The IDEAL Reporting Guidelines: A Delphi Consensus Statement Stage Specific Recommendations for Reporting the Evaluation of Surgical Innovation.

OBJECTIVE: The aim of this study was to define reporting standards for IDEAL format studies. BACKGROUND: The IDEAL Framework and Recommendations establish an integrated pathway for evaluation of new surgical techniques and complex therapeutic technologies. However guidance on implementation has been incomplete, and incorrect use is commonly seen. We describe the consensus development of reporting guidelines for the IDEAL stages, and plans for their dissemination and evaluation. METHODS: Using the EQUATOR Network recommendations, participants with knowledge of IDEAL were surveyed to determine which IDEAL stages needed reporting guidelines. Draft checklists for stages 1, 2a, 2b, and 4 were subsequently developed by 3 researchers (N.B., A.H., P.M.), and revised through a 2-round Delphi consensus process. A final consensus teleconference resolved outstanding disagreements and clarified wording for checklist items. RESULTS: Sixty-one participants completed the initial survey, a clear majority indicating that new reporting guidelines were needed for IDEAL Stage 1 (69.5%), Stage 2a (78%), Stage 2b (74.6%), and Stage 4 (66%). A proposed set of checklists was modified by survey participants in 2 online Delphi rounds (n = 54 and n = 47, respectively), resulting in a penultimate checklist for each stage. Fourteen expert working group members finalized the checklist items and successfully resolved any outstanding areas without agreement on a consensus call. CONCLUSIONS: Participants familiar with IDEAL called for reporting guidelines for studies in all IDEAL stages except stage 3. The checklists developed have the potential to improve standards of reporting and thereby advance the quality of research on surgery and complex interventions and technologies, but require further evaluation in use.

A pilot study of a breast surgery Enhanced Recovery After Surgery (ERAS) protocol to eliminate narcotic prescription at discharge.

BACKGROUND: The evolving conceptualization of the management of surgical pain was a major contributor to the supply of narcotics that led to the opioid crisis. We designed and implemented a breast surgery-specific Enhanced Recovery After Surgery (ERAS) protocol using opioid-sparing techniques to eliminate narcotic prescription at discharge without sacrificing perioperative pain control. METHODS: A pilot observational study included patients with and without cancer undergoing lumpectomy. The convenience sample consisted of an ERAS group and a control usual care (UC) group who underwent surgery during the same time period. Discharge narcotic prescriptions were compared after converting to oral morphine milligram equivalents (MME's). Postoperative day one and week one pain scores were also compared between the two groups. RESULTS: Ninety ERAS and 67 UC patients were enrolled. Most lumpectomies were wire-localized, and half of the patients in each group had breast cancer. There were more obese patients in the ERAS group. UC lumpectomy patients were discharged with a median of 54.5 MMEs (range 0-120), while the ERAS lumpectomy patients were discharged with none (p < 0.001). Postoperative pain scores were not significantly different between groups, and there were few complications. CONCLUSION: A breast surgery-specific ERAS protocol employing opioid-sparing techniques successfully eliminated postoperative narcotic prescription without sacrificing perioperative pain control or increasing postoperative complications. By promoting the adoption of similar protocols, surgeons can continue to improve patient outcomes while decreasing the quantity of narcotics available for diversion within our patients' communities.

Association of Clinician Diagnostic Performance With Machine Learning-Based Decision Support Systems: A Systematic Review.

