Kashani, Kianoush

Background The impact of changes in Doppler‐derived kidney venous flow in heart failure (HF) is not well studied. We aimed to investigate the association of Doppler‐derived kidney venous stasis index (KVSI) and intrakidney venous‐flow (IKVF) patterns with adverse cardiorenal outcomes in patients with HF. Methods and Results In this observational cohort study, consecutive inpatients with HF referred to a nephrologist because of a history of diuretic resistance and abnormal kidney function (n=216) underwent spectral kidney assessments after admission (Doppler 1) and 25 to 35 days later (Doppler 2) to identify IKVF patterns (continuous/pulsatile/biphasic/monophasic) and KVSI levels. Cox proportional hazard regression models were used to evaluate the associations between KVSI/IKVF patterns at Doppler 1 as well as changes from Doppler 1 to Doppler 2 and risk of cardiorenal events up to 18 months after admission. Worsening HF or death occurred in 126 patients. Both baseline KVSI (hazard ratio [HR], 1.49 [95% CI, 1.37–1.61] per 0.1‐unit increase) and baseline IKVF pattern (HR, 2.47 [95% CI, 2.01–3.04] per 1 pattern severity increase) were significantly associated with worsening HF/death. Increases in both KVSI and IKVF pattern severity from Doppler 1 to 2 were also associated with an increased risk of worsening HF/death (HR, 3.00 [95% CI, 2.08–4.32] per 0.1‐unit increase change; and HR, 6.73 [95% CI, 3.27–13.86] per 1 pattern increase in severity change, respectively). Similar results were observed for kidney outcomes. Conclusions Baseline kidney venous flow predicted adverse cardiorenal events, and inclusion of serial kidney venous flow in cardiorenal risk stratification could facilitate clinical decision‐making for patients with HF. Registration URL: https://www.clinicaltrials.gov ; Unique identifier: NCT03039959.

Background: Urine output (UO) measurement utility after out-of-hospital cardiac arrest (OHCA) survivors who undergo targeted temperature management (TTM) is not well understood. Methods: We included 247 comatose adult patients who underwent TTM after OHCA between 2007 and 2017 and excluded those on maintenance dialysis. Groups were defined based on mean hourly UO during the first 24 hours: Group 1 (<0.5 ml/kg/hr, n=73), Group 2 (0.5-1 ml/kg/hr, n=81) and Group 3 (>1 ml/kg/hr, n=93). Kidney Disease: Improving Global Outcomes (KDIGO) serum creatinine criteria were used to define and stage acute kidney injury (AKI). Multivariable analysis was used to evaluate in-hospital mortality. Results: In-hospital mortality decreased as 24-hour mean UO increased (56.2% [41/73] vs 29.6% [24/81] vs 18.3% [17/93] in Groups 1, 2 and 3, respectively; adjusted OR 0.93 per 0.1 ml/kg/h higher, 95% CI 0.87-0.99, p = 0.03), and UO < 0.5 ml/kg/hr was strongly associated with in-hospital mortality (adjusted OR 4.2 [1.6-10.8], p=0.003). In-hospital mortality varied by the KDIGO stage and UO group (Figure), lowest in KDIGO stage 0 and highest in KDIGO stage 3. Both UO (adjusted OR 0.92 per 0.1 ml/kg/h higher, p = 0.002) and KDIGO stage (adjusted OR 1.62 per each stage, p = 0.002) were associated with in-hospital mortality when included in the same model. Among patients with KDIGO stage 0, lower UO portended higher mortality (Figure). Likewise, among patients with low UO (group 1), a higher KDIGO stage predicted higher mortality. Conclusion: Amongst OHCA survivors undergoing TTM, higher UO is incrementally associated with lower in-hospital mortality. The lowest mortality was observed at UO >=1 ml/kg/h, suggesting this as a target for resuscitation in OHCA patients undergoing TTM. Low UO remains associated with in-hospital mortality even when accounting for AKI by creatinine criteria, suggesting that oliguria is a more sensitive prognostic marker in the early post-OHCA phase.

