Background and objectives: Sepsis-associated AKI is a heterogeneous clinical entity. We aimed to agnostically identify sepsis-associated AKI subphenotypes using deep learning on routinely collected data in electronic health records. Design, setting, participants, & measurements: We used the Medical Information Mart for Intensive Care III database, which consists of electronic health record data from intensive care units in a tertiary care hospital in the United States. We included patients ≥18 years with sepsis who developed AKI within 48 hours of intensive care unit admission. We then used deep learning to utilize all available vital signs, laboratory measurements, and comorbidities to identify subphenotypes. Outcomes were mortality 28 days after AKI and dialysis requirement. Results: We identified 4001 patients with sepsis-associated AKI. We utilized 2546 combined features for K-means clustering, identifying three subphenotypes. Subphenotype 1 had 1443 patients, and subphenotype 2 had 1898 patients, whereas subphenotype 3 had 660 patients. Subphenotype 1 had the lowest proportion of liver disease and lowest Simplified Acute Physiology Score II scores compared with subphenotypes 2 and 3. The proportions of patients with CKD were similar between subphenotypes 1 and 3 (15%) but highest in subphenotype 2 (21%). Subphenotype 1 had lower median bilirubin levels, aspartate aminotransferase, and alanine aminotransferase compared with subphenotypes 2 and 3. Patients in subphenotype 1 also had lower median lactate, lactate dehydrogenase, and white blood cell count than patients in subphenotypes 2 and 3. Subphenotype 1 also had lower creatinine and BUN than subphenotypes 2 and 3. Dialysis requirement was lowest in subphenotype 1 (4% versus 7% [subphenotype 2] versus 26% [subphenotype 3]). The mortality 28 days after AKI was lowest in subphenotype 1 (23% versus 35% [subphenotype 2] versus 49% [subphenotype 3]). After adjustment, the adjusted odds ratio for mortality for subphenotype 3, with subphenotype 1 as a reference, was 1.9 (95% confidence interval, 1.5 to 2.4). Conclusions: Utilizing routinely collected laboratory variables, vital signs, and comorbidities, we were able to identify three distinct subphenotypes of sepsis-associated AKI with differing outcomes.

Background and objectives: Hypernatremia is common in hospitalized, critically ill patients. Although there are no clear guidelines on sodium correction rate for hypernatremia, some studies suggest a reduction rate not to exceed 0.5 mmol/L per hour. However, the data supporting this recommendation and the optimal rate of hypernatremia correction in hospitalized adults are unclear. Design, setting, participants, & measurements: We assessed the association of hypernatremia correction rates with neurologic outcomes and mortality in critically ill patients with hypernatremia at admission and those that developed hypernatremia during hospitalization. We used data from the Medical Information Mart for Intensive Care-III and identified patients with hypernatremia (serum sodium level >155 mmol/L) on admission (n=122) and hospital-acquired (n=327). We calculated different ranges of rapid correction rates (>0.5 mmol/L per hour overall and >8, >10, and >12 mmol/L per 24 hours) and utilized logistic regression to generate adjusted odds ratios (aOR) with 95% confidence intervals (95% CIs) to examine association with outcomes. Results: We had complete data on 122 patients with severe hypernatremia on admission and 327 patients who developed hospital-acquired hypernatremia. The difference in in-hospital 30-day mortality proportion between rapid (>0.5 mmol/L per hour) and slower (≤0.5 mmol/L per hour) correction rates were not significant either in patients with hypernatremia at admission with rapid versus slow correction (25% versus 28%; P=0.80) or in patients with hospital-acquired hypernatremia with rapid versus slow correction (44% versus 40%; P=0.50). There was no difference in aOR of mortality for rapid versus slow correction in either admission (aOR, 1.3; 95% CI, 0.5 to 3.7) or hospital-acquired hypernatremia (aOR, 1.3; 95% CI, 0.8 to 2.3). Manual chart review of all suspected chronic hypernatremia patients, which included all 122 with hypernatremia at admission, 128 of the 327 hospital-acquired hypernatremia, and an additional 28 patients with ICD-9 codes for cerebral edema, seizures and/or alteration of consciousness, did not reveal a single case of cerebral edema attributable to rapid hyprnatremia correction. Conclusions: We did not find any evidence that rapid correction of hypernatremia is associated with a higher risk for mortality, seizure, alteration of consciousness, and/or cerebral edema in critically ill adult patients with either admission or hospital-acquired hypernatremia.

