An atlas of healthy and injured cell states and niches in the human kidney.

Understanding kidney disease relies on defining the complexity of cell types and states, their associated molecular profiles and interactions within tissue neighbourhoods1. Here we applied multiple single-cell and single-nucleus assays (>400,000 nuclei or cells) and spatial imaging technologies to a broad spectrum of healthy reference kidneys (45 donors) and diseased kidneys (48 patients). This has provided a high-resolution cellular atlas of 51 main cell types, which include rare and previously undescribed cell populations. The multi-omic approach provides detailed transcriptomic profiles, regulatory factors and spatial localizations spanning the entire kidney. We also define 28 cellular states across nephron segments and interstitium that were altered in kidney injury, encompassing cycling, adaptive (successful or maladaptive repair), transitioning and degenerative states. Molecular signatures permitted the localization of these states within injury neighbourhoods using spatial transcriptomics, while large-scale 3D imaging analysis (around 1.2 million neighbourhoods) provided corresponding linkages to active immune responses. These analyses defined biological pathways that are relevant to injury time-course and niches, including signatures underlying epithelial repair that predicted maladaptive states associated with a decline in kidney function. This integrated multimodal spatial cell atlas of healthy and diseased human kidneys represents a comprehensive benchmark of cellular states, neighbourhoods, outcome-associated signatures and publicly available interactive visualizations.

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.

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.

Angiopoietins as Prognostic Markers for Future Kidney Disease and Heart Failure Events after Acute Kidney Injury.

BACKGROUND: The mechanisms underlying long-term sequelae after AKI remain unclear. Vessel instability, an early response to endothelial injury, may reflect a shared mechanism and early trigger for CKD and heart failure. METHODS: To investigate whether plasma angiopoietins, markers of vessel homeostasis, are associated with CKD progression and heart failure admissions after hospitalization in patients with and without AKI, we conducted a prospective cohort study to analyze the balance between angiopoietin-1 (Angpt-1), which maintains vessel stability, and angiopoietin-2 (Angpt-2), which increases vessel destabilization. Three months after discharge, we evaluated the associations between angiopoietins and development of the primary outcomes of CKD progression and heart failure and the secondary outcome of all-cause mortality 3 months after discharge or later. RESULTS: Median age for the 1503 participants was 65.8 years; 746 (50%) had AKI. Compared with the lowest quartile, the highest quartile of the Angpt-1:Angpt-2 ratio was associated with 72% lower risk of CKD progression (adjusted hazard ratio [aHR], 0.28; 95% confidence interval [CI], 0.15 to 0.51), 94% lower risk of heart failure (aHR, 0.06; 95% CI, 0.02 to 0.15), and 82% lower risk of mortality (aHR, 0.18; 95% CI, 0.09 to 0.35) for those with AKI. Among those without AKI, the highest quartile of Angpt-1:Angpt-2 ratio was associated with 71% lower risk of heart failure (aHR, 0.29; 95% CI, 0.12 to 0.69) and 68% less mortality (aHR, 0.32; 95% CI, 0.15 to 0.68). There were no associations with CKD progression. CONCLUSIONS: A higher Angpt-1:Angpt-2 ratio was strongly associated with less CKD progression, heart failure, and mortality in the setting of AKI.

Electronic Health Record Embedded Strategies for Improving Care of Patients With Heart Failure.

PURPOSE: A majority of clinical decisions use the electronic health record (EHR) and there is an unmet need to use its capability to help providers to make evidence-based decisions that improve care for heart failure patients. These electronic nudges are rooted in the human psychology of decision-making and often target specific cognitive biases. This review outlines the development of novel EHR nudges and specific lessons learned from each experience to inform the development of future interventions. RECENT FINDINGS: There have been several randomized clinical trials examining the impact of EHR alerts on quality of care for heart failure patients. These interventions have targeted both clinicians and patients. There are features of each trial that inform best practices and future directions for EHR nudges. Recent clinical trials have demonstrated that some EHR alerts can improve care for heart failure patients. These trials utilized default options, involved clinicians in the alert design process, provided actionable recommendations, and aimed to minimize disruptions to typical workflow. Alerts aimed at improving care should be examined in a randomized fashion in order to evaluate their impact on clinician satisfaction and patient care.

Structure-activity relationships of 2-pyrimidinecarbohydrazides as utrophin modulators for the potential treatment of Duchenne muscular dystrophy.

