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BackgroundPostoperative respiratory failure (PRF) is associated with increased hospital charges and worse patient outcomes. Reliable prediction models can help to guide postoperative planning to optimize care, to guide resource allocation, and to foster shared decision-making with patients.Research questionCan a predictive model be developed to accurately identify patients at high risk of PRF?Study design and methodsIn this single-site proof-of-concept study, we used structured query language to extract, transform, and load electronic health record data from 23,999 consecutive adult patients admitted for elective surgery (2014-2021). Our primary outcome was PRF, defined as mechanical ventilation after surgery of > 48 h. Predictors of interest included demographics, comorbidities, and intraoperative factors. We used logistic regression to build a predictive model and the least absolute shrinkage and selection operator procedure to select variables and to estimate model coefficients. We evaluated model performance using optimism-corrected area under the receiver operating curve and area under the precision-recall curve and calculated sensitivity, specificity, positive and negative predictive values, and Brier scores.ResultsTwo hundred twenty-five patients (0.94%) demonstrated PRF. The 18-variable predictive model included: operations on the cardiovascular, nervous, digestive, urinary, or musculoskeletal system; surgical specialty orthopedic (nonspine); Medicare or Medicaid (as the primary payer); race unknown; American Society of Anesthesiologists class ≥ III; BMI of 30 to 34.9 kg/m2; anesthesia duration (per hour); net fluid at end of the operation (per liter); median intraoperative FIO2, end title CO2, heart rate, and tidal volume; and intraoperative vasopressor medications. The optimism-corrected area under the receiver operating curve was 0.835 (95% CI,0.808-0.862) and the area under the precision-recall curve was 0.156 (95% CI, 0.105-0.203).InterpretationThis single-center proof-of-concept study demonstrated that a structured query language extract, transform, and load process, based on readily available patient and intraoperative variables, can be used to develop a prediction model for PRF. This PRF prediction model is scalable for multicenter research. Clinical applications include decision support to guide postoperative level of care admission and treatment decisions.

IntroductionElectronic referral (e-referral) to quitlines helps connect tobacco-using patients to free, evidence-based cessation counseling. Little has been published about the real-world implementation of e-referrals across U.S. health systems, their maintenance over time, and the outcomes of e-referred patients.Aims and methodsBeginning in 2014, the University of California (UC)-wide project called UC Quits scaled up quitline e-referrals and related modifications to clinical workflows from one to five UC health systems. Implementation strategies were used to increase site readiness. Maintenance was supported through ongoing monitoring and quality improvement programs. Data on e-referred patients (n = 20 709) and quitline callers (n = 197 377) were collected from April 2014 to March 2021. Analyses of referral trends and cessation outcomes were conducted in 2021-2022.ResultsOf 20 709 patients referred, the quitline contacted 47.1%, 20.6% completed intake, 15.2% requested counseling, and 10.9% received it. In the 1.5-year implementation phase, 1813 patients were referred. In the 5.5-year maintenance phase, volume was sustained, with 3436 referrals annually on average. Among referred patients completing intake (n = 4264), 46.2% were nonwhite, 58.8% had Medicaid, 58.7% had a chronic disease, and 48.8% had a behavioral health condition. In a sample randomly selected for follow-up, e-referred patients were as likely as general quitline callers to attempt quitting (68.5% vs. 71.4%; p = .23), quit for 30 days (28.3% vs. 26.9%; p = .52), and quit for 6 months (13.6% vs. 13.9%; p = .88).ConclusionsWith a whole-systems approach, quitline e-referrals can be established and sustained across inpatient and outpatient settings with diverse patient populations. Cessation outcomes were similar to those of general quitline callers.ImplicationsThis study supports the broad implementation of tobacco quitline e-referrals in health care. To the best of our knowledge, no other paper has described the implementation of e-referrals across multiple U.S. health systems or how they were sustained over time. Modifying electronic health records systems and clinical workflows to enable and encourage e-referrals, if implemented and maintained appropriately, can be expected to improve patient care, make it easier for clinicians to support patients in quitting, increase the proportion of patients using evidence-based treatment, provide data to assess progress on quality goals, and help meet reporting requirements for tobacco screening and prevention.

BackgroundWhile others have reported severe acute respiratory syndrome-related coronavirus 2(SARS-CoV-2) seroprevalence studies in health care workers (HCWs), we leverage the use of a highly sensitive coronavirus antigen microarray to identify a group of seropositive health care workers who were missed by daily symptom screening that was instituted prior to any epidemiologically significant local outbreak. Given that most health care facilities rely on daily symptom screening as the primary method to identify SARS-CoV-2 among health care workers, here, we aim to determine how demographic, occupational, and clinical variables influence SARS-CoV-2 seropositivity among health care workers.MethodsWe designed a cross-sectional survey of HCWs for SARS-CoV-2 seropositivity conducted from May 15th to June 30th 2020 at a 418-bed academic hospital in Orange County, California. From an eligible population of 5,349 HCWs, study participants were recruited in two ways: an open cohort, and a targeted cohort. The open cohort was open to anyone, whereas the targeted cohort that recruited HCWs previously screened for COVID-19 or work in high-risk units. A total of 1,557 HCWs completed the survey and provided specimens, including 1,044 in the open cohort and 513 in the targeted cohort. Demographic, occupational, and clinical variables were surveyed electronically. SARS-CoV-2 seropositivity was assessed using a coronavirus antigen microarray (CoVAM), which measures antibodies against eleven viral antigens to identify prior infection with 98% specificity and 93% sensitivity.ResultsAmong tested HCWs (n = 1,557), SARS-CoV-2 seropositivity was 10.8%, and risk factors included male gender (OR 1.48, 95% CI 1.05-2.06), exposure to COVID-19 outside of work (2.29, 1.14-4.29), working in food or environmental services (4.85, 1.51-14.85), and working in COVID-19 units (ICU: 2.28, 1.29-3.96; ward: 1.59, 1.01-2.48). Amongst 1,103 HCWs not previously screened, seropositivity was 8.0%, and additional risk factors included younger age (1.57, 1.00-2.45) and working in administration (2.69, 1.10-7.10).ConclusionSARS-CoV-2 seropositivity is significantly higher than reported case counts even among HCWs who are meticulously screened. Seropositive HCWs missed by screening were more likely to be younger, work outside direct patient care, or have exposure outside of work.

BackgroundThe COVID-19 standard of care (SOC) evolved rapidly during 2020 and 2021, but its cumulative effect over time is unclear.ObjectiveTo evaluate whether recovery and mortality improved as SOC evolved, using data from ACTT (Adaptive COVID-19 Treatment Trial).DesignACTT is a series of phase 3, randomized, double-blind, placebo-controlled trials that evaluated COVID-19 therapeutics from February 2020 through May 2021. ACTT-1 compared remdesivir plus SOC to placebo plus SOC, and in ACTT-2 and ACTT-3, remdesivir plus SOC was the control group. This post hoc analysis compared recovery and mortality between these comparable sequential cohorts of patients who received remdesivir plus SOC, adjusting for baseline characteristics with propensity score weighting. The analysis was repeated for participants in ACTT-3 and ACTT-4 who received remdesivir plus dexamethasone plus SOC. Trends in SOC that could explain outcome improvements were analyzed. (ClinicalTrials.gov: NCT04280705 [ACTT-1], NCT04401579 [ACTT-2], NCT04492475 [ACTT-3], and NCT04640168 [ACTT-4]).Setting94 hospitals in 10 countries (86% U.S. participants).ParticipantsAdults hospitalized with COVID-19.InterventionSOC.Measurements28-day mortality and recovery.ResultsAlthough outcomes were better in ACTT-2 than in ACTT-1, adjusted hazard ratios (HRs) were close to 1 (HR for recovery, 1.04 [95% CI, 0.92 to 1.17]; HR for mortality, 0.90 [CI, 0.56 to 1.40]). Comparable patients were less likely to be intubated in ACTT-2 than in ACTT-1 (odds ratio, 0.75 [CI, 0.53 to 0.97]), and hydroxychloroquine use decreased. Outcomes improved from ACTT-2 to ACTT-3 (HR for recovery, 1.43 [CI, 1.24 to 1.64]; HR for mortality, 0.45 [CI, 0.21 to 0.97]). Potential explanatory factors (SOC trends, case surges, and variant trends) were similar between ACTT-2 and ACTT-3, except for increased dexamethasone use (11% to 77%). Outcomes were similar in ACTT-3 and ACTT-4. Antibiotic use decreased gradually across all stages.LimitationUnmeasured confounding.ConclusionChanges in patient composition explained improved outcomes from ACTT-1 to ACTT-2 but not from ACTT-2 to ACTT-3, suggesting improved SOC. These results support excluding nonconcurrent controls from analysis of platform trials in rapidly changing therapeutic areas.Primary funding sourceNational Institute of Allergy and Infectious Diseases.

ObjectiveIn order to manage COVID-19 patient population and bed capacity issues, remote patient monitoring (RPM) is a strategy used to transition patients from inpatients to home. We describe our RPM implementation process for post-acute care COVID-19 pneumonia patients. We also evaluate the impact of RPM on patient outcomes, including hospital length of stay (LOS), post-discharge Emergency Department (ED) visits, and hospital readmission.Materials and methodsWe utilized a cloud-based RPM platform (Vivify Health) and a nurse-monitoring service (Global Medical Response) to enroll COVID-19 patients who required oxygen supplementation after hospital discharge. We evaluated patient participation, biometric alerts, and provider communication. We also assessed the program's impact by comparing RPM patient outcomes with a retrospective cohort of Control patients who similarly required oxygen supplementation after discharge but were not referred to the RPM program. Statistical analyses were performed to evaluate the 2 groups' demographic characteristics, hospital LOS, and readmission rates.ResultsThe RPM program enrolled 75 patients with respondents of a post-participation survey reporting high satisfaction with the program. Compared to the Control group (n = 150), which had similar demographics and baseline characteristics, the RPM group was associated with shorter hospital LOS (median 4.8 vs 6.1 days; P=.03) without adversely impacting return to the ED or readmission.ConclusionWe implemented a RPM program for post-acute discharged COVID-19 patients requiring oxygen supplementation. Our RPM program resulted in a shorter hospital LOS without adversely impacting quality outcomes for readmission rates and improved healthcare utilization by reducing the average LOS.

