Lung Protective Ventilation during Pregnancy: An Observational Cohort Study.

Objectives We sought to describe characteristics of mechanically ventilated pregnant patients, evaluate utilization of low-tidal-volume ventilation (LTVV) and high-tidal-volume ventilation (HTVV) by trimester, and describe maternal and fetal outcomes by ventilation strategy. Study Design This is a retrospective cohort study of pregnant women with mechanical ventilation for greater than 24 hours between July 2012 and August 2020 at a tertiary care academic medical center. We defined LTVV as average daily tidal volume 8 mL/kg of less of predicted body weight, and HTVV as greater than 8 mL/kg. We examined demographic characteristics, maternal and fetal characteristics, and outcomes by ventilation strategy. Results We identified 52 ventilated pregnant women, 43 had LTVV, and 9 had HTVV. Acute respiratory distress syndrome occurred in 73% ( N = 38) of patients, and infection was a common indication for ventilation ( N = 33, 63%). Patients had LTVV more often than HTVV in all trimesters. Obstetric complications occurred frequently, 21% ( N = 11) experienced preeclampsia or eclampsia, and among 43 patients with available delivery data, 60% delivered preterm ( N = 26) and 16% had fetal demise ( N = 7). Conclusion LTVV was utilized more often than HTVV among pregnant women in all trimesters. There was a high prevalence of maternal and fetal morbidity and fetal mortality among our cohort. Key Points Our center utilized low tidal more often than high-tidal-volume ventilation during all trimesters of pregnancy.Prone positioning can be performed at advanced gestations.Infection is a common cause of antepartum ventilation.

Contrast-associated acute kidney injury and cardiovascular events: a secondary analysis of the PRESERVE cohort.

Background: Contrast-associated acute kidney injury (CA-AKI) has been associated with a higher risk of cardiovascular (CV) events. We studied the risk of CV events in chronic kidney disease (CKD) patients undergoing angiography and whether biomarkers can predict such events. We also explored whether CA-AKI mediates the association of pre-angiography estimated glomerular filtration rate (eGFR) on CV events. Methods: We analysed participants from the Prevention of Serious Adverse Events following the Angiography (PRESERVE) trial. Urinary tissue inhibitor of matrix metalloproteinase [TIMP]-2 and insulin growth factor binding protein [IGFBP]-7, plasma brain-type natriuretic peptide (BNP), high sensitivity C-reactive protein (hs-CRP), and serum cardiac troponin-I (Tn-I) were assayed before and after angiography. We assessed the composite risk of CV events by day 90. Results: Of the 922 participants, 119 (12.9%) developed CV events, and 73 (7.9%) developed CA-AKI. Most cases of CA-AKI (90%) were stage 1. There were no differences in urinary [TIMP-2]•[IGFBP7] concentrations or the proportion of patients with CA-AKI among those with and without CV events. Higher BNP, Tn-I, and hs-CRP were associated with CV events, but their discriminatory capacity was modest (AUROC <0.7). CA-AKI did not mediate the association of the pre-angiography eGFR on CV events. Conclusions: Most episodes of CA-AKI are stage 1 AKI and are not associated with CV events. Less severe CA-AKI episodes also did not mediate the risk of pre-angiography eGFR on CV events. Our findings suggest that most CV events after contrast procedures are due to underlying CKD and CV risk factors rather than less severe CA-AKI episodes and should help enhance the utilization of clinically indicated contrast procedures among high-risk patients with CKD. Further research is required to examine whether moderate-to-severe CA-AKI episodes are associated with CV events.

Fluid Management during Continuous Renal Replacement Therapy: A Case-Based Approach.

Continuous renal replacement therapy (CRRT) is frequently used for fluid management of critically ill patients with acute or chronic kidney failure. There is significant practice variation worldwide in fluid management during CRRT. Multiple clinical studies have suggested that both the magnitude and duration of fluid overload are associated with morbidity and mortality in critically ill patients. Therefore, timely and effective fluid management with CRRT is paramount in managing critically ill patients with fluid overload. While the optimal method of fluid management during CRRT is still unclear and warrants further investigation, observational data have suggested a U-shape relationship between net ultrafiltration rate and mortality. Furthermore, recent clinical data have underpinned a significant gap in prescribed versus achieved fluid balance during CRRT, which is also associated with mortality. This review uses a case-based approach to discuss two fluid management strategies based on net ultrafiltration rate and fluid balance goals during CRRT and harmonizes operational definitions.