A therapeutic approach that holds the potential to treat all Duchenne muscular dystrophy (DMD) patient populations is utrophin modulation. Ezutromid, a first generation utrophin modulator which was later found to act via antagonism of the arylhydrocarbon receptor, progressed to Phase 2 clinical trials. Although interim data showed target engagement and functional improvements, ezutromid ultimately failed to meet its clinical endpoints. We recently described the identification of a new class of hydrazide utrophin modulators which has a different mechanism of action to ezutromid. In this study we report our early optimisation studies on this hydrazide series. The new analogues had significantly improved potency in cell-based assays, increased sp3 character and reduced lipophilicity, which also improved their physicochemical properties. A representative new analogue combining these attributes increased utrophin protein in dystrophic mouse cells showing it can be used as a chemical tool to reveal new insights regarding utrophin upregulation as a strategy for DMD therapeutic intervention.

Subtyping CKD Patients by Consensus Clustering: The Chronic Renal Insufficiency Cohort (CRIC) Study.

BACKGROUND: CKD is a heterogeneous condition with multiple underlying causes, risk factors, and outcomes. Subtyping CKD with multidimensional patient data holds the key to precision medicine. Consensus clustering may reveal CKD subgroups with different risk profiles of adverse outcomes. METHODS: We used unsupervised consensus clustering on 72 baseline characteristics among 2696 participants in the prospective Chronic Renal Insufficiency Cohort (CRIC) study to identify novel CKD subgroups that best represent the data pattern. Calculation of the standardized difference of each parameter used the cutoff of ±0.3 to show subgroup features. CKD subgroup associations were examined with the clinical end points of kidney failure, the composite outcome of cardiovascular diseases, and death. RESULTS: The algorithm revealed three unique CKD subgroups that best represented patients' baseline characteristics. Patients with relatively favorable levels of bone density and cardiac and kidney function markers, with lower prevalence of diabetes and obesity, and who used fewer medications formed cluster 1 (n=1203). Patients with higher prevalence of diabetes and obesity and who used more medications formed cluster 2 (n=1098). Patients with less favorable levels of bone mineral density, poor cardiac and kidney function markers, and inflammation delineated cluster 3 (n=395). These three subgroups, when linked with future clinical end points, were associated with different risks of CKD progression, cardiovascular disease, and death. Furthermore, patient heterogeneity among predefined subgroups with similar baseline kidney function emerged. CONCLUSIONS: Consensus clustering synthesized the patterns of baseline clinical and laboratory measures and revealed distinct CKD subgroups, which were associated with markedly different risks of important clinical outcomes. Further examination of patient subgroups and associated biomarkers may provide next steps toward precision medicine.

Results from the TRIBE-AKI Study found associations between post-operative blood biomarkers and risk of chronic kidney disease after cardiac surgery.

Patients undergoing cardiac surgery are placed under intense physiologic stress. Blood and urine biomarkers measured peri-operatively may help identify patients at higher risk for adverse long-term kidney outcomes.We sought to determine independent associations of various biomarkers with development or progression of chronic kidney disease (CKD) following cardiac surgery. In this sub-study of the prospective cohort -TRIBE-AKI Study, we evaluated 613 adult patients undergoing cardiac surgery in Canada in our primary analysis and tested the association of 40 blood and urinary biomarkers with the primary composite outcome of CKD incidence or progression. In those with baseline estimated glomerular filtration rate (eGFR) over 60 mL/min/1.73m2, we defined CKD incidence as a 25% reduction in eGFR and an eGFR under 60. In those with baseline eGFR under 60 mL/min/1.73m2, we defined CKD progression as a 50% reduction in eGFR or eGFR under 15. Results were evaluated in a replication cohort of 310 patients from one study site in the United States. Over a median follow-up of 5.6 years, 172 patients developed the primary outcome. Each log increase in basic fibroblast growth factor (adjusted hazard ratio 1.52 [95% confidence interval 1.19, 1.93]), Kidney Injury Molecule-1 (1.51 [0.98, 2.32]), N-terminal pro-B-type natriuretic peptide (1.19 [1.01, 1.41]), and tumor necrosis factor receptor 1 (1.75 [1.18, 2.59]) were associated with outcome after adjustment for demographic factors, serum creatinine, and albuminuria. Similar results were noted in the replication cohort. Although there was no interaction by acute kidney injury in continuous analysis, mortality was higher in the no acute kidney injury group by biomarker tertile. Thus, elevated post-operative levels of blood biomarkers following cardiac surgery were independently associated with the development of CKD. These biomarkers can provide additional value in evaluating CKD incidence and progression after cardiac surgery.

