Predictors of kidney complications and analysis of hypertension in children with allogeneic hematopoietic stem cell transplantation

Gurbanov, Anar; Gülhan, Bora; Kuşkonmaz, Barış; Okur, Fatma Visal; Özaltın, Fatih; Düzova, Ali; Çetinkaya, Duygu Uçkan; Topaloğlu, Rezan

doi:10.1007/s00467-022-05599-x

Cited by 11 publications

(6 citation statements)

References 25 publications

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“…Recent data have also confirmed that the incidence of AKI is significantly higher in children with documented viral infections [9]. These results are in concert with our data deciphering the impact of ADV/CMV infections on AKI incidence.…”

Section: Discussionsupporting

confidence: 90%

“…According to a recent analysis, the main factors are a matched unrelated donor, cord blood transplantation, and sinusoidal obstruction syndrome [5]. Other studies confirm the influence of unrelated donors, underlining the additional roles of viral infections, malignant disease as the indication, drug nephrotoxicity, complications like thrombotic microangiopathy, or an older child's age, in aggravating the risk of AKI development after HSCT [6][7][8][9][10]. Recent data also point to the impact of initially increased estimated glomerular filtration rate (eGFR) values on further AKI recurrence [11].…”

Section: Introductionmentioning

confidence: 99%

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Assessment of Risk Factors for Acute Kidney Injury with Machine Learning Tools in Children Undergoing Hematopoietic Stem Cell Transplantation

Musiał,

Stojanowski,

Augustynowicz

et al. 2024

JCM

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Background: Although acute kidney injury (AKI) is a common complication in patients undergoing hematopoietic stem cell transplantation (HSCT), its prophylaxis remains a clinical challenge. Attempts at prevention or early diagnosis focus on various methods for the identification of factors influencing the incidence of AKI. Our aim was to test the artificial intelligence (AI) potential in the construction of a model defining parameters predicting AKI development. Methods: The analysis covered the clinical data of children followed up for 6 months after HSCT. Kidney function was assessed before conditioning therapy, 24 h after HSCT, 1, 2, 3, 4, and 8 weeks after transplantation, and, finally, 3 and 6 months post-transplant. The type of donor, conditioning protocol, and complications were incorporated into the model. Results: A random forest classifier (RFC) labeled the 93 patients according to presence or absence of AKI. The RFC model revealed that the values of the estimated glomerular filtration rate (eGFR) before and just after HSCT, as well as methotrexate use, acute graft versus host disease (GvHD), and viral infection occurrence, were the major determinants of AKI incidence within the 6-month post-transplant observation period. Conclusions: Artificial intelligence seems a promising tool in predicting the potential risk of developing AKI, even before HSCT or just after the procedure.

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Section: Discussionsupporting

confidence: 90%

Section: Introductionmentioning

confidence: 99%

Assessment of Risk Factors for Acute Kidney Injury with Machine Learning Tools in Children Undergoing Hematopoietic Stem Cell Transplantation

Musiał,

Stojanowski,

Augustynowicz

et al. 2024

JCM

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“…25 Studies have demonstrated a significant benefit with the implementation of 24-hour ambulatory BP monitoring immediately after HSCT, as well as at regular intervals during the later periods post-HSCT. [26][27][28] Many of the medications prescribed to patients after HSCT may induce hypertension. For instance, the incidence of calcineurin inhibitor-associated hypertension ranges from 65% to 100% in adult trials, which contextualizes the prevalence of calcineurin inhibitor use in our study and the poor survival probability.…”

Section: Discussionmentioning

confidence: 99%

“…39 Gurbanov et al recommended that immunosuppressants should be discontinued altogether in HSCT patients without GVHD. 26 These recommendations may apply to the use of intravenous vancomycin, which is well-known for its nephrotoxic properties. 40 In a retrospective study of stem cell transplant patients, 38% of those who developed AKI were administered vancomycin; two went on to require dialysis.…”

Section: Discussionmentioning

confidence: 99%

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Epidemiology, Risk Factors, and Clinical Outcomes of AKI in Pediatric Hematopoietic Stem Cell Transplant Patients