IntroductionThe COVID-19 pandemic brought an urgent need to discover novel effective therapeutics for patients hospitalised with severe COVID-19. The Investigation of Serial studies to Predict Your Therapeutic Response with Imaging And moLecular Analysis (ISPY COVID-19 trial) was designed and implemented in early 2020 to evaluate investigational agents rapidly and simultaneously on a phase 2 adaptive platform. This manuscript outlines the design, rationale, implementation and challenges of the ISPY COVID-19 trial during the first phase of trial activity from April 2020 until December 2021.Methods and analysisThe ISPY COVID-19 Trial is a multicentre open-label phase 2 platform trial in the USA designed to evaluate therapeutics that may have a large effect on improving outcomes from severe COVID-19. The ISPY COVID-19 Trial network includes academic and community hospitals with significant geographical diversity across the country. Enrolled patients are randomised to receive one of up to four investigational agents or a control and are evaluated for a family of two primary outcomes-time to recovery and mortality. The statistical design uses a Bayesian model with 'stopping' and 'graduation' criteria designed to efficiently discard ineffective therapies and graduate promising agents for definitive efficacy trials. Each investigational agent arm enrols to a maximum of 125 patients per arm and is compared with concurrent controls. As of December 2021, 11 investigational agent arms had been activated, and 8 arms were complete. Enrolment and adaptation of the trial design are ongoing.Ethics and disseminationISPY COVID-19 operates under a central institutional review board via Wake Forest School of Medicine IRB00066805. Data generated from this trial will be reported in peer-reviewed medical journals.Trial registration numberNCT04488081.

Diabetes is the leading cause of end-stage renal disease (ESRD) and contributes to heightened morbidity and mortality in dialysis patients. Given that ESRD patients are susceptible to hypoglycemia and hyperglycemia via multiple pathways, adequate glycemic monitoring and control is a cornerstone in diabetic kidney disease management. In ESRD, existing glycemic metrics such as glycated hemoglobin, self-monitored blood glucose, fructosamine, and glycated albumin have limitations in accuracy, convenience, and accessibility. In contrast, continuous glucose monitoring (CGM) provides automated, less invasive glucose measurements and more comprehensive glycemic data versus conventional metrics. Here, we report a 48-year-old male with ESRD due to diabetes receiving thrice-weekly hemodialysis who experienced decreased patient-burden, greater glucose monitoring adherence, improved glycemic parameters, and reduction in hypoglycemia after transitioning to CGM. Through this case, we discuss how CGM is a practical, convenient patient-centered tool that may improve metabolic outcomes and quality of life in ESRD patients with diabetes.

BackgroundSevere coronavirus disease 2019 (Covid-19) is associated with dysregulated inflammation. The effects of combination treatment with baricitinib, a Janus kinase inhibitor, plus remdesivir are not known.MethodsWe conducted a double-blind, randomized, placebo-controlled trial evaluating baricitinib plus remdesivir in hospitalized adults with Covid-19. All the patients received remdesivir (≤10 days) and either baricitinib (≤14 days) or placebo (control). The primary outcome was the time to recovery. The key secondary outcome was clinical status at day 15.ResultsA total of 1033 patients underwent randomization (with 515 assigned to combination treatment and 518 to control). Patients receiving baricitinib had a median time to recovery of 7 days (95% confidence interval [CI], 6 to 8), as compared with 8 days (95% CI, 7 to 9) with control (rate ratio for recovery, 1.16; 95% CI, 1.01 to 1.32; P = 0.03), and a 30% higher odds of improvement in clinical status at day 15 (odds ratio, 1.3; 95% CI, 1.0 to 1.6). Patients receiving high-flow oxygen or noninvasive ventilation at enrollment had a time to recovery of 10 days with combination treatment and 18 days with control (rate ratio for recovery, 1.51; 95% CI, 1.10 to 2.08). The 28-day mortality was 5.1% in the combination group and 7.8% in the control group (hazard ratio for death, 0.65; 95% CI, 0.39 to 1.09). Serious adverse events were less frequent in the combination group than in the control group (16.0% vs. 21.0%; difference, -5.0 percentage points; 95% CI, -9.8 to -0.3; P = 0.03), as were new infections (5.9% vs. 11.2%; difference, -5.3 percentage points; 95% CI, -8.7 to -1.9; P = 0.003).ConclusionsBaricitinib plus remdesivir was superior to remdesivir alone in reducing recovery time and accelerating improvement in clinical status among patients with Covid-19, notably among those receiving high-flow oxygen or noninvasive ventilation. The combination was associated with fewer serious adverse events. (Funded by the National Institute of Allergy and Infectious Diseases; ClinicalTrials.gov number, NCT04401579.).

Purpose of reviewSevere acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) is the novel virus responsible for the current worldwide pandemic. The scientific and healthcare communities have made every effort to discover and implement treatment options at a historic pace. Patients with kidney disease are uniquely vulnerable to an infectious pandemic because of their need to be in frequent contact with the healthcare system for life-sustaining renal replacement therapy whether it be by dialysis or transplant.Recent findingsThe use of targeted viral therapies, extracorporeal therapies, immunosuppressive therapy and public health interventions are important in the management of patients with COVID-19 but require special consideration in patients with kidney disease because of the complexity of their condition.SummaryHere, we discuss some of the major efforts made to prevent spread and emerging treatment options for this virus, as they pertain to patients with kidney disease.

BackgroundCOVID-19's pulmonary manifestations are broad, ranging from pneumonia with no supplemental oxygen requirements to acute respiratory distress syndrome (ARDS) with acute respiratory failure (ARF). In response, new oxygenation strategies and therapeutics have been developed, but their large-scale effects on outcomes in severe COVID-19 patients remain unknown. Therefore, we aimed to examine the trends in mortality, mechanical ventilation, and cost over the first six months of the pandemic for adult COVID-19 patients in the US who developed ARDS or ARF.Methods and findingsThe Vizient Clinical Data Base, a national database comprised of administrative, clinical, and financial data from academic medical centers, was queried for patients ≥ 18-years-old with COVID-19 and either ARDS or ARF admitted between 3/2020-8/2020. Demographics, mechanical ventilation, length of stay, total cost, mortality, and discharge status were collected. Mann-Kendall tests were used to assess for significant monotonic trends in total cost, mechanical ventilation, and mortality over time. Chi-square tests were used to compare mortality rates between March-May and June-August. 110,223 adult patients with COVID-19 ARDS or ARF were identified. Mean length of stay was 12.1±13.3 days and mean total cost was $35,991±32,496. Mechanical ventilation rates were 34.1% and in-hospital mortality was 22.5%. Mean cost trended downward over time (p = 0.02) from $55,275 (March) to $18,211 (August). Mechanical ventilation rates trended down (p

BackgroundCOVID-19's pulmonary manifestations are broad, ranging from pneumonia with no supplemental oxygen requirements to acute respiratory distress syndrome (ARDS) with acute respiratory failure (ARF). In response, new oxygenation strategies and therapeutics have been developed, but their large-scale effects on outcomes in severe COVID-19 patients remain unknown. Therefore, we aimed to examine the trends in mortality, mechanical ventilation, and cost over the first six months of the pandemic for adult COVID-19 patients in the US who developed ARDS or ARF.Methods and findingsThe Vizient Clinical Data Base, a national database comprised of administrative, clinical, and financial data from academic medical centers, was queried for patients ≥ 18-years-old with COVID-19 and either ARDS or ARF admitted between 3/2020-8/2020. Demographics, mechanical ventilation, length of stay, total cost, mortality, and discharge status were collected. Mann-Kendall tests were used to assess for significant monotonic trends in total cost, mechanical ventilation, and mortality over time. Chi-square tests were used to compare mortality rates between March-May and June-August. 110,223 adult patients with COVID-19 ARDS or ARF were identified. Mean length of stay was 12.1±13.3 days and mean total cost was $35,991±32,496. Mechanical ventilation rates were 34.1% and in-hospital mortality was 22.5%. Mean cost trended downward over time (p = 0.02) from $55,275 (March) to $18,211 (August). Mechanical ventilation rates trended down (p

