Association between regional economic status and renal recovery of dialysis-requiring acute kidney injury among critically ill patients

Exploring the Landscape of Social and Economic Factors in Critical Illness Survivorship: A Scoping Review

OBJECTIVES

To explore the breadth of social, demographic, and economic (SDE) factors reported in critical illness survivorship research, with a focus on how they impact survivorship outcomes.

DATA SOURCES

We obtained articles from Medline, Embase, PsycInfo, and CINAHL, as well as reference list reviews of included articles and relevant reviews captured by searches.

STUDY SELECTION

SDE factors were defined as any nonmedical factor that can influence outcomes. We included primary studies published in English that explored SDE factors as an independent variable or as an outcome in post-ICU survivorship of adults. Two authors independently assessed each study for inclusion in duplicate, and conflicts were resolved by consensus. Our searches returned 7151 records, of which 83 were included for data extraction and final review.

DATA EXTRACTION

We used a standardized data collection form to extract data, focusing on the characteristics of each study (i.e., year and country of publication), SDE factors explored, how the factors were measured, the impacts of SDE factors on post-ICU survivorship outcomes, and the impacts of ICU admission on SDE outcomes.

DATA SYNTHESIS

We summarized the relationships between SDE factors and ICU survivorship in table format and performed a narrative synthesis. We identified 16 unique SDE factors explored in the current literature. We found that generally, higher education, income, and socioeconomic status were associated with better outcomes post-ICU; while non-White race, public insurance status, and social vulnerability were associated with poorer outcomes.

CONCLUSIONS

Various SDE factors have been explored in the critical illness survivorship literature and many are associated with post-ICU outcomes with varying effect sizes. There remains a gap in understanding longitudinal outcomes, mechanisms of how SDE factors interact with outcomes, and of the complexity and interconnectedness of these factors, all of which will be instrumental in guiding interventions to improve post-ICU survivorship.

Association of Neighborhood Social Determinants of Health with Acute Kidney Injury during Hospitalization

Key Points

AKI is common among hospitalized patients. However, the contribution of neighborhood social determinants of health to AKI risk is not known. We found that among 26,769 hospitalized patients, 26% developed AKI. Patients who lived in the most disadvantaged areas (highest tertile of Area Deprivation Index) had a 10% greater odds of developing AKI than counterparts in the lowest Area Deprivation Index tertile. Patients who lived in rural areas had 25% greater odds of not recovering from AKI by hospital discharge. This study demonstrates an association between neighborhood disadvantage and rurality on the development of AKI and lack of recovery from AKI. Further work is needed to understand the mechanisms of these associations and to develop community-level interventions to mitigate the health care burden of AKI for disadvantaged populations.

Background

AKI is common among hospitalized patients. However, the contribution of social determinants of health (SDOH) to AKI risk remains unclear. This study evaluated the association between neighborhood measures of SDOH and AKI development and recovery during hospitalization.

Methods

This is a retrospective cohort study of adults without ESKD admitted to a large Southern US health care system from October 2014 to September 2017. Neighborhood SDOH measures included (1 ) socioeconomic status: Area Deprivation Index (ADI) scores, (2 ) food access: Low-Income, Low-Access scores, (3 ) rurality: Rural–Urban Commuting Area scores, and (4 ) residential segregation: dissimilarity and isolation scores. The primary study outcome was AKI on the basis of serum creatinine Kidney Disease Improving Global Outcomes criteria. Our secondary outcome was lack of AKI recovery (requiring dialysis or elevated serum creatinine at discharge). The association of SDOH measures with AKI was evaluated using generalized estimating equation models adjusted for demographics and clinical characteristics.

Results

Among 26,769 patients, 26% developed AKI during hospitalization. Compared with those who did not develop AKI, those who developed AKI were older (median 60 versus 57 years), more commonly men (55% versus 50%), and more commonly self-identified as Black (38% versus 33%). Patients residing in most disadvantaged neighborhoods (highest ADI tertile) had 10% (95% confidence interval, 1.02 to 1.19) greater adjusted odds of developing AKI during hospitalization than counterparts in least disadvantaged areas (lowest ADI tertile). Patients living in rural areas had 25% higher adjusted odds of lack of AKI recovery by hospital discharge (95% confidence interval, 1.07 to 1.46). Food access and residential segregation were not associated with AKI development or recovery.