Importance: An increasing number of machine learning (ML)-based clinical decision support systems (CDSSs) are described in the medical literature, but this research focuses almost entirely on comparing CDSS directly with clinicians (human vs computer). Little is known about the outcomes of these systems when used as adjuncts to human decision-making (human vs human with computer). Objectives: To conduct a systematic review to investigate the association between the interactive use of ML-based diagnostic CDSSs and clinician performance and to examine the extent of the CDSSs' human factors evaluation. Evidence Review: A search of MEDLINE, Embase, PsycINFO, and grey literature was conducted for the period between January 1, 2010, and May 31, 2019. Peer-reviewed studies published in English comparing human clinician performance with and without interactive use of an ML-based diagnostic CDSSs were included. All metrics used to assess human performance were considered as outcomes. The risk of bias was assessed using Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) and Risk of Bias in Non-Randomised Studies-Intervention (ROBINS-I). Narrative summaries were produced for the main outcomes. Given the heterogeneity of medical conditions, outcomes of interest, and evaluation metrics, no meta-analysis was performed. Findings: A total of 8112 studies were initially retrieved and 5154 abstracts were screened; of these, 37 studies met the inclusion criteria. The median number of participating clinicians was 4 (interquartile range, 3-8). Of the 107 results that reported statistical significance, 54 (50%) were increased by the use of CDSSs, 4 (4%) were decreased, and 49 (46%) showed no change or an unclear change. In the subgroup of studies carried out in representative clinical settings, no association between the use of ML-based diagnostic CDSSs and improved clinician performance could be observed. Interobserver agreement was the commonly reported outcome whose change was the most strongly associated with CDSS use. Four studies (11%) reported on user feedback, and, in all but 1 case, clinicians decided to override at least some of the algorithms' recommendations. Twenty-eight studies (76%) were rated as having a high risk of bias in at least 1 of the 4 QUADAS-2 core domains, and 6 studies (16%) were considered to be at serious or critical risk of bias using ROBINS-I. Conclusions and Relevance: This systematic review found only sparse evidence that the use of ML-based CDSSs is associated with improved clinician diagnostic performance. Most studies had a low number of participants, were at high or unclear risk of bias, and showed little or no consideration for human factors. Caution should be exercised when estimating the current potential of ML to improve human diagnostic performance, and more comprehensive evaluation should be conducted before deploying ML-based CDSSs in clinical settings. The results highlight the importance of considering supported human decisions as end points rather than merely the stand-alone CDSSs outputs.

Rapid Adoption of an Interdisciplinary Care Team Model for Surgical Residents Managing Coronavirus Disease-19.

Introduction: Patients infected with SARS-Cov-2, the causative virus behind the coronavirus disease-19 (COVID-19) pandemic, have been increasing rapidly in New York City. New York City has the highest incidence in the United States and fully 45% of all deaths from COVID-19. Our medical center is located within a high-density region of cases in south Brooklyn and, in fact, three of our neighborhood zip codes are in the top seven in New York in incidence. As a result, our center has experienced a dramatic increase in hospitalizations, particularly respiratory distress secondary to COVID-19, which rapidly exceeded the capacity of our internal medicine service. This necessitated the formation of new COVID-19 units throughout the hospital, replacing all former service lines. These units employed management teams composed of residents from many medical and surgical disciplines, including general surgery residents. Methods: Our general surgery residency program established a surgical COVID-19 (SCOVID) management team. Initially, 4 surgical residents (2 senior and 2 junior), 1 attending surgeon, and 1 attending internal medicine physician were allocated to the initial SCOVID team. On day 3 of implementation, to achieve more rapid competence in the complex management of these patients, a senior medicine resident with direct experience in the care of COVID-19 patients was added in an advisory capacity. Results: The addition of an experienced senior medical resident and attending allowed for the quick adoption of uniform management protocols by surgical residents and attendings. Discussion: We describe a protocol for the establishment of COVID-19 management teams staffed with general surgical residents, as well as a strategy for the achievement of rapid increases in competency. The addition of a senior internal medicine resident and attending to our SCOVID team allowed for rapid achievement of competency in the care of COVID-19 patients in our large institution at the epicenter of the COVID-19 pandemic.

A Review of Pregnancy-Associated Breast Cancer: Diagnosis, Local and Systemic Treatment, and Prognosis.

The incidence of pregnancy-associated breast cancer (PABC) increases as more women choose to delay childbearing and the population-based incidence of breast cancer rises. Reliably and safely staging PABC is necessary to choose between starting with local or systemic therapy. With regard to local therapy, both lumpectomy and mastectomy can be considered depending on gestational age and the stage at diagnosis. By mirroring nonpregnant treatment regimens as much as possible, chemotherapy may improve long-term oncologic outcomes while allowing for surgical downstaging during pregnancy. Delaying treatment due to misconceptions regarding risk of local and systemic therapy most certainly worsens oncologic outcomes, and most neonatal morbidity is related to gestational age at delivery and not in utero exposures. Pregnancy itself was once considered an independent risk factor for worse outcome, but the prognosis of these patients is not significantly different than nonpregnant counterparts of a similar age.

Patterns of Caribbean Masculinities and Condom Compliance Among Males in Grenada.

The construction of Caribbean male identities based on ideas of masculinity has raised widespread concerns across the island states, and in a region with such high rates of teenage pregnancy (18%), stigmatizing safe sex, contraception, and HIV/AIDS prevalence can only exacerbate the problem. The purpose of this study was to examine the extent to which males use condoms and to explore the association of condom use with their concern with acquiring and transmission of sexually transmitted infections.