Setting reasonable goals for kidney transplant referral among dialysis facilities.

BACKGROUND: Determining whether a patient is eligible for kidney transplantation is complex. In this study, we estimate what proportion of patients with end-stage kidney disease (ESKD) might have been suitable candidates for kidney transplantation but were not referred. METHODS: We identified 43,952 people initiating dialysis for kidney failure between 2012 and 2017 in the states of Georgia, North Carolina, or South Carolina from the United States Renal Data System and linked to the Early-Steps to Transplant Access Registry to obtain data on referral and waitlisting up until December 2020. We identified 'good transplant candidates' as those who were waitlisted within 2-years of referral, among all patients referred within 1-year of dialysis initiation. Using propensity score cut-offs, logistic regression, and area under the curve (AUC), we then estimated the proportion of individuals who may have been good transplant candidates, but were not referred. RESULTS: Overall, 42.6% of incident dialysis patients were referred within one year and among them, 32.9% were waitlisted within 2 years of referral. Our model had reasonably good discrimination for identifying good transplant candidates with an AUC of 0.70 (95%CI 0.69-0.71), sensitivity of 0.68 and specificity of 0.61. Overall, 25% of individuals not referred for transplant may have been 'good' transplant candidates. Adding these patients to the existing 18,725 referred patients would increase the proportion of incident ESKD patients being referred within one year from 42.6% to 57.2% (a ~ 14.6% increase). CONCLUSIONS: In this study, we show that a significant proportion of potentially good transplant candidates are not being referred for transplant. A ~ 14% increase in the proportion of patients being referred from dialysis facilities is both a meaningful and realistic goal and could lead to more qualified patients being referred and subsequently waitlisted for a lifesaving transplant.

Referral and Evaluation for Kidney Transplantation Following Implementation of the 2014 National Kidney Allocation System.

RATIONALE & OBJECTIVE: The national kidney allocation system (KAS) implemented in December 2014 in the United States redefined the start of waiting time from the time of waitlisting to the time of kidney failure. Waitlisting has declined post-KAS, but it is unknown if this is due to transplant center practices or changes in dialysis facility referral and evaluation. The purpose of this study was to assess the impact of the 2014 KAS policy change on referral and evaluation for transplantation among a population of incident and prevalent patients with kidney failure. STUDY DESIGN: Cohort study. SETTING & PARTICIPANTS: 37,676 incident (2012-2016) patients in Georgia, North Carolina, and South Carolina identified within the US Renal Data System at 9 transplant centers and followed through December 2017. A prevalent population of 6,079 patients from the same centers receiving maintenance dialysis in 2012 but not referred for transplantation in 2012. EXPOSURE: KAS era (pre-KAS vs post-KAS). OUTCOME: Referral for transplantation, start of transplant evaluation, and waitlisting. ANALYTICAL APPROACH: Multivariable time-dependent Cox models for the incident and prevalent population. RESULTS: Among incident patients, KAS was associated with increased referrals (adjusted HR, 1.16 [95% CI, 1.12-1.20]) and evaluation starts among those referred (adjusted HR, 1.16 [95% CI, 1.10-1.21]), decreased overall waitlisting (adjusted HR, 0.70 [95% CI, 0.65-0.76]), and lower rates of active waitlisting among those evaluated compared to the pre-KAS era (adjusted HR, 0.81 [95% CI, 0.74-0.90]). Among the prevalent population, KAS was associated with increases in overall waitlisting (adjusted HR, 1.74 [95% CI, 1.15-2.63]) and active waitlisting among those evaluated (adjusted HR, 2.01 [95% CI, 1.16-3.49]), but had no significant impact on referral or evaluation starts among those referred. LIMITATIONS: Limited to 3 states, residual confounding. CONCLUSIONS: In the southeastern United States, the impact of KAS on steps to transplantation was different among incident and prevalent patients with kidney failure. Dialysis facilities referred more incident patients and transplant centers evaluated more incident patients after implementation of KAS, but fewer evaluated patients were placed onto the waitlist. Changes in dialysis facility and transplant center behaviors after KAS implementation may have influenced the observed changes in access to transplantation.

Sex/Gender Disparities in Preemptive Referrals for Kidney Transplantation.

