair: a comparison of learning curves and skill transference in general surgery residents.

BACKGROUND: There is no consensus on whether laparoscopic experience should be a prerequisite for robotic training. Further, there is limited information on skill transference between laparoscopic and robotic techniques. This study focused on the general surgery residents' learning curve and skill transference within the two minimally invasive platforms. METHODS: General surgery residents were observed during the performance of laparoscopic and robotic inguinal hernia repairs. The recorded data included objective measures (operative time, resident participation indicated by percent active time on console or laparoscopy relative to total case time, number of handoffs between the resident and attending), and subjective evaluations (preceptor and trainee assessments of operative performance) while controlling for case complexity, patient comorbidities, and residents' prior operative experience. Wilcoxon two-sample tests and Pearson Correlation coefficients were used for analysis. RESULTS: Twenty laparoscopic and forty-four robotic cases were observed. Mean operative times were 90 min for robotic and 95 min for laparoscopic cases (P = 0.4590). Residents' active participation time was 66% on the robotic platform and 37% for laparoscopic (P = < 0.0001). On average, hand-offs occurred 9.7 times during robotic cases and 6.3 times during laparoscopic cases (P = 0.0131). The mean number of cases per resident was 5.86 robotic and 1.67 laparoscopic (P = 0.0312). For robotic cases, there was a strong correlation between percent active resident participation and their prior robotic experience (r = 0.78) while there was a weaker correlation with prior laparoscopic experience (r = 0.47). On the other hand, prior robotic experience had minimal correlation with the percent active resident participation in laparoscopic cases (r = 0.12) and a weak correlation with prior laparoscopic experience (r = 0.37). CONCLUSION: The robotic platform may be a more effective teaching tool with a higher degree of entrustability indicated by the higher mean resident participation. We observed a greater degree of skill transference from laparoscopy to the robot, indicated by a higher degree of correlation between the resident's prior laparoscopic experience and the percent console time in robotic cases. There was minimal correlation between residents' prior robotic experience and their participation in laparoscopic cases. Our findings suggest that the learning curve for the robot may be shorter as prior robotic experience had a much stronger association with future robotic performance compared to the association observed in laparoscopy.

Skill transference and learning curves in novice learners: a randomized comparison of robotic and laparoscopic platforms.

BACKGROUND: While well-established protocols direct laparoscopic training, there remains a relative paucity of guidelines for robotic education. Furthermore, it is unknown how exposure to one platform influences trainees' proficiency in the other. This study aimed to compare and quantify (1) learning curves and (2) transference of skill between the two modalities in novice learners. METHODS: Thirty pre-clinical medical students were randomized into two groups. One group performed the peg-transfer task using the robot first, followed by laparoscopy, while the other group performed the same task laparoscopically first. Participants completed five repetitions with each methodology. Participants were timed and errors were recorded. We hypothesized that laparoscopic experience with the peg-transfer task would assist in completing the task robotically, and there would be a higher degree of skill transference from the laparoscopic to robotic platform. RESULTS: Peg-transfer task completion was consistently faster and more accurate with the robot compared to laparoscopy (p < 0.01). We observed a positive transference of skill from the laparoscopic to robotic platform. However, exposure to the robot-hindered students' ability to perform the task laparoscopically, evidenced by significantly increased time and errors when compared with baseline laparoscopic performance (p < 0.01). CONCLUSION: These findings encourage surgical residency programs to treat robotic and laparoscopic training as discrete entities and consider their unique learning curves and skill transference when designing an efficient curriculum. While these effects are observed in novices, future directions include uncovering the trends among resident trainees and practicing surgeons.

Randomized intervention and outpatient follow-up lowers 30-d readmissions for patients with hepatic encephalopathy, decompensated cirrhosis.

BACKGROUND: We previously reported national 30-d readmission rates of 27% in patients with decompensated cirrhosis (DC). AIM: To study prospective interventions to reduce early readmissions in DC at our tertiary center. METHODS: Adults with DC admitted July 2019 to December 2020 were enrolled and randomized into the intervention (INT) or standard of care (SOC) arms. Weekly phone calls for a month were completed. In the INT arm, case managers ensured outpatient follow-up, paracentesis, and medication compliance. Thirty-day readmission rates and reasons were compared. RESULTS: Calculated sample size was not achieved due to coronavirus disease 2019; 240 patients were randomized into INT and SOC arms. 30-d readmission rate was 33.75%, 35.83% in the INT vs 31.67% in the SOC arm (P = 0.59). The top reason for 30-d readmission was hepatic encephalopathy (HE, 32.10%). There was a lower rate of 30-d readmissions for HE in the INT (21%) vs SOC arm (45%, P = 0.03). There were fewer 30-d readmissions in patients who attended early outpatient follow-up (n = 17, 23.61% vs n = 55, 76.39%, P = 0.04). CONCLUSION: Our 30-d readmission rate was higher than the national rate but reduced by interventions in patients with DC with HE and early outpatient follow-up. Development of interventions to reduce early readmission in patients with DC is needed.