Conclusions

Hospitalized patients from the most socioeconomically disadvantaged neighborhoods and from rural areas had higher odds of developing AKI and not recovering from AKI by hospital discharge, respectively. A better understanding of the mechanisms underlying these associations is needed to inform interventions to reduce AKI risk during hospitalization among disadvantaged populations.

Predictive approach for liberation from acute dialysis in ICU patients using interpretable machine learning

Renal recovery following dialysis-requiring acute kidney injury (AKI-D) is a vital clinical outcome in critical care, yet it remains an understudied area. This retrospective cohort study, conducted in a medical center in Taiwan from 2015 to 2020, enrolled patients with AKI-D during intensive care unit stays. We aimed to develop and temporally test models for predicting dialysis liberation before hospital discharge using machine learning algorithms and explore early predictors. The dataset comprised 90 routinely collected variables within the first three days of dialysis initiation. Out of 1,381 patients who received acute dialysis, 27.3% experienced renal recovery. The cohort was divided into the training group (N = 1135) and temporal testing group (N = 251). The models demonstrated good performance, with an area under the receiver operating characteristic curve of 0.85 (95% CI, 0.81-0.88) and an area under the precision-recall curve of 0.69 (95% CI, 0.62-0.76) for the XGBoost model. Key predictors included urine volume, Charlson comorbidity index, vital sign derivatives (trend of respiratory rate and SpO2), and lactate levels. We successfully developed early prediction models for renal recovery by integrating early changes in vital signs and inputs/outputs, which have the potential to aid clinical decision-making in the ICU.

Unsupervised clustering identifies sub-phenotypes and reveals novel outcome predictors in patients with dialysis-requiring sepsis-associated acute kidney injury

INTRODUCTION

Heterogeneity exists in sepsis-associated acute kidney injury (SA-AKI). This study aimed to perform unsupervised consensus clustering in critically ill patients with dialysis-requiring SA-AKI.

PATIENTS AND METHODS

This prospective observational cohort study included all septic patients, defined by the Sepsis-3 criteria, with dialysis-requiring SA-AKI in surgical intensive care units in Taiwan between 2009 and 2018. We employed unsupervised consensus clustering based on 23 clinical variables upon initializing renal replacement therapy. Multivariate-adjusted Cox regression models and Fine-Gray sub-distribution hazard models were built to test associations between cluster memberships with mortality and being free of dialysis at 90 days after hospital discharge, respectively.

RESULTS

Consensus clustering among 999 enrolled patients identified three sub-phenotypes characterized with distinct clinical manifestations upon renal replacement therapy initiation (n = 352, 396 and 251 in cluster 1, 2 and 3, respectively). They were followed for a median of 48 (interquartile range 9.5-128.5) days. Phenotypic cluster 1, featured by younger age, lower Charlson Comorbidity Index, higher baseline estimated glomerular filtration rate but with higher severity of acute illness was associated with an increased risk of death (adjusted hazard ratio of 3.05 [95% CI, 2.35-3.97]) and less probability to become free of dialysis (adjusted sub-distribution hazard ratio of 0.55 [95% CI, 0.38-0.8]) than cluster 3. By examining distinct features of the sub-phenotypes, we discovered that pre-dialysis hyperlactatemia ≥3.3 mmol/L was an independent outcome predictor. A clinical model developed to determine high-risk sub-phenotype 1 in this cohort (C-static 0.99) can identify a sub-phenotype with high in-hospital mortality risk (adjusted hazard ratio of 1.48 [95% CI, 1.25-1.74]) in another independent multi-centre SA-AKI cohort.

CONCLUSIONS

Our data-driven approach suggests sub-phenotypes with clinical relevance in dialysis-requiring SA-AKI and serves an outcome predictor. This strategy represents further development toward precision medicine in the definition of high-risk sub-phenotype in patients with SA-AKI.Key messagesUnsupervised consensus clustering can identify sub-phenotypes of patients with SA-AKI and provide a risk prediction.Examining the features of patient heterogeneity contributes to the discovery of serum lactate levels ≥ 3.3 mmol/L upon initializing RRT as an independent outcome predictor.This data-driven approach can be useful for prognostication and lead to a better understanding of therapeutic strategies in heterogeneous clinical syndromes.

