Abstract
OBJECTIVE:
Compare costs of hospitalization between critically-ill neonates with patent ductus arteriosus (PDA) who did and did not develop acute kidney injury (AKI).
STUDY DESIGN:
Using the Children’s Hospital Association’s Pediatric Health Information System (PHIS) database, we ascertained the marginal estimated total cost of hospitalization between those who did and did not develop AKI.
RESULTS:
Query of 49 PHIS centers yielded 14,217 neonates with PDA, 1697 with AKI and 12,520 without AKI. Predictors of cost included AKI, birth weight, ethnicity, race, length of stay (LOS), and Feudtner Complex Chronic Conditions Classification System. LOS was the strongest predictor (AKI: median 71 days [IQR 28–130]; No AKI: 28 days [10–76]; p < 0.01). Neonates with AKI had $48,416 greater costs (95% CI: $43,804–53,227) after adjusting for these predictors (AKI: $190,063, 95% CI $183,735–196,610; No AKI: $141,647, 95% CI $139,931–143,383 l; p < 0.01).
CONCLUSION:
AKI is independently associated with increased hospital costs in critically-ill neonates with PDA.
INTRODUCTION
Acute kidney injury (AKI) is a frequent complication encountered in the neonatal intensive care unit (NICU) affecting both preterm and term infants. In the largest epidemiologic study of neonatal AKI, the Assessment of Worldwide Acute Kidney Injury Epidemiology in Neonates (AWAKEN) study, 30% of critically ill infants receiving care in the NICU developed AKI with the highest incidence found in those infants born between 22 and 29 weeks’ gestation [1]. When evaluating the entire cohort, the authors of this multicenter, international cohort determined AKI was independently associated with both length of stay (LOS) and mortality.
Despite the frequency with which AKI occurs in the NICU, the economic impacts of AKI in critically ill neonates remain unknown. In adults in the United States, AKI-associated hospitalization costs exceed those of other familiar, high-acuity pathologies including myocardial infarction and gastrointestinal bleeding [2–4]. In children and neonates with congenital heart disease, AKI is an independent predictor of increased cost, and in pediatric patients with sickle cell disease admitted with vaso-occlusive crises, development of AKI is associated with increased hospitalization costs and utilization of hospital resources [5, 6]. To our knowledge, however, no data exist evaluating the costs associated with AKI in critically ill neonates in the NICU.
The current study begins to fill this void by evaluating the cost associated with AKI in neonates at increased risk for AKI, those with patent ductus arteriosus (PDA), utilizing the Children’s Hospital Association’s (CHA) Pediatric Health Information System (PHIS) database. Specifically, we aim to: (1) describe the incidence of AKI in neonates with PDA in a national dataset, (2) evaluate the predictors of costs associated with AKI in neonates with PDA, and (3) evaluate the independent association of AKI with costs in neonates with PDA. We hypothesized that AKI will be independently associated with increased costs of hospitalization, and the strongest contributor to higher costs will be LOS.
MATERIALS/SUBJECTS AND METHODS
Data source and study population
Using the CHA PHIS database, we conducted a retrospective cohort study of critically ill neonates with the diagnosis of PDA. PHIS is a comparative, pediatric administrative database containing clinical and resource utilization data for inpatient, ambulatory surgery, emergency department, and observation unit patient encounters for 49 children’s hospitals in the United States. All neonates with an International Classification of Disease, Tenth Revision (ICD-10-CM) diagnosis code for PDA (Q250), a ‘NICU Flag’ indicating NICU stay, and hospital admission dates between 03/01/2019 and 02/28/2021 were included. Infants were determined to have AKI based on the presence or absence of ICD-10 diagnosis code for AKI (N17.0, N17.1, N17.2, N17.8, N17.9, N19, N99.0, R34) [7].
Data collection
For each patient, abstracted data included encrypted patient identification number, gestational age at birth, birthweight (BW), sex, ethnicity, race, LOS, all ICD-10 diagnosis codes, and all ICD-10 procedure codes. Cost to charge ratio (CCR)-based adjusted total costs (expressed in United States dollars) were also collected. In the PHIS database data dictionary, estimated cost is determined by multiplying the abstract based charges by a CCR for each encounter based on the hospital and discharge year. The CCR is determined from the official cost reports submitted to Centers for Medicare & Medicaid Services annually.