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.

Use of Proton Pump Inhibitors Increases Risk of Incident Kidney Stones.

BACKGROUND AND AIMS: Proton pump inhibitors (PPIs) are widely prescribed and have effects on gut ion absorption and urinary ion concentrations. PPIs might therefore protect against or contribute to development of kidney stones. We investigated the association between PPI use and kidney stones. METHODS: We performed a retrospective study using data from the Women's Veteran's Cohort Study, which comprised men and women, from October 1, 1999 through September 30, 2017. We collected data from 465,891 patients on PPI usage over time, demographics, laboratory results, comorbidities, and medication usage. Time-varying Cox proportional hazards and propensity matching analyses determined risk of PPI use and incident development of kidney stones. Use of histamine-2 receptor antagonists (H2RAs) was measured and levothyroxine use was a negative control exposure. RESULTS: PPI use was associated with kidney stones in the unadjusted analysis, with PPI use as a time-varying variable (hazard ratio [HR], 1.74; 95% CI, 1.67-1.82), and persisted in the adjusted analysis (HR, 1.46; CI, 1.38-1.55). The association was maintained in a propensity score-matched subset of PPI users and nonusers (adjusted HR, 1.25; CI 1.19-1.33). Increased dosage of PPI was associated with increased risk of kidney stones (HR, 1.11; CI, 1.09-1.14 for each increase in 30 defined daily doses over a 3-month period). H2RAs were also associated with increased risk (adjusted HR, 1.47; CI 1.31-1.64). We found no association, in adjusted analysis, of levothyroxine use with kidney stones (adjusted HR, 1.06; CI 0.94-1.21). CONCLUSIONS: In a large cohort study of veterans, we found PPI use to be associated with a dose-dependent increase in risk of kidney stones. H2RA use also has an association with risk of kidney stones, so acid suppression might be an involved mechanism. The effect is small and should not change prescribing for most patients.

Acute Kidney Injury in Decompensated Cirrhosis Is Associated With Both Hypo-coagulable and Hyper-coagulable Features.

BACKGROUND AND AIMS: Recent evidence suggests that acute kidney injury (AKI) is the main predictor of postparacentesis bleeding in patients with cirrhosis. To assess the factors responsible for bleeding tendency in AKI, we performed a prospective study comparing all three aspects of hemostasis (platelets, coagulation, and fibrinolysis) in patients with decompensated cirrhosis with and without AKI. APPROACH AND RESULTS: Primary hemostasis assessment included platelet aggregation and secretion (platelet function markers) and von Willebrand factor. Secondary hemostasis assessment included pro-coagulant (factor VIII and factor XIII) and anti-coagulant (protein C, protein S, and antithrombin) factors and thrombin generation. Tertiary hemostasis assessment included fibrinolytic factors and plasmin-antiplasmin complex. Eighty patients with decompensated cirrhosis were recruited (40 each with and without AKI). Severity of cirrhosis and platelet count were comparable between groups. Median serum creatinine was 1.8 mg/dL and 0.8 mg/dL in patients with and without AKI, respectively. At baseline, patients with cirrhosis and AKI had lower platelet aggregation and secretion, indicative of impaired platelet function (increased bleeding tendency), without differences in von Willebrand factor. Regarding coagulation factors, factor VIII was higher, whereas protein C, protein S, and antithrombin were all lower, which, together with increased thrombin generation, indicate hypercoagulability. In contrast, factor XIII was lower in AKI (increased bleeding tendency). Finally, while both hypofibrinolytic and hyperfibrinolytic changes were present in AKI, a higher plasmin-antiplasmin complex indicated a hyperfibrinolytic state. After AKI resolution (n = 23 of 40), platelet function and coagulation improved to levels observed in patients with cirrhosis patients without AKI; however, fibrinolysis remained hyperactivated. CONCLUSIONS: In patients with decompensated cirrhosis, AKI is associated with both hypocoagulable and hypercoagulable features that can potentially increase the risk of both bleeding and thrombosis.

Development and Validation of the Quick COVID-19 Severity Index: A Prognostic Tool for Early Clinical Decompensation.

