Sex-based Disparities in Access to Liver Transplantation for Waitlisted Patients With Model for End-stage Liver Disease Score of 40.

OBJECTIVE: To determine the association of sex with access to liver transplantation among candidates with the highest possible model for end-stage liver disease score (MELD 40). BACKGROUND: Women with end-stage liver disease are less likely than men to receive liver transplantation due in part to MELD's underestimation of renal dysfunction in women. The extent of the sex-based disparity among patients with high disease severity and equally high MELD scores is unclear. METHODS: Using national transplant registry data, we compared liver offer acceptance (offers received at match MELD 40) and waitlist outcomes (transplant vs death/delisting) by sex for 7654 waitlisted liver transplant candidates from 2009 to 2019 who reached MELD 40. Multivariable logistic and competing-risks regression was used to estimate the association of sex with the outcome and adjust for the candidate and donor factors. RESULTS: Women (N = 3019, 39.4%) spent equal time active at MELD 40 (median: 5 vs 5 days, P = 0.28) but had lower offer acceptance (9.2% vs 11.0%, P < 0.01) compared with men (N = 4635, 60.6%). Adjusting for candidate/donor factors, offers to women were less likely accepted (odds ratio = 0.87, P < 0.01). Adjusting for candidate factors, once they reached MELD 40, women were less likely to be transplanted (subdistribution hazard ratio = 0.90, P < 0.01) and more likely to die or be delisted (subdistribution hazard ratio = 1.14, P = 0.02). CONCLUSIONS: Even among candidates with high disease severity and equally high MELD scores, women have reduced access to liver transplantation and worse outcomes compared with men. Policies addressing this disparity should consider factors beyond MELD score adjustments alone.

Associations Among Circle-Based Kidney Allocation, Center Waiting Time, and Likelihood of Deceased-Donor Kidney Transplantation.

RATIONALE & OBJECTIVE: The kidney allocation system (KAS250), using circle-based distribution, attempts to address geographic disparities through broader sharing of deceased-donor kidney allografts. This study sought to evaluate the association between KAS250 and likelihood of deceased-donor kidney transplantation (DDKT) among waitlisted candidates, and whether the policy has differentially affected centers with shorter vs. longer waiting time. STUDY DESIGN: Retrospective cohort study. SETTING: & Participants: 160,941 candidates waitlisted at 176 transplant centers between 3/2017-3/2024. EXPOSURE: KAS250 allocation policy. OUTCOME: Rate of DDKT. ANALYTICAL APPROACH: Multivariable Cox regression, modeling KAS250 as a time-dependent variable. RESULTS: KAS250 was not independently associated with likelihood of DDKT overall (HR=1.01 vs. pre-KAS250, 95% C.I. 0.97-1.04). KAS250's association with likelihood of DDKT varied across centers from HR=0.18 (DDKT less likely after KAS250) to HR=17.12 (DDKT more likely) and varied even among neighboring centers. KAS250 was associated with decreased DDKT at 25.6% and increased DDKT at 18.2% of centers. Centers with previously long median waiting times (57+ months) experienced increased likelihood of DDKT after KAS250 (HR=1.20, 95% C.I. 1.15-1.26), whereas centers with previously short median waiting times (6-24mo.; HR=0.88, 0.84-0.92) experienced decreased likelihood of DDKT. LIMITATIONS: Retrospective study of allocation policy changes, confounded by multiple changes over the study timeframe. CONCLUSION: Association between KAS250 and DDKT varied across centers. For one-in-four centers, DDKT was less likely after KAS250 relative to pre-KAS250 trends. Candidates at centers with previously long waiting times experienced increased likelihood of DDKT after KAS250. Thus, broader distribution of kidneys may be associated with improved equity in access to DDKT, but additional strategies may be needed to minimize disparities between centers.

Racial-ethnic differences in liver transplant waitlist outcomes in patients with hepatocellular carcinoma before and after recent changes to allocation policy.

