BACKGROUNDFrailty is a marker of dependency, disability, hospitalization, and mortality in community‐dwelling older adults. However, existing tools for measuring frailty are too cumbersome for rapid point‐of‐care assessment. The Risk Analysis Index (RAI) of frailty is validated in surgical populations, but its performance outside surgical populations is unknown.OBJECTIVEValidate the RAI in ambulatory patients.DESIGN, SETTING, AND PARTICIPANTSObservational cohort study of outpatient surgical clinics within the University of Pittsburgh Medical Center Healthcare System between July 1, 2016, and December 31, 2016. Frailty was assessed using the RAI. Current Procedural Terminology codes following RAI assessment identified patients with and without minor office‐based procedures (eg, joint injection, laryngoscopy).MAIN OUTCOMES AND MEASURESAll‐cause 1‐year mortality, assessed by stratified Cox proportional hazard models.RESULTSOf 28,059 patients, 13,861 were matched to a minor, office‐based procedure and 14,198 did not undergo any procedure. The mean (SD) age was 56.7 (17.2) years; women constituted 15,797 (56.3%) of the cohort. Median time (interquartile range 25th‐75th percentile) to measure RAI was 30 (22–47) seconds. Mortality among the frail was two to five times that of patients with normal RAI scores. For example, the hazard ratio for frail ambulatory patients without a minor procedure was 3.69 (95% confidence interval [CI] = 2.51‐5.41), corresponding to 30‐, 180‐, and 365‐day mortality rates of 2.9%, 11.2%, and 17.4%, respectively, compared to 0.3%, 2.3%, and 4.0% among patients with normal RAI scores. Discrimination of mortality (overall, and censored at 30, 180, and 365 days) was excellent, ranging from c = 0.838 (95% CI = 0.773‐0.902) for 30‐day mortality after minor procedures to c = 0.909 (95% CI = 0.855‐0.964) without a procedure.CONCLUSIONRAI is a valid, easily administered tool for point‐of‐care frailty assessment in ambulatory populations that may help clinicians and patients make better informed decisions about care choices—especially among patients considered high risk with a potentially limited life span. J Am Geriatr Soc 68:1818‐1824, 2020.

Objective With the intensification and utilization of multimodal treatment, acute toxicities have increased; however, the frequency of treatment sequelae in long‐term head and neck cancer (HNC) survivors are poorly described. The purpose of this analysis was to determine the prevalence and predictors of patient‐reported late and long‐term treatment‐related sequelae in HNC survivors. Methods We performed a cross‐sectional analysis of patient‐reported outcomes from 228 survivors attending a multidisciplinary HNC survivorship clinic. The primary outcomes comprised quality of life (QOL), symptoms of anxiety and depression, and swallowing dysfunction. Results Male gender, tumor sites in the oropharynx and larynx, longer time since treatment, and treatment with surgery alone were associated with higher physical QOL (P < .05). Male gender, longer time since treatment, and treatment with surgery alone were associated with higher social‐emotional QOL (P < .05). A reduction in anxiety symptoms and a higher QOL were related to longer time since treatment; however, a reduction in swallowing dysfunction symptoms was only related to longer time since treatment until approximately 6 years. After 6 years, survivors reported worse swallowing dysfunction (P < .05). One hundred thirty‐two survivors (56%) reported at least three treatment‐related effects that impacted their daily life. Finally, advanced stage disease at diagnosis (stage III–IV) was also associated with severe swallowing dysfunction (P = .004). Conclusion These data indicate the remarkable prevalence of treatment‐related effects in HNC survivors. These results highlight the need for de‐intensification of therapies, where appropriate, and for a better understanding of pathophysiology and new approaches to mitigating treatment effects. Level of Evidence 4 Laryngoscope, 129:E437–E444, 2019

