Acute Kidney Injury and In-Hospital Mortality: A Retrospective Analysis of a Nationwide Administrative Database of Elderly Subjects in Italy

Urinary microRNAs in sepsis function as a novel prognostic marker

Renal dysfunction is a common complication of sepsis. Early diagnosis and prompt treatment of sepsis with renal insufficiency are crucial for improving patient outcomes. Diagnostic markers can help identify patients at risk for sepsis and AKI, allowing for early intervention and potentially preventing the development of severe complications. The aim of the present study was to investigate the expression difference of urinary microRNAs (miRNAs/miRs) in elderly patients with sepsis and secondary renal insufficiency, and to evaluate their diagnostic value in these patients. In the present study, RNA was extracted from urine samples of elderly sepsis-related acute renal damage patients and the expression profiles of several miRNAs were analyzed. In order to evaluate the expression profile of several miRNAs, urine samples from elderly patients with acute renal damage brought on by sepsis were obtained. RNA extraction and sequencing were then performed on the samples. Furthermore, multiple bioinformatics methods were used to analyze miRNA profiles, including differential expression analysis, and Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analysis of different miRNA target genes, to further explore miRNAs that are suitable for utilization as biomarkers. A total of four miRNAs, including hsa-miR-31-5p, hsa-miR-151a-3p, hsa-miR-142-5p and hsa-miR-16-5p, were identified as potential biological markers and were further confirmed in sepsis using reverse transcription-quantitative PCR. The results of the present study demonstrated that the four urinary miRNAs were differentially expressed and may serve as specific markers for prediction of secondary acute kidney injury in elderly patients with sepsis.

Development and validation of a nomogram for predicting in-hospital mortality of elderly patients with persistent sepsis-associated acute kidney injury in intensive care units: a retrospective cohort study using the MIMIC-IV database

OBJECTIVES

To identify the clinical risk factors that influence in-hospital mortality in elderly patients with persistent sepsis-associated acute kidney injury (S-AKI) and to establish and validate a nomogram to predict in-hospital mortality.

DESIGN

Retrospective cohort analysis.

SETTING

Data from critically ill patients at a US centre between 2008 and 2021 were extracted from the Medical Information Mart for Intensive Care (MIMIC)-IV database (V.1.0).

PARTICIPANTS

Data from 1519 patients with persistent S-AKI were extracted from the MIMIC-IV database.

PRIMARY OUTCOME

All-cause in-hospital death from persistent S-AKI.

RESULTS

Multiple logistic regression revealed that gender (OR 0.63, 95% CI 0.45-0.88), cancer (2.5, 1.69-3.71), respiratory rate (1.06, 1.01-1.12), AKI stage (2.01, 1.24-3.24), blood urea nitrogen (1.01, 1.01-1.02), Glasgow Coma Scale score (0.75, 0.70-0.81), mechanical ventilation (1.57, 1.01-2.46) and continuous renal replacement therapy within 48 hours (9.97, 3.39-33.9) were independent risk factors for mortality from persistent S-AKI. The consistency indices of the prediction and the validation cohorts were 0.780 (95% CI: 0.75-0.82) and 0.80 (95% CI: 0.75-0.85), respectively. The model's calibration plot suggested excellent consistency between the predicted and actual probabilities.

CONCLUSIONS

This study's prediction model demonstrated good discrimination and calibration abilities to predict in-hospital mortality of elderly patients with persistent S-AKI, although it warrants further external validation to verify its accuracy and applicability.

Seasonal pattern in elderly hospitalized with acute kidney injury: a retrospective nationwide study in Italy

Purpose

Acute kidney injury (AKI) frequently complicates hospitalization and is associated with in-hospital mortality (IHM). It has been reported a seasonal trend in different clinical conditions. The aim of this study was to evaluate the possible relationship between seasons of the year and IHM in elderly hospitalized patients with AKI.

Methods

We selected all admissions complicated by AKI between 2000 and 2015 recorded in the Italian National Hospital Database. ICD-9-CM code 584.xx identified subjects with age ≥ 65 years and age, sex, comorbidity burden, need of dialysis treatment and IHM were compared in hospitalizations recorded during the four seasons. Moreover, we plotted the AKI observed/expected ratio and percentage of mortality during the study period.

Results

We evaluated 759,720 AKI hospitalizations (mean age 80.5 ± 7.8 years, 52.2% males). Patients hospitalized with AKI during winter months had higher age, prevalence of dialysis-dependent AKI, and number of deceased patients. In whole population IHM was higher in winter and lower in summer, while the AKI observed/expected ratio demonstrated two peaks, one in summer and one in winter. Logistic regression analysis demonstrated that parameters such as age, autumn, winter, comorbidity burden were positively associated with IHM.

Conclusion

We conclude that a seasonality exists in AKI, however, relationship between seasons and AKI could vary depending on the aspects considered. Both autumn and winter months are independent risk factors for IHM in patients with AKI regardless of age, sex and comorbidity burden. On the contrary, summer time reduces the risk of death during hospitalizations with AKI.