BACKGROUND: In May 2019, liver transplant (LT) allocation policy changed to limit MELD exception points for hepatocellular carcinoma (HCC) to median MELD at transplant minus three (MMaT-3). We evaluated this policy's impact on waitlist outcomes for HCC candidates, by race and ethnicity, hypothesizing that the introduction of the MMaT-3 reduced inequities in waitlist outcomes. METHODS: Retrospective cohort study of the Scientific Registry for Transplant Recipients, including all adult LT candidates (N = 10 751) who received HCC exception points from May 17, 2017 to May 18, 2019 (pre-policy; N = 6627) to May 19, 2019 to March 1, 2021 (post-policy; N = 4124). We compared incidence of LT and waitlist removal for death or becoming too sick pre- and post-policy for non-Hispanic White, non-Hispanic Black, Hispanic/Latinx, and Asian patients using competing risk regression adjusted for candidate characteristics. RESULTS: One-year cumulative incidence of LT decreased significantly pre-/post-policy among White (77.4% vs. 64.5%; p < .01) and Black (76.2% vs. 63.1%; p < .01) candidates only, while a 1-year incidence of death/non-LT waitlist removal decreased significantly only among Hispanics (13.4% vs. 7.5%; p < .01). After covariate adjustment, the effect of the policy change was a significantly decreased incidence of LT for White (SHR: .63 compared to pre-policy; p < .001), Black (SHR: .62; p < .001), and Asian (SHR: .68; p = .002), but no change for Hispanic patients. Only Hispanic patients had a significant decrease in death/waitlist removal after the policy change (SHR:  .69; p = .04). Compared to White patients in the pre-policy era, Hispanic (SHR:  .88, p < .007) and Asian candidates (SHR:  .72; p < .001) had lower unadjusted incidence of LT. This disparity was mitigated in the post-policy era where Hispanic patients had higher likelihood of LT than Whites (SHR: 1.22; p = .002). For the outcome of death/non-LT waitlist removal, the only significant difference was a 42% lower incidence of waitlist removal for Asian compared to White patients in the post-policy era (SHR:  .58; p = .03). CONCLUSION: Among LT recipients with HCC, racial/ethnic subpopulations were differentially affected by the MMAT-3 policy, resulting in a post-policy reduction of some of the previous disparities.

Association between donor kidney cysts and donor and recipient outcomes after living donor kidney transplantation.

INTRODUCTION: Incidental kidneys cysts are typically considered benign, but the presence of cysts is more frequent in individuals with other early markers of kidney disease. We studied the association of donor kidney cysts with donor and recipient outcomes after living donor kidney transplantation. METHODS: We retrospective identified 860 living donor transplants at our center (1/1/2011-7/31/2022) without missing data. Donor cysts were identified by review of pre-donation CT scan reports. We used linear regression to study the association between donor cysts and 6-month single-kidney estimated glomerular filtration rate (eGFR) increase, and time-to-event analyses to study the association between donor cysts and recipient death-censored graft failure. RESULTS: Among donors, 77% donors had no kidney cysts, 13% had ≥1 cyst on the kidney not donated, and 11% only had cysts on the donated kidney. In adjusted linear regression, cysts on the donated kidney and kidney not donated were not significantly associated with 6-month single-kidney eGFR increase. Among transplants, 17% used a transplanted kidney with a cyst and 6% were from donors with cysts only on the kidney not transplanted. There was no association between donor cyst group and post-transplant death-censored graft survival. Results were similar in sensitivity analyses comparing transplants using kidneys with no cysts versus 1-2 cysts versus ≥3 cysts. CONCLUSIONS: Kidney cysts in living kidney donors were not associated with donor kidney recovery or recipient allograft longevity, suggesting incidental kidney cysts need not be taken into account when determining living donor candidate suitability or the laterality of planned donor nephrectomy.

Increased volume of organ offers and decreased efficiency of kidney placement under circle-based kidney allocation.

The newest kidney allocation policy kidney allocation system 250 (KAS250) broadened geographic distribution while increasing allocation system complexity. We studied the volume of kidney offers received by transplant centers and the efficiency of kidney placement since KAS250. We identified deceased-donor kidney offers (N = 907,848; N = 36,226 donors) to 185 US transplant centers from January 1, 2019, to December 31, 2021 (policy implemented March 15, 2021). Each unique donor offered to a center was considered a single offer. We compared the monthly volume of offers received by centers and the number of centers offered before the first acceptance using an interrupted time series approach (pre-/post-KAS250). Post-KAS250, transplant centers received more kidney offers (level change: 32.5 offers/center/mo, P < .001; slope change: 3.9 offers/center/mo, P = .003). The median monthly offer volume post-/pre-KAS250 was 195 (interquartile range 137-253) vs. 115 (76-151). There was no significant increase in deceased-donor transplant volume at the center level after KAS250, and center-specific changes in offer volume did not correlate with changes in transplant volume (r = -0.001). Post-KAS250, the number of centers to whom a kidney was offered before acceptance increased significantly (level change: 1.7 centers/donor, P < .001; slope change: 0.1 centers/donor/mo, P = .014). These findings demonstrate the logistical burden of broader organ sharing, and future allocation policy changes will need to balance equity in transplant access with the operational efficiency of the allocation system.