Forecasting imminent atrial fibrillation in long-term electrocardiogram recordings.

BACKGROUND: Despite the morbidity associated with acute atrial fibrillation (AF), no models currently exist to forecast its imminent onset. We sought to evaluate the ability of deep learning to forecast the imminent onset of AF with sufficient lead time, which has important implications for inpatient care. METHODS: We utilized the Physiobank Long-Term AF Database, which contains 24-h, labeled ECG recordings from patients with a history of AF. AF episodes were defined as ≥5 min of sustained AF. Three deep learning models incorporating convolutional and transformer layers were created for forecasting, with two models focusing on the predictive nature of sinus rhythm segments and AF epochs separately preceding an AF episode, and one model utilizing all preceding waveform as input. Cross-validated performance was evaluated using area under time-dependent receiver operating characteristic curves (AUC(t)) at 7.5-, 15-, 30-, and 60-min lead times, precision-recall curves, and imminent AF risk trajectories. RESULTS: There were 367 AF episodes from 84 ECG recordings. All models showed average risk trajectory divergence of those with an AF episode from those without ∼15 min before the episode. Highest AUC was associated with the sinus rhythm model [AUC = 0.74; 7.5-min lead time], though the model using all preceding waveform data had similar performance and higher AUCs at longer lead times. CONCLUSIONS: In this proof-of-concept study, we demonstrated the potential utility of neural networks to forecast the onset of AF in long-term ECG recordings with a clinically relevant lead time. External validation in larger cohorts is required before deploying these models clinically.

Economic Analysis of Renal Replacement Therapy Modality in Acute Kidney Injury Patients With Fluid Overload.

Acute kidney injury (AKI) and fluid overload (FO) are among the top reasons to initiate intermittent hemodialysis (IHD) or continuous renal replacement therapy (CRRT). Prior research suggests CRRT provides more precise volume control, but whether CRRT is cost-effective remains unclear. We assessed the cost-effectiveness of CRRT for volume control compared with IHD from a U.S. healthcare payer perspective. DESIGN: Decision analytical model comparing health outcomes and healthcare costs of CRRT versus IHD initiation for AKI patients with FO. The model had an inpatient phase (over 90-d) followed by post-discharge phase (over lifetime). The 90-day phase had three health states: FO, fluid control, and death. After 90 days, surviving patients entered the lifetime phase with four health states: dialysis independent (DI), dialysis dependent (DD), renal transplantation, and death. Model parameters were informed by current literature. Sensitivity analyses were performed to evaluate results robustness to parametric uncertainty. SETTING: ICU. PATIENTS OR SUBJECTS: AKI patients with FO. INTERVENTIONS: IHD or CRRT. MEASUREMENTS AND MAIN RESULTS: The 90-day horizon revealed better outcomes for patients initiated on CRRT (survival: CRRT 59.2% vs IHD 57.5% and DD rate among survivors: CRRT 5.5% vs IHD 6.9%). Healthcare cost was 2.7% (+$2,836) higher for CRRT. Over lifetime, initial CRRT was associated with +0.313 life years (LYs) and +0.187 quality-adjusted life years (QALYs) compared with initial IHD. Even though important savings were observed for initial CRRT with a lower rate of DD among survivors (-$13,437), it did not fully offset the incremental cost of CRRT (+$1,956) and DI survival (+$12,830). The incremental cost-per-QALY gained with CRRT over IRRT was +$10,429/QALY. Results were robust to sensitivity analyses. CONCLUSIONS: Our analysis provides an economic rationale for CRRT as the initial modality of choice in AKI patients with FO who require renal replacement therapy. Our finding needs to be confirmed in future research.

Digital health and acute kidney injury: consensus report of the 27th Acute Disease Quality Initiative workgroup.