AbstractBackgroundThe rapid spread of coronavirus disease 2019 (COVID-19) revealed significant constraints in critical care capacity. In anticipation of subsequent waves, reliable prediction of disease severity is essential for critical care capacity management and may enable earlier targeted interventions to improve patient outcomes. The purpose of this study is to develop and externally validate a prognostic model/clinical tool for predicting COVID-19 critical disease at presentation to medical care.MethodsThis is a retrospective study of a prognostic model for the prediction of COVID-19 critical disease where critical disease was defined as ICU admission, ventilation, and/or death. The derivation cohort was used to develop a multivariable logistic regression model. Covariates included patient comorbidities, presenting vital signs, and laboratory values. Model performance was assessed on the validation cohort by concordance statistics. The model was developed with consecutive patients with COVID-19 who presented to University of California Irvine Medical Center in Orange County, California. External validation was performed with a random sample of patients with COVID-19 at Emory Healthcare in Atlanta, Georgia.ResultsOf a total 3208 patients tested in the derivation cohort, 9% (299/3028) were positive for COVID-19. Clinical data including past medical history and presenting laboratory values were available for 29% (87/299) of patients (median age, 48 years [range, 21-88 years]; 64% [36/55] male). The most common comorbidities included obesity (37%, 31/87), hypertension (37%, 32/87), and diabetes (24%, 24/87). Critical disease was present in 24% (21/87). After backward stepwise selection, the following factors were associated with greatest increased risk of critical disease: number of comorbidities, body mass index, respiratory rate, white blood cell count, % lymphocytes, serum creatinine, lactate dehydrogenase, high sensitivity troponin I, ferritin, procalcitonin, and C-reactive protein. Of a total of 40 patients in the validation cohort (median age, 60 years [range, 27-88 years]; 55% [22/40] male), critical disease was present in 65% (26/40). Model discrimination in the validation cohort was high (concordance statistic: 0.94, 95% confidence interval 0.87-1.01). A web-based tool was developed to enable clinicians to input patient data and view likelihood of critical disease.Conclusions and RelevanceWe present a model which accurately predicted COVID-19 critical disease risk using comorbidities and presenting vital signs and laboratory values, on derivation and validation cohorts from two different institutions. If further validated on additional cohorts of patients, this model/clinical tool may provide useful prognostication of critical care needs.

AbstractBackgroundRecent epidemiological evidence has demonstrated a higher rate of COVID-19 hospitalizations and deaths among minorities. This pattern of race-ethnic disparities emerging throughout the United States raises the question of what social factors may influence spread of a highly transmissible novel coronavirus. The purpose of this study is to describe race-ethnic and socioeconomic disparities associated with COVID-19 in patients in our community in Orange County, California and understand the role of individual-level factors, neighborhood-level factors, and access to care on outcomes.MethodsThis is a case-series of COVID-19 patients from the University of California, Irvine (UCI) across six-weeks between 3/12/2020 and 4/22/2020. Note, California’s shelter-in-place order began on 3/19/2020. Individual-level factors included race-ethnicity status were recorded. Neighborhood-level factors from census tracts included median household income, mean household size, proportion without a college degree, proportion working from home, and proportion without health insurance were also recorded.ResultsA total of 210-patients tested were COVID-19 positive, of which 73.3% (154/210) resided in Orange County. Hispanic/Latinx patients residing in census tracts below the median income demonstrated exponential growth (rate = 55.9%, R2 = 0.9742) during the study period. In addition, there was a significant difference for both race-ethnic (p < 0.001) and income bracket (p = 0.001) distributions prior to and after California’s shelter-in-place. In addition, the percentage of individuals residing in neighborhoods with denser households (p = 0.046), lower levels of college graduation (p < 0.001), health insurance coverage (p = 0.01), and ability to work from home (p < 0.001) significantly increased over the same timeframe.Conclusions and RelevanceOur study examines the race-ethnic disparities in Orange County, CA, and highlights vulnerable populations that are at increased risk for contracting COVID-19. Our descriptive case series illustrates that we also need to consider socioeconomic factors, which ultimately set the stage for biological and social disparities.

BackgroundPopulation-based studies show there is a high prevalence of chronic kidney disease (CKD) patients suffering from chronic pain. While opiates are frequently prescribed in non-dialysis-dependent CKD (NDD-CKD) patients, there may be toxic accumulation of metabolites, particularly among those progressing to end-stage renal disease (ESRD). We examined the association of opiate versus other analgesic use during the pre-ESRD period with post-ESRD mortality among NDD-CKD patients transitioning to dialysis.MethodsWe examined a national cohort of US Veterans with NDD-CKD who transitioned to dialysis over 2007-14. Among patients who received ≥1 prescription(s) in the Veterans Affairs (VA) Healthcare System within 1 year of transitioning to dialysis, we examined associations of pre-ESRD analgesic status, defined as opiate, gabapentin/pregabalin, other non-opiate analgesic, versus no analgesic use, with post-ESRD mortality using multivariable Cox models.ResultsAmong 57,764 patients who met eligibility criteria, pre-ESRD opiate and gabapentin/pregabalin use were each associated with higher post-ESRD mortality (ref: no analgesic use), whereas non-opiate analgesic use was not associated with higher mortality in expanded case-mix analyses: HRs (95% CIs) 1.07 (1.05-1.10), 1.07 (1.01-1.13), and 1.00 (0.94-1.06), respectively. In secondary analyses, increasing frequency of opiate prescriptions exceeding 1 opiate prescription in the 1-year pre-ESRD period was associated with incrementally higher post-ESRD mortality (ref: no analgesic use).ConclusionsIn NDD-CKD patients transitioning to dialysis, pre-ESRD opiate and gabapentin/pregabalin use were associated with higher post-ESRD mortality, whereas non-opiate analgesic use was not associated with death. There was a graded association between increasing frequency of pre-ESRD opiate use and incrementally higher mortality.

Novel coronavirus disease 2019 (COVID-19) is a highly infectious, rapidly spreading viral disease with an alarming case fatality rate up to 5%. The risk factors for severe presentations are concentrated in patients with chronic kidney disease, particularly patients with end-stage renal disease (ESRD) who are dialysis dependent. We report the first US case of a 56-year-old nondiabetic male with ESRD secondary to IgA nephropathy undergoing thrice-weekly maintenance hemodialysis for 3 years, who developed COVID-19 infection. He has hypertension controlled with angiotensin receptor blocker losartan 100 mg/day and coronary artery disease status-post stent placement. During the first 5 days of his febrile disease, he presented to an urgent care, 3 emergency rooms, 1 cardiology clinic, and 2 dialysis centers in California and Utah. During this interval, he reported nausea, vomiting, diarrhea, and low-grade fevers but was not suspected of COVID-19 infection until he developed respiratory symptoms and was admitted to the hospital. Imaging studies upon admission were consistent with bilateral interstitial pneumonia. He was placed in droplet-eye precautions while awaiting COVID-19 test results. Within the first 24 h, he deteriorated quickly and developed acute respiratory distress syndrome (ARDS), requiring intubation and increasing respiratory support. Losartan was withheld due to hypotension and septic shock. COVID-19 was reported positive on hospital day 3. He remained in critical condition being treated with hydroxychloroquine and tocilizumab in addition to the standard medical management for septic shock and ARDS. Our case is unique in its atypical initial presentation and highlights the importance of early testing.

ObjectiveTo assess the impact of a newly developed Central-Line Insertion Site Assessment (CLISA) score on the incidence of local inflammation or infection for CLABSI prevention.DesignA pre- and postintervention, quasi-experimental quality improvement study.Setting and participantsAdult inpatients with central venous catheters (CVCs) hospitalized in an intensive care unit or oncology ward at a large academic medical center.MethodsWe evaluated CLISA score impact on insertion site inflammation and infection (CLISA score of 2 or 3) incidence in the baseline period (June 2014-January 2015) and the intervention period (April 2015-October 2017) using interrupted times series and generalized linear mixed-effects multivariable analyses. These were run separately for days-to-line removal from identification of a CLISA score of 2 or 3. CLISA score interrater reliability and photo quiz results were evaluated.ResultsAmong 6,957 CVCs assessed 40,846 times, percentage of lines with CLISA score of 2 or 3 in the baseline and intervention periods decreased by 78.2% (from 22.0% to 4.7%), with a significant immediate decrease in the time-series analysis (P < .001). According to the multivariable regression, the intervention was associated with lower percentage of lines with a CLISA score of 2 or 3, after adjusting for age, gender, CVC body location, and hospital unit (odds ratio, 0.15; 95% confidence interval, 0.06-0.34; P < .001). According to the multivariate regression, days to removal of lines with CLISA score of 2 or 3 was 3.19 days faster after the intervention (P < .001). Also, line dwell time decreased 37.1% from a mean of 14 days (standard deviation [SD], 10.6) to 8.8 days (SD, 9.0) (P < .001). Device utilization ratios decreased 9% from 0.64 (SD, 0.08) to 0.58 (SD, 0.06) (P = .039).ConclusionsThe CLISA score creates a common language for assessing line infection risk and successfully promotes high compliance with best practices in timely line removal.

ObjectiveTo assess the impact of a newly developed Central-Line Insertion Site Assessment (CLISA) score on the incidence of local inflammation or infection for CLABSI prevention.DesignA pre- and postintervention, quasi-experimental quality improvement study.Setting and participantsAdult inpatients with central venous catheters (CVCs) hospitalized in an intensive care unit or oncology ward at a large academic medical center.MethodsWe evaluated CLISA score impact on insertion site inflammation and infection (CLISA score of 2 or 3) incidence in the baseline period (June 2014-January 2015) and the intervention period (April 2015-October 2017) using interrupted times series and generalized linear mixed-effects multivariable analyses. These were run separately for days-to-line removal from identification of a CLISA score of 2 or 3. CLISA score interrater reliability and photo quiz results were evaluated.ResultsAmong 6,957 CVCs assessed 40,846 times, percentage of lines with CLISA score of 2 or 3 in the baseline and intervention periods decreased by 78.2% (from 22.0% to 4.7%), with a significant immediate decrease in the time-series analysis (P < .001). According to the multivariable regression, the intervention was associated with lower percentage of lines with a CLISA score of 2 or 3, after adjusting for age, gender, CVC body location, and hospital unit (odds ratio, 0.15; 95% confidence interval, 0.06-0.34; P < .001). According to the multivariate regression, days to removal of lines with CLISA score of 2 or 3 was 3.19 days faster after the intervention (P < .001). Also, line dwell time decreased 37.1% from a mean of 14 days (standard deviation [SD], 10.6) to 8.8 days (SD, 9.0) (P < .001). Device utilization ratios decreased 9% from 0.64 (SD, 0.08) to 0.58 (SD, 0.06) (P = .039).ConclusionsThe CLISA score creates a common language for assessing line infection risk and successfully promotes high compliance with best practices in timely line removal.