Influence of organ quality on the observed association between deceased donor kidney procurement biopsy findings and graft survival.

Deceased donor kidney procurement biopsies findings are the most common reason for kidney discard. Retrospective studies have found inconsistent associations with post-transplant outcomes but may have been limited by selection bias because kidneys with advanced nephrosclerosis from high-risk donors are typically discarded. We conducted a retrospective cohort study of kidneys transplanted in the United States from 2015 to 2019 with complete biopsy data available, defining "suboptimal histology" as glomerulosclerosis ≥11%, IFTA ≥mild, and/or vascular disease ≥mild. We used time-to-event analyses to determine the association between suboptimal histology and death-censored graft failure after stratification by kidney donor profile index (KDPI) (≤35%, 36%-84%, ≥85%) and final creatinine (<1 mg/dl, 1-2 mg/dl, >2 mg/dl). Among 30 469 kidneys included, 36% had suboptimal histology. In adjusted analyses, suboptimal histology was associated with death-censored graft failure among kidneys with KDPI 36-84% (HR 1.22, 95% CI 1.09-1.36), but not KDPI≤35% (HR 1.24, 0.94-1.64) or ≥ 85% (HR 0.99, 0.81-1.22). Similarly, suboptimal histology was associated with death-censored graft failure among kidneys from donors with creatinine 1-2 mg/dl (HR 1.39, 95% CI 1.20-1.60) but not <1 mg/dl (HR 1.07, 0.93-1.23) or >2 mg/dl (HR 0.95, 0.75-1.20). The association of procurement histology with graft longevity among intermediate-quality kidneys that were likely to be both biopsied and transplanted suggests biopsies provide independent organ quality assessments.

Association of transplant center market concentration and local organ availability with deceased donor kidney utilization.

Although there is a shortage of kidneys available for transplantation, many transplantable kidneys are not procured or are discarded after procurement. We investigated whether local market competition and/or organ availability impact kidney procurement/utilization. We calculated the Herfindahl-Hirschman Index (HHI) for deceased donor kidney transplants (2015-2019) for 58 US donation service areas (DSAs) and defined 4 groups: HHI ≤ 0.32 (high competition), HHI = 0.33-0.51 (medium), HHI = 0.53-0.99 (low), and HHI = 1 (monopoly). We calculated organ availability for each DSA as the number kidneys procured per incident waitlisted candidate, grouped as: <0.42, 0.42-0.69, >0.69. Characteristics of procured organs were similar across groups. In adjusted logistic regression, the HHI group was inconsistently associated with composite export/discard (reference: high competition; medium: OR 1.16, 95% CI 1.11-1.20; low 1.01, 0.96-1.06; monopoly 1.19, 1.13-1.26) and increasing organ availability was associated with export/discard (reference: availability <0.42; 0.42-0.69: OR 1.35, 95% CI 1.30-1.40; >0.69: OR 1.83, 95% CI 1.73-1.93). When analyzing each endpoint separately, lower competition was associated with higher export and only market monopoly was weakly associated with lower discard, whereas higher organ availability was associated with export and discard. These results indicate that local organ utilization is more strongly influenced by the relative intensity of the organ shortage than by market competition between centers.

The Association Between Preoperative Opioid Exposure and Prolonged Postoperative Use.