Acute kidney injury (AKI), which is a common complication of acute illnesses, affects the health of individuals in community, acute care and post-acute care settings. Although the recognition, prevention and management of AKI has advanced over the past decades, its incidence and related morbidity, mortality and health care burden remain overwhelming. The rapid growth of digital technologies has provided a new platform to improve patient care, and reports show demonstrable benefits in care processes and, in some instances, in patient outcomes. However, despite great progress, the potential benefits of using digital technology to manage AKI has not yet been fully explored or implemented in clinical practice. Digital health studies in AKI have shown variable evidence of benefits, and the digital divide means that access to digital technologies is not equitable. Upstream research and development costs, limited stakeholder participation and acceptance, and poor scalability of digital health solutions have hindered their widespread implementation and use. Here, we provide recommendations from the Acute Disease Quality Initiative consensus meeting, which involved experts in adult and paediatric nephrology, critical care, pharmacy and data science, at which the use of digital health for risk prediction, prevention, identification and management of AKI and its consequences was discussed.

Restrictive versus Liberal Rate of Extracorporeal Volume Removal Evaluation in Acute Kidney Injury (RELIEVE-AKI): a pilot clinical trial protocol.

INTRODUCTION: Observational studies have linked slower and faster net ultrafiltration (UFNET) rates during kidney replacement therapy (KRT) with mortality in critically ill patients with acute kidney injury (AKI) and fluid overload. To inform the design of a larger randomised trial of patient-centered outcomes, we conduct a feasibility study to examine restrictive and liberal approaches to UFNET during continuous KRT (CKRT). METHODS AND ANALYSIS: This study is an investigator-initiated, unblinded, 2-arm, comparative-effectiveness, stepped-wedged, cluster randomised trial among 112 critically ill patients with AKI treated with CKRT in 10 intensive care units (ICUs) across 2 hospital systems. In the first 6 months, all ICUs started with a liberal UFNET rate strategy. Thereafter, one ICU is randomised to the restrictive UFNET rate strategy every 2 months. In the liberal group, the UFNET rate is maintained between 2.0 and 5.0 mL/kg/hour; in the restrictive group, the UFNET rate is maintained between 0.5 and 1.5 mL/kg/hour. The three coprimary feasibility outcomes are (1) between-group separation in mean delivered UFNET rates; (2) protocol adherence; and (3) patient recruitment rate. Secondary outcomes include daily and cumulative fluid balance, KRT and mechanical ventilation duration, organ failure-free days, ICU and hospital length of stay, hospital mortality and KRT dependence at hospital discharge. Safety endpoints include haemodynamics, electrolyte imbalance, CKRT circuit issues, organ dysfunction related to fluid overload, secondary infections and thrombotic and haematological complications. ETHICS AND DISSEMINATION: The University of Pittsburgh Human Research Protection Office approved the study, and an independent Data and Safety Monitoring Board monitors the study. A grant from the United States National Institute of Diabetes and Digestive and Kidney Diseases sponsors the study. The trial results will be submitted for publication in peer-reviewed journals and presented at scientific conferences. TRIAL REGISTRATION NUMBER: This trial has been prospectively registered with clinicaltrials.gov (NCT05306964). Protocol version identifier and date: 1.5; 13 June 2023.

A deep learning-based dynamic model for predicting acute kidney injury risk severity in postoperative patients.

BACKGROUND: Acute kidney injury is a common postoperative complication affecting between 10% and 30% of surgical patients. Acute kidney injury is associated with increased resource usage and chronic kidney disease development, with more severe acute kidney injury suggesting more aggressive deterioration in clinical outcomes and mortality. METHODS: We considered 42,906 surgical patients admitted to University of Florida Health (n = 51,806) between 2014 and 2021. Acute kidney injury stages were determined using the Kidney Disease Improving Global Outcomes serum creatinine criteria. We developed a recurrent neural network-based model to continuously predict acute kidney injury risk and state in the following 24 hours and compared it with logistic regression, random forest, and multi-layer perceptron models. We used medications, laboratory and vital measurements, and derived features from past one-year records as inputs. We analyzed the proposed model with integrated gradients for enhanced explainability. RESULTS: Postoperative acute kidney injury at any stage developed in 20% (10,664) of the cohort. The recurrent neural network model was more accurate in predicting nearly all categories of next-day acute kidney injury stages (including the no acute kidney injury group). The area under the receiver operating curve and 95% confidence intervals for recurrent neural network and logistic regression models were for no acute kidney injury (0.98 [0.98-0.98] vs 0.93 [0.93-0.93]), stage 1 (0.95 [0.95-0.95] vs. 0.81 [0.80-0.82]), stage 2/3 (0.99 [0.99-0.99] vs 0.96 [0.96-0.97]), and stage 3 with renal replacement therapy (1.0 [1.0-1.0] vs 1.0 [1.0-1.0]. CONCLUSION: The proposed model demonstrates that temporal processing of patient information can lead to more granular and dynamic modeling of acute kidney injury status and result in more continuous and accurate acute kidney injury prediction. We showcase the integrated gradients framework's utility as a mechanism for enhancing model explainability, potentially facilitating clinical trust for future implementation.