Using each patient’s ICD-10 diagnosis and procedure codes, Feudtner Pediatric Complex Chronic Conditions Classification (CCC) System version 2 categorizations were applied to each patient as a method of measuring patient comorbid burden [8]. Potential Feudtner CCC categories include: cardiovascular, respiratory, neuromuscular, renal, gastrointestinal, hematologic or immunologic, metabolic, other congenital or genetic, malignancy, and premature or neonatal complex chronic conditions.
Statistical analysis
Baseline and demographic data were compared between those neonates with PDA who did and did not experience AKI. Continuous variables are presented as medians (interquartile ranges) for non-normally distributed variables, and comparisons were made using Wilcoxon-Mann-Whitney test. Categorical variables were presented as counts (percentages), and comparisons were made using Chi-squared test. All analyses were performed using SAS version 9.4 (SAS Institute, Cary, NC). Statistical significance was determined a priori to be at the α = 0.05 level.
The adjusted marginal total cost of hospitalization between those neonates with PDA who did and did not develop AKI was estimated using a gamma-distributed, log-transformed link function generalized linear model. The final model was adjusted for factors that might bias cost comparisons including AKI, ethnicity, race, LOS, CCC, and BW.
This study was approved by the Medical University of South Carolina (MUSC) Institutional Review Board and performed in accordance with the Declaration of Helsinki. A waiver of informed consent was granted due to the retrospective data collection and anonymity of protected health information. Methods and results are reported as required by STROBE guidelines [9].
RESULTS
Data from 14,217 neonates with PDA from 49 CHA PHIS centers, 1697 (11.9%) with AKI and 12,520 (88.1%) without AKI, were included (Fig. 1). Demographic and baseline characteristic of those with and without AKI are detailed in Table 1. Notably, significant differences were found in nearly every demographic and baseline characteristic category between those who did and did not develop AKI. Those infants who developed AKI were primarily male (56%), with a median BW of 1615 grams (IQR 740–2900 grams) and a median GA of 31 weeks (IQR 25–37 weeks). Those without AKI had a median BW 2470 grams (IQR 1190–3240 grams) and a median GA 36 weeks (IQR 29–38 weeks). Overall, 359 infants(2.5%) for our cohort died prior to discharge, and the rate of death was higher among those with AKI (AKI: 128/1697 died (7.5%) vs No AKI: 231/12520 died (1.9%); p < 0.01).
Fig. 1. Flow diagram detailing the study population.
The population was identified within the specified study dates in the Children’s Hospital Association’s (CHA) Pediatric Health Information System (PHIS) database, including those with and without acute kidney injury (AKI). NICU, neonatal intensive care unit. PDA, patent ductus arteriosus.
Table 1.
Demographic and baseline characteristics of neonates with and without acute kidney Injury (AKI).
| Demographics and characteristics | No AKI (n = 12,520) | AKI (n = 1697) | p value | |
|---|---|---|---|---|
| Gender | Female | 5930 (47) | 752 (44) | 0.02 |
| Male | 6578 (53) | 943 (56) | ||
| Missing | 12 (0.1) | 2 (0.1) | ||
| Race | Asian/Pacific Islander/American Indian | 489 (4) | 73 (4) | 0.17 |
| Black | 2719 (22) | 390 (23) | ||
| White | 6416 (51) | 827 (49) | ||
| Other | 1906 (15) | 252 (15) | ||
| Unknown | 990 (8) | 155 (9) | ||
| Ethnicity | Hispanic/Latino | 2104 (17) | 345 (20) | <0.01 |
| Not Hispanic/Latino | 9427 (75) | 1230 (73) | ||
| Unknown | 989 (8) | 122 (7) | ||
| Birthweight Groups | <500 grams | 205 (2) | 61 (4) | <0.01 |
| 500–<1000 grams | 2301 (18) | 625 (37) | ||
| 1000–<1500 grams | 1370 (11) | 139 (8) | ||
| 1500–<2500 grams | 2472 (20) | 270 (16) | ||
