The impact of delaying colonoscopies during the COVID-19 pandemic on colorectal cancer detection and prevention.

PURPOSE: The COVID-19 pandemic resulted in a partial to total shutdown of endoscopy in many healthcare centers. This study aims to quantify the impact of the reduction in colonoscopies on colorectal cancer (CRC) detection and screening. METHODS: After institutional ethics board approval, the endoscopy database at an academic tertiary-care center in Montreal, Canada, was searched for all colonoscopies performed from during the first wave locally (March-June 2020), and during the ramp up period where endoscopy service resumed (July to August 2020). We compared these periods to the same periods in 2019, the pre-pandemic periods. The indications, CRC and adenoma detection rates, as well as the prioritization of urgent procedures were compared. RESULTS: In the first wave, only 462 colonoscopies were performed, compared to 2515 in the same period in 2019, an 82% reduction. The ramp up period saw 843 colonoscopies performed compared to 1328 in 2019, a 35% reduction. Urgent and inpatient colonoscopies numbers increased (324 (24.8%) vs. 220 (5.7%)) while surveillance and high-risk screening colonoscopies fell (376 (28.8%) vs 1869 (48.6%)). Emergency access to colonoscopy was preserved with a median time to endoscopy of < 1 day (IQR 0,1) in both pandemic periods. During the pandemic periods, there was an absolute reduction in CRC diagnosis of 28, despite the CRC detection per colonoscopy rate increasing slightly in the first wave from 1.7% (44) to 3.9% (18), and in the ramp up period from 2.5% (33) to 3.6% (31). The rate of adenoma detection per colonoscopy did not increase significantly between the pre- and pandemic periods, resulting in reduction in adenoma removal in 723 patients. DISCUSSION: The restriction of access to colonoscopy resulted in a significant reduction in screening and surveillance of high-risk patients, adenomas removed, and CRCs diagnosed. Clinicians and patients will face the oncologic ramifications this the coming years.

A rapid review for developing a co-design framework for a pediatric surgical communication application.

BACKGROUND: The exponential growth in the use of mobile health (mHealth) applications in patient care has highlighted the importance of understanding end-users' needs for successful interventions, achievable through the process of co-design. This review aims to summarize previously published uses of co-design in mHealth applications. It will inform the development of a local mHealth tool in pediatric surgery. METHODS: The rapid review was conducted following Cochrane Rapid Review guidelines. We searched four databases from inception until August 2021 for collaborative design in mHealth apps. Two reviewers independently screened titles and abstracts using Rayyan, with a third reviewer resolving any conflicts. Studies were excluded if they were non-empirical or in other languages than English. RESULTS: Out of 984 records screened, 175 were included for full-text screening, and 27 met all eligibility criteria. The purpose of the studies related to care support, communication, self-management or information management. All interventions involved their target audience in the co-design process, and 85% included healthcare professionals for expert opinion. Stakeholder participation was solicited via interviews, surveys, focus groups, design sessions, and prototype evaluation. To initiate the process, 15 studies included needs identification, 8 did background research, and 7 performed literature reviews. CONCLUSION: Co-design has a positive impact on mHealth development, research processes and outcomes. Its success relies on a clearly identified framework of terminology, activities involved, and evaluation techniques. The findings of this review will be integrated into a novel co-design framework, which will be used to inform the development of a pediatric surgery mHealth application. LEVEL OF EVIDENCE: This review uses manuscripts that are rated level III-V.

Low Anterior Resection Syndrome in a Reference North American Sample: Prevalence and Associated Factors.