Health Care Analytics With Time-Invariant and Time-Variant Feature Importance to Predict Hospital-Acquired Acute Kidney Injury: Observational Longitudinal Study

Background

Acute kidney injury (AKI) develops in 4% of hospitalized patients and is a marker of clinical deterioration and nephrotoxicity. AKI onset is highly variable in hospitals, which makes it difficult to time biomarker assessment in all patients for preemptive care.

Objective

The study sought to apply machine learning techniques to electronic health records and predict hospital-acquired AKI by a 48-hour lead time, with the aim to create an AKI surveillance algorithm that is deployable in real time.

Methods

The data were sourced from 20,732 case admissions in 16,288 patients over 1 year in our institution. We enhanced the bidirectional recurrent neural network model with a novel time-invariant and time-variant aggregated module to capture important clinical features temporal to AKI in every patient. Time-series features included laboratory parameters that preceded a 48-hour prediction window before AKI onset; the latter’s corresponding reference was the final in-hospital serum creatinine performed in case admissions without AKI episodes.

Results

The cohort was of mean age 53 (SD 25) years, of whom 29%, 12%, 12%, and 53% had diabetes, ischemic heart disease, cancers, and baseline eGFR <90 mL/min/1.73 m², respectively. There were 911 AKI episodes in 869 patients. We derived and validated an algorithm in the testing dataset with an AUROC of 0.81 (0.78-0.85) for predicting AKI. At a 15% prediction threshold, our model generated 699 AKI alerts with 2 false positives for every true AKI and predicted 26% of AKIs. A lowered 5% prediction threshold improved the recall to 60% but generated 3746 AKI alerts with 6 false positives for every true AKI. Representative interpretation results produced by our model alluded to the top-ranked features that predicted AKI that could be categorized in association with sepsis, acute coronary syndrome, nephrotoxicity, or multiorgan injury, specific to every case at risk.

Conclusions

We generated an accurate algorithm from electronic health records through machine learning that predicted AKI by a lead time of at least 48 hours. The prediction threshold could be adjusted during deployment to optimize recall and minimize alert fatigue, while its precision could potentially be augmented by targeted AKI biomarker assessment in the high-risk cohort identified.

Acute kidney injury and aging

Our aging population is growing and developing treatments for age-related diseases such as Alzheimer's and Parkinson's disease has taken on an increasing urgency and is accompanied by high public awareness. The already high and rising incidence of acute kidney injury (AKI) in the elderly, however, has received relatively little attention despite the potentially fatal outcomes associated with an episode of AKI in this age group. When discussing AKI and aging, one should consider two aspects: first, elderly patients have an increased susceptibility to an AKI episode, and second, they have decreased kidney repair after AKI given the high incidence of progression to chronic kidney disease (CKD). It is unclear if the same factors that drive the increased susceptibility to AKI could be playing a role in the decreased repair capacity or if they are totally different and unrelated. This review will examine current knowledge on the risk factors for the increased susceptibility to AKI in the elderly and will also explore potential aspects that might contribute to a decreased kidney repair response in this age group.

Kidney problems in disaster situations

Mass disasters, particularly earthquakes, cause many medical problems, including kidney problems, but an organized approach to cope with them was initiated only at the end of previous century, subsequent to the Armenian Spitak earthquake in 1988. Originally, interventions were focused on acute kidney injury (AKI) following crush injury and rhabdomyolysis in victims who had been trapped under the debris of collapsed buildings. However, similar problems were also registered in the context of other catastrophic events, especially man-made disasters like wars and torture. Other kidney-related problems, such as the preservation of treatment continuity in chronic kidney disease (CKD), especially in maintenance dialysis patients, deserved attention as well. Specific therapeutic principles apply to disaster-related kidney problems and these may differ from usual day-to-day clinical practice. Those approaches have been formulated in global and specific country-related guidelines and recommendations. It is clear that a well-conceived and organized management of kidney diseases in disasters benefits outcomes. Furthermore, it may be useful if the model and philosophy that were applied over the last three decades could be adapted by broadening the scope of disasters leading to intervention. Actions should be guided and coordinated by a panel of experts steering ad hoc interventions, rather than applying the "old" static model where a single coordinating center instructs and uses volunteers listed long before a potential event occurs.

A Review on the Application and Limitations of Administrative Health Care Data for the Study of Acute Kidney Injury Epidemiology and Outcomes in Children

Administrative health care databases contain valuable patient information generated by health care encounters. These "big data" repositories have been increasingly used in epidemiological health research internationally in recent years as they are easily accessible and cost-efficient and cover large populations for long periods. Despite these beneficial characteristics, it is also important to consider the limitations that administrative health research presents, such as issues related to data incompleteness and the limited sensitivity of the variables. These barriers potentially lead to unwanted biases and pose threats to the validity of the research being conducted. In this review, we discuss the effectiveness of health administrative data in understanding the epidemiology of and outcomes after acute kidney injury (AKI) among adults and children. In addition, we describe various validation studies of AKI diagnostic or procedural codes among adults and children. These studies reveal challenges of AKI research using administrative data and the lack of this type of research in children and other subpopulations. Additional pediatric-specific validation studies of administrative health data are needed to promote higher volume and increased validity of this type of research in pediatric AKI, to elucidate the large-scale epidemiology and patient and health systems impacts of AKI in children, and to devise and monitor programs to improve clinical outcomes and process of care.