| ≥2500 grams | 6172 (49) | 602 (36) | ||
| Gestational Age Groups | 22–26 weeks | 1838 (15) | 581 (34) | <0.01 |
| 27–30 weeks | 1508 (12) | 151 (9) | ||
| 31–34 weeks | 1367 (11) | 156 (9) | ||
| 35–37 weeks | 2617 (21) | 295 (17) | ||
| ≥38 weeks | 3752 (30) | 336 (20) | ||
| Missing | 1438 (12) | 178 (11) | ||
| Feudtner Pediatric Complex Chronic Conditions (CCC) | Any CCC? | 10,908 (87) | 1680 (99) | <0.01 |
| # of CCC’s | 2.2 ± 1.7 | 3.3 ± 1.8 | <0.01 | |
| Cardiovascular | 5745 (46) | 932 (55) | <0.01 | |
| Congenital/Genetic | 2564 (21) | 338 (20) | 0.60 | |
| Gastrointestinal | 3225 (26) | 649 (38) | <0.01 | |
| Hematologic/Immunologic | 401 (3) | 119 (7) | <0.01 | |
| Metabolic | 640 (5) | 229 (14) | <0.01 | |
| Neonatal | 6638 (53) | 1380 (82) | <0.01 | |
| Renal | 1855 (15) | 490 (29) | <0.01 | |
| Respiratory | 1733 (14) | 380 (22) | <0.01 | |
| Medical Technology (i.e. Device Dependency) | 2865 (23) | 699 (41) | <0.01 |
Continuous variables presented as mean ± standard deviation; Categorical variables presented as counts (percentages).
Significant predictors of cost included AKI, BW, race, ethnicity, LOS, and Feudtner CCC, specifically cardiovascular, other congenital or genetic, gastrointestinal, hematologic or immunologic, metabolic, premature and neonatal, renal and urology, respiratory, and technology dependence CCCs (all p value < 0.01). LOS was the strongest predictor of cost (AKI: median 71 days [IQR 28–130 days]; No AKI: 28 days [10–76 days]; p < 0.01) (Table 2). Neonates with AKI had on average $48,416 greater costs (95% CI: $43,804–53,227) than those without AKI after adjusting for these predictors (AKI: $190,063, 95% CI $183,735–196,610; No AKI: $141,647, 95% CI $139,931–143,383; p < 0.01) (Table 2).
Table 2.
Outcomes of Interest.
| Outcomes of interest | No AKI (n = 12,520) | AKI (n = 1697) | p-value |
|---|---|---|---|
| Adjusted° Costs of Hospitalization, average costs (95% CI) | $141,647 (139,931–143,383) | $190,063 (183,735–196,610) | <0.01 |
| Length of stay, median [IQR] | 28 days [10–76] | 71 days [28–130] | <0.01 |
Adjusted for acute kidney injury, birth weight, race, ethnicity, length of stay, and Feudtner pediatric complex chronic conditions classifications.
We conducted several secondary analyses. Although significant multicollinearity between gestational age and BW were noted, we included gestational age as a categorical covariate (22–26 weeks, 27–30 weeks, 31–34 weeks, 35–37 weeks, and ≥38 weeks of gestation) to calculate the adjusted total costs of neonates with and without AKI. To account for a small amount of missingness in gestational age (11.4%), we utilized multiple imputation by chained equations, utilizing 25 multiply-imputed datasets, imputing gestational ages using predictive mean matching. The result of this analysis was very similar to the primary cost analysis, demonstrating neonates with AKI had $49,384 greater costs (95% CI: $44,737–54,228) (Table 3).
Table 3.
Comparison of Adjusted Total Cost Models.
| Models | No AKI | AKI | Difference |
|---|---|---|---|
| Original (no gestational age (GA)) | $141,647 | $190,063 | $48,416 |
| With GA (multiple imputations of GA) | $141,420 | $190,804 | $49,384 |
| Survivors only (same as original) | $141,478 | $187,662 | $46,184 |
In a sub-analysis including only those who survived their index admission (n = 13,858), LOS was again the strongest predictor of costs, and it was still significantly longer for those with AKI than those without AKI (AKI: median 76 days [IQR 31–132 days]; No AKI: median 29 days [IQR 11–76 days]; p < 0.01). We also found that those with AKI had $46,184 greater costs (95% CI $41,438–51,139) than those without AKI after adjusting for the same predictors (AKI: $187,662, 95% CI $181,193–194,362; No AKI: $141,478, 95% CI $139,755–143,223; p < 0.01) (Table 3).