Socio-ecological influences on adolescent dietary typologies.

Background: Dietary behaviours of adolescence are concerning, and this may impact long-term well-being. Aim: This study examined the socio-ecological determinants of dietary behaviours in a national prospective cohort study of English adolescents. Methods: Latent class analysis was used to identify the typologies of eight dietary behaviours: fruit, vegetable, breakfast, sugar-sweetened beverages, artificial-sweetened beverages, fast-food, bread, and milk from 7402 adolescents aged 13-15 years (mean 13.8 ± 0.45 years) (50.3% female and 71.3% white ethnicity) participating in the U.K. Millennium Cohort Study (sixth survey). Multinomial logistic regression and path analysis predicted associations between personal characteristics, individual, influential others, social environment and physical environment determinants and three distinct diet typologies: (1) healthy, (2) less-healthy and (3) mixed, (reference category = mixed). Results: Within Path analysis, the magnitudes of coefficients were small to moderate suggesting a relatively weak relationship between the variables. Model 1 reported adolescents within the less-healthy compared to mixed typology had lower levels of physical activity (ß = 0.074, 95% CI = -0.115, -0.033), and have siblings (ß = 0.246, 95% CI = 0.105, 0.387). Model 2 reported adolescents within the healthy compared to mixed typology had lower screen time (ß = 0.104, 95% CI = 0.067, 0.141), and lower social media usage (ß = 0.035, 95% CI = 0.024, 0.046). Conclusion: This study highlights the importance of considering multiple dietary determinants. These findings are likely to be useful in supporting the development of multi-faceted interventions. They emphasise the need to move away from investigating silo behaviours on individual diet components and a step towards more systems thinking to improve adolescent eating behaviours.

The robot doesn't lie: real-life validation of robotic performance metrics.

BACKGROUND: Degree of resident participation in a case is often used as a surrogate marker for operative autonomy, an essential element of surgical resident training. Previous studies have demonstrated a considerable disagreement between the perceptions of attending surgeons and trainees when it comes to estimating operative participation. The Da Vinci Surgical System dual console interface allows machine generated measurements of trainee's active participation, which has the potential to obviate the need for labor intensive direct observation of surgical procedures. However, the robotic metrics require validation. We present a comparison of operative participation as perceived by the resident, faculty, trained research staff observer (gold standard), and robotic machine generated data. METHODS: A total of 28 consecutive robotic inguinal hernia repair procedures were observed by research staff. Operative time, percent active time for the resident, and number of handoffs between the resident and attending were recorded by trained research staff in the operating room and the Da Vinci Surgical System. Attending and resident evaluations of operative performance and perceptions of percent active time for the resident were collected using standardized forms and compared with the research staff observed values and the robot-generated console data. Wilcoxon two-sample tests and Pearson Correlation coefficients statistical analysis were performed. RESULTS: Robotic inguinal hernia repair cases had a mean operative time of 91.3 (30) minutes and an attending-rated mean difficulty of 3.1 (1.26) out of 5. Residents were recorded to be the active surgeon 71.8% (17.7) of the total case time by research staff. There was a strong correlation (r = 0.77) in number of handoffs between faculty and trainee as recorded by the research staff and robot (4.28 (2.01) vs. 5.8 (3.04) respectively). The robotic machine generated data demonstrated the highest degree of association when compared to the gold standard (research staff observed data), with r = 0.98, p < 0.0001. Lower levels of association were seen with resident reported (r = 0.66) perceptions and faculty-reported (r = 0.55) perceptions of resident active operative time. CONCLUSIONS: Our findings suggest that robot-generated performance metrics are an extremely accurate and reliable measure of intraoperative resident participation indicated by a very strong correlation with the data recorded by research staff's direct observation of the case. Residents demonstrated a more accurate awareness of their degree of participation compared with faculty surgeons. With high accuracy and ease of use, robotic surgical system performance metrics have the potential to be a valuable tool in surgical training and skill assessment.

