Trajectory of Kidney Function: The Canary in Sepsis.
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ABSTRACT:
SUBMITTER: Bhatraju PK
PROVIDER: S-EPMC7605179 | biostudies-literature | 2020 Nov
REPOSITORIES: biostudies-literature
Publications
Trajectory of Kidney Function: The Canary in Sepsis.
Bhatraju Pavan K PK Wurfel Mark M MM Himmelfarb Jonathan J
American journal of respiratory and critical care medicine 20201101 9
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Project description:Autosomal dominant polycystic kidney disease (ADPKD) is characterized by cyst and kidney growth, which is hypothesized to cause loss of functioning renal mass and eventually end-stage kidney disease. However, the time course of decline in glomerular filtration rate (GFR) is poorly defined. The Consortium for Radiologic Imaging Studies of Polycystic Kidney Disease study is a 14-year observational cohort study of 241 adults with ADPKD. As an estimate of the rate of kidney growth, participants were stratified into 5 subclasses based on baseline age and magnetic resonance imaging measurements of total kidney volume (TKV) according to the method of Irazabal. GFR trajectories spanning over four decades of life were reconstructed and fitted using mixed polynomial models, which were validated using data from the HALT-PKD study. GFR trajectories were nonlinear, with a period of relative stability in most participants, followed by accelerating decline. The shape and slope of these trajectories were strongly associated with baseline Irazabal class. Patients with PKD1 mutations had a steeper GFR decline than patients with PKD2 mutations or with no detected mutation, largely mediated by the effect of genotype on Irazabal class. Thus, GFR decline in ADPKD is nonlinear, and its trajectory throughout adulthood can be predicted from a single measurement of kidney volume. These models can be used for clinical prognostication, clinical trial design, and patient selection for clinical interventions. Our findings support a causal link between growth in kidney volume and GFR decline, adding support for the use of TKV as a surrogate endpoint in clinical trials.
| S-EPMC6478515 | biostudies-literature
Project description:Rationale & objectiveEarly prediction of chronic kidney disease (CKD) progression to end-stage kidney disease (ESKD) currently use Cox models including baseline estimated glomerular filtration rate (eGFR) only. Alternative approaches include a Cox model that includes eGFR slope determined over a baseline period of time, a Cox model with time varying GFR, or a joint modeling approach. We studied if these more complex approaches may further improve ESKD prediction.Study designProspective cohort.Setting & participantsWe re-used data from two CKD cohorts including patients with baseline eGFR >30ml/min per 1.73m2. MASTERPLAN (N = 505; 55 ESKD events) was used as development dataset, and NephroTest (N = 1385; 72 events) for validation.PredictorsAll models included age, sex, eGFR, and albuminuria, known prognostic markers for ESKD.Analytical approachWe trained the models on the MASTERPLAN data and determined discrimination and calibration for each model at 2 years follow-up for a prediction horizon of 2 years in the NephroTest cohort. We benchmarked the predictive performance against the Kidney Failure Risk Equation (KFRE).ResultsThe C-statistics for the KFRE was 0.94 (95%CI 0.86 to 1.01). Performance was similar for the Cox model with time-varying eGFR (0.92 [0.84 to 0.97]), eGFR (0.95 [0.90 to 1.00]), and the joint model 0.91 [0.87 to 0.96]). The Cox model with eGFR slope showed the best calibration.ConclusionIn the present studies, where the outcome was rare and follow-up data was highly complete, the joint models did not offer improvement in predictive performance over more traditional approaches such as a survival model with time-varying eGFR, or a model with eGFR slope.
| S-EPMC6508737 | biostudies-literature
Project description:AimThe features and outcomes of sepsis-associated acute kidney injury (SA-AKI) may be affected by chronic kidney disease (CKD). Accordingly, we aimed to compare SA-AKI in patients with or without CKD.MethodsRetrospective cohort study in 12 intensive care units (ICU). We studied the prevalence, patient characteristics, timing, trajectory, treatment and outcomes of SA-AKI with and without CKD.ResultsOf 84 240 admissions, 7255 (8.6%) involved patients with CKD. SA-AKI was more common in patients with CKD (21% vs 14%; p < .001). CKD patients were older (70 vs. 60 years; p < .001), had a higher median Charlson co-morbidity index (5 vs. 3; p < .001) and acute physiology and chronic health evaluation (APACHE) III score (78 vs. 60; p < .001) and were more likely to receive renal replacement therapy (RRT) (25% vs. 17%; p < .001). They had less complete return to baseline function at ICU discharge (48% vs. 60%; p < .001), higher major adverse kidney events at day 30 (MAKE-30) (38% vs. 27%; p < .001), and higher hospital and 90-day mortality (21% vs. 13%; p < .001, and 27% vs. 16%; p < .001, respectively). After adjustment for patient characteristics and severity of illness, however, CKD was not an independent risk factor for increased 90-day mortality (OR 0.88; 95% CI 0.76-1.02; p = .08) or MAKE-30 (OR 0.98; 95% CI 0.80-1.09; p = .4).ConclusionSA-AKI is more common in patients with CKD. Such patients are older, more co-morbid, have higher disease severity, receive different ICU therapies and have different trajectories of renal recovery and greater unadjusted mortality. However, after adjustment day-90 mortality and MAKE-30 risk were not increased by CKD.