Socioeconomic Influences on the Outcomes of Dialysis-Requiring Acute Kidney Injury in Brazil

Introduction

Although research suggests that socioeconomic deprivation is linked to a higher incidence of acute kidney injury (AKI) and worse outcomes in high-income countries, there is limited knowledge about these epidemiologic factors in developing countries. In addition, the impact of medical institution administration (private versus public) on AKI outcomes remains to be determined.

Methods

We studied 15,186 pediatric and adult patients with dialysis-requiring AKI (AKI-D) admitted to private and public hospitals in Rio de Janeiro, Brazil. According to Brazil's demographic census, socioeconomic indicators were derived from patient zip codes. Propensity score matching analysis and a mixed-effect Cox regression were used to assess the impact of socioeconomic indicators and hospital governance on patient survival.

Results

Crude mortality rates were higher in private hospitals than in public hospitals (71.8% vs. 59.5%, P < 0.001) and were associated with significant differences in age (75 years, interquartile range [IQR]: 61-83 vs. 53 years, IQR: 31-66), baseline renal function (prevalence of chronic kidney disease [CKD]: 33.2% vs. 23%, P < 0.001), comorbidities (Charlson score: 2.03 ± 0.87 vs. 1.72 ± 0.75, P < 0.001), and severity of presentation (mechanical ventilation: 76.5% vs. 58% and vasopressors: 72.8% vs. 50.5%, P < 0.001). After adjustments and propensity score matching, we found no effect of different hospital administrations or socioeconomic factors on mortality. Baseline characteristics and the severity of presentation primarily influenced AKI-D prognosis.

Conclusions

Despite significant racial and socioeconomic differences in hospital governance, these indicators had no independent influence on mortality. Future epidemiologic studies should investigate these relevant assumptions to allow healthcare systems to manage this severe syndrome promptly.

Wet depositions of cations in forests across NADP, EMEP, and EANET monitoring networks over the last two decades

Studies focused on emissions and acid deposition of sulfur (S) and nitrogen (N) and the consequent precipitation acidity have a long history. However, atmospheric depositions of cations play a critical role in buffering precipitation acidity, and providing cationic nutrients for vegetation growth lacks sufficient studies equally. The spatiotemporal patterns of cation depositions and their neutralization potential across broad scales remain unclear. Through synthesizing the long-term data in forest sites (n = 128) derived from three monitoring networks (NADP in Northern America, EMEP in Europe, and EANET in East Asia) on wet deposition of cations (Na+, NH4-N, K+, Mg2+, and Ca2+), this study assesses the temporal changes and spatial patterns of cation depositions and their neutralization potential over the last two decades. The results showed that the depositions of cationic nutrients were considerably higher in EANET compared to NADP and EMEP. The depositions of sea salt-associated sodium exhibited a significant transition from marine (> 15 kg ha-1 year-1) to inland (< 3.0 kg ha-1 year-1) forest sites attributable to the precipitation quantity and influences of sea spray. The higher emissions of NH3 and particulate matter in East Asia explained the higher cation depositions in EANET than NADP and EMEP. The annual trends of cations revealed that only 20-30% of the forest sites showed significant changing trends and the sites widely spread across the three networks. Possibly, base cation (BC) deposition has reached a low and stable condition in NADP and EMEP, while it has high spatial heterogeneity in the temporal change in EANET. The difference in BC deposition among the three networks reflects their distinct development of economy. Our synthesis indicates that the annual trends of neutralization factor (NF) in NADP can be explained by the declining of acid potential (AP), not by neutralization potential (NP) as BC deposition has been stably low over the past two decades. Whereas, the concurrent decreases of AP and NP in EMEP or plateau period of both AP and NP in EANET have come to a standstill of acid neutralizing capacity.

