Raymond K. Hsu

Temporal Changes in Incidence of Dialysis-Requiring AKI

The population epidemiology of AKI is not well described. Here, we analyzed data from the Nationwide Inpatient Sample, a nationally representative dataset, to identify cases of dialysis-requiring AKI using validated International Classification of Diseases, Ninth Revision (ICD-9) codes. From 2000 to 2009, the incidence of dialysis-requiring AKI increased from 222 to 533 cases per million person-years, averaging a 10% increase per year (incidence rate ratio=1.10, 95% CI=1.10-1.11 per year). Older age, male sex, and black race associated with higher incidence of dialysis-requiring AKI. The rapid increase in incidence was evident in all age, sex, and race subgroups examined. Temporal changes in the population distribution of age, race, and sex as well as trends of sepsis, acute heart failure, and receipt of cardiac catheterization and mechanical ventilation accounted for about one third of the observed increase in dialysis-requiring AKI among hospitalized patients. The total number of deaths associated with dialysis-requiring AKI rose from 18,000 in 2000 to nearly 39,000 in 2009. In conclusion, the incidence of dialysis-requiring AKI increased rapidly in all patient subgroups in the past decade in the United States, and the number of deaths associated with dialysis-requiring AKI more than doubled.

Elevated BP after AKI

The connection between AKI and BP elevation is unclear. We conducted a retrospective cohort study to evaluate whether AKI in the hospital is independently associated with BP elevation during the first 2 years after discharge among previously normotensive adults. We studied adult members of Kaiser Permanente Northern California, a large integrated health care delivery system, who were hospitalized between 2008 and 2011, had available preadmission serum creatinine and BP measures, and were not known to be hypertensive or have BP>140/90 mmHg. Among 43,611 eligible patients, 2451 experienced AKI defined using observed changes in serum creatinine concentration measured during hospitalization. Survivors of AKI were more likely than those without AKI to have elevated BP--defined as documented BP>140/90 mmHg measured during an ambulatory, nonemergency department visit--during follow-up (46.1% versus 41.2% at 730 days; P<0.001). This difference was evident within the first 180 days (30.6% versus 23.1%; P<0.001). In multivariable models, AKI was independently associated with a 22% (95% confidence interval, 12% to 33%) increase in the odds of developing elevated BP during follow-up, with higher adjusted odds with more severe AKI. Results were similar in sensitivity analyses when elevated BP was defined as having at least two BP readings of >140/90 mmHg or those with evidence of CKD were excluded. We conclude that AKI is an independent risk factor for subsequent development of elevated BP. Preventing AKI during a hospitalization may have clinical and public health benefits beyond the immediate hospitalization.

FGF-23 and PTH levels in patients with acute kidney injury: A cross-sectional case series study

BackgroundFibroblast growth factor-23 (FGF-23), a novel regulator of mineral metabolism, is markedly elevated in chronic kidney disease and has been associated with poor long-term outcomes. However, whether FGF-23 has an analogous role in acute kidney injury is unknown. The goal of this study was to measure FGF-23 levels in critically ill patients with acute kidney injury to determine whether FGF-23 levels were elevated, as in chronic kidney disease.MethodsPlasma FGF-23 and intact parathyroid hormone (PTH) levels were measured in 12 patients with acute kidney injury and 8 control subjects.ResultsFGF-23 levels were significantly higher in acute kidney injury cases than in critically ill subjects without acute kidney injury, with a median FGF-23 level of 1948 RU/mL (interquartile range (IQR), 437-4369) in cases compared with 252 RU/mL (IQR, 65-533) in controls (p = 0.01). No correlations were observed between FGF-23 and severity of acute kidney injury (defined by the Acute Kidney Injury Network criteria); among patients with acute kidney injury, FGF-23 levels were higher in nonsurvivors than survivors (median levels of 4446 RU/mL (IQR, 3455-5443) versus 544 RU/mL (IQR, 390-1948; p = 0.02). Severe hyperparathyroidism (defined as intact PTH >250 mg/dL) was present in 3 of 12 (25%) of the acute kidney injury subjects versus none of the subjects without acute kidney injury, although this result did not meet statistical significance.ConclusionsWe provide novel data that demonstrate that FGF-23 levels are elevated in acute kidney injury, suggesting that FGF-23 dysregulation occurs in acute kidney injury as well as chronic kidney disease. Further studies are needed to define the short- and long-term clinical effects of dysregulated mineral metabolism in acute kidney injury patients.

