Documentation of acute kidney injury at discharge from the neonatal intensive care unit and role of nephrology consultation.
Ontology highlight
ABSTRACT: Objective
To investigate whether NICU discharge summaries documented neonatal AKI and estimate if nephrology consultation mediated this association.Study design
Secondary analysis of AWAKEN multicenter retrospective cohort.Exposures
AKI severity and diagnostic criteria.Outcome
AKI documentation on NICU discharge summaries using multivariable logistic regression to estimate associations and test for causal mediation.Results
Among 605 neonates with AKI, 13% had documented AKI. Those with documented AKI were more likely to have severe AKI (70.5% vs. 51%, p < 0.001) and SCr-only AKI (76.9% vs. 50.1%, p = 0.04). Nephrology consultation mediated 78.0% (95% CL 46.5-109.4%) of the total effect of AKI severity and 82.8% (95% CL 70.3-95.3%) of the total effect of AKI diagnostic criteria on documentation.Conclusion
We report a low prevalence of AKI documentation at NICU discharge. AKI severity and SCr-only AKI increased odds of AKI documentation. Nephrology consultation mediated the associations of AKI severity and diagnostic criteria with documentation.
SUBMITTER: Chmielewski J
PROVIDER: S-EPMC9280854 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:ObjectiveTo determine the incidence of acute kidney injury (AKI) in infants exposed to nephrotoxic drug combinations admitted to 268 neonatal intensive care units managed by the Pediatrix Medical Group.Study designWe included infants born at 22-36 weeks gestational age, ≤120 days postnatal age, exposed to nephrotoxic drug combinations, with serum creatinine measurements available, and discharged between 2007 and 2016. To identify risk factors associated with a serum creatinine definition of AKI based on the Kidney Disease: Improving Global Outcomes criteria, we performed multivariable logistic and Cox regression adjusting for gestational age, sex, birth weight, postnatal age, race/ethnicity, sepsis, respiratory distress syndrome, baseline serum creatinine, and duration of combination drug exposure. The adjusted odds of AKI were determined relative to gentamicin + indomethacin for the following nephrotoxic drug combinations: chlorothiazide + ibuprofen; chlorothiazide + indomethacin; furosemide + gentamicin; furosemide + ibuprofen; furosemide + tobramycin; ibuprofen + spironolactone; and vancomycin + piperacillin-tazobactam.ResultsAmong 8286 included infants, 1384 (17%) experienced AKI. On multivariable analysis, sepsis, lower baseline creatinine, and duration of combination therapy were associated with increased odds of AKI. Furosemide + tobramycin and vancomycin + piperacillin-tazobactam were associated with a decreased risk of AKI relative to gentamicin + indomethacin in both the multivariable and Cox regression models.ConclusionsIn this cohort, infants receiving longer durations of nephrotoxic combination therapy had an increased odds of developing AKI.
| S-EPMC7752849 | biostudies-literature
Project description:High-risk infants transitioning from the neonatal intensive care unit (NICU) to home represent a vulnerable population, given their complex care requirements. Little is known about errors during this period.Identify and describe homecare and healthcare utilization errors in high-risk infants following NICU discharge.This was a prospective observational cohort study of homecare (feeding, medication, and equipment) and healthcare utilization (appointment) errors in infants discharged from a regional NICU between 2011 and 2015. Chi-square test and Wilcoxon rank-sum test were used to compare infant and maternal demographics between infants with and without errors.A total of 363 errors were identified in 241 infants during 635 home visits. The median number of visits was 2. No significance was found between infant and maternal demographics in those with or without errors.High-risk infants have complex care needs and can benefit from regular follow-up services. Home visits provide an opportunity to identify, intervene, and resolve homecare and healthcare utilization errors.Further research is needed to evaluate the prevalence and cause of homecare errors in high-risk infants and how healthcare resources and infant health outcomes are affected by those errors. Preventive measures and mitigating interventions that best address homecare errors require further development and subsequent description.
| S-EPMC5533584 | biostudies-other
Project description:ObjectiveTo evaluate the impact of nephrology integration in the NICU on acute kidney injury (AKI) incidence, provider reporting, and nephrology referral.Study designCohort study in a single-center NICU from January 2012 to December 2017 (n = 1464). We assessed the impact of clinical practice changes including neonatal-nephrology rounds on the incidence of AKI.ResultsAKI occurred in 318 neonates (22%). AKI occurred less frequently in those admitted after clinical practice changes (P < 0.001). After multivariable adjustment, clinical practice changes were associated with reduced odds of AKI (adjusted odds ratio, 0.31; 95% CI 0.22-0.44, P < 0.001). Provider reporting of AKI improved (P < 0.001) and more neonates were referred for nephrology follow-up (P < 0.001).ConclusionsIncreased nephrology integration in the NICU was associated with decreased AKI incidence. While recognition of AKI improved, AKI remained poorly reported and nephrology AKI follow-up did not routinely occur. This study supports the importance of increased nephrology involvement in the NICU.