| S-EPMC11579568 | biostudies-literature
Project description:ObjectivesCognitive impairment is an important consequence of sepsis. We sought to determine long-term trajectories of cognitive function after sepsis.DesignProspective study of the Reasons for Geographic and Racial Differences in Stroke cohort.SettingUnited States.PatientsTwenty-one thousand eight-hundred twenty-three participants greater than or equal to 45 years, mean (sd) age 64.3 (9.2) years at first cognitive assessment, 30.9% men, and 27.1% Black.Measurements and main resultsThe main exposure was time-dependent sepsis hospitalization. The primary outcome was global cognitive function (Six-Item Screener range, 0-6). Secondary outcomes were incident cognitive impairment (Six-Item Screener score ≤ 4 [impaired] vs ≥5 [unimpaired]), new learning (Consortium to Establish a Registry for Alzheimer Disease Word List Learning range, 0-30), verbal memory (word list delayed recall range, 0-10), and executive function/semantic fluency (animal fluency test range, ≥ 30). Over a median follow-up of 10 years (interquartile range, 6-12 yr), 840 (3.8%) experienced sepsis (incidence 282 per 1,000 person-years). Sepsis was associated with faster long-term declines in Six-Item Screener (-0.02 points per year faster [95% CI, -0.01 to -0.03]; p < 0.001) and faster long-term rates of incident cognitive impairment (odds ratio 1.08 per year [95% CI, 1.02-1.15]; p = 0.008) compared with presepsis slopes. Although cognitive function acutely changed after sepsis (0.05 points [95% CI, 0.01-0.09]; p = 0.01), the odds of acute cognitive impairment (Six-Item Screener ≤ 4) immediately after sepsis was not significant (odds ratio, 0.81 [95% CI, 0.63-1.06]; p = 0.12). Sepsis hospitalization was not associated with acute changes or faster declines in word list learning, word list delayed recall, or animal fluency test.ConclusionsSepsis is associated with accelerated long-term decline in global cognitive function.
| S-EPMC8217073 | biostudies-literature
Project description:BackgroundSepsis is a heterogeneous syndrome. This study aimed to identify new sepsis sub-phenotypes using plasma cortisol trajectory.MethodsThis retrospective study included patients with sepsis admitted to the intensive care unit of Zhongshan Hospital Fudan University between March 2020 and July 2022. A group-based cortisol trajectory model was used to classify septic patients into different sub-phenotypes. The clinical characteristics, biomarkers, and outcomes were compared between sub-phenotypes.ResultsA total of 258 patients with sepsis were included, of whom 186 were male. Patients were divided into two trajectory groups: the lower-cortisol group (n = 217) exhibited consistently low and slowly declining cortisol levels, while the higher-cortisol group (n = 41) showed relatively higher levels in comparison. The 28-day mortality (65.9% vs.16.1%, P < 0.001) and 90-day mortality (65.9% vs. 19.8%, P < 0.001) of the higher-cortisol group were significantly higher than the lower-cortisol group. Multivariable Cox regression analysis showed that the trajectory sub-phenotype (HR = 5.292; 95% CI 2.218-12.626; P < 0.001), APACHE II (HR = 1.109; 95% CI 1.030-1.193; P = 0.006), SOFA (HR = 1.161; 95% CI 1.045-1.291; P = 0.006), and IL-1β (HR = 1.001; 95% CI 1.000-1.002; P = 0.007) were independent risk factors for 28-day mortality. Besides, the trajectory sub-phenotype (HR = 4.571; 95% CI 1.980-10.551; P < 0.001), APACHE II (HR = 1.108; 95% CI 1.043-1.177; P = 0.001), SOFA (HR = 1.270; 95% CI 1.130-1.428; P < 0.001), and IL-1β (HR = 1.001; 95% CI 1.000-1.001; P = 0.015) were also independent risk factors for 90-day mortality.ConclusionThis study identified two novel cortisol trajectory sub-phenotypes in patients with sepsis. The trajectories were associated with mortality, providing new insights into sepsis classification.
