Correlates of Spontaneous Blood Pressure Reduction Following Severe Inpatient Hypertension Development.

BACKGROUND: Severe hypertension (sHTN) is prevalent in 10% of hospitalized patients and treatment guidelines are lacking. As such, patients who develop sHTN might unnecessarily receive antihypertensive medications which could lead to worse outcomes. Our goal was to investigate correlates of spontaneous blood pressure (BP) reduction to help guide future treatment decisions and avoid harm associated with aggressive BP treatment. METHODS: This is a retrospective cohort study of hospitalized adults between 2016 and 2020 who developed sHTN, SBP >180 or DBP >110 mm Hg, after admission. Spontaneous BP reduction was defined as a SBP <160 and a DBP <100 mm Hg achieved within 3 h of sHTN in the absence of antihypertensive therapy. Multivariable logistic regression was used to identify correlates of spontaneous BP reduction. RESULTS: Of the 12,825 patients who developed sHTN, 44.2% had spontaneous BP reduction. After adjustment, we found that patients most likely to experience a BP drop received steroids before onset of sHTN (Odds ratio [OR]: 1.3 [1.09, 1.56]), had higher potassium levels on admission (OR: 1.2 [1.09, 1.24]) and were more likely to have a history of chronic pulmonary disease (OR: 1.1 [1.01, 1.18]) or cardiac arrythmia (OR: 1.1 [1.01, 1.18]). While numerically different, these differences were not clinically relevant. CONCLUSIONS: Our findings indicate that almost half the patients who develop sHTN have spontaneous BP reduction. Conventional clinical and demographic characteristics were not strong predictors of spontaneous BP reduction following sHTN development. More research is needed to confirm our findings and help guide treatment of sHTN.

Electronic health record alerts for management of heart failure with reduced ejection fraction in hospitalized patients: the PROMPT-AHF trial.

BACKGROUND AND AIMS: Patients hospitalized for acute heart failure (AHF) continue to be discharged on an inadequate number of guideline-directed medical therapies (GDMT) despite evidence that inpatient initiation is beneficial. This study aimed to examine whether a tailored electronic health record (EHR) alert increased rates of GDMT prescription at discharge in eligible patients hospitalized for AHF. METHODS: Pragmatic trial of messaging to providers about treatment of acute heart failure (PROMPT-AHF) was a pragmatic, multicenter, EHR-based, and randomized clinical trial. Patients were automatically enrolled 48 h after admission if they met pre-specified criteria for an AHF hospitalization. Providers of patients in the intervention arm received an alert during order entry with relevant patient characteristics along with individualized GDMT recommendations with links to an order set. The primary outcome was an increase in the number of GDMT prescriptions at discharge. RESULTS: Thousand and twelve patients were enrolled between May 2021 and November 2022. The median age was 74 years; 26% were female, and 24% were Black. At the time of the alert, 85% of patients were on ß-blockers, 55% on angiotensin-converting enzyme inhibitor/angiotensin receptor blocker/angiotensin receptor-neprilysin inhibitor, 20% on mineralocorticoid receptor antagonist (MRA) and 17% on sodium-glucose cotransporter 2 inhibitor. The primary outcome occurred in 34% of both the alert and no alert groups [adjusted risk ratio (RR): 0.95 (0.81, 1.12), P = .99]. Patients randomized to the alert arm were more likely to have an increase in MRA [adjusted RR: 1.54 (1.10, 2.16), P = .01]. At the time of discharge, 11.2% of patients were on all four pillars of GDMT. CONCLUSIONS: A real-time, targeted, and tailored EHR-based alert system for AHF did not lead to a higher number of overall GDMT prescriptions at discharge. Further refinement and improvement of such alerts and changes to clinician incentives are needed to overcome barriers to the implementation of GDMT during hospitalizations for AHF. GDMT remains suboptimal in this setting, with only one in nine patients being discharged on a comprehensive evidence-based regimen for heart failure.

Use of Wearable Devices in Individuals With or at Risk for Cardiovascular Disease in the US, 2019 to 2020.