OBJECTIVE: To determine the effect of nonchronic, periodic preoperative opioid use on prolonged opioid fills after surgery. BACKGROUND: Nonchronic, periodic opioid use is common, but its effect on prolonged postoperative opioid fills is not well understood. We hypothesize greater periodic opioid use before surgery is correlated with persistent postoperative use. METHODS: We used a national private insurance claims database, Optum's de-identifed Clinformatics Data Mart Database, to identify adults undergoing general, gynecologic, and urologic surgical procedures between 2008 and 2015 (N = 191,043). We described patterns of opioid fills based on dose, recency, duration, and continuity to categorize preoperative opioid exposure. Patients with chronic use were excluded. Our primary outcome was persistent postoperative use, defined as filling an opioid prescription between 91- and 180-days post-discharge. The association between preoperative opioid use and persistent use was determined using multivariable logistic regression, controlling for clinical covariates. RESULTS: In the year before surgery, 41% of patients had nonchronic, periodic opioid fills. Compared with other risk factors, patterns of preoperative fills were most strongly correlated with persistent postoperative opioid use. Patients with recent intermittent use were significantly more likely to have prolonged fills after surgery compared with opioid-naïve patients [minimal use: odds ratio (OR): 2.0, 95% confidence interval (CI) 1.89-2.03; remote intermittent: OR 4.7, 95% CI 4.46-4.93; recent intermittent: OR 12.2, 95% CI 11.49-12.90]. CONCLUSIONS: Patients with nonchronic, periodic opioid use before surgery are vulnerable to persistent postoperative opioid use. Identifying opioid use before surgery is a critical opportunity to optimize care after surgery.

Association of balanced abdominal organ transplant center volumes with patient outcomes.

BACKGROUND: The volume-outcome relationship for organ-specific transplantation is well-described; it is unknown if the relative balance of kidney compared with liver volumes within an institution relates to organ-specific outcomes. We assessed the association between relative balance within a transplant center and outcomes. METHODS: National retrospective analysis of isolated kidney and liver transplants in United States 2005-2014 followed through 2019. Latent class analysis defined transplant center phenotypes. Multivariate Cox models estimated death-censored graft loss and mortality. RESULTS: Latent class analysis identified four phenotypes: kidney only (n = 117), kidney dominant (n = 36), mixed/balanced (n = 90), and liver dominant (n = 13). Compared to mixed centers, the risk of kidney graft loss was higher at kidney-dominant (HR 1.07, p < .001) and liver-dominant (HR 1.10, p < .001) centers, while kidney-only (HR 1.06, p = .01) centers had higher mortality. Liver graft loss was not associated with phenotype, but risk of patient death was lower (HR 0.93, p = .02) at liver dominant and higher (HR 1.06, p = .02) at kidney-dominant centers. CONCLUSIONS: A mixed phenotype was associated with improved kidney transplant outcomes, whereas liver transplant outcomes were best at liver-dominant centers. While these findings need to be verified with center-level resources, optimization of shared resources could improve patient and organ outcomes.

Classifying Preoperative Opioid Use for Surgical Care.

OBJECTIVE: We characterized patterns of preoperative opioid use in patients undergoing elective surgery to identify the relationship between preoperative use and subsequent opioid fill after surgery. BACKGROUND: Preoperative opioid use is common, and varies by dose, recency, duration, and continuity of fills. To date, there is little evidence to guide postoperative prescribing need based on prior opioid use. METHODS: We analyzed claims data from Clinformatics DataMart Database for patients aged 18 to 64 years undergoing major and minor surgery between 2008 and 2015. Preoperative use was defined as any opioid prescription filled in the year before surgery. We used cluster analysis to group patients by the dose, recency, duration, and continuity of use. Our primary outcome was second postoperative fill within 30 postoperative days. Our primary explanatory variable was opioid use group. We used logistic regression to examine likelihood of second fill by opioid use group. RESULTS: Out of 267,252 patients, 102,748 (38%) filled an opioid prescription in the 12 months before surgery. Cluster analysis yielded 6 groups of preoperative opioid use, ranging from minimal (27.6%) to intermittent (7.7%) to chronic use (2.7%). Preoperative opioid use was the most influential predictor of second fill, with larger effect sizes than other factors even for patients with minimal or intermittent opioid use. Increasing preoperative use was associated with risk-adjusted likelihood of requiring a second opioid fill compared with naive patients [minimal use: odds ratio (OR) 1.49, 95% confidence interval (95% CI) 1.45-1.53; recent intermittent use: OR 6.51, 95% CI 6.16-6.88; high chronic use: OR 60.79, 95% CI 27.81-132.92, all P values <0.001). CONCLUSION: Preoperative opioid use is common among patients who undergo elective surgery. Although the majority of patients infrequently fill opioids before surgery, even minimal use increases the probability of needing additional postoperative prescriptions in the 30 days after surgery when compared with opioid-naive patients. Going forward, identifying preoperative opioid use can inform surgeon prescribing and care coordination for pain management after surgery.