Background: Etiologies for acute kidney injury (AKI) vary by geographic region and socioeconomic status. While considerable information is now available on AKI in the Americas, Europe and China, large comprehensive epidemiologic studies of AKI from Southeast Asia (SEA) are still lacking. The aim of this study was to investigate the rates and characteristics of AKI among intensive care unit (ICU) patients in Thailand. Methods: We conducted the largest prospective observational study of AKI in SEA. The data were serially collected on the first 28 days of ICU admission by registration in electronic web-based format. AKI status was defined by full Kidney Disease: Improving Global Outcome criteria. We used AKI occurrence as the clinical outcome and explored the impact of modifiable and non-modifiable risk factors on the development and progression of AKI. Results: We enrolled 5476 patients from 17 ICU centres across Thailand from February 2013 to July 2015. After excluding patients with end-stage renal disease and those with incomplete data, AKI occurred in 2471 of 4668 patients (52.9%). Overall, the maximum AKI stage was Stage 1 in 7.5%, Stage 2 in 16.5% and Stage 3 in 28.9%. In the multivariable adjusted model, we found that older age, female sex, admission to a regional hospital, medical ICU, high body mass index, primary diagnosis of cardiovascular-related disease and infectious disease, higher Acute Physiology and Chronic Health Evaluation II, non-renal Sequential Organ Failure Assessment scores, underlying anemia and use of vasopressors were all independent risk factors for AKI development. Conclusions: In Thai ICUs, AKI is very common. Identification of risk factors of AKI development will help in the development of a prognostic scoring model for this population and should help in decision making for timely intervention, ultimately leading to better clinical outcomes.

Very-low-carbohydrate diets or ketogenic diets are frequently used for weight loss in adults and as a therapy for epilepsy in children. The incidence and characteristics of kidney stones in patients on ketogenic diets are not well studied. Methods: A systematic literature search was performed, using MEDLINE, EMBASE, and Cochrane Database of Systematic Reviews from the databases’ inception through April 2020. Observational studies or clinical trials that provide data on the incidence and/or types of kidney stones in patients on ketogenic diets were included. We applied a random-effects model to estimate the incidence of kidney stones. Results: A total of 36 studies with 2795 patients on ketogenic diets were enrolled. The estimated pooled incidence of kidney stones was 5.9% (95% CI, 4.6–7.6%, I2 = 47%) in patients on ketogenic diets at a mean follow-up time of 3.7 +/− 2.9 years. Subgroup analyses demonstrated the estimated pooled incidence of kidney stones of 5.8% (95% CI, 4.4–7.5%, I2 = 49%) in children and 7.9% (95% CI, 2.8–20.1%, I2 = 29%) in adults, respectively. Within reported studies, 48.7% (95% CI, 33.2–64.6%) of kidney stones were uric stones, 36.5% (95% CI, 10.6–73.6%) were calcium-based (CaOx/CaP) stones, and 27.8% (95% CI, 12.1–51.9%) were mixed uric acid and calcium-based stones, respectively. Conclusions: The estimated incidence of kidney stones in patients on ketogenic diets is 5.9%. Its incidence is approximately 5.8% in children and 7.9% in adults. Uric acid stones are the most prevalent kidney stones in patients on ketogenic diets followed by calcium-based stones. These findings may impact the prevention and clinical management of kidney stones in patients on ketogenic diets.

Contrast-induced acute kidney injury (CI-AKI) is the most common iatrogenic cause of acute kidney injury after intravenous contrast media administration. In general, the incidence of CI-AKI is low in patients with normal renal function. However, the rate is remarkably elevated in patients with preexisting chronic kidney disease, diabetes mellitus, old age, high volume of contrast agent, congestive heart failure, hypotension, anemia, use of nephrotoxic drug, and volume depletion. Consequently, CI-AKI particularly in high risk patients contributes to extended hospitalizations and increases long-term morbidity and mortality. The pathogenesis of CI-AKI involves at least three mechanisms; contrast agents induce renal vasoconstriction, increase of oxygen free radicals through oxidative stress, and direct tubular toxicity. Several strategies to prevent CI-AKI have been evaluated in experimental studies and clinical trials. At present, intravascular volume expansion with either isotonic saline or sodium bicarbonate solutions has provided more consistent positive results and was recommended in the prevention of CI-AKI. However, the proportion of patients with risk still develops CI-AKI. This review critically evaluated the current evidence for pharmacological strategies to prevent CI-AKI in patients with a risk of developing CI-AKI.