BackgroundThe rapid spread of coronavirus disease 2019 (COVID-19) revealed significant constraints in critical care capacity. In anticipation of subsequent waves, reliable prediction of disease severity is essential for critical care capacity management and may enable earlier targeted interventions to improve patient outcomes. The purpose of this study is to develop and externally validate a prognostic model/clinical tool for predicting COVID-19 critical disease at presentation to medical care.MethodsThis is a retrospective study of a prognostic model for the prediction of COVID-19 critical disease where critical disease was defined as ICU admission, ventilation, and/or death. The derivation cohort was used to develop a multivariable logistic regression model. Covariates included patient comorbidities, presenting vital signs, and laboratory values. Model performance was assessed on the validation cohort by concordance statistics. The model was developed with consecutive patients with COVID-19 who presented to University of California Irvine Medical Center in Orange County, California. External validation was performed with a random sample of patients with COVID-19 at Emory Healthcare in Atlanta, Georgia.ResultsOf a total 3208 patients tested in the derivation cohort, 9% (299/3028) were positive for COVID-19. Clinical data including past medical history and presenting laboratory values were available for 29% (87/299) of patients (median age, 48 years [range, 21-88 years]; 64% [36/55] male). The most common comorbidities included obesity (37%, 31/87), hypertension (37%, 32/87), and diabetes (24%, 24/87). Critical disease was present in 24% (21/87). After backward stepwise selection, the following factors were associated with greatest increased risk of critical disease: number of comorbidities, body mass index, respiratory rate, white blood cell count, % lymphocytes, serum creatinine, lactate dehydrogenase, high sensitivity troponin I, ferritin, procalcitonin, and C-reactive protein. Of a total of 40 patients in the validation cohort (median age, 60 years [range, 27-88 years]; 55% [22/40] male), critical disease was present in 65% (26/40). Model discrimination in the validation cohort was high (concordance statistic: 0.94, 95% confidence interval 0.87-1.01). A web-based tool was developed to enable clinicians to input patient data and view likelihood of critical disease.Conclusions and relevanceWe present a model which accurately predicted COVID-19 critical disease risk using comorbidities and presenting vital signs and laboratory values, on derivation and validation cohorts from two different institutions. If further validated on additional cohorts of patients, this model/clinical tool may provide useful prognostication of critical care needs.

Novel coronavirus disease 2019 (COVID-19) is a highly infectious, rapidly spreading viral disease with an alarming case fatality rate up to 5%. The risk factors for severe presentations are concentrated in patients with chronic kidney disease, particularly patients with end-stage renal disease (ESRD) who are dialysis dependent. We report the first US case of a 56-year-old nondiabetic male with ESRD secondary to IgA nephropathy undergoing thrice-weekly maintenance hemodialysis for 3 years, who developed COVID-19 infection. He has hypertension controlled with angiotensin receptor blocker losartan 100 mg/day and coronary artery disease status-post stent placement. During the first 5 days of his febrile disease, he presented to an urgent care, 3 emergency rooms, 1 cardiology clinic, and 2 dialysis centers in California and Utah. During this interval, he reported nausea, vomiting, diarrhea, and low-grade fevers but was not suspected of COVID-19 infection until he developed respiratory symptoms and was admitted to the hospital. Imaging studies upon admission were consistent with bilateral interstitial pneumonia. He was placed in droplet-eye precautions while awaiting COVID-19 test results. Within the first 24 h, he deteriorated quickly and developed acute respiratory distress syndrome (ARDS), requiring intubation and increasing respiratory support. Losartan was withheld due to hypotension and septic shock. COVID-19 was reported positive on hospital day 3. He remained in critical condition being treated with hydroxychloroquine and tocilizumab in addition to the standard medical management for septic shock and ARDS. Our case is unique in its atypical initial presentation and highlights the importance of early testing.

Background Recent epidemiological evidence has demonstrated a higher rate of COVID-19 hospitalizations and deaths among minorities. This pattern of race-ethnic disparities emerging throughout the United States raises the question of what social factors may influence spread of a highly transmissible novel coronavirus. The purpose of this study is to describe race-ethnic and socioeconomic disparities associated with COVID-19 in patients in our community in Orange County, California and understand the role of individual-level factors, neighborhood-level factors, and access to care on outcomes. Methods This is a case-series of COVID-19 patients from the University of California, Irvine (UCI) across six-weeks between 3/12/2020 and 4/22/2020. Note, California’s shelter-in-place order began on 3/19/2020. Individual-level factors included race-ethnicity status were recorded. Neighborhood-level factors from census tracts included median household income, mean household size, proportion without a college degree, proportion working from home, and proportion without health insurance were also recorded. Results A total of 210-patients tested were COVID-19 positive, of which 73.3% (154/210) resided in Orange County. Hispanic/Latinx patients residing in census tracts below the median income demonstrated exponential growth (rate = 55.9%, R2 = 0.9742) during the study period. In addition, there was a significant difference for both race-ethnic (p < 0.001) and income bracket (p = 0.001) distributions prior to and after California’s shelter-in-place. In addition, the percentage of individuals residing in neighborhoods with denser households (p = 0.046), lower levels of college graduation (p < 0.001), health insurance coverage (p = 0.01), and ability to work from home (p < 0.001) significantly increased over the same timeframe. Conclusions and Relevance Our study examines the race-ethnic disparities in Orange County, CA, and highlights vulnerable populations that are at increased risk for contracting COVID-19. Our descriptive case series illustrates that we also need to consider socioeconomic factors, which ultimately set the stage for biological and social disparities.

Background The rapid spread of coronavirus disease 2019 (COVID-19) revealed significant constraints in critical care capacity. In anticipation of subsequent waves, reliable prediction of disease severity is essential for critical care capacity management and may enable earlier targeted interventions to improve patient outcomes. The purpose of this study is to develop and externally validate a prognostic model/clinical tool for predicting COVID-19 critical disease at presentation to medical care. Methods This is a retrospective study of a prognostic model for the prediction of COVID-19 critical disease where critical disease was defined as ICU admission, ventilation, and/or death. The derivation cohort was used to develop a multivariable logistic regression model. Covariates included patient comorbidities, presenting vital signs, and laboratory values. Model performance was assessed on the validation cohort by concordance statistics. The model was developed with consecutive patients with COVID-19 who presented to University of California Irvine Medical Center in Orange County, California. External validation was performed with a random sample of patients with COVID-19 at Emory Healthcare in Atlanta, Georgia. Results Of a total 3208 patients tested in the derivation cohort, 9% (299/3028) were positive for COVID-19. Clinical data including past medical history and presenting laboratory values were available for 29% (87/299) of patients (median age, 48 years [range, 21-88 years]; 64% [36/55] male). The most common comorbidities included obesity (37%, 31/87), hypertension (37%, 32/87), and diabetes (24%, 24/87). Critical disease was present in 24% (21/87). After backward stepwise selection, the following factors were associated with greatest increased risk of critical disease: number of comorbidities, body mass index, respiratory rate, white blood cell count, % lymphocytes, serum creatinine, lactate dehydrogenase, high sensitivity troponin I, ferritin, procalcitonin, and C-reactive protein. Of a total of 40 patients in the validation cohort (median age, 60 years [range, 27-88 years]; 55% [22/40] male), critical disease was present in 65% (26/40). Model discrimination in the validation cohort was high (concordance statistic: 0.94, 95% confidence interval 0.87-1.01). A web-based tool was developed to enable clinicians to input patient data and view likelihood of critical disease. Conclusions and Relevance We present a model which accurately predicted COVID-19 critical disease risk using comorbidities and presenting vital signs and laboratory values, on derivation and validation cohorts from two different institutions. If further validated on additional cohorts of patients, this model/clinical tool may provide useful prognostication of critical care needs.

BackgroundThe rapid spread of coronavirus disease 2019 (COVID-19) revealed significant constraints in critical care capacity. In anticipation of subsequent waves, reliable prediction of disease severity is essential for critical care capacity management and may enable earlier targeted interventions to improve patient outcomes. The purpose of this study is to develop and externally validate a prognostic model/clinical tool for predicting COVID-19 critical disease at presentation to medical care.MethodsThis is a retrospective study of a prognostic model for the prediction of COVID-19 critical disease where critical disease was defined as ICU admission, ventilation, and/or death. The derivation cohort was used to develop a multivariable logistic regression model. Covariates included patient comorbidities, presenting vital signs, and laboratory values. Model performance was assessed on the validation cohort by concordance statistics. The model was developed with consecutive patients with COVID-19 who presented to University of California Irvine Medical Center in Orange County, California. External validation was performed with a random sample of patients with COVID-19 at Emory Healthcare in Atlanta, Georgia.ResultsOf a total 3208 patients tested in the derivation cohort, 9% (299/3028) were positive for COVID-19. Clinical data including past medical history and presenting laboratory values were available for 29% (87/299) of patients (median age, 48 years [range, 21-88 years]; 64% [36/55] male). The most common comorbidities included obesity (37%, 31/87), hypertension (37%, 32/87), and diabetes (24%, 24/87). Critical disease was present in 24% (21/87). After backward stepwise selection, the following factors were associated with greatest increased risk of critical disease: number of comorbidities, body mass index, respiratory rate, white blood cell count, % lymphocytes, serum creatinine, lactate dehydrogenase, high sensitivity troponin I, ferritin, procalcitonin, and C-reactive protein. Of a total of 40 patients in the validation cohort (median age, 60 years [range, 27-88 years]; 55% [22/40] male), critical disease was present in 65% (26/40). Model discrimination in the validation cohort was high (concordance statistic: 0.94, 95% confidence interval 0.87-1.01). A web-based tool was developed to enable clinicians to input patient data and view likelihood of critical disease.Conclusions and relevanceWe present a model which accurately predicted COVID-19 critical disease risk using comorbidities and presenting vital signs and laboratory values, on derivation and validation cohorts from two different institutions. If further validated on additional cohorts of patients, this model/clinical tool may provide useful prognostication of critical care needs.