Proteinuria and reduced glomerular filtration rate as risk factors for acute kidney injury.

Purpose of reviewAcute kidney injury (AKI) is a major public health concern, and preexisting kidney disease may be one of the most important risk factors. We review recent epidemiologic evidence supporting baseline proteinuria and reduced glomerular filtration rate as risk factors for AKI. Recent findingsIn 2008, a case–control study of over 600 000 patients in an integrated healthcare system in California first quantified a graded association between reduced baseline estimated glomerular filtration rate (eGFR) and risk of dialysis-requiring AKI; it also showed proteinuria as an independent predictor for AKI. In 2010, a cohort study consisting of 1235 adults undergoing coronary artery bypass graft in Taiwan demonstrated that mild and heavy degrees of proteinuria detected by dipstick were associated with increasingly higher odds ratio of postoperative AKI, independent of chronic kidney disease stage. A US cohort study in 2010 of over 11 000 patients determined that elevated urine albumin-to-creatinine ratio (UACR) was an independent risk factor for hospitalizations with AKI; this association started with the submicroalbuminuric range (UACR 11–29 mg/g) and increased stepwise along severity of albuminuria, after adjustment for eGFR. A cohort study in 2010 of over 900 000 adults in Alberta demonstrated increased rates of hospital admissions with AKI for patients with mild and moderate dipstick proteinuria across all values of eGFR. SummaryThe presence of baseline proteinuria and reduced baseline eGFR are powerful independent predictors for AKI and should be taken into account in clinical practice to identify high-risk patients for receipt of aggressive preventive measures to reduce risk of AKI.

The Role of Acute Kidney Injury in Chronic Kidney Disease.

There is increasing recognition that acute kidney injury (AKI) and chronic kidney disease (CKD) are closely linked and likely promote one another. Underlying CKD now is recognized as a clear risk factor for AKI because both decreased glomerular filtration rate and increased proteinuria have been shown to be associated strongly with AKI. A growing body of literature also provides evidence that AKI accelerates the progression of CKD. Individuals who suffered dialysis-requiring AKI are particularly vulnerable to worse long-term renal outcomes, including end-stage renal disease. The association between AKI and subsequent renal function decline is amplified by pre-existing severity of CKD, higher stage of AKI, and the cumulative number of AKI episodes. However, residual confounding and ascertainment bias may partly explain the epidemiologic association between AKI and CKD in observational studies. As the number of AKI survivors increases, we need to better understand other clinically important outcomes after AKI, identify those at highest risk for the most adverse sequelae, and develop strategies to optimize their care.

Regional variation in the incidence of dialysis-requiring AKI in the United States

BACKGROUND AND OBJECTIVES Little is known about geographic differences in the incidence of AKI. The objective of this study was to determine if regional variation exists in the population incidence of dialysis-requiring AKI in the United States. DESIGN, SETTING, PARTICIPANTS, & METHODS Data from the Nationwide Inpatient Sample, a US nationally representative sample of hospitalizations, were used to determine the incidence rates of dialysis-requiring AKI between 2007 and 2009 among the four US Census-designated regions. Cases were identified using validated discharge codes. Poisson regression models were used to estimate overall regional rates, accounting for the datas sampling scheme. RESULTS In 2007-2009, the population incidence rates of dialysis-requiring AKI differed across the four Census-designated regions (P=0.04). Incidence was highest in the Midwest (523 cases/million person-yr, 95% confidence interval=483 to 568) and lowest in the Northeast (457 cases/million person-yr, 95% confidence interval=426 to 492). The pattern of regional variation in the incidence of dialysis-requiring AKI was not the same as the pattern of regional variation in the incidence of renal replacement therapy-requiring ESRD (obtained from the US Renal Data System). In-hospital mortality associated with dialysis-requiring AKI differed across the four regions, with the highest case fatality in the Northeast (25.9%) and the lowest case fatality in the Midwest (19.4%). CONCLUSIONS Significant regional variation exists in the population incidence of dialysis-requiring AKI in the United States, and additional investigation is warranted to uncover potential causes behind these geographic differences.