Provider Characteristics Associated With Outpatient Opioid Prescribing After Surgery.

OBJECTIVE: To characterize differences in postoperative opioid prescribing across surgical, nonsurgical, and advanced practice providers. BACKGROUND: There is a critical need to identify best practices around perioperative opioid prescribing. To date, differences in postoperative prescribing among providers are poorly understood. METHODS: This is a retrospective multicenter analysis of commercial insurance claims from a statewide quality collaborative. We identified 15,657 opioid-naïve patients who underwent a range of surgical procedures between January 2012 and October 2015 and filled an opioid prescription within 30 days postoperatively. Our primary outcome was total amount of opioid filled per prescription within 30 days postoperatively [in oral morphine equivalents (OME)]. Hierarchical linear regression was used to determine the association between provider characteristics [specialty, advanced practice providers (nurse practitioners and physician assistants) vs. physician, and gender] and outcome while adjusting for patient factors. RESULTS: Average postoperative opioid prescription amount was 326 ± 285 OME (equivalent: 65 tablets of 5 mg hydrocodone). Advanced practice providers accounted for 19% of all prescriptions, and amount per prescription was 18% larger in this group compared with physicians (315 vs. 268, P < 0.001). Primary care providers accounted for 13% of all prescriptions and prescribed on average 279 OME per prescription. The amount of opioid prescribed varied by surgical specialty and ranged from 178 OME (urology) to 454 OME (neurosurgery). CONCLUSIONS: Advanced practice providers account for 1-in-5 postoperative opioid prescriptions and prescribe larger amounts per prescription relative to surgeons. Engaging all providers involved in postoperative care is necessary to understand prescribing practices, identify barriers to reducing prescribing, and tailor interventions accordingly.

Effect of Preoperative Opioid Exposure on Healthcare Utilization and Expenditures Following Elective Abdominal Surgery.

OBJECTIVE: To examine the extent to which preoperative opioid use is correlated with healthcare utilization and costs following elective surgical procedures. SUMMARY BACKGROUND DATA: Morbidity and mortality associated with prescription opioid use is escalating in the United States. The extent to which chronic opioid use influences postoperative outcomes following elective surgery is not well understood. METHODS: Truven Health Marketscan Databases were used to identify adult patients who underwent elective abdominal surgery between June 2009 and December 2012 (n = 200,005). Generalized linear regression was used to determine the effect of preoperative opioid use on postoperative healthcare utilization (length of stay, 30-d readmission, and discharge destination) and cost (hospital stay, 90-, 180-, and 365-d) after adjusting for number of comorbidities, psychological conditions, and demographic characteristics. RESULTS: In this cohort, 8.8% of patients used opioids preoperatively. Compared with non-users, patients using opioids preoperatively were more likely to have a longer hospital stay (2.9 d vs. 2.5 d, P <0.001) and were more likely to be discharged to a rehabilitation facility (3.6% vs. 2.5%, P <0.001), adjusting for covariates. Preoperative opioid use was also correlated with a greater rate of 30-day readmission (4.5% vs. 3.6%, P <0.001) and overall greater expenditures at 90- ($12036.60 vs. $3863.40, P <0.001), 180- ($16973.70 vs. $6790.60, P <0.001), and 365- ($25495.70 vs. $12113.80, P <0.001) days following surgery, adjusted for covariates. Additionally, dose-effects were observed regarding readmission, discharge destination, and late healthcare expenditures. CONCLUSIONS: Preoperative interventions focused on opioid cessation and alternative analgesics may improve the safety and efficiency of elective surgery among chronic opioid users.

Preoperative Opioid Use is Independently Associated With Increased Costs and Worse Outcomes After Major Abdominal Surgery.