STUDY OBJECTIVE: The goal of this study is to create a predictive, interpretable model of early hospital respiratory failure among emergency department (ED) patients admitted with coronavirus disease 2019 (COVID-19). METHODS: This was an observational, retrospective, cohort study from a 9-ED health system of admitted adult patients with severe acute respiratory syndrome coronavirus 2 (COVID-19) and an oxygen requirement less than or equal to 6 L/min. We sought to predict respiratory failure within 24 hours of admission as defined by oxygen requirement of greater than 10 L/min by low-flow device, high-flow device, noninvasive or invasive ventilation, or death. Predictive models were compared with the Elixhauser Comorbidity Index, quick Sequential [Sepsis-related] Organ Failure Assessment, and the CURB-65 pneumonia severity score. RESULTS: During the study period, from March 1 to April 27, 2020, 1,792 patients were admitted with COVID-19, 620 (35%) of whom had respiratory failure in the ED. Of the remaining 1,172 admitted patients, 144 (12.3%) met the composite endpoint within the first 24 hours of hospitalization. On the independent test cohort, both a novel bedside scoring system, the quick COVID-19 Severity Index (area under receiver operating characteristic curve mean 0.81 [95% confidence interval {CI} 0.73 to 0.89]), and a machine-learning model, the COVID-19 Severity Index (mean 0.76 [95% CI 0.65 to 0.86]), outperformed the Elixhauser mortality index (mean 0.61 [95% CI 0.51 to 0.70]), CURB-65 (0.50 [95% CI 0.40 to 0.60]), and quick Sequential [Sepsis-related] Organ Failure Assessment (0.59 [95% CI 0.50 to 0.68]). A low quick COVID-19 Severity Index score was associated with a less than 5% risk of respiratory decompensation in the validation cohort. CONCLUSION: A significant proportion of admitted COVID-19 patients progress to respiratory failure within 24 hours of admission. These events are accurately predicted with bedside respiratory examination findings within a simple scoring system.

Characterisation of utrophin modulator SMT C1100 as a non-competitive inhibitor of firefly luciferase.

Firefly luciferase (FLuc) is a powerful tool for molecular and cellular biology, and popular in high-throughput screening and drug discovery. However, FLuc assays have been plagued with positive and negative artefacts due to stabilisation and inhibition by small molecules from a range of chemical classes. Here we disclose Phase II clinical compound SMT C1100 for the treatment of Duchenne muscular dystrophy as an FLuc inhibitor (KD of 0.40 ±â€¯0.15 µM). Enzyme kinetic studies using SMT C1100 and other non-competitive inhibitors including resveratrol and NFκBAI4 identified previously undescribed modes of inhibition with respect to FLuc's luciferyl adenylate intermediate. Employing a photoaffinity strategy to identify SMT C1100's binding site, a photolabelled SMT C1100 probe instead underwent FLuc-dependent photooxidation. Our findings support novel binding sites on FLuc for non-competitive inhibitors.

Synthesis of SMT022357 enantiomers and in vivo evaluation in a Duchenne muscular dystrophy mouse model.

Following on from ezutromid, the first-in-class benzoxazole utrophin modulator that progressed to Phase 2 clinical trials for the treatment of Duchenne muscular dystrophy, a new chemotype was designed to optimise its physicochemical and ADME profile. Herein we report the synthesis of SMT022357, a second generation utrophin modulator preclinical candidate, and an asymmetric synthesis of its constituent enantiomers. The pharmacological properties of both enantiomers were evaluated in vitro and in vivo. No significant difference in the activity or efficacy was observed between the two enantiomers; activity was found to be comparable to the racemic mixture.

Chemical Proteomics and Phenotypic Profiling Identifies the Aryl Hydrocarbon Receptor as a Molecular Target of the Utrophin Modulator Ezutromid.

Duchenne muscular dystrophy (DMD) is a fatal muscle-wasting disease arising from mutations in the dystrophin gene. Upregulation of utrophin to compensate for the missing dystrophin offers a potential therapy independent of patient genotype. The first-in-class utrophin modulator ezutromid/SMT C1100 was developed from a phenotypic screen through to a Phase 2 clinical trial. Promising efficacy and evidence of target engagement was observed in DMD patients after 24 weeks of treatment, however trial endpoints were not met after 48 weeks. The objective of this study was to understand the mechanism of action of ezutromid which could explain the lack of sustained efficacy and help development of new generations of utrophin modulators. Using chemical proteomics and phenotypic profiling we show that the aryl hydrocarbon receptor (AhR) is a target of ezutromid. Several lines of evidence demonstrate that ezutromid binds AhR with an apparent KD of 50 nm and behaves as an AhR antagonist. Furthermore, other reported AhR antagonists also upregulate utrophin, showing that this pathway, which is currently being explored in other clinical applications including oncology and rheumatoid arthritis, could also be exploited in future DMD therapies.