Distinct Subtyping of Successful Weaning from Acute Kidney Injury Requiring Renal Replacement Therapy by Consensus Clustering in Critically Ill Patients

Background: Clinical decisions regarding the appropriate timing of weaning off renal replacement therapy (RRT) in critically ill patients are complex and multifactorial. The aim of the current study was to identify which critical patients with acute kidney injury (AKI) may be more likely to be successfully weaned off RRT using consensus cluster analysis. Methods: In this study, critically ill patients who received RRT at three multicenter referral hospitals at several timepoints from August 2016 to July 2018 were enrolled. An unsupervised consensus clustering algorithm was used to identify distinct phenotypes. The outcomes of interest were the ability to wean off RTT and 90-day mortality. Results: A total of 124 patients with AKI requiring RRT (AKI-RRT) were enrolled. The 90-day mortality rate was 30.7% (38/124), and 49.2% (61/124) of the patients were successfully weaned off RRT for over 90 days. The consensus clustering algorithm identified three clusters from a total of 45 features. The three clusters had distinct features and could be separated according to the combination of urinary neutrophil gelatinase-associated lipocalin to creatinine ratio (uNGAL/Cr), Sequential Organ Failure Assessment (SOFA) score, and estimated glomerular filtration rate at the time of weaning off RRT. uNGAL/Cr (hazard ratio [HR] 2.43, 95% confidence interval [CI]: 1.36–4.33) and clustering phenotype (cluster 1 vs. 3, HR 2.7, 95% CI: 1.11–6.57; cluster 2 vs. 3, HR 44.5, 95% CI: 11.92–166.39) could predict 90-day mortality or re-dialysis. Conclusions: Almost half of the critical patients with AKI-RRT could wean off dialysis for over 90 days. Urinary NGAL/Cr and distinct clustering phenotypes could predict 90-day mortality or re-dialysis.

Predialysis serum lactate levels could predict dialysis withdrawal in Type 1 cardiorenal syndrome patients

BACKGROUND

Renal replacement therapy (RRT) is an effective rescue therapy for Type 1 cardiorenal syndrome (CRS). Previous studies have demonstrated that type 1 CRS patients with severe renal dysfunction were susceptible to sepsis, and that serum lactate has been correlated with the risk of mortality in patients with sepsis. However, the association between serum lactate level and the prognosis of type 1 CRS patients requiring RRT is unknown.

METHODS

An inception cohort of 500 type 1 CRS patients who received RRT in a tertiary-care referral hospital in Taiwan from August 2011 to January 2018 were enrolled. The outcomes of interest were dialysis withdrawal and 90-day mortality. The results were further externally validated using sampling data of type 1 CRS patients requiring dialysis from multiple tertiary-care centers.

FINDINGS

The 90-day mortality rate was 52.8% and the incidence rate of dialysis withdrawal was 34.8%. Lower pre-dialysis lactate was correlated with a higher rate of dialysis withdrawal and lower rate of mortality. Generalized additive model showed that 4.2 mmol/L was an adequate cut-off value of lactate to predict mortality. Taking mortality as a competing risk, Fine-Gray subdistribution hazard analysis further indicated that a low lactate level (≦ 4.2 mmol/L) was an independent predictor for the possibility of dialysis withdrawal, as also shown in external validation. The interaction of quick Sequential Organ Failure Assessment score and lactate was associated with dialysis dependence in a disease severity-dependent manner. Furthermore, the associations between hyperlactatemia and dialysis dependence were consistent in the patients with and without sepsis.

INTERPRETATION

Serum lactate level is accurate and capable of forecasting the prognosis along with qSOFA severity for clinical decision-making for treating type 1 CRS patients. Further studies are needed to validate our results.

FUNDING

This study was supported by grants from Taiwan National Science Council [104-2314-B-002-125-MY3,106-2314-B-002-166-MY3,107-2314-B-002-026-MY3], National Taiwan University Hospital [106-FTN20,106-P02,UN106-014,106-S3582,107-S3809,107-T02,PC1246,VN109-09,109-S4634,UN109-041], Ministry of Science and Technology of the Republic of China [MOST106-2321-B-182-002,106-2314-B-182A-064,MOST107-2321-B-182-004,MOST107-2314-B-182A-138, MOST108-2321-B-182-003,MOST109-2321-B-182-001, MOST108-2314-B-182A-027], Chang Gung Memorial Hospital [CMRPG-2G0361,CMRPG-2H0161,CMRPG-2J0261, CMRPG-2K0091], and Ministry of Health and Welfare of the Republic of China [PMRPG-2L0011].