BackgroundReliable, timely-onset, oral treatments with an acceptable safety profile for patients with hyperkalemia are needed. We examined the efficacy and safety of sodium zirconium cyclosilicate (SZC; formerly ZS-9) treatment for ≤ 48 h in patients with baseline serum potassium level ≥ 5.5 mmol/L.MethodsData were pooled from two phase 3 studies (ZS-003 and HARMONIZE) among patients receiving SZC 10 g three times daily. Outcomes included mean and absolute change from baseline, median time to potassium level ≤ 5.5 and ≤ 5.0 mmol/L, and proportion achieving potassium level ≤ 5.5 and ≤ 5.0 mmol/L at 4, 24, and 48 h. Outcomes were stratified by baseline potassium. Safety outcomes were evaluated.ResultsAt baseline, 125 of 170 patients (73.5%) had potassium level 5.5- 6.5 mmol/L. Regardless of baseline potassium, mean potassium decreased at 1 h post-initial dose. By 4 and 48 h, 37.5% and 85.0% of patients achieved potassium level ≤ 5.0 mmol/L, respectively. Median (95% confidence interval) times to potassium level ≤ 5.5 and ≤ 5.0 mmol/L were 2.0 (1.1-2.0) and 21.6 (4.1-22.4) h, respectively. Fifteen patients (8.8%) experienced adverse events; none were serious.ConclusionsSZC 10 g three times daily achieved serum potassium reduction and normokalemia, with a favorable safety profile.Trial registrationClinicalTrials.gov identifiers: ZS-003: NCT01737697 and HARMONIZE: NCT02088073.

BackgroundReliable, timely-onset, oral treatments with an acceptable safety profile for patients with hyperkalemia are needed. We examined the efficacy and safety of sodium zirconium cyclosilicate (SZC; formerly ZS-9) treatment for ≤ 48 h in patients with baseline serum potassium level ≥ 5.5 mmol/L.MethodsData were pooled from two phase 3 studies (ZS-003 and HARMONIZE) among patients receiving SZC 10 g three times daily. Outcomes included mean and absolute change from baseline, median time to potassium level ≤ 5.5 and ≤ 5.0 mmol/L, and proportion achieving potassium level ≤ 5.5 and ≤ 5.0 mmol/L at 4, 24, and 48 h. Outcomes were stratified by baseline potassium. Safety outcomes were evaluated.ResultsAt baseline, 125 of 170 patients (73.5%) had potassium level 5.5- 6.5 mmol/L. Regardless of baseline potassium, mean potassium decreased at 1 h post-initial dose. By 4 and 48 h, 37.5% and 85.0% of patients achieved potassium level ≤ 5.0 mmol/L, respectively. Median (95% confidence interval) times to potassium level ≤ 5.5 and ≤ 5.0 mmol/L were 2.0 (1.1-2.0) and 21.6 (4.1-22.4) h, respectively. Fifteen patients (8.8%) experienced adverse events; none were serious.ConclusionsSZC 10 g three times daily achieved serum potassium reduction and normokalemia, with a favorable safety profile.Trial registrationClinicalTrials.gov identifiers: ZS-003: NCT01737697 and HARMONIZE: NCT02088073.

ObjectiveThe impact of glycemic control in diabetic patients with chronic kidney disease (CKD) who may or may not transition to dialysis remains uncertain, given recent interest in the conservative management of advanced CKD without dialysis therapy, which may benefit from alternative glycemic control strategies.Design and methodsAmong a national cohort of US Veterans, we examined the association of glycemic status, defined by averaged random blood glucose and hemoglobin A1c (HbA1c), with mortality after transitioning to dialysis over 2007-2011 (Transition Cohort) compared with patients in a one-to-one matched cohort of CKD patients with diabetes who did not transition to dialysis (Nontransition Cohort).ResultsAmong 17,121 patients in the Transition Cohort, averaged random glucose ≥200 mg/dL was associated with higher mortality in expanded case-mix analyses (reference: 100-

Rationale & objectiveDiabetic patients with declining kidney function are at heightened risk for hypoglycemia. We sought to determine whether hypoglycemia-related hospitalizations in the interval before dialysis therapy initiation are associated with post-end-stage renal disease (ESRD) mortality among incident patients with ESRD with diabetes.Study designObservational cohort study.Setting & participantsUS veterans from the national Veterans Affairs database with diabetes and chronic kidney disease transitioning to dialysis therapy from October 2007 to September 2011.ExposureHypoglycemia-related hospitalizations during the pre-ESRD period and antidiabetic medication regimens.OutcomeThe outcome of post-ESRD all-cause mortality was evaluated relative to pre-ESRD hypoglycemia. The outcome of pre-ESRD hypoglycemia-related hospitalization was evaluated relative to antidiabetic medication regimens.Analytic approachWe examined whether the occurrence and frequency of pre-ESRD hypoglycemia-related hospitalizations are associated with post-ESRD mortality using Cox regression models adjusted for case-mix covariates. In a subcohort of patients prescribed 0 to 2 oral antidiabetic drugs and/or insulin, we examined the 12 most commonly prescribed antidiabetic medication regimens and risk for pre-ESRD hypoglycemia-related hospitalization using logistic regression models adjusted for case-mix covariates.ResultsAmong 30,156 patients who met eligibility criteria, the occurrence of pre-ESRD hypoglycemia-related hospitalization(s) was associated with higher post-ESRD mortality risk: adjusted HR (aHR), 1.25; 95% CI, 1.17-1.34 (reference group: no hypoglycemia hospitalization). Increasing frequency of hypoglycemia-related hospitalizations was independently associated with incrementally higher mortality risk: aHRs of 1.21 (95% CI, 1.12-1.30), 1.47 (95% CI, 1.19-1.82), and 2.07 (95% CI, 1.46-2.95) for 1, 2, and 3 or more hypoglycemia-related hospitalizations, respectively (reference group: no hypoglycemia hospitalization). Compared with patients who were prescribed neither oral antidiabetic drugs nor insulin, medication regimens that included sulfonylureas and/or insulin were associated with higher risk for hypoglycemia.LimitationsResidual confounding cannot be excluded.ConclusionsAmong incident patients with ESRD with diabetes, a dose-dependent relationship between frequency of pre-ESRD hypoglycemia-related hospitalizations and post-ESRD mortality was observed. Further study of diabetic management strategies that prevent hypoglycemia as patients with chronic kidney disease transition to ESRD are warranted.

Rationale & objectiveDiabetic patients with declining kidney function are at heightened risk for hypoglycemia. We sought to determine whether hypoglycemia-related hospitalizations in the interval before dialysis therapy initiation are associated with post-end-stage renal disease (ESRD) mortality among incident patients with ESRD with diabetes.Study designObservational cohort study.Setting & participantsUS veterans from the national Veterans Affairs database with diabetes and chronic kidney disease transitioning to dialysis therapy from October 2007 to September 2011.ExposureHypoglycemia-related hospitalizations during the pre-ESRD period and antidiabetic medication regimens.OutcomeThe outcome of post-ESRD all-cause mortality was evaluated relative to pre-ESRD hypoglycemia. The outcome of pre-ESRD hypoglycemia-related hospitalization was evaluated relative to antidiabetic medication regimens.Analytic approachWe examined whether the occurrence and frequency of pre-ESRD hypoglycemia-related hospitalizations are associated with post-ESRD mortality using Cox regression models adjusted for case-mix covariates. In a subcohort of patients prescribed 0 to 2 oral antidiabetic drugs and/or insulin, we examined the 12 most commonly prescribed antidiabetic medication regimens and risk for pre-ESRD hypoglycemia-related hospitalization using logistic regression models adjusted for case-mix covariates.ResultsAmong 30,156 patients who met eligibility criteria, the occurrence of pre-ESRD hypoglycemia-related hospitalization(s) was associated with higher post-ESRD mortality risk: adjusted HR (aHR), 1.25; 95% CI, 1.17-1.34 (reference group: no hypoglycemia hospitalization). Increasing frequency of hypoglycemia-related hospitalizations was independently associated with incrementally higher mortality risk: aHRs of 1.21 (95% CI, 1.12-1.30), 1.47 (95% CI, 1.19-1.82), and 2.07 (95% CI, 1.46-2.95) for 1, 2, and 3 or more hypoglycemia-related hospitalizations, respectively (reference group: no hypoglycemia hospitalization). Compared with patients who were prescribed neither oral antidiabetic drugs nor insulin, medication regimens that included sulfonylureas and/or insulin were associated with higher risk for hypoglycemia.LimitationsResidual confounding cannot be excluded.ConclusionsAmong incident patients with ESRD with diabetes, a dose-dependent relationship between frequency of pre-ESRD hypoglycemia-related hospitalizations and post-ESRD mortality was observed. Further study of diabetic management strategies that prevent hypoglycemia as patients with chronic kidney disease transition to ESRD are warranted.