Enhancing the prediction of acute kidney injury risk after percutaneous coronary intervention using machine learning techniques: A retrospective cohort study.

BACKGROUND: The current acute kidney injury (AKI) risk prediction model for patients undergoing percutaneous coronary intervention (PCI) from the American College of Cardiology (ACC) National Cardiovascular Data Registry (NCDR) employed regression techniques. This study aimed to evaluate whether models using machine learning techniques could significantly improve AKI risk prediction after PCI. METHODS AND FINDINGS: We used the same cohort and candidate variables used to develop the current NCDR CathPCI Registry AKI model, including 947,091 patients who underwent PCI procedures between June 1, 2009, and June 30, 2011. The mean age of these patients was 64.8 years, and 32.8% were women, with a total of 69,826 (7.4%) AKI events. We replicated the current AKI model as the baseline model and compared it with a series of new models. Temporal validation was performed using data from 970,869 patients undergoing PCIs between July 1, 2016, and March 31, 2017, with a mean age of 65.7 years; 31.9% were women, and 72,954 (7.5%) had AKI events. Each model was derived by implementing one of two strategies for preprocessing candidate variables (preselecting and transforming candidate variables or using all candidate variables in their original forms), one of three variable-selection methods (stepwise backward selection, lasso regularization, or permutation-based selection), and one of two methods to model the relationship between variables and outcome (logistic regression or gradient descent boosting). The cohort was divided into different training (70%) and test (30%) sets using 100 different random splits, and the performance of the models was evaluated internally in the test sets. The best model, according to the internal evaluation, was derived by using all available candidate variables in their original form, permutation-based variable selection, and gradient descent boosting. Compared with the baseline model that uses 11 variables, the best model used 13 variables and achieved a significantly better area under the receiver operating characteristic curve (AUC) of 0.752 (95% confidence interval [CI] 0.749-0.754) versus 0.711 (95% CI 0.708-0.714), a significantly better Brier score of 0.0617 (95% CI 0.0615-0.0618) versus 0.0636 (95% CI 0.0634-0.0638), and a better calibration slope of observed versus predicted rate of 1.008 (95% CI 0.988-1.028) versus 1.036 (95% CI 1.015-1.056). The best model also had a significantly wider predictive range (25.3% versus 21.6%, p < 0.001) and was more accurate in stratifying AKI risk for patients. Evaluated on a more contemporary CathPCI cohort (July 1, 2015-March 31, 2017), the best model consistently achieved significantly better performance than the baseline model in AUC (0.785 versus 0.753), Brier score (0.0610 versus 0.0627), calibration slope (1.003 versus 1.062), and predictive range (29.4% versus 26.2%). The current study does not address implementation for risk calculation at the point of care, and potential challenges include the availability and accessibility of the predictors. CONCLUSIONS: Machine learning techniques and data-driven approaches resulted in improved prediction of AKI risk after PCI. The results support the potential of these techniques for improving risk prediction models and identification of patients who may benefit from risk-mitigation strategies.

Compensatory Distal Reabsorption Drives Diuretic Resistance in Human Heart Failure.

Understanding the tubular location of diuretic resistance (DR) in heart failure (HF) is critical to developing targeted treatment strategies. Rodents chronically administered loop diuretics develop DR due to compensatory distal tubular sodium reabsorption, but whether this translates to human DR is unknown. We studied consecutive patients with HF (n=128) receiving treatment with loop diuretics at the Yale Transitional Care Center. We measured the fractional excretion of lithium (FELi), the gold standard for in vivo assessment of proximal tubular and loop of Henle sodium handling, to assess sodium exit after loop diuretic administration and FENa to assess the net sodium excreted into the urine. The mean±SD prediuretic FELi was 16.2%±9.5%, similar to that in a control cohort without HF not receiving diuretics (n=52; 16.6%±9.2%; P=0.82). Administration of a median of 160 (interquartile range, 40-270) mg intravenous furosemide equivalents increased FELi by 12.6%±10.8% (P<0.001) but increased FENa by only 4.8%±3.3%. Thus, only 34% (interquartile range, 15.6%-75.7%) of the estimated diuretic-induced sodium release did not undergo distal reabsorption. After controlling for urine diuretic levels, the increase in FELi explained only 6.4% of the increase in FENa (P=0.002). These data suggest that administration of high-dose loop diuretics to patients with HF yields meaningful increases in sodium exit from the proximal tubule/loop of Henle. However, little of this sodium seems to reach the urine, consistent with findings from animal models that indicate that distal tubular compensatory sodium reabsorption is a primary driver of DR.