| S-EPMC7442645 | biostudies-literature
Project description:Background and objectivesLittle is known about the long-term burden of AKI in the pediatric intensive care unit. We aim to evaluate if pediatric AKI is associated with higher health service use post-hospital discharge.Design, setting, participants, & measurementsThis is a retrospective cohort study of children (?18 years old) admitted to two tertiary centers in Montreal, Canada. Only the first admission per patient was included. AKI was defined in two ways: serum creatinine alone or serum creatinine and/or urine output. The outcomes were 30-day, 1-year, and 5-year hospitalizations, emergency room visits, and physician visits per person-time using provincial administrative data. Univariable and multivariable Poisson regression were used to evaluate AKI associations with outcomes.ResultsA total of 2041 children were included (56% male, mean admission age 6.5±5.8 years); 299 of 1575 (19%) developed AKI defined using serum creatinine alone, and when urine output was included in the AKI definition 355 of 1622 (22%) children developed AKI. AKI defined using serum creatinine alone and AKI defined using serum creatinine and urine output were both associated with higher 1- and 5-year hospitalization risk (AKI by serum creatinine alone adjusted relative risk, 1.42; 95% confidence interval, 1.12 to 1.82; and 1.80; 1.54 to 2.11, respectively [similar when urine output was included]) and higher 5-year physician visits (adjusted relative risk, 1.26; 95% confidence interval, 1.14 to 1.39). AKI was not associated with emergency room use after adjustments.ConclusionsAKI is independently associated with higher hospitalizations and physician visits postdischarge.
| S-EPMC5969475 | biostudies-literature
Project description:IntroductionAcute kidney injury (AKI) is common among hospitalized patients and has a significant impact on morbidity and mortality. Although early prediction of AKI has the potential to reduce adverse patient outcomes, it remains a difficult condition to predict and diagnose. The purpose of this study was to evaluate the ability of a machine learning algorithm to predict for AKI as defined by Kidney Disease: Improving Global Outcomes (KDIGO) stage 2 or 3 up to 48 hours in advance of onset using convolutional neural networks (CNNs) and patient electronic health record (EHR) data.MethodsA CNN prediction system was developed to use EHR data gathered during patients' stays to predict AKI up to 48 hours before onset. A total of 12,347 patient encounters were retrospectively analyzed from the Medical Information Mart for Intensive Care III (MIMIC-III) database. An XGBoost AKI prediction model and the sequential organ failure assessment (SOFA) scoring system were used as comparators. The outcome was AKI onset. The model was trained on routinely collected patient EHR data. Measurements included area under the receiver operating characteristic (AUROC) curve, positive predictive value (PPV), and a battery of additional performance metrics for advance prediction of AKI onset.ResultsOn a hold-out test set, the algorithm attained an AUROC of 0.86 and PPV of 0.24, relative to a cohort AKI prevalence of 7.62%, for long-horizon AKI prediction at a 48-hour window before onset.ConclusionA CNN machine learning-based AKI prediction model outperforms XGBoost and the SOFA scoring system, revealing superior performance in predicting AKI 48 hours before onset, without reliance on serum creatinine (SCr) measurements.
| S-EPMC8116756 | biostudies-literature
Project description: Not available
| S-EPMC10547050 | biostudies-literature
Project description:BackgroundAcute kidney injury (AKI) represents a significant global health challenge, leading to increased patient distress and financial health care burdens. The development of AKI in intensive care unit (ICU) settings is linked to prolonged ICU stays, a heightened risk of long-term renal dysfunction, and elevated short- and long-term mortality rates. The current diagnostic approach for AKI is based on late indicators, such as elevated serum creatinine and decreased urine output, which can only detect AKI after renal injury has transpired. There are no treatments to reverse or restore renal function once AKI has developed, other than supportive care. Early prediction of AKI enables proactive management and may improve patient outcomes.ObjectiveThe primary aim was to develop a machine learning algorithm, NAVOY Acute Kidney Injury, capable of predicting the onset of AKI in ICU patients using data routinely collected in ICU electronic health records. The ultimate goal was to create a clinical decision support tool that empowers ICU clinicians to proactively manage AKI and, consequently, enhance patient outcomes.MethodsWe developed the NAVOY Acute Kidney Injury algorithm using a hybrid ensemble model, which combines the strengths of both a Random Forest (Leo Breiman and Adele Cutler) and an XGBoost model (Tianqi Chen). To ensure the accuracy of predictions, the algorithm used 22 clinical variables for hourly predictions of AKI as defined by the Kidney Disease: Improving Global Outcomes guidelines. Data for algorithm development were sourced from the Massachusetts Institute of Technology Lab for Computational Physiology Medical Information Mart for Intensive Care IV clinical database, focusing on ICU patients aged 18 years or older.ResultsThe developed algorithm, NAVOY Acute Kidney Injury, uses 4 hours of input and can, with high accuracy, predict patients with a high risk of developing AKI 12 hours before onset. The prediction performance compares well with previously published prediction algorithms designed to predict AKI onset in accordance with Kidney Disease: Improving Global Outcomes diagnosis criteria, with an impressive area under the receiver operating characteristics curve (AUROC) of 0.91 and an area under the precision-recall curve (AUPRC) of 0.75. The algorithm's predictive performance was externally validated on an independent hold-out test data set, confirming its ability to predict AKI with exceptional accuracy.ConclusionsNAVOY Acute Kidney Injury is an important development in the field of critical care medicine. It offers the ability to predict the onset of AKI with high accuracy using only 4 hours of data routinely collected in ICU electronic health records. This early detection capability has the potential to strengthen patient monitoring and management, ultimately leading to improved patient outcomes. Furthermore, NAVOY Acute Kidney Injury has been granted Conformite Europeenne (CE)-marking, marking a significant milestone as the first CE-marked AKI prediction algorithm for commercial use in European ICUs.