Investigating where adolescents engage in moderate to vigorous physical activity and sedentary behaviour: An exploratory study.

BACKGROUND: There is a persistent lack of understanding on the influence of the environment on behaviour and health. While the environment is considered an important modifiable determinant of health behaviour, past research assessing environments often relies on static, researcher-defined buffers of arbitrary distance. This likely leads to misrepresentation of true environmental exposures. This exploratory study aims to compare researcher-defined and self-drawn buffers in reflecting the spaces and time adolescents engage in physical activity (PA) and sedentary behaviour. It also investigates if adolescent's access the PA facility and greenspace nearest their home or school for PA, as well as examine how much time adolescents spent in PA at any PA facilities and greenspaces. METHODS: Adolescents (aged 14-18 years; n = 34) were recruited from schools in West Yorkshire, England. Seven consecutive days of global positioning system (GPS) and accelerometer data were collected at 15 second intervals. Using ArcGIS, we compared 30 different researcher-defined buffers including: radial, network and ellipse buffers at 400m, 800m, 1000m, 1600m and 3000m and participant-defined self-drawn neighbourhoods to objectively measured PA and sedentary space and PA time. Location of PA was also compared to Points of Interest data to determine if adolescents use the nearest PA facility or greenspace to their home or school and to examine how much PA was undertaken within these locations. RESULTS: Our exploratory findings show the inadequacy of researcher-defined buffer size in assessing MVPA space or sedentary space. Furthermore, less than 35% of adolescents used the greenspaces or PA facilities nearest to their home or school. Approximately 50% of time spent in PA did not occur within the home, school, PA facility, or greenspace environments. CONCLUSION: Our exploratory findings help to begin to quantify the inadequacy of researcher-defined, and self-drawn buffers in capturing adolescent MVPA and sedentary space, as well as time spent in PA. Adolescents often do not use PA facilities and greenspaces nearest their home and school and a large proportion of PA is achieved outside PA facilities and greenspaces. Further research with larger samples are needed to confirm the findings of this exploratory study.

Can We Deliver Person-Centred Obesity Care Across the Globe?

PURPOSE OF REVIEW: This article discusses what person-centred care is; why it is critically important in providing effective care of a chronic, complex disease like obesity; and what can be learnt from international best practice to inform global implementation. RECENT FINDINGS: There are four key principles to providing person-centred obesity care: providing care that is coordinated, personalised, enabling and delivered with dignity, compassion and respect. The Canadian 5AsT framework provides a co-developed person-centred obesity care approach that addresses complexity and is being tested internationally. Embedding person-centred obesity care across the globe will require a complex system approach to provide a framework for healthcare system redesign, advances in people-driven discovery and advocacy for policy change. Additional training, tools and resources are required to support local implementation, delivery and evaluation. Delivering high-quality, effective person-centred care across the globe will be critical in addressing the current obesity epidemic.

Successful infusional 5-fluorouracil administration in a patient with vasospastic angina.

A 48-year-old female with metastatic colon adenocarcinoma and history of pre-existing coronary vasospasm with ventricular tachycardia (VT) successfully tolerated de novo 5-fluorouracil (5-FU) chemotherapy infusions with prophylactic administration and optimization of anti-spasm medications. 5-FU has been reported to produce severe cardiotoxic side effects, including coronary vasospasm, ventricular arrhythmias, and sudden cardiac death, and is not typically reported in individuals with pre-existing coronary vasospasm.

Exploring factors affecting individual GPS-based activity space and how researcher-defined food environments represent activity space, exposure and use of food outlets.

BACKGROUND: Obesity remains one of the most challenging public health issues of our modern time. Despite the face validity of claims for influence, studies on the causes of obesity have reported the influence of the food environment to be inconsistent. This inconsistency has been attributed to the variability of measures used by researchers to represent the food environments-Researcher-Defined Food Environments (RDFE) like circular, street-network buffers, and others. This study (i.) determined an individual's Activity Space (AS) (ii.) explored the accuracy of the RDFE in representing the AS, (iii.) investigated the accuracy of the RDFE in representing actual exposure, and (iv.) explored whether exposure to food outlet reflects the use of food outlets. METHODS: Data were collected between June and December 2018. A total of 65 participants collected Global Positioning System (GPS) data, kept receipt of all their food purchases, completed a questionnaire about their personal information and had their weight and height measured. A buffer was created around the GPS points and merged to form an AS (GPS-based AS). RESULTS: Statistical and geospatial analyses found that the AS size of participants working away from home was positively related to the Euclidean distance from home to workplace; the orientation (shape) of AS was also influenced by the direction of workplace from home and individual characteristics were not predictive of the size of AS. Consistent with some previous studies, all types and sizes of RDFE variably misrepresented individual exposure in the food environments. Importantly, the accuracy of the RDFE was significantly improved by including both the home and workplace domains. The study also found no correlation between exposure and use of food outlets. CONCLUSIONS: Home and workplace are key activity nodes in modelling AS or food environments and the relationship between exposure and use is more complex than is currently suggested in both empirical and policy literature.