Urine biomarkers of tubular injury do not improve on the clinical model predicting chronic kidney disease progression.

Few investigations have evaluated the incremental usefulness of tubular injury biomarkers for improved prediction of chronic kidney disease (CKD) progression. As such, we measured urinary kidney injury molecule-1, neutrophil gelatinase-associated lipocalin, N-acetyl-ß-D-glucosaminidase and liver fatty acid binding protein under highly standardized conditions among 2466 enrollees of the prospective Chronic Renal Insufficiency Cohort Study. During 9433 person-years of follow-up, there were 581 cases of CKD progression defined as incident end-stage renal disease or halving of the estimated glomerular filtration rate. Levels of the urine injury biomarkers, normalized for urine creatinine, were strongly associated with CKD progression in unadjusted Cox proportional hazard models with hazard ratios in the range of 7 to 15 comparing the highest with the lowest quintiles. However, after controlling for the serum creatinine-based estimated glomerular filtration rate and urinary albumin/creatinine ratio, none of the normalized biomarkers was independently associated with CKD progression. None of the biomarkers improved on the high (0.89) C-statistic for the base clinical model. Thus, among patients with CKD, risk prediction with a clinical model that includes the serum creatinine-based estimated glomerular filtration rate and the urinary albumin/creatinine ratio is not improved on with the addition of renal tubular injury biomarkers.

Second-generation compound for the modulation of utrophin in the therapy of DMD.

Duchenne muscular dystrophy (DMD) is a lethal, X-linked muscle-wasting disease caused by lack of the cytoskeletal protein dystrophin. There is currently no cure for DMD although various promising approaches are progressing through human clinical trials. By pharmacologically modulating the expression of the dystrophin-related protein utrophin, we have previously demonstrated in dystrophin-deficient mdx studies, daily SMT C1100 treatment significantly reduced muscle degeneration leading to improved muscle function. This manuscript describes the significant disease modifying benefits associated with daily dosing of SMT022357, a second-generation compound in this drug series with improved physicochemical properties and a more robust metabolism profile. These studies in the mdx mouse demonstrate that oral administration of SMT022357 leads to increased utrophin expression in skeletal, respiratory and cardiac muscles. Significantly, utrophin expression is localized along the length of the muscle fibre, not just at the synapse, and is fibre-type independent, suggesting that drug treatment is modulating utrophin transcription in extra-synaptic myonuclei. This results in improved sarcolemmal stability and prevents dystrophic pathology through a significant reduction of regeneration, necrosis and fibrosis. All these improvements combine to protect the mdx muscle from contraction induced damage and enhance physiological function. This detailed evaluation of the SMT C1100 drug series strongly endorses the therapeutic potential of utrophin modulation as a disease modifying therapeutic strategy for all DMD patients irrespective of their dystrophin mutation.

Association between e-alert implementation for detection of acute kidney injury and outcomes: a systematic review.

Background: Electronic alerts (e-alerts) for acute kidney injury (AKI) in hospitalized patients are increasingly being implemented; however, their impact on outcomes remains uncertain. Methods: We performed a systematic review. Electronic databases and grey literature were searched for original studies published between 1990 and 2016. Randomized, quasi-randomized, observational and before-and-after studies that included hospitalized patients, implemented e-alerts for AKI and described their impact on one of care processes, patient-centred outcomes or resource utilization measures were included. Results: Our search yielded six studies ( n = 10 165 patients). E-alerts were generally automated, triggered through electronic health records and not linked to clinical decision support. In pooled analysis, e-alerts did not improve mortality [odds ratio (OR) 1.05; 95% confidence intervals (CI), 0.84-1.31; n = 3 studies; n = 3425 patients; I 2 = 0%] or reduce renal replacement therapy (RRT) use (OR 1.20; 95% CI, 0.91-1.57; n = 2 studies; n = 3236 patients; I 2 = 0%). Isolated studies reported improvements in selected care processes. Pooled analysis found no significant differences in prescribed fluid therapy. Conclusions: In the available studies, e-alerts for AKI do not improve survival or reduce RRT utilization. The impact of e-alerts on processes of care was variable. Additional research is needed to understand those aspects of e-alerts that are most likely to improve care processes and outcomes.