| S-EPMC10755657 | biostudies-literature
Project description:Acute kidney injury (AKI) is a prevalent and serious condition in the intensive care unit (ICU), associated with significant morbidity and mortality. Septic acute kidney injury (SAKI) contributes substantially to AKI cases in the ICU. However, current diagnostic methods have limitations, necessitating the exploration of novel biomarkers. In this study, we investigated the potential of plasma and urine CCL2 levels as diagnostic markers for AKI and SAKI in 216 ICU patients. Our findings revealed significant differences in plasma (p < 0.01) and urine CCL2 (p < 0.0001) levels between AKI and non-AKI patients in the ICU. Notably, urine CCL2 demonstrated promising predictive value for AKI, exhibiting high specificity and sensitivity (AUC = 0.8976; p < 0.0001). Furthermore, we observed higher urine CCL2 levels in SAKI compared to non-septic AKI (p < 0.001) and urine CCL2 could also differentiate SAKI from non-septic AKI (AUC = 0.7597; p < 0.0001). These results suggest that urine CCL2 levels hold promise as early biomarkers for AKI and SAKI, offering valuable insights for timely intervention and improved management of ICU patients.
| S-EPMC10863526 | biostudies-literature
Project description:Leading organisations recommend follow-up of acute kidney injury (AKI) survivors, as these patients are at risk of long-term complications and increased mortality. Information transfer between specialties and from tertiary to primary care is essential to ensure timely and appropriate follow-up. Our aim was to examine the association between completeness of discharge documentation and subsequent follow-up of AKI survivors who received kidney replacement therapy (KRT) in the Intensive Care Unit (ICU). We retrospectively analysed the data of 433 patients who had KRT for AKI during ICU admission in a tertiary care centre in the UK between June 2017 and May 2018 and identified patients who were discharged from hospital alive. Patients with pre-existing end-stage kidney disease and patients who were transferred from hospitals outside the catchment area were excluded. The primary objective was to assess the completeness of discharge documentation from critical care and hospital; secondary objectives were to determine cardiovascular medications reconciliation after AKI, and to investigate kidney care and outcomes at 1 year. The development of AKI and the need for KRT were mentioned in 85 and 82% of critical care discharge letters, respectively. Monitoring of kidney function post-discharge was recommended in 51.6% of critical care and 36.3% of hospital discharge summaries. Among 35 patients who were prescribed renin-angiotensin-aldosterone system inhibitors before hospitalisation, 15 (42.9%) were not re-started before discharge from hospital. At 3 months, creatinine and urine protein were measured in 88.2 and 11.8% of survivors, respectively. The prevalence of chronic kidney disease stage III or worse increased from 27.2% pre-hospitalisation to 54.9% at 1 year (p < 0.001). Our data demonstrate that discharge summaries of patients with AKI who received KRT lacked essential information. Furthermore, even in patients with appropriate documentation, renal follow-up was poor suggesting the need for more education and streamlined care pathways.
| S-EPMC8476795 | biostudies-literature
Project description:BACKGROUND:Feeding dysfunction is a common consequence of prematurity and illness in neonates, often requiring supplemental nasogastric (NG) or gastrostomy (GT) feeding tubes. A standardized approach to the discharge of infants receiving home enteral nutrition (HEN) is currently lacking. METHODS:The Home Enteral Feeding Transitions (HEFT) program was developed to identify patients eligible for HEN and create a standard discharge process. A structured tool helped determine discharge timing and route, and a dedicated outpatient clinic was created for infants discharged on HEN. Demographic, inpatient, and outpatient data were prospectively collected and compared with a historical cohort. RESULTS:A total of 232 infants discharged from our neonatal intensive care unit (NICU) over 9 months met inclusion criteria. Ninety-eight (42%) were discharged with HEN, 68 NG and 30 GT, compared with 134 (58%) receiving full oral feeds. This represented a 10% increase in HEN utilization (P = 0.003) compared with our historical control group. Median HEN length of stay was 31.5 days compared with our historical average of 41 days (P = 0.23). Frequency of emergency department visits and admissions because of HEN was unchanged postintervention. Parents were satisfied (8.6/10), and 98% said they would choose HEN again. The median time to NG discontinuation after discharge was 13.5 days, with an estimated cost savings of $2163 per NICU day. CONCLUSION:Our program is the first of which we know to use a standard care-process model to guide the decision-making and utilization of HEN at NICU discharge. HEFT shows that HEN at NICU discharge can be safe and effective, with high parental satisfaction.
| S-EPMC7060820 | biostudies-literature