Ashruf,

Orozco

et al. 2024

Kidney360

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Key Points The cumulative incidence of AKI diagnosis post–hematopoietic stem cell transplantation was 12.9%. Calcineurin inhibitor use was associated with the highest cumulative incidence, 21.6%, after hematopoietic stem cell transplantation.Patients with AKI with hypertension/hypertensive disease had a 30-day survival probability of 63.9% (hazard ratio, 4.86, 95% confidence interval, 3.58 to 6.60).Patients with AKI were 2.5 times more likely to experience composite hospitalization and/or mortality at 30 days. Of patients who developed AKI, dialysis dependence has nearly tripled since 2014. Background AKI is a common complication in pediatric patients undergoing hematopoietic stem cell transplantation (HSCT), with a reported prevalence ranging from 68% to 84%. Few multicenter pediatric studies comprehensively assess the epidemiologic associations and clinical outcomes associated with AKI development. Methods An observational, retrospective analysis was conducted using an aggregated electronic health record data platform. The study population consisted of pediatric patients (age <18 years) who underwent HSCT over a 20-year period. The study groups consisted of patients with an encounter diagnosis of AKI (n=713) and those without AKI (n=4455). Both groups were propensity matched for age, sex, race, prior cancer diagnosis, and other comorbidities. End points were incidence, mortality risk, clinical outcomes, and prevalence of dialysis dependence. Competing risks analysis, Cox proportional hazard analyses, Kaplan–Meier survival curves, and incidence/prevalence rates were calculated. Results After matching, 688 patients were identified. Cumulative incidence of AKI diagnosis post-HSCT was 13.7%. Hypertensive disease, calcineurin inhibitors, and vancomycin were the most prevalent risk factors for AKI, with calcineurin inhibitors showing the highest cumulative incidence (21.6%). Patients with AKI with hypertensive disease had a survival probability of 63.9% at 30 days, followed by calcineurin inhibitors (64.4%) and vancomycin (65.9%). Patients with AKI were 1.7 times more likely to experience composite hospitalization and/or mortality at 30 days. At 365 days post-HSCT, patients with AKI had higher rates of all-cause emergency department visits, intensive care unit admissions, and mechanical ventilation compared with non-AKI. Of patients who developed AKI, the prevalence of dialysis dependence has nearly tripled since 2014. Conclusions The findings highlight a strong association between specific risk factors, such as hypertension, calcineurin inhibitor use, and vancomycin use, with increased mortality and adverse clinical outcomes in patients with AKI after HSCT. These results emphasize the need for preventative actions such as 24-hour BP monitoring and discontinuation of potential nephrotoxic medications.

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A Two‐Center Study of a Prognostic Model Related to Acute Kidney Injury After Allogeneic Hematopoietic Stem Cell Transplantation in Children: Development of a New Predictive Dynamic Nomogram

Chen,

Jia,

Guo

et al. 2024

Pediatric Blood & Cancer

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ObjectivesThe purpose of this study was to develop a straightforward, easy‐to‐use online dynamic nomogram for the identification of children who are at high risk of developing acute kidney injury (AKI) after allogeneic hematopoietic stem cell transplantation (allo‐HSCT).MethodsThis was a two‐center study in which 242 children in Henan Provincial Children's Hospital composed the training cohort, and 115 children in the First Affiliated Hospital of Zhengzhou University composed the validation cohort. Kaplan–Meier survival analysis was used to compare survival between children with nonacute kidney injury (NAKI) and children with AKI. Multivariate logistic regression analysis was used to identify risk factors for AKI in children who underwent HSCT. The selected variables were utilized to construct nomograms, which were validated via the concordance index (C‐index), decision curve analysis, calibration curve analysis, and receiver operating characteristic (ROC) curve analysis.ResultsCumulative survival was significantly lower in children with AKI than in children without kidney injury (p < 0.01). Eight variables were included in the nomogram: hepatic veno‐occlusive disease (HVOD), graft‐versus‐host disease (GVHD), ferritin, C‐reactive protein (CRP), Cytomegalovirus infection (CMV), thrombotic microangiopathy (TMA), human leukocyte antigen (HLA), and nephrotoxic drugs. The nomogram calibration curves in the training and validation cohorts were highly comparable to the standard curves. The areas under the curve (AUCs) of the prediction model were 0.963 and 0.910 in the training cohort and validation cohort, respectively. The decision curve analysis (DCA) revealed that the model had a significant clinical benefit.ConclusionsThe occurrence of AKI affects the prognosis of children who undergo HSCT. We developed a dynamic online nomogram for predicting AKI in children who underwent allo‐HSCT on the basis of eight variables. The predictive value and clinical benefit of the nomogram model were acceptable.

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Predictors of kidney complications and analysis of hypertension in children with allogeneic hematopoietic stem cell transplantation

Cited by 11 publications

References 25 publications

Assessment of Risk Factors for Acute Kidney Injury with Machine Learning Tools in Children Undergoing Hematopoietic Stem Cell Transplantation

Assessment of Risk Factors for Acute Kidney Injury with Machine Learning Tools in Children Undergoing Hematopoietic Stem Cell Transplantation

Epidemiology, Risk Factors, and Clinical Outcomes of AKI in Pediatric Hematopoietic Stem Cell Transplant Patients

A Two‐Center Study of a Prognostic Model Related to Acute Kidney Injury After Allogeneic Hematopoietic Stem Cell Transplantation in Children: Development of a New Predictive Dynamic Nomogram

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