Importance: Wearable devices may be able to improve cardiovascular health, but the current adoption of these devices could be skewed in ways that could exacerbate disparities. Objective: To assess sociodemographic patterns of use of wearable devices among adults with or at risk for cardiovascular disease (CVD) in the US population in 2019 to 2020. Design, Setting, and Participants: This population-based cross-sectional study included a nationally representative sample of the US adults from the Health Information National Trends Survey (HINTS). Data were analyzed from June 1 to November 15, 2022. Exposures: Self-reported CVD (history of heart attack, angina, or congestive heart failure) and CVD risk factors (≥1 risk factor among hypertension, diabetes, obesity, or cigarette smoking). Main Outcomes and Measures: Self-reported access to wearable devices, frequency of use, and willingness to share health data with clinicians (referred to as health care providers in the survey). Results: Of the overall 9303 HINTS participants representing 247.3 million US adults (mean [SD] age, 48.8 [17.9] years; 51% [95% CI, 49%-53%] women), 933 (10.0%) representing 20.3 million US adults had CVD (mean [SD] age, 62.2 [17.0] years; 43% [95% CI, 37%-49%] women), and 5185 (55.7%) representing 134.9 million US adults were at risk for CVD (mean [SD] age, 51.4 [16.9] years; 43% [95% CI, 37%-49%] women). In nationally weighted assessments, an estimated 3.6 million US adults with CVD (18% [95% CI, 14%-23%]) and 34.5 million at risk for CVD (26% [95% CI, 24%-28%]) used wearable devices compared with an estimated 29% (95% CI, 27%-30%) of the overall US adult population. After accounting for differences in demographic characteristics, cardiovascular risk factor profile, and socioeconomic features, older age (odds ratio [OR], 0.35 [95% CI, 0.26-0.48]), lower educational attainment (OR, 0.35 [95% CI, 0.24-0.52]), and lower household income (OR, 0.42 [95% CI, 0.29-0.60]) were independently associated with lower use of wearable devices in US adults at risk for CVD. Among wearable device users, a smaller proportion of adults with CVD reported using wearable devices every day (38% [95% CI, 26%-50%]) compared with overall (49% [95% CI, 45%-53%]) and at-risk (48% [95% CI, 43%-53%]) populations. Among wearable device users, an estimated 83% (95% CI, 70%-92%) of US adults with CVD and 81% (95% CI, 76%-85%) at risk for CVD favored sharing wearable device data with their clinicians to improve care. Conclusions and Relevance: Among individuals with or at risk for CVD, fewer than 1 in 4 use wearable devices, with only half of those reporting consistent daily use. As wearable devices emerge as tools that can improve cardiovascular health, the current use patterns could exacerbate disparities unless there are strategies to ensure equitable adoption.

Pragmatic trial of messaging to providers about treatment of acute heart failure: The PROMPT-AHF trial.

Acute Heart failure (AHF) is among the most frequent causes of hospitalization in the United States, contributing to substantial health care costs, morbidity, and mortality. Inpatient initiation of guideline-directed medical therapy (GDMT) is recommended for patients with heart failure with reduced ejection fraction (HFrEF) to reduce the risk of cardiovascular death or HF hospitalization. However, underutilization of GDMT prior to discharge is pervasive, representing a valuable missed opportunity to optimize evidence-based care. The PRagmatic Trial Of Messaging to Providers about Treatment of Acute Heart Failure tests the effectiveness of an electronic health record embedded clinical decision support system that informs providers during hospital management about indicated but not yet prescribed GDMT for eligible AHF patients with HFrEF. PRagmatic Trial Of Messaging to Providers about Treatment of Acute Heart Failureis an open-label, multicenter, pragmatic randomized controlled trial of 1,012 patients hospitalized with HFrEF. Eligible patients randomized to the intervention group are exposed to a tailored best practice advisory embedded within the electronic health record that alerts providers to prescribe omitted GDMT. The primary outcome is an increase in the proportion of additional GDMT medication classes prescribed at the time of discharge compared to those in the usual care arm.

Generating hard-to-obtain information from easy-to-obtain information: Applications in drug discovery and clinical inference.

Often when biological entities are measured in multiple ways, there are distinct categories of information: some information is easy-to-obtain information (EI) and can be gathered on virtually every subject of interest, while other information is hard-to-obtain information (HI) and can only be gathered on some. We propose building a model to make probabilistic predictions of HI using EI. Our feature mapping GAN (FMGAN), based on the conditional GAN framework, uses an embedding network to process conditions as part of the conditional GAN training to create manifold structure when it is not readily present in the conditions. We experiment on generating RNA sequencing of cell lines perturbed with a drug conditioned on the drug's chemical structure and generating FACS data from clinical monitoring variables on a cohort of COVID-19 patients, effectively describing their immune response in great detail.

Rationale and design of the Kidney Precision Medicine Project.