Evidence from big data in obesity research: international case studies.

BACKGROUND/OBJECTIVE: Obesity is thought to be the product of over 100 different factors, interacting as a complex system over multiple levels. Understanding the drivers of obesity requires considerable data, which are challenging, costly and time-consuming to collect through traditional means. Use of 'big data' presents a potential solution to this challenge. Big data is defined by Delphi consensus as: always digital, has a large sample size, and a large volume or variety or velocity of variables that require additional computing power (Vogel et al. Int J Obes. 2019). 'Additional computing power' introduces the concept of big data analytics. The aim of this paper is to showcase international research case studies presented during a seminar series held by the Economic and Social Research Council (ESRC) Strategic Network for Obesity in the UK. These are intended to provide an in-depth view of how big data can be used in obesity research, and the specific benefits, limitations and challenges encountered. METHODS AND RESULTS: Three case studies are presented. The first investigated the influence of the built environment on physical activity. It used spatial data on green spaces and exercise facilities alongside individual-level data on physical activity and swipe card entry to leisure centres, collected as part of a local authority exercise class initiative. The second used a variety of linked electronic health datasets to investigate associations between obesity surgery and the risk of developing cancer. The third used data on tax parcel values alongside data from the Seattle Obesity Study to investigate sociodemographic determinants of obesity in Seattle. CONCLUSIONS: The case studies demonstrated how big data could be used to augment traditional data to capture a broader range of variables in the obesity system. They also showed that big data can present improvements over traditional data in relation to size, coverage, temporality, and objectivity of measures. However, the case studies also encountered challenges or limitations; particularly in relation to hidden/unforeseen biases and lack of contextual information. Overall, despite challenges, big data presents a relatively untapped resource that shows promise in helping to understand drivers of obesity.

Reconsidering the relationship between fast-food outlets, area-level deprivation, diet quality and body mass index: an exploratory structural equation modelling approach.

BACKGROUND: Internationally, the prevalence of adults with obesity is a major public health concern. Few studies investigate the explanatory pathways between fast-food outlets and body mass index (BMI). We use structural equation modelling to explore an alternative hypothesis to existing research using area-level deprivation as the predictor of BMI and fast-food outlets and diet quality as mediators. METHODS: Adults (n=7544) from wave II of the Yorkshire Health Study provided self-reported diet, height and weight (used to calculate BMI). Diet quality was based on sugary drinks, wholemeal (wholegrain) bread and portions of fruit and vegetables. Fast-food outlets were mapped using the Ordnance Survey Points of Interest within 2 km radial buffers around home postcode which were summed to indicate availability. Age (years), gender (female/male) and long-standing health conditions (yes/no) were included as covariates. RESULTS: There was little evidence linking fast-food outlets to diet or BMI. An independent association between fast-food outlet availability and BMI operated counterintuitively and was small in effect. There was also little evidence of mediation between fast-food outlet availability and BMI. However, there was more evidence that area-level deprivation was associated with increased BMI, both as an independent effect and through poorer diet quality. CONCLUSION: This exploratory study offers a first step for considering complexity and pathways linking fast-food outlets, area-level deprivation, diet quality and BMI. Research should respond to and build on the hypothesised pathways and our simple framework presented within our study.

Methods of measuring associations between the Retail Food Environment and weight status: Importance of classifications and metrics.