Abstract Background and Aims At least 30% of acute kidney injury (AKI) survivors lack appropriate follow up after hospital discharge. AKI survivors have highly dynamic posthospital course which warrants close monitoring to prevent adverse outcomes. Digital health solutions like remote patient monitoring (RPM) could be used to improve quality and efficiency of AKI survivor care. The purpose for this study was to assess the feasibility and effectiveness of the Mayo Clinic AKI RPM program, launched in October 2021. Method The Mayo Clinic AKI RPM program enrolled individuals who experienced AKI during a hospitalization and underwent nephrology consultation (Figure 1). Feasibility was assessed as the proportion of individuals approached for AKI RPM enrollment during the first year of the program who submitted at least one set of vital signs after discharge. An effectiveness analysis compared stage 3 AKI survivors enrolled in AKI RPM with at least 30-days of follow-up to matched historical controls (3:1) sampled from before RPM was available (2018-2021). The primary endpoint was hospital readmission or emergency department (ED) visit within 30-days, assessed with the Chi-square test. Secondarily we explored time to first readmission or ED visit with a Kaplan-Meier survival curve with a non-parametric comparison between groups, as well as readmission length of stay with the Wilcoxon Rank Sum test due to right skewed data distribution. Results Of the 50 individuals approached for AKI RPM participation, 45 (90%) submitted at least one set of vitals. Among AKI RPM patients, 34 patients with stage 3 AKI were matched to 102 controls based on baseline characteristics and demographics. Dialysis during hospitalization (liberated by discharge) was used in 36 (27%) of patients. Sixty (44%) individuals required ICU level of care. Median (IQR) discharge estimated glomerular filtration rate was 15 (11, 27) mL/min/1.73m2. Through matching, groups were well balanced with respect to pertinent baseline demographics. Hospital readmission or ED visit occurred in 17 (50%) of AKI RPM patients within 30-days compared to 39 (38%) of controls within 30-days (P = .23). The endpoint appeared driven by ED visits within 30-days, not readmissions [At least one ED visit: 13 (38%) vs 21 (21%), respectively (P = .04); At least one hospital readmission: 7 (21%) vs 26 (26%), respectively (P = .56)]. Time to first readmission or ED visit within 30-days was similar between groups (P = .35; Figure 2). Among the 33 patients who were readmitted to the hospital within 30-days, readmission length of stay was similar in the AKI RPM group compared to controls [Median (IQR) 76 (10.6, 121) hours vs 108 (70, 165) hours); P = 0.33]. Conclusion In conclusion, AKI RPM was a feasible program when used to bridge the care continuum (hospital to home) in non-dialysis dependent AKI survivors. Incidence of at least one hospital readmission or ED visit within 30-days was statistically similar between AKI RPM patients and controls. More AKI RPM patients experienced ED encounters in the 30-days after discharge, but frequency of hospital readmission was similar. Digital health solutions such as RPM offer a unique opportunity to address the important gap in AKI care after discharging from the hospital. Additional research is needed to explore the impact of AKI RPM on patient outcomes.

ABSTRACT The Food and Drug Administration defines digital health (DH) as “a convergence of people, information, technology, and connectivity to improve health care and health outcomes”. Information and communication technologies are categorized under the DH umbrella. While still in their infancy, these technologies have great potential to revolutionize the clinical approaches to bedside management and overall health care. Over the past few decades, there has been a substantial improvement in the technology in smart wearable devices that enabled them to enhance their abilities to collect patient-related data, including physiological and behavioral information in the Internet of things. This has resulted in implementing several controlled clinical trials that have confirmed their validity and safety. These digital diagnostics have led to the expansion of digital therapies and specialized software (for example, apps) capable of effectively and measurably guiding patients’ progress toward improving their clinical condition. These technologies are clinically validated treatments for many diseases with particular effectiveness in pathological conditions related to behavior and psychological factors. In this review paper, we describe the outlines of some of the recent progress made in this field.

ABSTRACT The Food and Drug Administration defines digital health (DH) as “a convergence of people, information, technology, and connectivity to improve health care and health outcomes”. Information and communication technologies are categorized under the DH umbrella. While still in their infancy, these technologies have great potential to revolutionize the clinical approaches to bedside management and overall health care. Over the past few decades, there has been a substantial improvement in the technology in smart wearable devices that enabled them to enhance their abilities to collect patient-related data, including physiological and behavioral information in the Internet of things. This has resulted in implementing several controlled clinical trials that have confirmed their validity and safety. These digital diagnostics have led to the expansion of digital therapies and specialized software (for example, apps) capable of effectively and measurably guiding patients’ progress toward improving their clinical condition. These technologies are clinically validated treatments for many diseases with particular effectiveness in pathological conditions related to behavior and psychological factors. In this review paper, we describe the outlines of some of the recent progress made in this field.

ABSTRACT Background: The Society for Cardiovascular Angiography and Intervention (SCAI) Shock Classification can define shock severity. We evaluated the vasoactive-inotropic score (VIS) combined with the SCAI Shock Classification for mortality risk stratification. Methods: This was a single-center retrospective cohort analysis including Mayo Clinic cardiac intensive care unit patients from 2007 to 2015. The peak VIS was calculated at 1 and 24 h after cardiac intensive care unit admission. In-hospital mortality was evaluated using multivariable logistic regression. Results: Of 9,916 included patients, vasoactive drugs were used in 875 (8.8%) within 1 h and 2,196 (22.1%) within 24 h. A total of 888 patients (9.0%) died during hospitalization. Patients who required vasoactive drugs within 1 h had higher in-hospital mortality (adjusted odds ratio [OR], 1.30; 95% confidence interval [CI], 1.03–1.65; P = 0.03) and in-hospital mortality rose with the VIS during the first 1 h (adjusted OR per 10 units, 1.22; 95% CI, 1.12–1.33; P < 0.001). The increase in VIS from 1 to 24 h was associated with higher in-hospital mortality (adjusted OR per 10 units, 1.16; 95% CI, 1.10–1.21; P < 0.001). These results were consistent in the 1,067 patients (10.9%) with cardiogenic shock. A gradient of in-hospital mortality was observed according to the VIS at 1 h and the increase in VIS from 1 to 24 h. Conclusions: Higher vasoactive drug requirements portend a higher risk of mortality, particularly a high VIS early after admission. The VIS provides incremental prognostic information beyond the SCAI Shock Classification, emphasizing the continuum of risk that exists across the spectrum of shock severity.