Kidney Cell Cycle Arrest and Cardiac Biomarkers and Acute Kidney Injury Following Angiography: The Prevention of Serious Adverse Events Following Angiography (PRESERVE) Study.

Rationale & Objective: Recent studies in patients with chronic kidney disease (CKD) indicate that most cases of contrast-associated acute kidney injury (CA-AKI) are mild and are not associated with elevation in kidney injury biomarkers. We used highly sensitive kidney cell cycle arrest and cardiac biomarkers to assess the risk of CA-AKI and major adverse kidney events in patients with CKD undergoing angiography. Study Design: A retrospective study. Setting & Participants: A subset of 922 participants from the Prevention of Serious Adverse Events following Angiography trial. Predictors: Pre- and postangiography urinary tissue inhibitor of matrix metalloproteinase [TIMP]-2 and insulin growth factor binding protein [IGFBP]-7 were measured in 742 subjects, and plasma ß natriuretic peptide (BNP) and high-sensitivity C-reactive protein (hs-CRP), and serum troponin (Tn) in 854 participants using samples obtained 1-2 hours before and 2-4 hours after angiography. Outcomes: CA-AKI and major adverse kidney events. Analytical Approach: We fitted logistic regression to examine association and area under the receiver operating characteristic curves for risk prediction. Results: There were no differences in postangiography urinary [TIMP-2]•[IGFBP7], plasma BNP, serum Tn, and hs-CRP concentrations among patients with and without CA-AKI and major adverse kidney events. However, higher pre- and postangiography median plasma BNP (pre: 200.0 vs 71.5, pg/mL, P = 0.05; post: 165.0 vs 81 pg/mL, P = 0.02); serum Tn (pre: 0.03 vs 0.01, ng/mL, P < 0.001; post, 0.04 vs 0.02, ng/mL, P = 0.01); and hs-CRP (pre: 9.55 vs 3.40 mg/L, P = 0.01; post: 9.90 vs 3.20 mg/L, P = 0.002) concentrations were associated with major adverse kidney events, although their discriminatory capacity was only modest (area under the receiver operating characteristic curves <0.7). Limitations: Most participants were men. Conclusions: Most mild CA-AKI cases are not associated with urinary cell cycle arrest biomarker elevation. Significant elevation in preangiography cardiac biomarkers may reflect patients with more significant cardiovascular disease that may predispose to poor long-term outcomes independent of CA-AKI status.

Recovery after AKI: Effects on outcomes over 15 years.

PURPOSE: To examine the effect of kidney recovery on mortality, dialysis and kidney transplantation up to 15 years after AKI. MATERIALS AND METHODS: We studied 29,726 survivors of critical illness and compared these outcomes stratified by AKI and recovery status at hospital discharge. Kidney recovery was defined as a return of serum creatinine to ≤150% of baseline without dialysis prior to hospital discharge. RESULTS: Overall AKI occurred in 59.2% in which two thirds developed stage 2-3 AKI. Recovery rate of AKI at hospital discharge was 80.8%. Patients who did not recover experienced the worst 15-year mortality compared to those who recovered and those without AKI (57.8% vs 45.2% vs 30.3%, p < 0.001). This pattern was also found in subgroups of patients with suspected sepsis-associated (57.1% vs 47.9% vs 36.5%, p < 0.001) and cardiac surgery-associated AKI (60.1% vs 41.8% vs 25.9%, p < 0.001). The rates of dialysis and transplantation at 15 years were low and not associated with recovery status. CONCLUSIONS: Recovery of AKI in critically ill patients at hospital discharge had an effect on long-term mortality for up to 15 years. These results have implications for acute care, follow-up and choice of endpoints for clinical trials.

Case presentations of medication management for patients at risk for drug-associated acute kidney injury identified with a CDS system and a novel biomarker.