Despite considerable research, evidence supporting associations between the 'Retail Food Environment' (RFE) and obesity remains mixed. Differences in the methods used to measure the RFE may explain this heterogeneity. Using data on a large (n = 10,111) sample of adults from the Yorkshire Health Study (UK), we modelled cross-sectional associations between the RFE and weight status using (i) multiple definitions of 'Fast Food', 'Convenience' and 'Supermarkets' and (ii) multiple RFE metrics, identified in a prior systematic review to be common in the literature. Both the choice of outlet definition and the choice of RFE metric substantively impacted observed associations with weight status. Findings differed in relation to statistical significance, effect sizes, and directions of association. This study provides novel evidence that the diversity of RFE measurement methods is contributing to heterogeneous study findings and conflicting policy messages. Greater attention is needed when selecting and communicating RFE measures in research.

A systematic review employing the GeoFERN framework to examine methods, reporting quality and associations between the retail food environment and obesity.

This systematic review quantifies methods used to measure the 'retail food environment' (RFE), appraises the quality of methodological reporting, and examines associations with obesity, accounting for differences in methods. Only spatial measures of the RFE, such as food outlet proximity were included. Across the 113 included studies, methods for measuring the RFE were extremely diverse, yet reporting of methods was poor (average reporting quality score: 58.6%). Null associations dominated across all measurement methods, comprising 76.0% of 1937 associations in total. Outcomes varied across measurement methods (e.g. narrow definitions of 'supermarket': 20.7% negative associations vs 1.7% positive; broad definitions of 'supermarket': 9.0% negative associations vs 10.4% positive). Researchers should report methods more clearly, and should articulate findings in the context of the measurement methods employed.

A Delphi study to build consensus on the definition and use of big data in obesity research.

BACKGROUND: 'Big data' has great potential to help address the global health challenge of obesity. However, lack of clarity with regard to the definition of big data and frameworks for effectively using big data in the context of obesity research may be hindering progress. The aim of this study was to establish agreed approaches for the use of big data in obesity-related research. METHODS: A Delphi method of consensus development was used, comprising three survey rounds. In Round 1, participants were asked to rate agreement/disagreement with 77 statements across seven domains relating to definitions of, and approaches to, using big data in the context of obesity research. Participants were also asked to contribute further ideas in relation to these topics, which were incorporated as new statements (n = 8) in Round 2. In Rounds 2 and 3 participants re-appraised their ratings in view of the group consensus. RESULTS: Ninety-six experts active in obesity-related research were invited to participate. Of these, 36/96 completed Round 1 (37.5% response rate), 29/36 completed Round 2 (80.6% response rate) and 26/29 completed Round 3 (89.7% response rate). Consensus (defined as > 70% agreement) was achieved for 90.6% (n = 77) of statements, with 100% consensus achieved for the Definition of Big Data, Data Governance, and Quality and Inference domains. CONCLUSIONS: Experts agreed that big data was more nuanced than the oft-cited definition of 'volume, variety and velocity', and includes quantitative, qualitative, observational or intervention data from a range of sources that have been collected for research or other purposes. Experts repeatedly called for third party action, for example to develop frameworks for reporting and ethics, to clarify data governance requirements, to support training and skill development and to facilitate sharing of big data. Further advocacy will be required to encourage organisations to adopt these roles.

Can big data solve a big problem? Reporting the obesity data landscape in line with the Foresight obesity system map.

BACKGROUND: Obesity research at a population level is multifaceted and complex. This has been characterised in the UK by the Foresight obesity systems map, identifying over 100 variables, across seven domain areas which are thought to influence energy balance, and subsequent obesity. Availability of data to consider the whole obesity system is traditionally lacking. However, in an era of big data, new possibilities are emerging. Understanding what data are available can be the first challenge, followed by an inconsistency in data reporting to enable adequate use in the obesity context. In this study we map data sources against the Foresight obesity system map domains and nodes and develop a framework to report big data for obesity research. Opportunities and challenges associated with this new data approach to whole systems obesity research are discussed. METHODS: Expert opinion from the ESRC Strategic Network for Obesity was harnessed in order to develop a data source reporting framework for obesity research. The framework was then tested on a range of data sources. In order to assess availability of data sources relevant to obesity research, a data mapping exercise against the Foresight obesity systems map domains and nodes was carried out. RESULTS: A reporting framework was developed to recommend the reporting of key information in line with these headings: Background; Elements; Exemplars; Content; Ownership; Aggregation; Sharing; Temporality (BEE-COAST). The new BEE-COAST framework was successfully applied to eight exemplar data sources from the UK. 80% coverage of the Foresight obesity systems map is possible using a wide range of big data sources. The remaining 20% were primarily biological measurements often captured by more traditional laboratory based research. CONCLUSIONS: Big data offer great potential across many domains of obesity research and need to be leveraged in conjunction with traditional data for societal benefit and health promotion.