BACKGROUND: Low anterior resection syndrome (LARS) is a well-described consequence of rectal cancer treatment. Studying the degree to which bowel dysfunction exists in the general population may help to better interpret to what extent LARS is related to disease and/or cancer treatment. Currently, North American LARS normative data are lacking. The aim of this study was to describe the prevalence of bowel dysfunction, as measured by the LARS score, and quality of life (QoL) in a reference North American sample. Quality of life was measured and associations between participant characteristics and LARS were identified. STUDY DESIGN: This was a single-institution cross-sectional study of asymptomatic adults who underwent screening and surveillance colonoscopies from 2018 to 2021 with no/benign endoscopic findings. Survey was conducted on select comorbidities, sociodemographic factors, LARS, and QoL. Outcomes were LARS and QoL. Multivariable linear regression accounting for a priori clinical factors associated with bowel dysfunction was performed. RESULTS: Of 1,004 subjects approached, 502 (50.0%) participated, and 135 (26.9%) participants had major/minor LARS. On multiple linear regression, female sex (ß = 2.15, 95% CI 0.30 to 4.00), younger age (ß = -0.10, 95% CI -0.18 to -0.03), White ethnicity (ß = 2.45, 95% CI 0.15 to 4.74), and the presence of at least one of the following factors: diabetes, depression, neurologic disorder, or cholecystectomy (ß = 3.54, 95% CI 1.57 to 5.51) were independently associated with a higher LARS score. Individuals with LARS had lower global QoL, functional subscales, and various symptom subscale scores. CONCLUSIONS: Our study identified the baseline prevalence of LARS in asymptomatic adults who have not undergone a low anterior resection. These normative data will allow for more accurate interpretation of ongoing studies on LARS in North American rectal cancer patients.

Application of Artificial Intelligence in Shared Decision Making: Scoping Review.

BACKGROUND: Artificial intelligence (AI) has shown promising results in various fields of medicine. It has the potential to facilitate shared decision making (SDM). However, there is no comprehensive mapping of how AI may be used for SDM. OBJECTIVE: We aimed to identify and evaluate published studies that have tested or implemented AI to facilitate SDM. METHODS: We performed a scoping review informed by the methodological framework proposed by Levac et al, modifications to the original Arksey and O'Malley framework of a scoping review, and the Joanna Briggs Institute scoping review framework. We reported our results based on the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) reporting guideline. At the identification stage, an information specialist performed a comprehensive search of 6 electronic databases from their inception to May 2021. The inclusion criteria were: all populations; all AI interventions that were used to facilitate SDM, and if the AI intervention was not used for the decision-making point in SDM, it was excluded; any outcome related to patients, health care providers, or health care systems; studies in any health care setting, only studies published in the English language, and all study types. Overall, 2 reviewers independently performed the study selection process and extracted data. Any disagreements were resolved by a third reviewer. A descriptive analysis was performed. RESULTS: The search process yielded 1445 records. After removing duplicates, 894 documents were screened, and 6 peer-reviewed publications met our inclusion criteria. Overall, 2 of them were conducted in North America, 2 in Europe, 1 in Australia, and 1 in Asia. Most articles were published after 2017. Overall, 3 articles focused on primary care, and 3 articles focused on secondary care. All studies used machine learning methods. Moreover, 3 articles included health care providers in the validation stage of the AI intervention, and 1 article included both health care providers and patients in clinical validation, but none of the articles included health care providers or patients in the design and development of the AI intervention. All used AI to support SDM by providing clinical recommendations or predictions. CONCLUSIONS: Evidence of the use of AI in SDM is in its infancy. We found AI supporting SDM in similar ways across the included articles. We observed a lack of emphasis on patients' values and preferences, as well as poor reporting of AI interventions, resulting in a lack of clarity about different aspects. Little effort was made to address the topics of explainability of AI interventions and to include end-users in the design and development of the interventions. Further efforts are required to strengthen and standardize the use of AI in different steps of SDM and to evaluate its impact on various decisions, populations, and settings.

Exploring the roles of artificial intelligence in surgical education: A scoping review.

BACKGROUND: Technology-enhanced teaching and learning, including Artificial Intelligence (AI) applications, has started to evolve in surgical education. Hence, the purpose of this scoping review is to explore the current and future roles of AI in surgical education. METHODS: Nine bibliographic databases were searched from January 2010 to January 2021. Full-text articles were included if they focused on AI in surgical education. RESULTS: Out of 14,008 unique sources of evidence, 93 were included. Out of 93, 84 were conducted in the simulation setting, and 89 targeted technical skills. Fifty-six studies focused on skills assessment/classification, and 36 used multiple AI techniques. Also, increasing sample size, having balanced data, and using AI to provide feedback were major future directions mentioned by authors. CONCLUSIONS: AI can help optimize the education of trainees and our results can help educators and researchers identify areas that need further investigation.