Introduction: Sex/gender inequities persist in access to kidney transplantation. Whether differences in preemptive referral (i.e., referral before dialysis start) explain this inequity remains unknown. Methods: All adults (aged 18-79 years; N = 44,204) initiating kidney replacement therapy (KRT; dialysis or transplant) in Georgia (GA), North Carolina (NC), or South Carolina (SC) between 2015 and 2019 were identified from the United States Renal Data System (USRDS). Individuals were linked to the Early Steps to Kidney Transplant Access Registry (E-STAR) to obtain data on preemptive referral and followed-up with through November 13, 2020, for outcomes of waitlisting and living donor transplant. Logistic regression assessed the association between sex/gender and likelihood of preemptive referral among all KRT patients. Cox-proportional hazards assessed the association between sex/gender and waitlisting or living donor among preemptively referred patients. Results: Overall, men and women were similarly likely to be preemptively referred (odds ratio [OR]: 0.99 [0.95-1.04]). Preemptively referred women (vs. men) were, on average, younger and with fewer comorbidities. There were no sex/gender differences in waitlisting once patients were preemptively referred (hazard ratio [HR]: 0.97 [0.91-1.03]); however, women (vs. men) who were preemptively referred remained 25% (HR: 0.75 [0.66-0.86]) less likely to receive a living donor transplant. Conclusion: In the Southeast US, men and women initiating KRT are similarly likely to be preemptively referred for a kidney transplant, and this appears, at least in part, to mitigate known sex/gender inequities in access to waitlisting, but not living donor transplant. Despite this, preemptively referred women, on average, had a more favorable medical profile relative to preemptively referred men.

Improving Statewide Post-Operative Sepsis Performance Measurement Using Hospital Risk Adjustment Within a Surgical Collaborative.

Background: The Georgia Quality Improvement Program (GQIP) surgical collaborative participating hospitals have shown consistently poor performance in the post-operative sepsis category of National Surgical Quality Improvement Program data as compared with national benchmarks. We aimed to compare crude versus risk-adjusted post-operative sepsis rankings to determine high and low performers amongst GQIP hospitals. Patients and Methods: The cohort included intra-abdominal general surgery patients across 10 collaborative hospitals from 2015 to 2020. The American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP) sepsis definition was used among all hospitals for case abstraction and NSQIP data were utilized to train and validate a multivariable risk-adjustment model with post-operative sepsis as the outcome. This model was used to rank GQIP hospitals by risk-adjusted post-operative sepsis rates. Rankings between crude and risk-adjusted post-operative sepsis rankings were compared ordinally and for changes in tertile. Results: The study included 20,314 patients with 595 cases of post-operative sepsis. Crude 30-day post-operative sepsis risk among hospitals ranged from 0.81 to 5.11. When applying the risk-adjustment model which included: age, American Society of Anesthesiology class, case complexity, pre-operative pneumonia/urinary tract infection/surgical site infection, admission status, and wound class, nine of 10 hospitals were re-ranked and four hospitals changed performance tertiles. Conclusions: Inter-collaborative risk-adjusted post-operative sepsis rankings are important to present. These metrics benchmark collaborating hospitals, which facilitates best practice exchange from high to low performers.

Modification engineering of TiO2-based nanoheterojunction photocatalysts.

Titanium dioxide (TiO2)-based photocatalysts have gained increasing attention for their versatile applications in organic degradation, hydrogen production, air purification, and CO2 reduction. Various TiO2-based heterojunction structures, including type I, type II, Schottky junction, Z-scheme, and S-scheme, have been extensively studied. The current research frontier is centered on the engineering modifications of TiO2-based nanoheterojunction photocatalysts, such as defect engineering, morphological engineering, crystal phase/facet engineering, and multijunction engineering. These modifications enhance carrier transport, separation, and light absorption, thereby improving the photocatalytic performance. Remarkably, this aspect has been less addressed in existing reviews. This review aims to fill this gap by focusing on the engineering modifications of TiO2-based nanoheterojunction photocatalysts. We delve into specific topics like oxygen vacancies, n-p homojunctions, and double defects. The review also systematically discusses the applications of multidimensional heterojunctions and examines carrier transport pathways in heterophase/facet junctions and their interactions with heterojunctions. A comprehensive summary of multijunction systems, including multi-Schottky junctions, semiconductor-based heterojunction-attached Schottky junctions, and multisemiconductor-based heterojunctions, is presented. Lastly, we outline future perspectives in this promising research field. This paper will assist researchers in constructing more efficient TiO2-based nanoheterojunction photocatalysts.