Background and objectivesVeterans with ESKD initiate dialysis under the Veterans Health Administration (VHA), an integrated health system, or are outsourced to non-VHA providers. It is unknown whether outcomes differ according to their dialysis provider at initiation. We sought to evaluate the association between dialysis provider and mortality and hospitalization among United States veterans initiating dialysis.Design, setting, participants, & measurementsAmong 68,727 United States veterans who initiated dialysis in 2007-2014, we examined the association of dialysis provider (VHA versus non-VHA) at initiation with mortality and hospitalization rates in the first 12 months post-initiation. Associations were examined across adjusted models, accounting for demographics and comorbidities.ResultsPatients were 72±11 years, 5% were women, 24% were black, and 10% (n=7584) initiated at VHA dialysis centers. VHA dialysis center patients were younger, more likely to be black, had fewer cardiovascular comorbidities, and lower eGFR at dialysis initiation. VHA provider patients were more likely to be hospitalized in the first 12 months (adjusted incidence rate ratio, 1.10; 95% confidence interval, 1.07 to 1.14), but had lower all-cause mortality risk (adjusted hazard ratio, 0.87; 95% confidence interval, 0.83 to 0.93) in fully adjusted models.ConclusionsVeteran patients initiating dialysis with a VHA dialysis provider appear to have a lower mortality risk but higher hospitalization rates than veterans initiating dialysis at non-VHA dialysis units.

Background and objectivesVeterans with ESKD initiate dialysis under the Veterans Health Administration (VHA), an integrated health system, or are outsourced to non-VHA providers. It is unknown whether outcomes differ according to their dialysis provider at initiation. We sought to evaluate the association between dialysis provider and mortality and hospitalization among United States veterans initiating dialysis.Design, setting, participants, & measurementsAmong 68,727 United States veterans who initiated dialysis in 2007-2014, we examined the association of dialysis provider (VHA versus non-VHA) at initiation with mortality and hospitalization rates in the first 12 months post-initiation. Associations were examined across adjusted models, accounting for demographics and comorbidities.ResultsPatients were 72±11 years, 5% were women, 24% were black, and 10% (n=7584) initiated at VHA dialysis centers. VHA dialysis center patients were younger, more likely to be black, had fewer cardiovascular comorbidities, and lower eGFR at dialysis initiation. VHA provider patients were more likely to be hospitalized in the first 12 months (adjusted incidence rate ratio, 1.10; 95% confidence interval, 1.07 to 1.14), but had lower all-cause mortality risk (adjusted hazard ratio, 0.87; 95% confidence interval, 0.83 to 0.93) in fully adjusted models.ConclusionsVeteran patients initiating dialysis with a VHA dialysis provider appear to have a lower mortality risk but higher hospitalization rates than veterans initiating dialysis at non-VHA dialysis units.

Hyponatremia (HN) occurs commonly in patients with acute heart failure and confers a worse prognosis. Current HN treatment varies widely, with no consensus. This study recorded treatment practices currently used for patients hospitalized with acute heart failure and HN. Data were collected prospectively from 146 US sites on patients hospitalized with acute heart failure and HN (serum sodium concentration [Na+] ≤130 mEq/L) present at admission or developing in the hospital. Baseline variables, HN treatment, and laboratory values were recorded. Of 762 patients, median [Na+] was 126 mEq/L (interquartile range, 7) at baseline and increased to 130 mEq/L at discharge. Fluid restriction was the most commonly prescribed therapy (44%), followed by no specific HN treatment beyond therapy for congestion (23%), isotonic saline (5%), tolvaptan (4%), and hypertonic saline (2%). Median rate of change in [Na+] varied by treatment (0.5 [interquartile range, 1.0] to 2.3 [8.0] mEq/L/d) and median treatment duration ranged from 1 (interquartile range, 1) to 6 (5) days. Fluid restriction and no specific HN treatment resulted in similar changes in [Na+], and were least effective in correcting HN. Few patients (19%) had [Na+] ≥135 mEq/L at discharge. The most commonly used treatment approaches for HN (fluid restriction and no specific treatment) in acute heart failure increased [Na+] minimally, and most patients remained hyponatremic at discharge.

BackgroundSodium disarrays are common in peritoneal dialysis (PD) patients, and may be associated with adverse outcomes in this population. However, few studies of limited sample size have examined the association of serum sodium with mortality in PD patients, with inconsistent results. We hypothesized that both hypo- and hypernatremia are associated with higher death risk in a nationally representative cohort of US PD patients.MethodsWe sought to examine the association of serum sodium over time and mortality among 4687 adult incident PD patients from a large US dialysis organization who underwent one or more serum sodium measurements within the first 3 months of dialysis over January 2007 to December 2011. We examined the association of time-dependent and baseline sodium with all-cause mortality as a proxy of short- and long-term sodium-mortality associations, respectively. Hazard ratios were estimated using Cox models with three adjustment levels: minimally adjusted, case-mix adjusted, and case-mix + laboratory adjusted.ResultsIn time-dependent analyses, sodium levels

BackgroundSodium disarrays are common in peritoneal dialysis (PD) patients, and may be associated with adverse outcomes in this population. However, few studies of limited sample size have examined the association of serum sodium with mortality in PD patients, with inconsistent results. We hypothesized that both hypo- and hypernatremia are associated with higher death risk in a nationally representative cohort of US PD patients.MethodsWe sought to examine the association of serum sodium over time and mortality among 4687 adult incident PD patients from a large US dialysis organization who underwent one or more serum sodium measurements within the first 3 months of dialysis over January 2007 to December 2011. We examined the association of time-dependent and baseline sodium with all-cause mortality as a proxy of short- and long-term sodium-mortality associations, respectively. Hazard ratios were estimated using Cox models with three adjustment levels: minimally adjusted, case-mix adjusted, and case-mix + laboratory adjusted.ResultsIn time-dependent analyses, sodium levels

Obesity, a risk factor for de novo chronic kidney disease (CKD), confers survival advantages in advanced CKD. This so-called obesity paradox is the archetype of the reverse epidemiology of cardiovascular risks, in addition to the lipid, blood pressure, adiponectin, homocysteine, and uric acid paradoxes. These paradoxical phenomena are in sharp contradistinction to the known epidemiology of cardiovascular risks in the general population. In addition to advanced CKD, the obesity paradox has also been observed in heart failure, chronic obstructive lung disease, liver cirrhosis, and metastatic cancer, as well as in the elderly. These are populations in whom protein-energy wasting and inflammation are strong predictors of early death. Both larger muscle mass and higher body fat provide longevity in these patients, whereas thinner body habitus and weight loss are associated with higher mortality. Muscle mass appears to be superior to body fat in conferring an even greater survival. The obesity paradox may be the result of a time discrepancy between competing risk factors, i.e., overnutrition as the long-term killer versus undernutrition as the short-term killer. Hemodynamic stability of obesity, lipoprotein defense against circulating endotoxins, protective cytokine profiles, toxin sequestration of fat mass, and antioxidation of muscle may play important roles. Despite claims that obesity paradox is a statistical fallacy and a result of residual confounding, the consistency of data and other causality clues suggest a high biologic plausibility. Examining the causes and consequences of the obesity paradox may help discover important pathophysiologic mechanisms leading to improved outcomes in patients with CKD.

Obesity, a risk factor for de novo chronic kidney disease (CKD), confers survival advantages in advanced CKD. This so-called obesity paradox is the archetype of the reverse epidemiology of cardiovascular risks, in addition to the lipid, blood pressure, adiponectin, homocysteine, and uric acid paradoxes. These paradoxical phenomena are in sharp contradistinction to the known epidemiology of cardiovascular risks in the general population. In addition to advanced CKD, the obesity paradox has also been observed in heart failure, chronic obstructive lung disease, liver cirrhosis, and metastatic cancer, as well as in the elderly. These are populations in whom protein-energy wasting and inflammation are strong predictors of early death. Both larger muscle mass and higher body fat provide longevity in these patients, whereas thinner body habitus and weight loss are associated with higher mortality. Muscle mass appears to be superior to body fat in conferring an even greater survival. The obesity paradox may be the result of a time discrepancy between competing risk factors, i.e., overnutrition as the long-term killer versus undernutrition as the short-term killer. Hemodynamic stability of obesity, lipoprotein defense against circulating endotoxins, protective cytokine profiles, toxin sequestration of fat mass, and antioxidation of muscle may play important roles. Despite claims that obesity paradox is a statistical fallacy and a result of residual confounding, the consistency of data and other causality clues suggest a high biologic plausibility. Examining the causes and consequences of the obesity paradox may help discover important pathophysiologic mechanisms leading to improved outcomes in patients with CKD.

BackgroundImproper use of bronchodilators is associated with poor disease control, nonadherence to long-term therapy, and poor clinical outcomes. Our current understanding of factors associated with correct inhaler use and adherence is limited. We measured physician-and patient-reported confidence in device usage and associations with treatment adherence and COPD-related health status.MethodsThis was an analysis of a US observational, point-in-time survey of physicians and patients. Physicians who met study eligibility criteria completed surveys for 5 consecutive, eligible patients who were then invited to respond to questionnaires. We assessed patient demographics, type of prescribed inhaler device(s), device training, COPD severity, comorbidities, physician-and patient self-reported confidence in device usage, treatment adherence, and health status.ResultsCompleted questionnaires for 373 patients were provided by 134 physicians. Complete confidence in device usage was observed for 22% and 17% of patients as reported by patients and physicians, respectively. Greater confidence was associated with higher self-reported adherence to inhaler usage. Physicians were more likely than patients to report lower levels of patient confidence in device usage. High physician- and patient-reported confidence were associated with more favorable health status. Predictors of confidence in device usage included fewer comorbidities, no depression, and higher education levels.ConclusionLow confidence in inhaler usage was associated with lower adherence and poor COPD-related health status. Choice of inhaler device tailored to patients' ability to use specific devices and ongoing education to support optimal inhaler usage may improve patient confidence and enhance both adherence and health status.