Chronic kidney disease (CKD) and acute kidney injury (AKI) are common, heterogeneous, and morbid diseases. Mechanistic characterization of CKD and AKI in patients may facilitate a precision-medicine approach to prevention, diagnosis, and treatment. The Kidney Precision Medicine Project aims to ethically and safely obtain kidney biopsies from participants with CKD or AKI, create a reference kidney atlas, and characterize disease subgroups to stratify patients based on molecular features of disease, clinical characteristics, and associated outcomes. An additional aim is to identify critical cells, pathways, and targets for novel therapies and preventive strategies. This project is a multicenter prospective cohort study of adults with CKD or AKI who undergo a protocol kidney biopsy for research purposes. This investigation focuses on kidney diseases that are most prevalent and therefore substantially burden the public health, including CKD attributed to diabetes or hypertension and AKI attributed to ischemic and toxic injuries. Reference kidney tissues (for example, living-donor kidney biopsies) will also be evaluated. Traditional and digital pathology will be combined with transcriptomic, proteomic, and metabolomic analysis of the kidney tissue as well as deep clinical phenotyping for supervised and unsupervised subgroup analysis and systems biology analysis. Participants will be followed prospectively for 10 years to ascertain clinical outcomes. Cell types, locations, and functions will be characterized in health and disease in an open, searchable, online kidney tissue atlas. All data from the Kidney Precision Medicine Project will be made readily available for broad use by scientists, clinicians, and patients.

A Comparison Study of Coronavirus Disease 2019 Outcomes in Hospitalized Kidney Transplant Recipients.

Background: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) can infect any human host, but kidney transplant recipients (KTR) are considered more susceptible on the basis of previous experience with other viral infections. We evaluated rates of hospital complications between SARS-CoV-2-positive KTR and comparator groups. Methods: We extracted data from the electronic health record on patients who were hospitalized with SARS-CoV-2, testing at six hospitals from March 4 through September 9, 2020. We compared outcomes between SARS-CoV-2-positive KTR and controls: SARS-CoV-2-positive non-KTR, SARS-CoV-2-negative KTR, and SARS-CoV-2-negative non-KTR. Results: Of 31,540 inpatients, 3213 tested positive for SARS-CoV-2. There were 32 SARS-CoV-2-positive and 224 SARS-CoV-2-negative KTR. SARS-CoV-2-positive KTR had higher ferritin levels (1412; interquartile range, 748-1749 versus 553; interquartile range, 256-1035; P<0.01) compared with SARS-CoV-2-positive non-KTR. SARS-CoV-2-positive KTR had higher rates of ventilation (34% versus 14%, P<0.01; versus 9%, P<0.01; versus 5%, P<0.01), vasopressor use (41% versus 16%, P<0.01; versus 17%, P<0.01; versus 12%, P<0.01), and AKI (47% versus 15%, P<0.01; versus 23%, P<0.01; versus 10%, P<0.01) compared with SARS-CoV-2-positive non-KTR, SARS-CoV-2-negative KTR, and SARS-CoV-2-negative non-KTR, respectively. SARS-CoV-2-positive KTR continued to have increased odds of ventilation, vasopressor use, and AKI compared with SARS-CoV-2-positive non-KTR independent of Elixhauser score, Black race, and baseline eGFR. Mortality was not significantly different between SARS-CoV-2-positive KTR and non-KTR, but there was a notable trend toward higher mortality in SARS-CoV-2-positive KTR (25% versus 16%, P=0.15, respectively). Conclusions: Hospitalized SARS-CoV-2-positive KTR had a high rate of mortality and hospital complications, such as requiring ventilation, vasopressor use, and AKI. Additionally, they had higher odds of hospital complications compared with SARS-CoV-2-positive non-KTR after adjusting for Elixhauser score, Black race, and baseline eGFR. Future studies with larger sample size of KTR are needed to validate our findings. Podcast: This article contains a podcast at https://dts.podtrac.com/redirect.mp3/www.asn-online.org/media/podcast/K360/2021_03_25_KID0005652020.mp3.

Patient factors associated with SARS-CoV-2 in an admitted emergency department population.