Sex/Gender-Based Disparities in Early Transplant Access by Attributed Cause of Kidney Disease-Evidence from a Multiregional Cohort in the Southeast United States.

Introduction: We examined sex/gender disparities across the continuum of transplant care by attributed cause of end-stage kidney disease (ESKD). Methods: All adults (18-79 years; N = 43,548) with new-onset ESKD in Georgia, North Carolina, or South Carolina between 2015 and 2019 were identified from the United States Renal Data System (USRDS). Individuals were linked to the Early Steps to Transplant Access Registry (E-STAR) to obtain data on referral and evaluation. Waitlisting data was ascertained from USRDS. Using a Cox-proportional hazards model, with follow-up through 2020, we assessed the association between sex/gender and referral within 12 months (among all incident dialysis patients), evaluation start within 6 months (among referred patients), and waitlisting (among all evaluated patients) by attributed cause of ESKD (type 1 diabetes mellitus, type 2 diabetes mellitus, hypertension, glomerulonephritis, cystic disease, and other). Results: Overall, women (vs. men) with type 2 diabetes-attributed ESKD were 13% (crude hazard ratio [HR]: 0.87 [0.83-0.91]), 14% (crude HR: 0.86 [0.81-0.91]), and 14% (crude HR: 0.86 [0.78-0.94]) less likely to be referred, evaluated, and waitlisted, respectively. Women (vs. men) with hypertension-attributed ESKD were 14% (crude HR: 0.86 [0.82-0.90]) and 8% (crude HR: 0.92 [0.87-0.98]) less likely to be referred and evaluated, respectively, but similarly likely to be waitlisted once evaluated (crude HR: 1.06 [0.97-1.15]). For all other attributed causes of ESKD, there was no sex/gender disparity in referral, evaluation, or waitlisting rates. Conclusion: In the Southeast United States, sex/gender disparities in early access to kidney transplantation are specific to people with ESKD attributed to type 2 diabetes and hypertension.

Rational design of covalent triazine frameworks based on pore size and heteroatomic toward high performance supercapacitors.

A series of covalent triazine frameworks (CTFs) are prepared via ionothermal synthesis for supercapacitors. Due to the feature of adjustable pore structure and rich nitrogen, CTFs with regular structure can be used as a group of model compounds to further investigate the influence of pore size and heteroatom on supercapacitors. By comparing the performance of CTFs with different pore structures and nitrogen contents, the experimental results show that BPY-CTF with high specific surface area of 2278 m2 g-1, mesopores structure, and suitable nitrogen content displays a specific capacitance of 393.6 F g-1 at 0.5 A g-1. According to the results and analysis, the existence of mesopores largely enhance the contact area between the electrode material and electrolyte, and then boost the charge transfer. On the other hand, N-doping has a prominent effect on improving the Faradaic pseudo-capacitance and conductivity for CTF electrode materials. This work will inspire further research on the development of highly efficient electrode materials for energy storage devices.

The Use of a Self-triage Tool to Predict COVID-19 Cases and Hospitalizations in the State of Georgia.

INTRODUCTION: The coronavirus 2019 (COVID-19) pandemic has created significant burden on healthcare systems throughout the world. Syndromic surveillance, which collects real-time data based on a range of symptoms rather than laboratory diagnoses, can help provide timely information in emergency response. We examined the effectiveness of a web-based COVID-19 symptom checking tool (C19Check) in the state of Georgia (GA) in predicting COVID-19 cases and hospitalizations. METHODS: We analyzed C19Check use data, COVID-19 cases, and hospitalizations from April 22-November 28, 2020. Cases and hospitalizations in GA were extracted from the Georgia Department of Public Health data repository. We used the Granger causality test to assess whether including C19Check data can improve predictions compared to using previous COVID-19 cases and hospitalizations data alone. Vector autoregression (VAR) models were fitted to forecast cases and hospitalizations from November 29 - December 12, 2020. We calculated mean absolute percentage error to estimate the errors in forecast of cases and hospitalizations. RESULTS: There were 25,861 C19Check uses in GA from April 22-November 28, 2020. Time-lags tested in Granger causality test for cases (6-8 days) and hospitalizations (10-12 days) were significant (P= <0.05); the mean absolute percentage error of fitted VAR models were 39.63% and 15.86%, respectively. CONCLUSION: The C19Check tool was able to help predict COVID-19 cases and related hospitalizations in GA. In settings where laboratory tests are limited, a real-time, symptom-based assessment tool can provide timely and inexpensive data for syndromic surveillance to guide pandemic response. Findings from this study demonstrate that online symptom-checking tools can be a source of data for syndromic surveillance, and the data may help improve predictions of cases and hospitalizations.