BackgroundMaintenance hemodialysis is typically prescribed thrice weekly irrespective of a patient's residual kidney function (RKF). We hypothesized that a less frequent schedule at hemodialysis therapy initiation is associated with greater preservation of RKF without compromising survival among patients with substantial RKF.Study designA longitudinal cohort.Setting & participants23,645 patients who initiated maintenance hemodialysis therapy in a large dialysis organization in the United States (January 2007 to December 2010), had available RKF data during the first 91 days (or quarter) of dialysis, and survived the first year.PredictorIncremental (routine twice weekly for >6 continuous weeks during the first 91 days upon transition to dialysis) versus conventional (thrice weekly) hemodialysis regimens during the same time.OutcomesChanges in renal urea clearance and urine volume during 1 year after the first quarter and survival after the first year.ResultsAmong 23,645 included patients, 51% had substantial renal urea clearance (≥3.0mL/min/1.73m(2)) at baseline. Compared with 8,068 patients with conventional hemodialysis regimens matched based on baseline renal urea clearance, urine volume, age, sex, diabetes, and central venous catheter use, 351 patients with incremental regimens exhibited 16% (95% CI, 5%-28%) and 15% (95% CI, 2%-30%) more preserved renal urea clearance and urine volume at the second quarter, respectively, which persisted across the following quarters. Incremental regimens showed higher mortality risk in patients with inadequate baseline renal urea clearance (≤3.0mL/min/1.73m(2); HR, 1.61; 95% CI, 1.07-2.44), but not in those with higher baseline renal urea clearance (HR, 0.99; 95% CI, 0.76-1.28). Results were similar in a subgroup defined by baseline urine volume of 600mL/d.LimitationsPotential selection bias and wide CIs.ConclusionsAmong incident hemodialysis patients with substantial RKF, incremental hemodialysis may be a safe treatment regimen and is associated with greater preservation of RKF, whereas higher mortality is observed after the first year of dialysis in those with the lowest RKF. Clinical trials are needed to examine the safety and effectiveness of twice-weekly hemodialysis.

BackgroundMaintenance hemodialysis is typically prescribed thrice weekly irrespective of a patient's residual kidney function (RKF). We hypothesized that a less frequent schedule at hemodialysis therapy initiation is associated with greater preservation of RKF without compromising survival among patients with substantial RKF.Study designA longitudinal cohort.Setting & participants23,645 patients who initiated maintenance hemodialysis therapy in a large dialysis organization in the United States (January 2007 to December 2010), had available RKF data during the first 91 days (or quarter) of dialysis, and survived the first year.PredictorIncremental (routine twice weekly for >6 continuous weeks during the first 91 days upon transition to dialysis) versus conventional (thrice weekly) hemodialysis regimens during the same time.OutcomesChanges in renal urea clearance and urine volume during 1 year after the first quarter and survival after the first year.ResultsAmong 23,645 included patients, 51% had substantial renal urea clearance (≥3.0mL/min/1.73m(2)) at baseline. Compared with 8,068 patients with conventional hemodialysis regimens matched based on baseline renal urea clearance, urine volume, age, sex, diabetes, and central venous catheter use, 351 patients with incremental regimens exhibited 16% (95% CI, 5%-28%) and 15% (95% CI, 2%-30%) more preserved renal urea clearance and urine volume at the second quarter, respectively, which persisted across the following quarters. Incremental regimens showed higher mortality risk in patients with inadequate baseline renal urea clearance (≤3.0mL/min/1.73m(2); HR, 1.61; 95% CI, 1.07-2.44), but not in those with higher baseline renal urea clearance (HR, 0.99; 95% CI, 0.76-1.28). Results were similar in a subgroup defined by baseline urine volume of 600mL/d.LimitationsPotential selection bias and wide CIs.ConclusionsAmong incident hemodialysis patients with substantial RKF, incremental hemodialysis may be a safe treatment regimen and is associated with greater preservation of RKF, whereas higher mortality is observed after the first year of dialysis in those with the lowest RKF. Clinical trials are needed to examine the safety and effectiveness of twice-weekly hemodialysis.

BackgroundA consistent association between low serum sodium measured at a single-point-in-time (baseline sodium) and higher mortality has been observed in hemodialysis patients. We hypothesized that both low and high time-varying sodium levels (sodium levels updated at quarterly intervals as a proxy of short-term exposure) are independently associated with higher death risk in hemodialysis patients.MethodsWe examined the association of baseline and time-varying pre-dialysis serum sodium levels with all-cause mortality among adult incident hemodialysis patients receiving care from a large national dialysis organization during January 2007-December 2011. Hazard ratios were estimated using multivariable Cox models accounting for case-mix+laboratory covariates and incrementally adjusted for inter-dialytic weight gain, blood urea nitrogen and glucose.ResultsAmong 27 180 patients, a total of 7562 deaths were observed during 46 194 patient-years of follow-up. Median (IQR) at-risk time was 1.4 (0.6, 2.5) years. In baseline analyses adjusted for case-mix+laboratory results, sodium levels

BackgroundA consistent association between low serum sodium measured at a single-point-in-time (baseline sodium) and higher mortality has been observed in hemodialysis patients. We hypothesized that both low and high time-varying sodium levels (sodium levels updated at quarterly intervals as a proxy of short-term exposure) are independently associated with higher death risk in hemodialysis patients.MethodsWe examined the association of baseline and time-varying pre-dialysis serum sodium levels with all-cause mortality among adult incident hemodialysis patients receiving care from a large national dialysis organization during January 2007-December 2011. Hazard ratios were estimated using multivariable Cox models accounting for case-mix+laboratory covariates and incrementally adjusted for inter-dialytic weight gain, blood urea nitrogen and glucose.ResultsAmong 27 180 patients, a total of 7562 deaths were observed during 46 194 patient-years of follow-up. Median (IQR) at-risk time was 1.4 (0.6, 2.5) years. In baseline analyses adjusted for case-mix+laboratory results, sodium levels

BackgroundCardiorenal syndrome (CRS) encompasses conditions in which cardiac and renal disorders co-exist and are pathophysiologically related. The newest classification of CRS into seven etiologically and clinically distinct types for direct patient management purposes includes hemodynamic, uremic, vascular, neurohumoral, anemia- and/or iron metabolism-related, mineral metabolism-related and protein-energy wasting-related CRS. This classification also emphasizes the pathophysiologic pathways. The leading CRS category remains hemodynamic CRS, which is the most commonly encountered type in patient care settings and in which acute or chronic heart failure leads to renal impairment.SummaryThis review focuses on selected therapeutic strategies for the clinical management of hemodynamic CRS. This is often characterized by an exceptionally high ratio of serum urea to creatinine concentrations. Loop diuretics, positive inotropic agents including dopamine and dobutamine, vasopressin antagonists including vasopressin receptor antagonists such as tolvaptan, nesiritide and angiotensin-neprilysin inhibitors are among the pharmacologic agents used. Additional therapies include ultrafiltration (UF) via hemofiltration or dialysis. The beneficial versus unfavorable effects of these therapies on cardiac decongestion versus renal blood flow may act in opposite directions. Some of the most interesting options for the outpatient setting that deserve revisiting include portable continuous dobutamine infusion, peritoneal dialysis and outpatient UF via hemodialysis or hemofiltration.Key messagesThe new clinically oriented CRS classification system is helpful in identifying therapeutic targets and offers a systematic approach to an optimal management algorithm with better understanding of etiologies. Most interventions including UF have not shown a favorable impact on outcomes. Outpatient portable dobutamine infusion is underutilized and not well studied. Revisiting traditional and novel strategies for outpatient management of CRS warrants clinical trials.

BackgroundCardiorenal syndrome (CRS) encompasses conditions in which cardiac and renal disorders co-exist and are pathophysiologically related. The newest classification of CRS into seven etiologically and clinically distinct types for direct patient management purposes includes hemodynamic, uremic, vascular, neurohumoral, anemia- and/or iron metabolism-related, mineral metabolism-related and protein-energy wasting-related CRS. This classification also emphasizes the pathophysiologic pathways. The leading CRS category remains hemodynamic CRS, which is the most commonly encountered type in patient care settings and in which acute or chronic heart failure leads to renal impairment.SummaryThis review focuses on selected therapeutic strategies for the clinical management of hemodynamic CRS. This is often characterized by an exceptionally high ratio of serum urea to creatinine concentrations. Loop diuretics, positive inotropic agents including dopamine and dobutamine, vasopressin antagonists including vasopressin receptor antagonists such as tolvaptan, nesiritide and angiotensin-neprilysin inhibitors are among the pharmacologic agents used. Additional therapies include ultrafiltration (UF) via hemofiltration or dialysis. The beneficial versus unfavorable effects of these therapies on cardiac decongestion versus renal blood flow may act in opposite directions. Some of the most interesting options for the outpatient setting that deserve revisiting include portable continuous dobutamine infusion, peritoneal dialysis and outpatient UF via hemodialysis or hemofiltration.Key messagesThe new clinically oriented CRS classification system is helpful in identifying therapeutic targets and offers a systematic approach to an optimal management algorithm with better understanding of etiologies. Most interventions including UF have not shown a favorable impact on outcomes. Outpatient portable dobutamine infusion is underutilized and not well studied. Revisiting traditional and novel strategies for outpatient management of CRS warrants clinical trials.