Exploring Potential Reasons for the Temporal Trend in Dialysis-Requiring AKI in the United States

BACKGROUND AND OBJECTIVES The population incidence of dialysis-requiring AKI has risen substantially in the last decade in the United States, and factors associated with this temporal trend are not well known. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS We conducted a retrospective cohort study using data from the Nationwide Inpatient Sample, a United States nationally representative database of hospitalizations from 2007 to 2009. We used validated International Classification of Diseases, Ninth Revision codes to identify hospitalizations with dialysis-requiring AKI and then, selected the diagnostic and procedure codes most highly associated with dialysis-requiring AKI in 2009. We applied multivariable logistic regression adjusting for demographics and used a backward selection technique to identify a set of diagnoses or a set of procedures that may be a driver for this changing risk in dialysis-requiring AKI. RESULTS From 2007 to 2009, the population incidence of dialysis-requiring AKI increased by 11% per year (95% confidence interval, 1.07 to 1.16; P<0.001). Using backward selection, we found that the temporal trend in the six diagnoses, septicemia, hypertension, respiratory failure, coagulation/hemorrhagic disorders, shock, and liver disease, sufficiently and fully accounted for the temporal trend in dialysis-requiring AKI. In contrast, temporal trends in 15 procedures most commonly associated with dialysis-requiring AKI did not account for the increasing dialysis-requiring AKI trend. CONCLUSIONS The increasing risk of dialysis-requiring AKI among hospitalized patients in the United States was highly associated with the changing burden of six acute and chronic conditions but not with surgeries and procedures.

Utilizing Electronic Health Records to Predict Acute Kidney Injury Risk and Outcomes: Workgroup Statements from the 15th ADQI Consensus Conference

The data contained within the electronic health record (EHR) is “big” from the standpoint of volume, velocity, and variety. These circumstances and the pervasive trend towards EHR adoption have sparked interest in applying big data predictive analytic techniques to EHR data. Acute kidney injury (AKI) is a condition well suited to prediction and risk forecasting; not only does the consensus definition for AKI allow temporal anchoring of events, but no treatments exist once AKI develops, underscoring the importance of early identification and prevention. The Acute Dialysis Quality Initiative (ADQI) convened a group of key opinion leaders and stakeholders to consider how best to approach AKI research and care in the “Big Data” era. This manuscript addresses the core elements of AKI risk prediction and outlines potential pathways and processes. We describe AKI prediction targets, feature selection, model development, and data display.AbrégéLes données figurant dans les dossiers médicaux électroniques (DMÉ) sont considérables, tant au point de vue du volume que du débit ou de la variété. Ces trois caractéristiques et la tendance générale à adopter les DMÉ ont soulevé un intérêt pour appliquer les techniques d’analyse prédictive des mégadonnées aux données contenues dans les dossiers médicaux électroniques. L’insuffisance rénale aiguë (IRA) est une maladie qui convient parfaitement à une méthode de prévision et de prévention des risques: non seulement la définition acceptée de cette affection permet-elle un ancrage temporel des événements ; mais il n’existe aucun traitement une fois que la maladie est déclarée, ce qui montre l’importance d’une détection précoce. L’Acute Dialysis Quality Initiative (ADQI) a convoqué un groupe de travail constitué de leaders d’opinion et autres intervenants du milieu pour se pencher sur la meilleure façon d’approcher la recherche et les soins offerts aux patients atteints d’IRA en cette ère de mégadonnées. Le présent article traite des éléments centraux de la prévention des risques et en expose les procédures potentielles. Nous y décrivons les cibles de prévention de l’IRA, la sélection des paramètres, l’élaboration des modèles et l’affichage des données.