Comparison of Work Relative Value Units for Outpatient Pediatric and Adult Dermatology Encounters.

Importance: Dermatologists with specialty training in pediatric dermatology are scarce, which can mean extended wait times and reduced access to care for patients. Lower compensation for pediatric dermatology visits compared with adult visits may affect physician career choice and contribute to workforce shortages. Objective: To evaluate differences in work relative value units (wRVUs) generated by pediatric and adult outpatient dermatology encounters. Design, Setting, and Participants: This cross-sectional study used data from outpatient dermatology encounters at a single-site academic center in Atlanta, Georgia, from September 1, 2016, to March 31, 2020. Encounters with patients younger than 18 years were classified as pediatric, and encounters with those 18 years or older were classified as adult. Encounters with missing data were excluded as were those generating 0 wRVUs, inpatient visits, nursing visits, postoperative encounters, cosmetic procedures, phototherapy visits, and Mohs surgery encounters. Main Outcomes and Measures: Work relative value units generated per encounter type were assessed through multivariable linear regression models adjusted for the potential confounder of sex. Results: The study included 12 989 pediatric dermatology encounters (mean [SD] age, 7.3 [5.2] years; 7586 [58.4%] girls) and 78 057 adult dermatology encounters (mean [SD] age, 54.9 [18.9] years; 45 724 [58.6%] women). Pediatric encounters were associated with 0.23 (95% CI, 0.21-0.25; P < .001) fewer wRVUs than adult encounters after adjusting for sex. In a mediation analysis, biopsies and destruction of premalignant lesions explained 74.1% (95% CI, 69.6%-77.9%; P < .001) of the wRVU difference between pediatric and adult encounters. Conclusions and Relevance: This cross-sectional study found significant differences in wRVUs generated between adult and pediatric dermatology encounters that were largely attributable to biopsies and destruction of premalignant lesions. Policies that increase the value of cognitive services to be on par with procedural care may mitigate wRVU differences and improve reimbursement for pediatric dermatologists.

COVID-19-associated venous thromboembolism portends worse survival.

Patients with coronavirus disease 2019 (COVID-19) seem to be at high risk for venous thromboembolism (VTE) development, but there is a paucity of data exploring both the natural history of COVID-19-associated VTE and the risk for poor outcomes after VTE development. This investigation aims to explore the relationship between COVID-19-associated VTE development and mortality. A prospectively maintained registry of patients older than 18 years admitted for COVID-19-related illnesses within an academic health care network between March and September 2020 was reviewed. Codes from the tenth revision of the International Classification of Diseases for VTE were collected. The charts of those patients with a code for VTE were manually reviewed to confirm VTE diagnosis. There were 2,552 patients admitted with COVID-19-related illnesses. One hundred and twenty-six patients (4.9%) developed a VTE. A disproportionate percentage of patients of Black race developed a VTE (70.9% VTE v 57.8% non-VTE; P = .012). A higher proportion of patients with VTE expired during their index hospitalization (22.8% VTE v 8.4% non-VTE; P < .001). On multivariable logistic regression analysis, VTE was independently associated with mortality (odds ratio = 3.17; 95% confidence interval, 1.9-5.2; P < .001). Hispanic/Latinx ethnicity was associated with decreased mortality (odds ratio = 0.45; 95% confidence interval, 0.21-1.00; P = .049). Hospitalized patients of Black race with COVID-19 were more prone to VTE development, and patients with COVID-19 who developed in-hospital VTE had roughly nearly threefold higher odds of mortality. Further emphasis should be placed on optimizing COVID-19 anticoagulation protocols to reduce mortality in this high-risk cohort.