PURPOSE: Traditional methods used to evaluate changes in kidney function to identify acute kidney injury (AKI) have significant limitations. Damage biomarkers can identify patients at risk for AKI prior to changes in kidney function. While clinical trials have shown that biomarker-guided treatment can improve outcomes, whether these biomarkers can influence providers' choice of treatment strategy for risk prediction, surveillance, or diagnostic evaluation in clinical practice is uncertain. SUMMARY: This case series describes 4 patients at an academic medical center whose care was informed by kidney biomarker utilization in conjunction with a clinical decision support system (CDSS). Though each patient's clinical presentation was unique, kidney biomarkers were successfully employed as clinical tools in evaluating the risks and benefits of nephrotoxic medications. CONCLUSION: This case series demonstrates 4 scenarios in which a kidney injury biomarker used in conjunction with CDSS and consideration of the patients' clinical presentation informed treatment strategies with the intent to prevent AKI.

Interventions, Barriers, and Proposed Solutions Associated With the Implementation of a Protocol That Uses Clinical Decision Support and a Stress Biomarker Test to Identify ICU Patients at High-Risk for Drug Associated Acute Kidney Injury.

BACKGROUND: Damage biomarkers are helpful in early identification of patients who are at risk of developing acute kidney injury (AKI). Investigations are ongoing to identify the optimal role of stress/damage biomarkers in clinical practice regarding AKI risk prediction, surveillance, diagnosis, and prognosis. OBJECTIVE: To determine the impact of utilizing a clinical decision support system (CDSS) to guide stress biomarker testing in intensive care unit (ICU) patients at risk for drug-induced acute kidney injury (D-AKI). METHODS: A protocol was designed utilizing a clinical decision support system (CDSS) alert to identify patients that were ordered 3 or more potentially nephrotoxic medications, suggesting risk for progressing to AKI from nephrotoxic burden. Once alerted to these high-risk patients, the pharmacist determined if action was needed by ordering a stress biomarker test, tissue inhibitor of metalloproteinase-2-insulin-like growth factor-binding protein 7 (TIMP-2•IGFBP7). If the biomarker test result was elevated, the pharmacist provided nephrotoxin stewardship recommendations to the team. Pharmacists recorded the response to the clinical decision support alert, ordering, and interpreting the TIMP-2•IGFBP7, and information regarding clinical interventions. An alert in conjunction with TIMP-2•IGFBP7 as a strategy for AKI risk prediction and stimulant for patient care management was assessed. In addition, barriers and solutions to protocol implementation were evaluated. RESULTS: There were 394 total activities recorded by pharmacists for 345 unique patients. Ninety-three (93/394; 23.6%) actionable alerts resulted in a TIMP-2•IGFBP7 test being ordered. Thirty-one TIMP-2•IGFBP7 results were >0.3 (31/81; 38.3%), suggesting a high-risk of progression to AKI, which prompted 191 pharmacist/team interventions. On average, there were 1.64 interventions per patient in the low-risk patients, 3.43 in high-risk patients, and 3.75 in the highest-risk patients. CONCLUSION AND RELEVANCE: Stress biomarkers can be used in conjunction with CDSS alerts to affect therapeutic decisions in ICU patients at high-risk for D-AKI.

Fluid Overload and Precision Net Ultrafiltration in Critically Ill Patients.

BACKGROUND: Fluid overload is present in two-thirds of critically ill patients with acute kidney injury and is associated with morbidity, mortality, and increased healthcare resource utilization. Kidney replacement therapy is frequently used for net fluid removal (i.e., net ultrafiltration) in patients with severe oliguric acute kidney injury. However, ultrafiltration has considerable risks associated with it and there is a need for newer technology to perform ultrafiltration safely and to improve outcomes. SUMMARY: Caring for a critically ill patient with oliguric acute kidney injury and fluid overload is one of the most challenging problems. Although diuretics are the first line treatment for management of fluid overload, diuretic resistance is common. Various clinical practice guidelines support fluid removal using ultrafiltration during kidney replacement therapy. Emerging evidence from observational studies in critically ill patients suggests that both slow and fast rates of net fluid removal during continuous kidney replacement therapy are associated with increased mortality compared with moderate UFNET rates. In addition, fast UFNET rates are associated with an increased risk of cardiac arrhythmias. Randomized trials are required to examine whether moderate UFNET rates are associated with a reduced risk of hemodynamic instability, organ injury and improved outcomes in critically ill patients. There is a need for newer technology for fluid removal in patients who do not meet traditional criteria for initiation of KRT. Emerging newer and miniaturized ultrafiltration devices may address an unmet clinical need.