Background: Acute kidney injury (AKI) is associated with significant short- and long-term morbidity and mortality. In critically ill patients with sepsis, AKI tends to be more severe, more likely to require kidney replacement therapy (KRT), with less chance of recovery. Consequently, critically ill patients with sepsis-associated AKI (SA-AKI) have extended intensive care unit (ICU) stays and higher mortality rates. This study evaluated the predictive value of clinical and transthoracic echocardiographic (TTE) parameters for recovery from moderate-to-severe SA-AKI in critically ill patients. Methods: This single-center historical cohort study was conducted at a tertiary academic medical center. We analyzed the data of all adults (age ≥ 18 years) admitted to the ICU at Mayo Clinic, Rochester, MN, from June 1, 2018, to December 31, 2020. We included all patients who developed sepsis within the initial 24 h of their ICU stay. Results: We identified 2,919 eligible septic patients with available TTE, among which 1,431 patients (49%) had moderate-to-severe SA-AKI. The mean age of the patients was 68 ± 15 years, and the male-to-female ratio was 1.3:1. The most common comorbidities were diabetes mellitus and chronic lung and kidney diseases. Clinical predictors associated with SA-AKI non-recovery were the presence of stage III AKI (HR 1.5, 95% CI 1.0-2.1, p = 0.03) and utilization of kidney replacement therapy (KRT) (HR 6.8, 95% CI 3.6-12.4, p = 0.01). On the other hand, higher TAPSE was the only TTE variable associated with SA-AKI recovery (HR 1.1; 95% CI 1.08-1.15; p = 0.01). Conclusion: Our data from a single-center provide new information on the clinical (AKI stage, utilization of KRT, BMI, and peak serum creatinine) and echocardiographic features (TAPSE) associated with improved recovery in SA-AKI. There is a definite knowledge gap in the current literature regarding optimizing recovery in moderate-to-severe SA-AKI. Larger, multi-center studies are required to confirm these findings.

Key Points Urinary TIMP2×IGFBP7 (uTIMP2×IGFBP7) concentrations experienced a rapid and sustained decline after high-dose methotrexate (MTX) exposure. uTIMP2×IGFBP7 kinetics and concentrations after high-dose MTX exposure demonstrated no utility in predicting AKI.

Background Sepsis is associated with an elevated risk of late cardiovascular events among hospital survivors. Methods and Results We included OptumLabs Data Warehouse patients from 2009 to 2019 who survived a medical/nonsurgical hospitalization lasting at least 2 nights. The association between sepsis during hospitalization, based on explicit and implicit discharge International Classification of Diseases, Ninth Revision ( ICD‐9 )/ Tenth Revision ( ICD‐10 ) diagnosis codes, with subsequent death and rehospitalization was analyzed using Kaplan–Meier survival analysis and multivariable Cox proportional‐hazards models. The study population included 2 258 464 survivors of nonsurgical hospitalization (5 396 051 total patient‐years of follow‐up). A total of 808 673 (35.8%) patients had a sepsis hospitalization, including implicit sepsis only in 448 644, explicit sepsis only in 124 841, and both in 235 188. Patients with sepsis during hospitalization had an elevated risk of all‐cause mortality (adjusted hazard ratio [HR], 1.27 [95% CI, 1.25–1.28]; P <0.001), all‐cause rehospitalization (adjusted HR, 1.38 [95% CI, 1.37–1.39]; P <0.001), and cardiovascular hospitalization (adjusted HR, 1.43 [95% CI, 1.41–1.44]; P <0.001), especially heart failure hospitalization (adjusted HR, 1.51 [95% CI, 1.49–1.53]). Patients with implicit sepsis had higher risk than those with explicit sepsis. A sensitivity analysis using the first hospitalization yielded concordant results for cardiovascular hospitalization (adjusted HR, 1.78 [95% CI, 1.76–1.78]; P <0.001), as did a propensity‐weighted analysis (adjusted HR, 1.52 [95% CI, 1.50–1.54]; P <0.001). Conclusions Survivors of sepsis hospitalization are at elevated risk of early and late post‐discharge death as well as cardiovascular and non‐cardiovascular rehospitalization. This hazard spans the spectrum of cardiovascular events and may suggest that sepsis is an important cardiovascular risk factor.