Background: The SARS-CoV-2 (COVID-19) virus has wide community spread. The aim of this study was to describe patient characteristics and to identify factors associated with COVID-19 among emergency department (ED) patients under investigation for COVID-19 who were admitted to the hospital. Methods: This was a retrospective observational study from 8 EDs within a 9-hospital health system. Patients with COVID-19 testing around the time of hospital admission were included. The primary outcome measure was COVID-19 test result. Patient characteristics were described and a multivariable logistic regression model was used to identify factors associated with a positive COVID-19 test. Results: During the study period from March 1, 2020 to April 8, 2020, 2182 admitted patients had a test resulted for COVID-19. Of these patients, 786 (36%) had a positive test result. For COVID-19-positive patients, 63 (8.1%) died during hospitalization. COVID-19-positive patients had lower pulse oximetry (0.91 [95% confidence interval, CI], [0.88-0.94]), higher temperatures (1.36 [1.26-1.47]), and lower leukocyte counts than negative patients (0.78 [0.75-0.82]). Chronic lung disease (odds ratio [OR] 0.68, [0.52-0.90]) and histories of alcohol (0.64 [0.42-0.99]) or substance abuse (0.39 [0.25-0.62]) were less likely to be associated with a positive COVID-19 result. Conclusion: We observed a high percentage of positive results among an admitted ED cohort under investigation for COVID-19. Patient factors may be useful in early differentiation of patients with COVID-19 from similarly presenting respiratory illnesses although no single factor will serve this purpose.

Effect on Survival of Concurrent Hemoconcentration and Increase in Creatinine During Treatment of Acute Decompensated Heart Failure.

Hemoconcentration during the treatment of acute decompensated heart failure is a surrogate for plasma volume reduction and is associated with improved survival, but most definitions only allow for hemoconcentration to be determined retrospectively. An increase in serum creatinine can also be a marker of aggressive decongestion, but in isolation is not specific. Our objective was to determine if combined hemoconcentration and worsening creatinine could better identify patients that were aggressively treated and, as such, may have improved postdischarge outcomes. A total of 4,181 patients hospitalized with acute decompensated heart failure were evaluated. Those who experienced both hemoconcentration and worsening creatinine at any point had a profile consistent with aggressive in-hospital treatment and longer length of stay (p <0.01), higher loop diuretic doses (p <0.001), greater weight (p = 0.001), and net fluid loss (p <0.001) compared with the remainder of the cohort. In isolation, neither worsening creatinine (p = 0.11) nor hemoconcentration (p = 0.36) at any time were associated with improved survival. However, patients who experienced both (21%) had significantly better survival (hazard ratio 0.80, 95% confidence interval 0.69 to 0.94, pinteraction = 0.005). In conclusion, this combination of hemoconcentration and worsening creatinine, which can be determined prospectively during patient care, was associated with in-hospital parameters consistent with aggressive diuresis and improved postdischarge survival.

Development of biomarker combinations for postoperative acute kidney injury via Bayesian model selection in a multicenter cohort study.

BACKGROUND: Acute kidney injury (AKI) is a frequent complication of cardiac surgery. We sought prognostic combinations of postoperative biomarkers measured within 6 h of surgery, potentially in combination with cardiopulmonary bypass time (to account for the degree of insult to the kidney). We used data from a large cohort of patients and adapted methods for developing biomarker combinations to account for the multicenter design of the study. METHODS: The primary endpoint was sustained mild AKI, defined as an increase of 50% or more in serum creatinine over preoperative levels lasting at least 2 days during the hospital stay. Severe AKI (secondary endpoint) was defined as a serum creatinine increase of 100% or more or dialysis during hospitalization. Data were from a cohort of 1219 adults undergoing cardiac surgery at 6 medical centers; among these, 117 developed sustained mild AKI and 60 developed severe AKI. We considered cardiopulmonary bypass time and 22 biomarkers as candidate predictors. We adapted Bayesian model averaging methods to develop center-adjusted combinations for sustained mild AKI by (1) maximizing the posterior model probability and (2) retaining predictors with posterior variable probabilities above 0.5. We used resampling-based methods to avoid optimistic bias in evaluating the biomarker combinations. RESULTS: The maximum posterior model probability combination included plasma N-terminal-pro-B-type natriuretic peptide, plasma heart-type fatty acid binding protein, and change in serum creatinine from before to 0-6 h after surgery; the median probability combination additionally included plasma interleukin-6. The center-adjusted, optimism-corrected AUCs for these combinations were 0.80 (95% CI: 0.78, 0.87) and 0.81 (0.78, 0.87), respectively, for predicting sustained mild AKI, and 0.81 (0.76, 0.90) and 0.83 (0.76, 0.90), respectively, for predicting severe AKI. For these data, the Bayesian model averaging methods yielded combinations with prognostic capacity comparable to that achieved by standard frequentist methods but with more parsimonious models. CONCLUSIONS: Pending external validation, the identified combinations could be used to identify individuals at high risk of AKI immediately after cardiac surgery and could facilitate clinical trials of renoprotective agents.