Atomically Dispersed Au on In2O3 Nanosheets for Highly Sensitive and Selective Detection of Formaldehyde.

As an important industrial chemical, formaldehyde is used in various fields but is harmful to health. Developing a convenient detection device for formaldehyde is significant. Based on atomically dispersed Au on In2O3 nanosheets, a formaldehyde sensor was fabricated in this work. The highly dispersed Au obtained by the ultraviolet (UV) light-assisted reduction method helps improve the sensing performance. A meager loading amount (0.01 wt %) of Au on In2O3 nanosheets exhibits high sensitivity toward ppb-level formaldehyde. Au acts as an electron sink and promotes the oxidation of formaldehyde. Atomically dispersed Au on In2O3 nanosheets decreases the activation energy and increases the number of active sites, which result in a highly efficient conversion of formaldehyde and a marked resistance change of the fabricated sensors. The selective adsorption and oxidation of formaldehyde on single atom Au's uniform sites establish excellent selectivity. Besides, the sensor exhibits short response/recovery time and excellent stability, with promising applications in formaldehyde detection.

Prediction of emergency department resource requirements during triage: An application of current natural language processing techniques.

OBJECTIVE: Accurate triage in the emergency department (ED) is critical for medical safety and operational efficiency. We aimed to predict the number of future required ED resources, as defined by the Emergency Severity Index (ESI) triage protocol, using natural language processing of nursing triage notes. METHODS: We constructed a retrospective cohort of all 265,572 consecutive ED encounters from 2015 to 2016 from 3 separate clinically heterogeneous academically affiliated EDs. We excluded encounters missing relevant information, leaving 226,317 encounters. We calculated the number of resources used by patients in the ED retrospectively and based outcome categories on criteria defined in the ESI algorithm: 0 (30,604 encounters), 1 (49,315 encounters), and 2 or more (146,398 encounters). A neural network model was trained on a training subset to predict the number of resources using triage notes and clinical variables at triage. Model performance was evaluated using the test subset and was compared with human ratings. RESULTS: Overall model accuracy and macro F1 score for number of resources were 66.5% and 0.601, respectively. The model had similar macro F1 (0.589 vs 0.592) and overall accuracy (65.9% vs 69.0%) compared to human raters. Model predictions had slightly higher F1 scores and accuracy for 0 resources and were less accurate for 2 or more resources. CONCLUSIONS: Machine learning of nursing triage notes, combined with clinical data available at ED presentation, can be used to predict the number of required future ED resources. These findings suggest that machine learning may be a valuable adjunct tool in the initial triage of ED patients.

Prediction of emergency department patient disposition based on natural language processing of triage notes.

BACKGROUND: Nursing triage documentation is the first free-form text data created at the start of an emergency department (ED) visit. These 1-3 unstructured sentences reflect the clinical impression of an experienced nurse and are key in gauging a patient's illness. We aimed to predict final ED disposition using three commonly-employed natural language processing (NLP) techniques of nursing triage notes in isolation from other data. METHODS: We constructed a retrospective cohort of all 260,842 consecutive ED encounters in 2015-16, from three clinically heterogeneous academically-affiliated EDs. After exclusion of 3964 encounters based on completeness of triage, and disposition data, we included 256,878 encounters. We defined the outcome as: 1) admission, transfer, or in-ED death [68,092 encounters] vs. 2) discharge, "left without being seen," and "left against medical advice" [188,786 encounters]. The dataset was divided into training and testing subsets. Neural network regression models were trained using bag-of-words, paragraph vectors, and topic distributions to predict disposition and were evaluated using the testing dataset. RESULTS: Area under the curve for disposition using triage notes as bag-of-words, paragraph vectors, and topic distributions were 0.737 (95% CI: 0.734 - 0.740), 0.785 (95% CI: 0.782 - 0.788), and 0.687 (95% CI: 0.684 - 0.690), respectively. CONCLUSIONS: Nursing triage notes can be used to predict final ED patient disposition, even when used separately from other clinical information. These findings have substantial implications for future studies, suggesting that free text from medical records may be considered as a critical predictor in research of patient outcomes.