Cumulative iodinated contrast exposure for computed tomography during acute kidney injury and major adverse kidney events

OBJECTIVES

To determine if contrast-enhanced CT imaging performed in patients during their episode of AKI contributes to major adverse kidney events (MAKE).

METHODS

A propensity score-matched analysis of 1127 patients with AKI defined by KDIGO criteria was done. Their mean age was 63 ± 16 years with 56% males. A total of 419 cases exposed to CT contrast peri-AKI were matched with 798 non-exposed controls for 14 covariates including comorbidities, acute illnesses, and initial AKI severity; outcomes including MAKE and renal recovery in hospital were compared using bivariate analysis and logistic regression. MAKE was a composite of mortality, renal replacement therapy, and doubling of serum creatinine on discharge over baseline; renal recovery was classified as early versus late based on a 7-day timeline from AKI onset to nadir creatinine or cessation of renal replacement therapy in survivors.

RESULTS

Sixty-two patients received cumulatively > 100 mL of CT contrast, 143 patients had > 50-100 mL, and 214 patients had 50 mL or less; MAKE occurred in 34%, 17%, and 21%, respectively, as compared with 20% in non-exposed controls (p = 0.008 for patients with > 100 mL contrast versus none). More contrast-exposed patients experienced late renal recovery (27% versus 20%) and longer hospital days (median 10 versus 8) than non-exposed patients (all p < 0.01). On multivariate analysis, cumulative CT contrast > 100 mL was independently associated with MAKE (odds ratio 2.39 versus non-contrast, adjusted for all confounders, p = 0.005); cumulative CT contrast under 100 mL was not associated with MAKE.

CONCLUSIONS

High cumulative volume of CT contrast administered to patients with AKI is associated with worse short-term renal outcomes and delayed renal recovery.

KEY POINTS

• Cumulative intravenous iodinated contrast for CT imaging of more than 100 mL, during an episode of acute kidney injury, was independently associated with worse renal outcomes and less renal recovery. • These adverse outcomes including renal replacement therapy were not more frequent in similar patients who received cumulatively 100 mL or less of CT contrast, compared with non-exposed patients. • More patients with CT contrast exposure during acute kidney injury experienced delayed renal recovery.

Weekend Effect and in-Hospital Mortality in Elderly Patients with Acute Kidney Injury: A Retrospective Analysis of a National Hospital Database in Italy

Background: The aim of this study was to relate the weekend (WE) effect and acute kidney injury (AKI) in elderly patients by using the Italian National Hospital Database (NHD). Methods: Hospitalizations with AKI of subjects aged ≥ 65 years from 2000–2015 who were identified by the ICD-9-CM were included. Admissions from Friday to Sunday were considered as WE, while all the other days were weekdays (WD). In-hospital mortality (IHM) was our outcome, and the comorbidity burden was calculated by the modified Elixhauser Index (mEI), based on ICD-9-CM codes. Results: 760,664 hospitalizations were analyzed. Mean age was 80.5 ± 7.8 years and 52.2% were males. Of the studied patients, 9% underwent dialysis treatment, 24.3% were admitted during WE, and IHM was 27.7%. Deceased patients were more frequently comorbid males, with higher age, treated with dialysis more frequently, and had higher admission during WE. WE hospitalizations were more frequent in males, and in older patients with higher mEI. IHM was independently associated with dialysis-dependent AKI (OR 2.711; 95%CI 2.667–2.755, p < 0.001), WE admission (OR 1.113; 95%CI 1.100–1.126, p < 0.001), and mEI (OR 1.056; 95% CI 1.055–1.057, p < 0.001). Discussion: Italian elderly patients admitted during WE with AKI are exposed to a higher risk of IHM, especially if they need dialysis treatment and have high comorbidity burden.

Diagnostics, Risk Factors, Treatment and Outcomes of Acute Kidney Injury in a New Paradigm

Acute kidney injury (AKI) is a common clinical condition among patients admitted in the hospitals. The condition is associated with both increased short-term and long-term mortality. With the development of a standardized definition for AKI and the acknowledgment of the impact of AKI on patient outcomes, there has been increased recognition of AKI. Two advances from past decades, the usage of computer decision support and the discovery of AKI biomarkers, have the ability to advance the diagnostic method to and further management of AKI. The increasingly widespread use of electronic health records across hospitals has substantially increased the amount of data available to investigators and has shown promise in advancing AKI research. In addition, progress in the finding and validation of different forms of biomarkers of AKI within diversified clinical environments and has provided information and insight on testing, etiology and further prognosis of AKI, leading to future of precision and personalized approach to AKI management. In this this article, we discussed the changing paradigms in AKI: from mechanisms to diagnostics, risk factors, and management of AKI.