Predicting Mortality Using Machine Learning Algorithms in Patients Who Require Renal Replacement Therapy in the Critical Care Unit.

Background: General severity of illness scores are not well calibrated to predict mortality among patients receiving renal replacement therapy (RRT) for acute kidney injury (AKI). We developed machine learning models to make mortality prediction and compared their performance to that of the Sequential Organ Failure Assessment (SOFA) and HEpatic failure, LactatE, NorepInephrine, medical Condition, and Creatinine (HELENICC) scores. Methods: We extracted routinely collected clinical data for AKI patients requiring RRT in the MIMIC and eICU databases. The development models were trained in 80% of the pooled dataset and tested in the rest of the pooled dataset. We compared the area under the receiver operating characteristic curves (AUCs) of four machine learning models (multilayer perceptron [MLP], logistic regression, XGBoost, and random forest [RF]) to that of the SOFA, nonrenal SOFA, and HELENICC scores and assessed calibration, sensitivity, specificity, positive (PPV) and negative (NPV) predicted values, and accuracy. Results: The mortality AUC of machine learning models was highest for XGBoost (0.823; 95% confidence interval [CI], 0.791−0.854) in the testing dataset, and it had the highest accuracy (0.758). The XGBoost model showed no evidence of lack of fit with the Hosmer−Lemeshow test (p > 0.05). Conclusion: XGBoost provided the highest performance of mortality prediction for patients with AKI requiring RRT compared with previous scoring systems.

VASOPRESSOR-RESISTANT HYPOTENSION, COMBINATION VASOPRESSOR THERAPY, AND SHOCK PHENOTYPES IN CRITICALLY ILL ADULTS WITH VASODILATORY SHOCK.

ABSTRACT: Objective: To examine the risk factors, resource utilization, and 1-year mortality associated with vasopressor-resistant hypotension (VRH) compared with vasopressor-sensitive hypotension (VSH) among critically ill adults with vasodilatory shock. We also examined whether combination vasopressor therapy and patient phenotype were associated with mortality. Design: Retrospective cohort study. Setting: Eight medical-surgical intensive care units at the University of Pittsburgh Medical Center, Pittsburgh, PA. Patients : Critically ill patients with vasodilatory shock admitted between July 2000 and October 2008. Interventions : None. Measurements and Main Results: Vasopressor-resistant hypotension was defined as those requiring greater than 0.2 µg/kg per minute of norepinephrine equivalent dose of vasopressor consecutively for more than 6 h, and VSH was defined as patients requiring ≤0.2 µg/kg per minute to maintain MAP between 55 and 70 mm Hg after adequate fluid resuscitation. Of 5,313 patients with vasodilatory shock, 1,291 patients (24.3%) developed VRH. Compared with VSH, VRH was associated with increased risk of acute kidney injury (72.7% vs. 65.0%; P < 0.001), use of kidney replacement therapy (26.0% vs. 11.0%; P < 0.001), longer median (interquartile range [IQR]) intensive care unit length of stay (10 [IQR, 4.0-20.0] vs. 6 [IQR, 3.0-13.0] days; P < 0.001), and increased 1-year mortality (64.7% vs. 34.8%; P < 0.001). Vasopressor-resistant hypotension was associated with increased odds of risk-adjusted mortality (adjusted odds ratio [aOR], 2.93; 95% confidence interval [CI], 2.52-3.40; P < 0.001). When compared with monotherapy, combination vasopressor therapy with two (aOR, 0.91; 95% CI, 0.78-1.06) and three or more vasopressors was not associated with lower mortality (aOR, 0.93; 95% CI, 0.68-1.27). Using a finite mixture model, we identified four unique phenotypes of patient clusters that differed with respect to demographics, severity of illness, processes of care, vasopressor use, and outcomes. Conclusions: Among critically ill patients with vasodilatory shock, VRH compared with VSH is associated with increased resource utilization and long-term risk of death. However, combination vasopressor therapy was not associated with lower risk of death. We identified four unique phenotypes of patient clusters that require further validation.

Association of Metformin Use During Hospitalization and Mortality in Critically Ill Adults With Type 2 Diabetes Mellitus and Sepsis.