Group analysis identifies differentially elevated biomarkers with distinct outcomes for advanced acute kidney injury in cardiac surgery.

AIM: To investigate early postoperative biomarkers for risk discrimination of advanced acute kidney injury (AKI). MATERIALS & METHODS: Postoperative plasma biomarkers including NGAL, h-FABP, CK-MB, hsTNT, NT-proBNP, IL-6, IL-10 and VEGF were analyzed using group-based method among 426 patients with AKI after cardiac surgery. RESULTS: Six patient groups with distinct biomarker patterns were identified. Individual biomarker displayed significant difference across the groups. The groups showed better discrimination for advanced AKI than any single biomarker either with or without adjusting for clinical variables. Average concentration of a single biomarker within each group, mortality and risk of a secondary outcome all demonstrated an approximately U-shaped relationship with proportion of advanced AKI within each group. CONCLUSION: The group-based analysis revealed that the order of the patient groups with an increasing likelihood of advanced AKI had a nonlinear relationship with average concentration of an individual biomarker, mortality and risk of other outcomes.

Evaluating biomarkers for prognostic enrichment of clinical trials.

BACKGROUND/AIMS: A potential use of biomarkers is to assist in prognostic enrichment of clinical trials, where only patients at relatively higher risk for an outcome of interest are eligible for the trial. We investigated methods for evaluating biomarkers for prognostic enrichment. METHODS: We identified five key considerations when considering a biomarker and a screening threshold for prognostic enrichment: (1) clinical trial sample size, (2) calendar time to enroll the trial, (3) total patient screening costs and the total per-patient trial costs, (4) generalizability of trial results, and (5) ethical evaluation of trial eligibility criteria. Items (1)-(3) are amenable to quantitative analysis. We developed the Biomarker Prognostic Enrichment Tool for evaluating biomarkers for prognostic enrichment at varying levels of screening stringency. RESULTS: We demonstrate that both modestly prognostic and strongly prognostic biomarkers can improve trial metrics using Biomarker Prognostic Enrichment Tool. Biomarker Prognostic Enrichment Tool is available as a webtool at http://prognosticenrichment.com and as a package for the R statistical computing platform. CONCLUSION: In some clinical settings, even biomarkers with modest prognostic performance can be useful for prognostic enrichment. In addition to the quantitative analysis provided by Biomarker Prognostic Enrichment Tool, investigators must consider the generalizability of trial results and evaluate the ethics of trial eligibility criteria.

Provider acceptance of an automated electronic alert for acute kidney injury.

BACKGROUND: Clinical decision support systems, including electronic alerts, ideally provide immediate and relevant patient-specific information to improve clinical decision-making. Despite the growing capabilities of such alerts in conjunction with an expanding electronic medical record, there is a paucity of information regarding their perceived usefulness. We surveyed healthcare providers' opinions concerning the practicality and efficacy of a specific text-based automated electronic alert for acute kidney injury (AKI) in a single hospital during a randomized trial of AKI alerts. METHODS: Providers who had received at least one electronic AKI alert in the previous 6 months, as part of a separate randomized controlled trial (clinicaltrials.gov #01862419), were asked to complete a survey concerning their opinions about this specific AKI alert system. Individual approval of the alert system was defined by a provider's desire to continue receiving the alert after termination of the trial. RESULTS: A total of 98 individuals completed the survey, including 62 physicians, 27 pharmacists and 7 non-physician providers. Sixty-nine percent of responders approved the alert, with no significant difference among the various professions (P = 0.28). Alert approval was strongly correlated with the belief that the alerts improved patient care (P < 0.0001), and negatively correlated with the belief that alerts did not provide novel information (P = 0.0001). With each additional 30 days of trial duration, odds of approval decreased by 20% (3-35%) (P = 0.02). CONCLUSIONS: The alert system was generally well received, although approval waned with time. Approval was correlated with the belief that this type of alert improved patient care. These findings suggest that perceived efficacy is critical to the success of future alert trials.

A trial of in-hospital, electronic alerts for acute kidney injury: design and rationale.

