Faculty Bibliography

Physical frailty and impaired cognition are common in patients with cirrhosis. Physical frailty can be assessed using performance-based tests, but the extent to which impaired cognition may impact performance is not well characterized. We assessed the relationship between impaired cognition and physical frailty in patients with cirrhosis. We enrolled 1,623 ambulatory adult patients with cirrhosis waiting for liver transplantation at 10 sites. Frailty was assessed with the liver frailty index (LFI; "frail," LFI ≥ 4.4). Cognition was assessed at the same visit with the number connection test (NCT); continuous "impaired cognition" was examined in primary analysis, with longer NCT (more seconds) indicating worse impaired cognition. For descriptive statistics, "impaired cognition" was NCT ≥ 45 seconds. Linear regression associated frailty and impaired cognition; competing risk regression estimated subhazard ratios (sHRs) of wait-list mortality (i.e., death/delisting for sickness). Median NCT was 41 seconds, and 42% had impaired cognition. Median LFI (4.2 vs. 3.8) and rates of frailty (38% vs. 20%) differed between those with and without impaired cognition. In adjusted analysis, every 10-second NCT increase associated with a 0.08-LFI increase (95% confidence interval [CI], 0.07-0.10). In univariable analysis, both frailty (sHR, 1.63; 95% CI, 1.43-1.87) and impaired cognition (sHR, 1.07; 95% CI, 1.04-1.10) associated with wait-list mortality. After adjustment, frailty but not impaired cognition remained significantly associated with wait-list mortality (sHR, 1.55; 95% CI, 1.33-1.79). Impaired cognition mediated 7.4% (95% CI, 2.0%-16.4%) of the total effect of frailty on 1-year wait-list mortality. Conclusion: Patients with cirrhosis with higher impaired cognition displayed higher rates of physical frailty, yet frailty independently associated with wait-list mortality while impaired cognition did not. Our data provide evidence for using the LFI to understand mortality risk in patients with cirrhosis, even when concurrent impaired cognition varies.

BACKGROUND:The association between exposure to air pollution and papillary thyroid carcinoma is unknown. We sought to estimate the relationship between long-term exposure to the fine (diameter ≤ 2.5 μm) particulate matter component of air pollution and the risk of papillary thyroid cancer. METHODS:Adult (age ≥18) patients with newly diagnosed papillary thyroid carcinoma between January 1, 2013 and December 31, 2016 across a single health system were identified using electronic medical records. Data from 1,990 patients with papillary thyroid carcinoma were compared with 3,980 age- and sex-matched control subjects without any evidence of thyroid disease. Cumulative fine (diameter <2.5 μm) particulate matter exposure was estimated by incorporating patients' residential zip codes into a deep learning neural networks model, which uses both meteorological and satellite-based measurements. Conditional logistic regression was performed to assess for association between papillary thyroid carcinoma and increasing fine (diameter ≤2.5 μm) particulate matter concentrations over 1, 2, and 3 years of cumulative exposure preceding papillary thyroid carcinoma diagnosis. RESULTS:n = 0.04). Among current smokers (n = 623), the risk of developing papillary thyroid carcinoma was highest (adjusted odds ratio = 1.35, 95% confidence interval: 1.12-1.63). CONCLUSION/CONCLUSIONS:Increasing concentration of fine (diameter ≤2.5 μm) particulate matter in air pollution is significantly associated with the incidence of papillary thyroid carcinoma with 2 and 3 years of exposure. Our novel findings provide additional insight into the potential associations between risk factors and papillary thyroid carcinoma and warrant further investigation, specifically in areas with high levels of air pollution both nationally and internationally.

Status 1A liver transplant candidates are given the highest medical priority for the allocation of deceased donor livers. Organ Procurement and Transplantation Network (OPTN) policy requires physicians to certify that a candidate has a life expectancy without a transplant of less than 7 days for that candidate to be given status 1A. Additionally, candidates receiving status 1A must have one of six medical conditions listed in policy. Using Scientific Registry of Transplant Recipients data from all prevalent liver transplant candidates from 2010 to 2020, we used a bias-corrected Kaplan-Meier model to calculate the survival of status 1A candidates and to determine their life expectancy without a transplant. We found that status 1A candidates have a life expectancy without a transplant of 24 (95% CI 20-46) days-over three times longer than what policy requires for status 1A designation. We repeated the analysis for subgroups of status 1A candidates based on the medical conditions that grant status 1A. We found that none of these subgroups met the life expectancy requirement. Harmonizing OPTN policy with observed data would sustain the integrity of the allocation process.