OBJECTIVE: To explore the clinical and financial implications of preoperative opioid use in major abdominal surgery. BACKGROUND: Opioids are increasingly used to manage chronic pain, and chronic opioid users are challenging to care for perioperatively. Given the epidemic of opioid-related morbidity and mortality, it is critical to understand how preoperative opioid use impacts surgical outcomes. METHODS: This was an analysis of nonemergent, abdominopelvic surgeries from 2008 to 2014 from a single center within the Michigan Surgical Quality Collaborative clinical registry database. Preoperative opioid use (binary exposure variable) was retrospectively queried from the home medication list of the preoperative evaluation. Our primary outcome was 90-day total hospital costs. Secondary outcomes included hospital length of stay, 30-day major complication rates, discharge destination, and 30-day hospital readmission rates. Analyses were risk-adjusted for case complexity and patient-specific risk factors such as demographics, insurance, smoking, comorbidities, and concurrent medication use. RESULTS: In all, 2413 patients met the inclusion criteria. Among them, 502 patients (21%) used opioids preoperatively. After covariate adjustment, opioid users (compared with those who were opioid-naïve) had 9.2% higher costs [95% confidence interval (CI) 2.8%-15.6%; adjusted means $26,604 vs $24,263; P = 0.005), 12.4% longer length of stay (95% CI 2.3%-23.5%; adjusted means 5.9 vs 5.2 days; P = 0.015), more complications (odds ratio 1.36; 95% CI 1.04-1.78; adjusted rates 20% vs 16%; P = 0.023), more readmissions (odds ratio 1.57; 95% CI 1.08-2.29; adjusted rates 10% vs 6%; P = 0.018), and no difference in discharge destination (P = 0.11). CONCLUSIONS: Opioid use is common before abdominopelvic surgery, and is independently associated with increased postoperative healthcare utilization and morbidity. Preoperative opioids represent a potentially modifiable risk factor and a novel target to improve quality and value of surgical care.

Morphometric age and survival following kidney transplantation.

BACKGROUND: As patients with chronic kidney disease become older, there is greater need to identify who will most benefit from kidney transplantation. Analytic morphomics has emerged as an objective risk assessment tool distinct from chronologic age. We hypothesize that morphometric age is a significant predictor of survival following transplantation. METHODS: A retrospective cohort of 158 kidney transplant patients from 2005 to 2014 with 1-year preoperative imaging was identified. Based on a control population comprising of trauma patients and kidney donors, morphometric age was calculated using the validated characteristics of psoas area, psoas density, and abdominal aortic calcification. The primary outcome was post-transplant survival. RESULTS: Cox regression showed morphometric age was a significant predictor of survival (hazard ratio, 1.06 per morphometric year [95% confidence interval, 1.03-1.08]; P < .001). Chronological age was not significant (hazard ratio, 1.03 per year [0.98-1.07]; P = .22). Among the chronologically oldest patients, those with younger morphometric age had greater survival rates compared to those with older morphometric age. CONCLUSIONS: Morphometric age predicts survival following kidney transplantation. Particularly for older patients, it offers improved risk stratification compared to chronologic age. Morphomics may improve the transplant selection process and provide a greater assessment of prospective survival benefits.

Using analytic morphomics to describe body composition associated with post-kidney transplantation diabetes mellitus.

BACKGROUND: Better risk assessment tools are needed to predict post-transplantation diabetes mellitus (PTDM). Using analytic morphomic measurements from computed tomography (CT) scans, we aimed to identify specific measures of body composition associated with PTDM. METHODS: We retrospectively reviewed 99 non-diabetic kidney transplant recipients who received pre-transplant CT scans at a single institution between 1/2005 and 5/2014. Analytic morphomic techniques were used to measure abdominal adiposity, abdominal size, and psoas muscle area and density, standardized by gender. We measured the associations of these morphomic factors with PTDM. RESULTS: One-year incidence of PTDM was 18%. The morphomic factors significantly associated with PTDM included visceral fat area (OR=1.84 per standard deviation increase, P=.020), body depth (OR=1.79, P=.035), and total body area (OR=1.67, P=.049). Clinical factors significantly associated with PTDM included African American race (OR=3.01, P=.044), hypertension (OR=2.97, P=.041), and dialysis vintage (OR=1.24 per year on dialysis, P=.048). Body mass index was not associated with PTDM (OR=1.05, P=.188). On multivariate modeling, visceral fat area was an independent predictor of PTDM (OR=1.91, P=.035). CONCLUSIONS: Analytic morphomics can identify pre-transplant measurements of body composition that are predictive of PTDM in kidney transplant recipients. Pre-transplant imaging contains a wealth of underutilized data that may inform PTDM prevention strategies.