OBJECTIVES: Whether metformin exposure is associated with improved outcomes in patients with type 2 diabetes mellitus and sepsis. DESIGN: Retrospective cohort study. SETTING: Patients admitted to ICUs in 16 hospitals in Pennsylvania from October 2008 to December 2014. PATIENTS: Adult critical ill patients with type 2 diabetes mellitus and sepsis. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: We conducted a retrospective cohort study to compare 90-day mortality in diabetic patients with sepsis with and without exposure to metformin during hospitalization. Data were obtained from the electronic health record of a large healthcare system in Pennsylvania from October 2008 to December 2014, on patients admitted to the ICU at any of the 16 hospitals within the system. The primary outcome was mortality at 90 days. The absolute and adjusted odds ratio (OR) with 95% CI were calculated in a propensity score-matched cohort. Among 14,847 patients with type 2 diabetes mellitus and sepsis, 682 patients (4.6%) were exposed to metformin during hospitalization and 14,165 (95.4%) were not. Within a total of 2,691 patients subjected to propensity score-matching at a 1:4 ratio, exposure to metformin (n = 599) was associated with decreased 90-day mortality (71/599, 11.9% vs 475/2,092, 22.7%; OR, 0.46; 95% CI, 0.35-0.60), reduced severe acute kidney injury (50% vs 57%; OR, 0.75; 95% CI, 0.62-0.90), less Major Adverse Kidney Events at 1 year (OR, 0.27; 95% CI, 0.22-0.68), and increased renal recovery (95% vs 86%; OR, 6.43; 95% CI, 3.42-12.1). CONCLUSIONS: Metformin exposure during hospitalization is associated with a decrease in 90-day mortality in patients with type 2 diabetes mellitus and sepsis.

Association between Net Ultrafiltration Rate and Renal Recovery among Critically Ill Adults with Acute Kidney Injury Receiving Continuous Renal Replacement Therapy: An Observational Cohort Study.

INTRODUCTION: Higher net ultrafiltration (UFNET) rates are associated with mortality among critically ill patients with acute kidney injury (AKI) and treated with continuous renal replacement therapy (CRRT). OBJECTIVE: The aim of the study was to discover whether UFNET rates are associated with renal recovery and independence from renal replacement therapy (RRT). METHODS: Retrospective cohort study using data from the Randomized Evaluation of Normal versus Augmented Level of Renal Replacement Therapy trial that enrolled 1,433 critically ill patients with AKI and treated with CRRT between December 2005 and November 2008 across 35 intensive care units in Australia and New Zealand. We examined the association between UFNET rate and time to independence from RRT by day 90 using competing risk regression after accounting for mortality. The UFNET rate was defined as the volume of fluid removed per hour adjusted for patient body weight. RESULTS AND CONCLUSIONS: Median age was 67.3 (interquartile range [IQR], 57-76.3) years, 64.4% were male, median Acute Physiology and Chronic Health Evaluation-III score was 100 (IQR, 84-118), and 634 (44.2%) died by day 90. Kidney recovery occurred in 755 patients (52.7%). Using tertiles of UFNET rates, 3 groups were defined: high, >1.75; middle, 1.01-1.75; and low, <1.01 mL/kg/h. Proportion of patients alive and independent of RRT among the groups were 47.8 versus 57.2 versus 53.0%; p = 0.01. Using competing risk regression, higher UFNET rate tertile compared with middle (cause-specific hazard ratio [csHR], 0.79, 95% CI, 0.66-0.95; subdistribution hazard ratio [sHR], 0.80, 95% CI, 0.67-0.97) and lower (csHR, 0.69, 95% CI, 0.56-0.85; sHR, 0.78, 95% CI 0.64-0.95) tertiles were associated with a longer time to independence from RRT. Every 1.0 mL/kg/h increase in rate was associated with a lower probability of kidney recovery (csHR, 0.81, 95% CI, 0.74-0.89; and sHR, 0.87, 95% CI, 0.80-0.95). Using the joint model, longitudinal increases in UFNET rates were also associated with a lower renal recovery (ß = -0.29, p < 0.001). UFNET rates >1.75 mL/kg/h compared with rates 1.01-1.75 and <1.01 mL/kg/h were associated with a longer duration of dependence on RRT. Randomized clinical trials are required to confirm this UFNET rate-outcome relationship.