| S-EPMC11370002 | biostudies-literature
Project description:BackgroundSepsis is a heterogeneous syndrome, and the identification of clinical subphenotypes is essential. Although organ dysfunction is a defining element of sepsis, subphenotypes of differential trajectory are not well studied. We sought to identify distinct Sequential Organ Failure Assessment (SOFA) score trajectory-based subphenotypes in sepsis.MethodsWe created 72-h SOFA score trajectories in patients with sepsis from four diverse intensive care unit (ICU) cohorts. We then used dynamic time warping (DTW) to compute heterogeneous SOFA trajectory similarities and hierarchical agglomerative clustering (HAC) to identify trajectory-based subphenotypes. Patient characteristics were compared between subphenotypes and a random forest model was developed to predict subphenotype membership at 6 and 24 h after being admitted to the ICU. The model was tested on three validation cohorts. Sensitivity analyses were performed with alternative clustering methodologies.ResultsA total of 4678, 3665, 12,282, and 4804 unique sepsis patients were included in development and three validation cohorts, respectively. Four subphenotypes were identified in the development cohort: Rapidly Worsening (n = 612, 13.1%), Delayed Worsening (n = 960, 20.5%), Rapidly Improving (n = 1932, 41.3%), and Delayed Improving (n = 1174, 25.1%). Baseline characteristics, including the pattern of organ dysfunction, varied between subphenotypes. Rapidly Worsening was defined by a higher comorbidity burden, acidosis, and visceral organ dysfunction. Rapidly Improving was defined by vasopressor use without acidosis. Outcomes differed across the subphenotypes, Rapidly Worsening had the highest in-hospital mortality (28.3%, P-value < 0.001), despite a lower SOFA (mean: 4.5) at ICU admission compared to Rapidly Improving (mortality:5.5%, mean SOFA: 5.5). An overall prediction accuracy of 0.78 (95% CI, [0.77, 0.8]) was obtained at 6 h after ICU admission, which increased to 0.87 (95% CI, [0.86, 0.88]) at 24 h. Similar subphenotypes were replicated in three validation cohorts. The majority of patients with sepsis have an improving phenotype with a lower mortality risk; however, they make up over 20% of all deaths due to their larger numbers.ConclusionsFour novel, clinically-defined, trajectory-based sepsis subphenotypes were identified and validated. Identifying trajectory-based subphenotypes has immediate implications for the powering and predictive enrichment of clinical trials. Understanding the pathophysiology of these differential trajectories may reveal unanticipated therapeutic targets and identify more precise populations and endpoints for clinical trials.
| S-EPMC9250715 | biostudies-literature
Project description:Timing and extent of kidney function recovery after an acute kidney injury (AKI) episode are associated with chronic kidney disease onset and progression. This study aimed to categorize AKI recovery patterns within 6 months after index hospital discharge and associate them with kidney outcomes. This was a retrospective cohort study of 234,867 patients, hospitalized between 2010 and 2017, and classified as AKI or no AKI. Kidney function recovery from pre-hospitalization baseline within 1.5× serum creatinine (SCr) were evaluated at 3 and 6 months after hospital discharge and categorized as persistent non-recovery (PNR: SCr not recovered at 3 and 6 months), non-recovery (NR: SCr not recovered at 6 months), and recovery (SCr recovered at 6 months). A composite of incident chronic kidney disease, kidney replacement therapy, and estimated glomerular filtration rate reduction >30% from baseline and <15 mL/min/1.73 m2 was evaluated. Of 14,673 AKI surviving patients, 10.18% had PNR and 14.33% showed NR. Compared with no AKI, PNR and NR of AKI were associated with an increased risk of composite adverse outcomes (adjusted subdistribution hazard ratio (SHR) 4.55; 95% CI, 4.05-5.11; SHR, 3.54; 95% CI, 3.18-3.94, respectively). Patients with NR showed a greater risk of adverse outcomes than those with non-rapid recovery at 3 months after hospital discharge. The AKI recovery pattern within 6 months following inpatient care revealed an increasing continuum of risk of long-term adverse kidney outcomes. Risk stratification and a kidney function monitoring plan at discharge are needed to improve post-AKI care.