IMPORTANCE Learning curves are unavoidable for practicing surgeons when adopting new technologies. However, patient outcomes are worse in the early stages of a learning curve vs after mastery. Therefore, it is critical to find a way to decrease these learning curves without compromising patient safety.OBJECTIVE To evaluate the association of mentorship and a formal proficiency-based skills curriculum with the learning curves of 3 generations of surgeons and to determine the association with increased patient safety. DESIGN, SETTING, AND PARTICIPANTS All consecutive robotic pancreaticoduodenectomies (RPDs) performed at the University of Pittsburgh Medical Center between 2008 and 2017 were included in this study. Surgeons were split into generations based on their access to mentorship and a proficiency-based skills curriculum. The generations are (1) no mentorship or curriculum, (2) mentorship but no curriculum, and (3) mentorship and curriculum. Univariable and multivariable analyses were used to create risk-adjusted learning curves by surgical generation and to analyze factors associated with operating room time, complications, and fellows completing the full resection. The participants include surgical oncology attending surgeons and fellows who participated in an RPD at University of Pittsburgh Medical Center between 2008 and 2017. MAIN OUTCOMES AND MEASURESThe primary outcome was operating room time (ORT). Secondary outcomes were postoperative pancreatic fistula and Clavien-Dindo classification higher than grade 2. RESULTSWe identified 514 RPDs completed between 2008 and 2017, of which 258 (50.2%) were completed by first-generation surgeons, 151 (29.3%) were completed by the second generation, and 82 (15.9%) were completed by the third generation. There was no statistically significant difference between groups with respect to age (66.3-67.3 years; P = .52) or female sex (n = 34 [41.5%] vs n = 121 [46.9%]; P = .60). There was a significant decrease in ORT (P < .001), from 450.8 minutes for the first-generation surgeons to 348.6 minutes for the third generation. Additionally, across generations, Clavien-Dindo classification higher than grade 2 (n = 74 [28.7%] vs n = 30 [9.9%] vs n = 12 [14.6%]; P = .01), conversion rates (n = 18 [7.0%] vs n = 7 [4.6%] vs n = 0; P = .006), and estimated blood loss (426 mL vs 288.6 mL vs 254.7 mL; P < .001) decreased significantly with subsequent generations. There were no significant differences in postoperative pancreatic fistula. CONCLUSIONS AND RELEVANCEIn this study, ORT, conversion rates, and estimated blood loss decreased across generations without a concomitant rise in adverse patient outcomes. These findings suggest that a proficiency-based curriculum coupled with mentorship allows for the safe introduction of less experienced surgeons to RPD without compromising patient safety.

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Background Processes for transferring patients to higher acuity facilities lack a standardized approach to prognostication, increasing the risk for low value care that imposes significant burdens on patients and their families with unclear benefits. We sought to develop a rapid and feasible tool for predicting mortality using variables readily available at the time of hospital transfer. Methods and findings All work was carried out at a single, large, multi-hospital integrated healthcare system. We used a retrospective cohort for model development consisting of patients aged 18 years or older transferred into the healthcare system from another hospital, hospice, skilled nursing or other healthcare facility with an admission priority of direct emergency admit. The cohort was randomly divided into training and test sets to develop first a 54-variable, and then a 14-variable gradient boosting model to predict the primary outcome of all cause in-hospital mortality. Secondary outcomes included 30-day and 90-day mortality and transition to comfort measures only or hospice care. For model validation, we used a prospective cohort consisting of all patients transferred to a single, tertiary care hospital from one of the 3 referring hospitals, excluding patients transferred for myocardial infarction or maternal labor and delivery. Prospective validation was performed by using a web-based tool to calculate the risk of mortality at the time of transfer. Observed outcomes were compared to predicted outcomes to assess model performance. The development cohort included 20,985 patients with 1,937 (9.2%) in-hospital mortalities, 2,884 (13.7%) 30-day mortalities, and 3,899 (18.6%) 90-day mortalities. The 14-variable gradient boosting model effectively predicted in-hospital, 30-day and 90-day mortality (c = 0.903 [95% CI:0.891–0.916]), c = 0.877 [95% CI:0.864–0.890]), and c = 0.869 [95% CI:0.857–0.881], respectively). The tool was proven feasible and valid for bedside implementation in a prospective cohort of 679 sequentially transferred patients for whom the bedside nurse calculated a SafeNET score at the time of transfer, taking only 4–5 minutes per patient with discrimination consistent with the development sample for in-hospital, 30-day and 90-day mortality (c = 0.836 [95%CI: 0.751–0.921], 0.815 [95% CI: 0.730–0.900], and 0.794 [95% CI: 0.725–0.864], respectively). Conclusions The SafeNET algorithm is feasible and valid for real-time, bedside mortality risk prediction at the time of hospital transfer. Work is ongoing to build pathways triggered by this score that direct needed resources to the patients at greatest risk of poor outcomes.