Abrupt Decline in Kidney Function Before Initiating Hemodialysis and All-Cause Mortality: The Chronic Renal Insufficiency Cohort (CRIC) Study

BACKGROUND It is not clear whether the pattern of kidney function decline in patients with chronic kidney disease (CKD) may relate to outcomes after reaching end-stage renal disease (ESRD). We hypothesize that an abrupt decline in kidney function prior to ESRD predicts early death after initiating maintenance hemodialysis therapy. STUDY DESIGN Prospective cohort study. SETTING & PARTICIPANTS The Chronic Renal Insufficiency Cohort (CRIC) Study enrolled men and women with mild to moderate CKD. For this study, we studied 661 individuals who developed chronic kidney failure that required hemodialysis therapy initiation. PREDICTORS The primary predictor was the presence of an abrupt decline in kidney function prior to ESRD. We incorporated annual estimated glomerular filtration rates (eGFRs) into a mixed-effects model to estimate patient-specific eGFRs at 3 months prior to initiation of hemodialysis therapy. Abrupt decline was defined as having an extrapolated eGFR≥30mL/min/1.73m(2) at that time point. OUTCOMES All-cause mortality within 1 year after initiating hemodialysis therapy. MEASUREMENTS Multivariable Cox proportional hazards. RESULTS Among 661 patients with CKD initiating hemodialysis therapy, 56 (8.5%) had an abrupt predialysis decline in kidney function and 69 died within 1 year after initiating hemodialysis therapy. After adjustment for demographics, cardiovascular disease, diabetes, and cancer, abrupt decline in kidney function was associated with a 3-fold higher risk for death within the first year of ESRD (adjusted HR, 3.09; 95% CI, 1.65-5.76). LIMITATIONS Relatively small number of outcomes; infrequent (yearly) eGFR determinations; lack of more granular clinical data. CONCLUSIONS Abrupt decline in kidney function prior to ESRD occurred in a significant minority of incident hemodialysis patients and predicted early death in ESRD.

Utilizing electronic health records to predict acute kidney injury risk and outcomes: workgroup statements from the 15th

The data contained within the electronic health record (EHR) is “big” from the standpoint of volume, velocity, and variety. These circumstances and the pervasive trend towards EHR adoption have sparked interest in applying big data predictive analytic techniques to EHR data. Acute kidney injury (AKI) is a condition well suited to prediction and risk forecasting; not only does the consensus definition for AKI allow temporal anchoring of events, but no treatments exist once AKI develops, underscoring the importance of early identification and prevention. The Acute Dialysis Quality Initiative (ADQI) convened a group of key opinion leaders and stakeholders to consider how best to approach AKI research and care in the “Big Data” era. This manuscript addresses the core elements of AKI risk prediction and outlines potential pathways and processes. We describe AKI prediction targets, feature selection, model development, and data display.AbrégéLes données figurant dans les dossiers médicaux électroniques (DMÉ) sont considérables, tant au point de vue du volume que du débit ou de la variété. Ces trois caractéristiques et la tendance générale à adopter les DMÉ ont soulevé un intérêt pour appliquer les techniques d’analyse prédictive des mégadonnées aux données contenues dans les dossiers médicaux électroniques. L’insuffisance rénale aiguë (IRA) est une maladie qui convient parfaitement à une méthode de prévision et de prévention des risques: non seulement la définition acceptée de cette affection permet-elle un ancrage temporel des événements ; mais il n’existe aucun traitement une fois que la maladie est déclarée, ce qui montre l’importance d’une détection précoce. L’Acute Dialysis Quality Initiative (ADQI) a convoqué un groupe de travail constitué de leaders d’opinion et autres intervenants du milieu pour se pencher sur la meilleure façon d’approcher la recherche et les soins offerts aux patients atteints d’IRA en cette ère de mégadonnées. Le présent article traite des éléments centraux de la prévention des risques et en expose les procédures potentielles. Nous y décrivons les cibles de prévention de l’IRA, la sélection des paramètres, l’élaboration des modèles et l’affichage des données.