Is adolescent body mass index and waist circumference associated with the food environments surrounding schools and homes? A longitudinal analysis.

BACKGROUND: There has been considerable interest in the role of access to unhealthy food options as a determinant of weight status. There is conflict across the literature as to the existence of such an association, partly due to the dominance of cross-sectional study designs and inconsistent definitions of the food environment. The aim of our study is to use longitudinal data to examine if features of the food environment are associated to measures of adolescent weight status. METHODS: Data were collected from secondary schools in Leeds (UK) and included measurements at school years 7 (ages 11/12), 9 (13/14), and 11 (15/16). Outcome variables, for weight status, were standardised body mass index and standardised waist circumference. Explanatory variables included the number of fast food outlets, supermarkets and 'other retail outlets' located within a 1 km radius of an individual's home or school, and estimated travel route between these locations (with a 500 m buffer). Multi-level models were fit to analyse the association (adjusted for confounders) between the explanatory and outcome variables. We also examined changes in our outcome variables between each time period. RESULTS: We found few associations between the food environment and measures of adolescent weight status. Where significant associations were detected, they mainly demonstrated a positive association between the number of amenities and weight status (although effect sizes were small). Examining changes in weight status between time periods produced mainly non-significant or inconsistent associations. CONCLUSIONS: Our study found little consistent evidence of an association between features of the food environment and adolescent weight status. It suggests that policy efforts focusing on the food environment may have a limited effect at tackling the high prevalence of obesity if not supported by additional strategies.

Efficacy of anthropometric measures for identifying cardiovascular disease risk in adolescents: review and meta-analysis.

INTRODUCTION: To compare the ability of Body Mass Index (BMI), waist circumference (WC) and waist to height ratio (WHtR) to estimate cardiovascular disease (CVD) risk levels in adolescents. EVIDENCE ACQUISITION: A systematic review and meta-analysis was performed after a database search for relevant literature (Cochrane, Centre for Review and Dissemination, PubMed, British Nursing Index, CINAHL, BIOSIS citation index, ChildData, metaRegister). EVIDENCE SYNTHESIS: The study included 117 records representing 96 studies with 994,595 participants were included in the systematic review, 14 of which (13 studies, N.=14,610) were eligible for the meta-analysis. The results of the meta-analysis showed that BMI was a strong indicator of systolic blood pressure, diastolic blood pressure, triglycerides, high-density lipoprotein cholesterol and insulin; but not total cholesterol, low-density lipoprotein or glucose. Few studies were eligible for inclusion in the meta-analysis considering WC or WHtR (N.≤2). The narrative synthesis found measures of central adiposity to be consistently valid indicators of the same risk factors as BMI. CONCLUSIONS: BMI was an indicator of CVD risk. WC and WHtR were efficacious for indicating the same risk factors BMI performed strongly for, though there was insufficient evidence to judge the relative strength of each measure possibly due to heterogeneity in the methods for measuring and classifying WC.

Cold therapy to prevent paclitaxel-induced peripheral neuropathy.

PURPOSE: This case-control study was designed to assess the efficacy of cryotherapy to prevent paclitaxel-induced painful peripheral neuropathy in women with breast cancer. METHODS: Participants served as their own paired control, with randomization of the cooled glove/sock to either the dominant or the non-dominant hand/foot, worn for 15 min prior to, during, and 15 min after completion of the paclitaxel infusion. Outcome measures included the Neuropathic Pain Symptom Inventory, the Brief Pain Inventory, and quantitative sensory testing. Data were measured at each of six time points-baseline, post-treatment (approximately 2 weeks after the last paclitaxel infusion), and at the first, fifth, ninth, and final weekly paclitaxel treatments. RESULTS: Of 29 randomized participants, 20 (69%) received at least one cryotherapy treatment, and 11 (38%) received all four cryotherapy treatments. Ten (34%) participants could not tolerate the cryotherapy, and six (21%) declined further participation at some point during the trial. Only seven participants (24%) were available for the final post-chemotherapy QST and questionnaires. There were no significant differences in measures of neuropathy or pain between treated and untreated hands or feet. CONCLUSIONS: Strategies to prevent painful peripheral neuropathy are urgently needed. In this current trial, dropout due to discomfort precluded adequate power to fully understand the potential benefits of cryotherapy. Much more research is needed to discover safe and effective preventive strategies that can be easily implemented within busy infusion centers.