| S-EPMC9605305 | biostudies-literature
Project description:BackgroundPrior nonrandomized studies have suggested nephroprotective effects of arteriovenous fistula (AVF) formation, but these are plausibly susceptible to immortal time and selection biases.MethodsWe studied patients attending nephrology clinics in the West of Scotland during 2010-22 with an estimated glomerular filtration rate (eGFR) ≤15 mL/min/1.73 m2 and no prior AVF. Using target trial emulation and a sequential trial design, we simulated a hypothetical trial that would randomize patients to either undergo AVF formation immediately or not to undergo AVF formation. The primary outcome was the difference in eGFR slope for the first 6 months of follow-up, estimated using a mixed-effects model. The secondary outcomes were 5-year absolute risks of dialysis and death, estimated using the Aalen-Johansen and Kaplan-Meier estimators respectively.ResultsA total of 1364 unique patients (mean age 51.1 years, 55.7% male) contributed 3125 person-trials, with 561 in the AVF and 2564 in the no AVF group. Mean eGFR was 12.6 mL/min/1.73 m2 and the median number of eGFR measurements per person-trial was 7 (interquartile range 4-12). Slope of eGFR decline did not differ significantly between the AVF and no AVF groups (between-group difference -0.67 mL/min/1.73 m2/year, 95% CI -1.43, 0.10). The 5-year absolute risk of dialysis was 87% (95% CI 84, 91) in the AVF group and 75% (95% CI 73, 77) in the no AVF group, and the 5-year survival probability was 77% (95% CI 70, 83) in the AVF group and 67% (95% CI 64, 69) in the no AVF group.ConclusionsIn this study of patients with advanced chronic kidney disease, there was no evidence of a nephroprotective effect of AVF formation.
| S-EPMC11647593 | biostudies-literature
Project description:The quick Sequential Organ Failure Assessment (qSOFA) system identifies an individual's risk to progress to poor sepsis-related outcomes using minimal variables. We used Support Vector Machine, Learning Using Concave and Convex Kernels, and Random Forest to predict an increase in qSOFA score using electronic health record (EHR) data, electrocardiograms (ECG), and arterial line signals. We structured physiological signals data in a tensor format and used Canonical Polyadic/Parallel Factors (CP) decomposition for feature reduction. Random Forests trained on ECG data show improved performance after tensor decomposition for predictions in a 6-h time frame (AUROC 0.67 ± 0.06 compared to 0.57 ± 0.08, p=0.01 ). Adding arterial line features can also improve performance (AUROC 0.69 ± 0.07, p<0.01 ), and benefit from tensor decomposition (AUROC 0.71 ± 0.07, p=0.01 ). Adding EHR data features to a tensor-reduced signal model further improves performance (AUROC 0.77 ± 0.06, p<0.01 ). Despite reduction in performance going from an EHR data-informed model to a tensor-reduced waveform data model, the signals-informed model offers distinct advantages. The first is that predictions can be made on a continuous basis in real-time, and second is that these predictions are not limited by the availability of EHR data. Additionally, structuring the waveform features as a tensor conserves structural and temporal information that would otherwise be lost if the data were presented as flat vectors.
| S-EPMC11300462 | biostudies-literature
Project description:PurposeThe Acute Disease Quality Initiative (ADQI) Workgroup recently released a consensus definition of sepsis-associated acute kidney injury (SA-AKI), combining Sepsis-3 and Kidney Disease Improving Global Outcomes (KDIGO) AKI criteria. This study aims to describe the epidemiology of SA-AKI.MethodsThis is a retrospective cohort study carried out in 12 intensive care units (ICUs) from 2015 to 2021. We studied the incidence, patient characteristics, timing, trajectory, treatment, and associated outcomes of SA-AKI based on the ADQI definition.ResultsOut of 84,528 admissions, 13,451 met the SA-AKI criteria with its incidence peaking at 18% in 2021. SA-AKI patients were typically admitted from home via the emergency department (ED) with a median time to SA-AKI diagnosis of 1 day (interquartile range (IQR) 1-1) from ICU admission. At diagnosis, most SA-AKI patients (54%) had a stage 1 AKI, mostly due to the low urinary output (UO) criterion only (65%). Compared to diagnosis by creatinine alone, or by both UO and creatinine criteria, patients diagnosed by UO alone had lower renal replacement therapy (RRT) requirements (2.8% vs 18% vs 50%; p < 0.001), which was consistent across all stages of AKI. SA-AKI hospital mortality was 18% and SA-AKI was independently associated with increased mortality. In SA-AKI, diagnosis by low UO only, compared to creatinine alone or to both UO and creatinine criteria, carried an odds ratio of 0.34 (95% confidence interval (CI) 0.32-0.36) for mortality.ConclusionSA-AKI occurs in 1 in 6 ICU patients, is diagnosed on day 1 and carries significant morbidity and mortality risk with patients mostly admitted from home via the ED. However, most SA-AKI is stage 1 and mostly due to low UO, which carries much lower risk than diagnosis by other criteria.
| S-EPMC10499944 | biostudies-literature