One-year postoperative resource utilization in sarcopenic patients.

BACKGROUND: It is well established that sarcopenic patients are at higher risk of postoperative complications and short-term health care utilization. Less well understood is how these patients fare over the long term after surviving the immediate postoperative period. We explored costs over the first postoperative year among sarcopenic patients. METHODS: We identified 1279 patients in the Michigan Surgical Quality Collaborative database who underwent inpatient elective surgery at a single institution from 2006-2011. Sarcopenia, defined by gender-stratified tertiles of lean psoas area, was determined from preoperative computed tomography scans using validated analytic morphomics. Data were analyzed to assess sarcopenia's relationship to costs, readmissions, discharge location, intensive care unit admissions, hospital length of stay, and mortality. Multivariate models were adjusted for patient demographics and surgical risk factors. RESULTS: Sarcopenia was independently associated with increased adjusted costs at 30, 90, and 180 but not 365 d. The difference in adjusted postsurgical costs between sarcopenic and nonsarcopenic patients was $16,455 at 30 d and $14,093 at 1 y. Sarcopenic patients were more likely to be discharged somewhere other than home (P < 0.001). Sarcopenia was not an independent predictor of increased readmission rates in the postsurgical year. CONCLUSIONS: The effects of sarcopenia on health care costs are concentrated in the immediate postoperative period. It may be appropriate to allocate additional resources to sarcopenic patients in the perioperative setting to reduce the incidence of negative postoperative outcomes.

Sarcopenia and failure to rescue following liver transplantation.

INTRODUCTION: Sarcopenic liver transplant recipients have higher rates of mortality, but mechanisms underlying these rates remain unclear. Failure to rescue (FTR) has been shown to be a primary driver of mortality following major general and vascular surgery. We hypothesized that FTR is common in sarcopenic liver transplant recipients. METHODS: We retrospectively reviewed 348 liver transplant recipients with perioperative CT scans. Analytic morphomic techniques were used to assess trunk muscle size via total psoas area (TPA). One-yr major complication and FTR rates were calculated across TPA tertiles. RESULTS: The one-yr complication rate was 77% and the FTR rate was 19%. Multivariate regression showed TPA as a significant predictor of FTR (OR = 0.27 per 1000 mm(2) increase in TPA, p < 0.001). Compared to patients in the largest muscle tertile, patients in the smallest tertile had 1.4-fold higher adjusted complication rates (91% vs. 66%) and 2.8-fold higher adjusted FTR rates (22% vs. 8%). DISCUSSION: These results suggest that mortality in sarcopenic liver transplant recipients may be strongly related to FTR. Efforts aimed at early recognition and management of complications may decrease postoperative mortality. Additionally, this work highlights the need for expanded multicenter collaborations aimed at collection and analysis of postoperative complications in liver transplant recipients.

Analytic morphomics identifies predictors of new-onset diabetes after liver transplantation.

UNLABELLED: Among liver transplant recipients, development of post-transplant complications such as new-onset diabetes after transplantation (NODAT) is common and highly morbid. Current methods of predicting patient risk are inaccurate in the pre-transplant period, making implementation of targeted therapies difficult. We sought to determine whether analytic morphomics (using computed tomography scans) could be used to predict the incidence of NODAT. We analyzed peri-transplant scans from 216 patients with varying indications for liver transplantation, among whom 61 (28%) developed NODAT. Combinations of visceral fat, subcutaneous fat, and psoas area were considered in addition to traditional risk factors. On multivariate analysis adjusting for usual risk factors such as type of immunosuppression, subcutaneous fat thickness remained significantly associated with NODAT (OR = 1.43, 95% CI 1.00-1.88, p = 0.047). Subgroup analysis showed that patients with later-onset of NODAT had higher visceral fat, whereas subcutaneous fat thickness was more correlated with earlier-onset of NODAT (using 10 months post-transplant as the cut-off). CONCLUSION: Analytic morphomics may be used to help assess NODAT risk in patients undergoing liver transplantation.