BACKGROUND: Acute kidney injury is common in hospitalized patients, increases morbidity and mortality, and is under-recognized. To improve provider recognition, we previously developed an electronic alert system for acute kidney injury. To test the hypothesis that this electronic acute kidney injury alert could improve patient outcome, we designed a randomized controlled trial to test the effectiveness of this alert in hospitalized patients. The study design presented several methodologic, ethical, and statistical challenges. PURPOSE: To highlight the challenges faced and the solutions employed in the design and implementation of a clinical trial to determine whether the provision of an early electronic alert for acute kidney injury would improve outcomes in hospitalized patients. Challenges included how to randomize the delivery of the alert system and the ethical framework for waiving informed consent. Other methodologic challenges included the selection and statistical evaluation of our study outcome, a ranked-composite of a continuous covariate (creatinine) and two dichotomous outcomes (dialysis and death), and the use of the medical record as a source of trial data. METHODS: We have designed a randomized trial to assess the effectiveness of an electronic alert system for acute kidney injury. With broad inclusion criteria, and a waiver of informed consent, we enroll and randomize virtually every patient with acute kidney injury in our hospital. RESULTS: As of 31 March 2014, we have enrolled 2373 patients of 2400 targeted. Pre-alert data demonstrated a strong association between severity of acute kidney injury and inpatient mortality with a range of 6.4% in those with mild, stage 1 acute kidney injury, to 29% among those with stage 3 acute kidney injury (p < 0.001). We judged that informed consent would undermine the scientific validity of the study and present harms that are out of proportion to the very low risk intervention. CONCLUSION: Our study demonstrates the feasibility of designing an ethical randomized controlled trial of an early electronic alert for acute kidney injury without obtaining informed consent from individual participants. Our study outcome may serve as a model for other studies of acute kidney injury, insofar as our paradigm accounts for the effect that early death and dialysis have on assessment of acute kidney injury severity as defined by maximum achieved serum creatinine.

The impact of documentation of severe acute kidney injury on mortality.

AIMS: Modification of the mortality risk associated with acute kidney injury (AKI) necessitates recognition of AKI when it occurs. We sought to determine whether formal documentation of AKI in the medical record, assessed by billing codes for AKI, would be associated with improved clinical outcomes. METHODS: Retrospective cohort study conducted at three hospitals within a single university health system. Adults without severe underlying kidney disease who suffered in-hospital AKI as defined by a doubling of baseline creatinine (n = 5,438) were included. Those whose AKI was formally documented according to discharge billing codes were compared to those without such documentation in terms of 30-day mortality. RESULTS: Formal documentation of AKI occurred in 2,325 patients (43%). Higher baseline creatinine, higher peak creatinine, medical admission status, and higher Sequential Organ Failure Assessment (SOFA) score were strongly associated with documentation of AKI. After adjustment for severity of disease, formal AKI documentation was associated with reduced 30-day mortality - OR 0.81 (0.68 - 0.96, p = 0.02). Patients with formal documentation were more likely to receive a nephrology consultation (31% vs. 6%, p < 0.001) and fluid boluses (64% vs. 45%, p < 0.001), and had a more rapid discontinuation of angiotensin-converting enzyme inhibitor and angiotensin-receptor blocker medications (HR 2.04, CI 1.69 - 2.46, p < 0.001). CONCLUSIONS: Formal documentation of AKI is associated with improved survival after adjustment for illness severity among patients with creatinine-defined AKI.

Predictors of death and dialysis in severe AKI: the UPHS-AKI cohort.

BACKGROUND AND OBJECTIVES: AKI carries a substantial risk of mortality, even after adjustment for comorbidities. Effective risk stratification may lead to more effective therapeutic interventions for high-risk subgroups. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: This study identified adults who suffered severe in-hospital AKI from January 1, 2004 to August 31, 2010 at three hospitals in the University of Pennsylvania Health System (UPHS). Patients were included if baseline creatinine was ≤1.4 mg/dl for men or ≤1.2 mg/dl for women, and serum creatinine doubled during the hospital admission. Cox proportional hazards models predicting death, dialysis, or a combined endpoint of death or dialysis were fit using data from patients admitted to the Hospital of the University of Pennsylvania (n=4263), and validated at the two other UPHS facilities (n=758, n=1098). RESULTS: In adjusted analyses, strong predictors of the combined endpoint included intensive care unit location (versus floor), medical service, liver disease, higher creatinine, greater rate of change in creatinine, and greater number of pressor medications. Higher absolute creatinine concentration was associated with greater use of dialysis, but lower overall mortality in adjusted analyses. Harrell's c-index (95% confidence interval) for the model predicting the combined endpoint was 0.85 (0.84-0.86) in the derivation cohort, and 0.83 (0.80-0.86) and 0.84 (0.82-0.86) in the validation cohorts. CONCLUSIONS: A small group of easily measured clinical factors has good ability to predict mortality and dialysis in severe AKI.