Background: Oral anticoagulation treatment (OAT) such as warfarin therapy is recommended for older adults with atrial fibrillation, heart failure, or who are at risk for venous thromboembolism. Despite its proven benefits, older adults report both dissatisfaction with OAT and reduced quality of life that can potentially lead to low adherence to OAT and decreased treatment efficacy. Objective: To test the feasibility of Mobile Applications for Seniors to enhance Safe anticoagulation therapy (MASS), a mobile-based health technology intervention designed to promote independence and self-care. Methods: This pilot study used a single-arm experimental pre-post design to test the feasibility of a 3-month intervention using MASS in 18 older adults (male: n = 14; White: n = 9; Hispanic: n = 7; Other: n = 2; M age = 67). MASS was available in English or Spanish. Participants completed surveys about their OAT knowledge, attitudes, quality of life with OAT, and adherence at baseline and at a 3-month follow-up. Satisfaction with the MASS intervention was also assessed at follow-up. Results: Anticoagulation knowledge significantly improved from baseline to follow-up (Mbase = 12.5 ± 5.51, Mfollow-up = 14.78 ± 3.93, p = .007). Other outcomes were not different, pre- and post-tests. Participants reported they were generally satisfied with MASS, its ease of use and its usefulness. Conclusion: The results showed use of MASS improved older adults' knowledge of OAT. Using mHealth apps may enhance self-care among older adults with chronic conditions who are also taking oral anticoagulants.

Background: Oral anticoagulation treatment (OAT) such as warfarin therapy is recommended for older adults with atrial fibrillation, heart failure, or who are at risk for venous thromboembolism. Despite its proven benefits, older adults report both dissatisfaction with OAT and reduced quality of life that can potentially lead to low adherence to OAT and decreased treatment efficacy. Objective: To test the feasibility of Mobile Applications for Seniors to enhance Safe anticoagulation therapy (MASS), a mobile-based health technology intervention designed to promote independence and self-care. Methods: This pilot study used a single-arm experimental pre-post design to test the feasibility of a 3-month intervention using MASS in 18 older adults (male: n = 14; White: n = 9; Hispanic: n = 7; Other: n = 2; M age = 67). MASS was available in English or Spanish. Participants completed surveys about their OAT knowledge, attitudes, quality of life with OAT, and adherence at baseline and at a 3-month follow-up. Satisfaction with the MASS intervention was also assessed at follow-up. Results: Anticoagulation knowledge significantly improved from baseline to follow-up (Mbase = 12.5 ± 5.51, Mfollow-up = 14.78 ± 3.93, p = .007). Other outcomes were not different, pre- and post-tests. Participants reported they were generally satisfied with MASS, its ease of use and its usefulness. Conclusion: The results showed use of MASS improved older adults' knowledge of OAT. Using mHealth apps may enhance self-care among older adults with chronic conditions who are also taking oral anticoagulants.

Current management practices for hyponatremia (HN) are incompletely understood. The HN Registry has recorded diagnostic measures, utilization, efficacy, and outcomes of therapy for eu- or hypervolemic HN. To better understand current practices, we analyzed data from 3087 adjudicated adult patients in the registry with serum sodium concentration of 130 mEq/l or less from 225 sites in the United States and European Union. Common initial monotherapy treatments were fluid restriction (35%), administration of isotonic (15%) or hypertonic saline (2%), and tolvaptan (5%); 17% received no active agent. Median (interquartile range) mEq/l serum sodium increases during the first day were as follows: no treatment, 1.0 (0.0-4.0); fluid restriction, 2.0 (0.0-4.0); isotonic saline, 3.0 (0.0-5.0); hypertonic saline, 5.0 (1.0-9.0); and tolvaptan, 4.0 (2.0-9.0). Adjusting for initial serum sodium concentration with logistic regression, the relative likelihoods for correction by 5 mEq/l or more (referent, fluid restriction) were 1.60 for hypertonic saline and 2.55 for tolvaptan. At discharge, serum sodium concentration was under 135 mEq/l in 78% of patients and 130 mEq/l or less in 49%. Overly rapid correction occurred in 7.9%. Thus, initial HN treatment often uses maneuvers of limited efficacy. Despite an association with poor outcomes and availability of effective therapy, most patients with HN are discharged from hospital still hyponatremic. Studies to assess short- and long-term benefits of correction of HN with effective therapies are needed.

Current management practices for hyponatremia (HN) are incompletely understood. The HN Registry has recorded diagnostic measures, utilization, efficacy, and outcomes of therapy for eu- or hypervolemic HN. To better understand current practices, we analyzed data from 3087 adjudicated adult patients in the registry with serum sodium concentration of 130 mEq/l or less from 225 sites in the United States and European Union. Common initial monotherapy treatments were fluid restriction (35%), administration of isotonic (15%) or hypertonic saline (2%), and tolvaptan (5%); 17% received no active agent. Median (interquartile range) mEq/l serum sodium increases during the first day were as follows: no treatment, 1.0 (0.0-4.0); fluid restriction, 2.0 (0.0-4.0); isotonic saline, 3.0 (0.0-5.0); hypertonic saline, 5.0 (1.0-9.0); and tolvaptan, 4.0 (2.0-9.0). Adjusting for initial serum sodium concentration with logistic regression, the relative likelihoods for correction by 5 mEq/l or more (referent, fluid restriction) were 1.60 for hypertonic saline and 2.55 for tolvaptan. At discharge, serum sodium concentration was under 135 mEq/l in 78% of patients and 130 mEq/l or less in 49%. Overly rapid correction occurred in 7.9%. Thus, initial HN treatment often uses maneuvers of limited efficacy. Despite an association with poor outcomes and availability of effective therapy, most patients with HN are discharged from hospital still hyponatremic. Studies to assess short- and long-term benefits of correction of HN with effective therapies are needed.

BackgroundFew data exist related to the impact of roflumilast on health care utilization. This retrospective study estimated 30-day hospital readmission rates between patients who did and did not use roflumilast among those with COPD hospitalizations.MethodsData were from MarketScan, a large US commercial health insurance claims database. Patients aged ≥40 years with at least one hospitalization for COPD between 2010 and 2011 were included. The roflumilast group included patients who used roflumilast within 14 days after the first hospitalization (index), while the comparison group (non-roflumilast) included patients who did not use roflumilast during the study period. Continuous enrollment for at least 6 months before and 30 days after the index date was required. The 30-day hospitalization rate was calculated after the index hospitalization. Conditional logistic regression with propensity score 1:3 matching was employed to assess the difference in 30-day hospital readmission rates between the roflumilast and non-roflumilast groups, adjusting for baseline characteristics, comorbidity, health care utilization, and COPD medication use within 14 days after the index date.ResultsA total of 15,755 COPD patients met the selection criteria, ie, 366 (2.3%) in the roflumilast group and 15,389 (97.7%) in the non-roflumilast group. The mean (± standard deviation) age was 71±12.5 years and 52% were female. After propensity score matching, all-cause 30-day hospitalization rates were 6.9% and 11.1% in the roflumilast and non-roflumilast groups, respectively. COPD-related 30-day hospitalization rates were 6.3% and 9.2% in the roflumilast and non-roflumilast groups, respectively. Conditional logistic regression identified a significantly lower likelihood of all-cause 30-day readmission (odds ratio 0.59, 95% confidence interval 0.37-0.93, P=0.023) for roflumilast patients relative to non-roflumilast patients.ConclusionThis study showed, in a real-world setting, that use of roflumilast was associated with a lower rate of hospital readmission within 30 days among patients hospitalized for COPD.

BackgroundFew data exist related to the impact of roflumilast on health care utilization. This retrospective study estimated 30-day hospital readmission rates between patients who did and did not use roflumilast among those with COPD hospitalizations.MethodsData were from MarketScan, a large US commercial health insurance claims database. Patients aged ≥40 years with at least one hospitalization for COPD between 2010 and 2011 were included. The roflumilast group included patients who used roflumilast within 14 days after the first hospitalization (index), while the comparison group (non-roflumilast) included patients who did not use roflumilast during the study period. Continuous enrollment for at least 6 months before and 30 days after the index date was required. The 30-day hospitalization rate was calculated after the index hospitalization. Conditional logistic regression with propensity score 1:3 matching was employed to assess the difference in 30-day hospital readmission rates between the roflumilast and non-roflumilast groups, adjusting for baseline characteristics, comorbidity, health care utilization, and COPD medication use within 14 days after the index date.ResultsA total of 15,755 COPD patients met the selection criteria, ie, 366 (2.3%) in the roflumilast group and 15,389 (97.7%) in the non-roflumilast group. The mean (± standard deviation) age was 71±12.5 years and 52% were female. After propensity score matching, all-cause 30-day hospitalization rates were 6.9% and 11.1% in the roflumilast and non-roflumilast groups, respectively. COPD-related 30-day hospitalization rates were 6.3% and 9.2% in the roflumilast and non-roflumilast groups, respectively. Conditional logistic regression identified a significantly lower likelihood of all-cause 30-day readmission (odds ratio 0.59, 95% confidence interval 0.37-0.93, P=0.023) for roflumilast patients relative to non-roflumilast patients.ConclusionThis study showed, in a real-world setting, that use of roflumilast was associated with a lower rate of hospital readmission within 30 days among patients hospitalized for COPD.