A secondary, sub-group analysis among infants with PDA who were very-low birthweight (i.e. <1500 grams) we found a statistically-significant difference in costs (p < 0.01), with costs markedly greater among infants with AKI—similar to the main analysis. However, the adjusted costs were much greater in this group of patients. In this analysis the adjusted total costs were $281,923 (95% CI: 276,941–286,995) for those without AKI and $312,102 (95% CI: 300,022–324,668) for those with AKI.
DISCUSSION
In this first examination of costs associated with AKI in a high risk NICU population, those with PDA, we found that neonatal AKI is independently associated with increased hospital costs by an average of $48,416 per patient with neonatal AKI. We have also identified key drivers of costs of hospitalization among neonates with PDA, including the most significant driver, LOS. Among neonates with both PDA and AKI, median LOS was 71 days [IQR 28–130 days] while those without AKI had significant shorter LOS at a median 28 days [10–76]; p < 0.01). In secondary sub-group analyses, we found similar results. When examining LOS and costs in only those who survived their index admission in our cohort, both LOS and costs were significantly higher in those with AKI compared to those without AKI, and we are confident that those who did not survive admission have little effect on our initial cost estimates. Similarly, when examining costs in only those with very low birthweight, we found a similar significant increase in costs among those infants with AKI; however, as one might expect, the adjusted costs were much greater in this group of patients. Together, these findings support our a priori hypotheses and may help to identify future high-value practices for prevention of neonatal AKI and cost mitigation strategies in this population.
With the publication of the AWAKEN study in 2017, understanding of the incidence and impacts of neonatal AKI has dramatically improved and interest in neonatal AKI has increased [1]. Across this broad, multicenter multinational cohort of critically ill neonates in the NICU, overall, 30% of neonates experienced AKI, but incidence of AKI varied by gestational age (22 to <29 weeks: 48%, 29 to <36 weeks: 18%, ≥36 weeks: 37%). AWAKEN authors found that neonatal AKI is not only common but independently associated with increased mortality (adjusted OR 4.6, 95% CI 2.5–8.3, p < 0.0001) and increased LOS (adjusted parameter estimate 8.8 days, 95% CI 6.1–11.5, p < 0.0001). Prior to AWAKEN, neonatal AKI was frequently thought to be a relatively infrequent clinical matter with few short- or long-term consequences. When comparing our findings to those of the AWAKEN study, the most obvious difference is the incidence rate of AKI; AWAKEN reported an overall AKI incidence of 30%, but we found only 11.9% (1697/14,217) of our high-risk cohort experienced AKI. This significant difference in AKI incidence is likely accounted for by the way in which AKI was identified. In AWAKEN, manual chart review was performed to identify AKI cases based on current Kidney Disease: Improving Global outcomes (KDIGO) modified neonatal AKI criteria while in this cohort, AKI was identified via ICD-10 codes as creatinine values are not available within the database [1, 10, 11]. Neonatal AKI is frequently under-recognized and under-reported, and our low AKI rate likely reflects this [12–16]. Further, a recent study by Schaffzin et al. suggests administrative databases such as the PHIS database may fail to identify AKI [16, 17]. If in fact under-recognition of neonatal AKI is the cause of our low AKI incidence rate, the AKI identified in our cohort was likely more clinically obvious and potentially severe, and milder cases could have gone undiagnosed. It is difficult to postulate how potential improved recognition of neonatal AKI would alter our results, but we hypothesize that milder cases of AKI are missing from our cohort leading to over-estimation of the costs associated with AKI.
Among neonates in the NICU, particularly the most premature, PDA is common, and neonates with PDA are at particularly high risk for AKI for multiple reasons [18–22]. Premature kidneys, by virtue of being premature and under-developed, are highly susceptible to injury [23]. Nephrotoxic medication exposure is common in premature infants and frequently is associated with AKI; specifically, non-steroidal anti-inflammatory medications, including indomethacin and ibuprofen, are frequently prescribed to medically treat the PDA [24]. Lastly, a “steal” phenomenon whereby there is poor perfusion to the kidneys due to diastolic run-off through the PDA also likely contributes to high AKI rates in neonates with PDA [18]. Regardless of the specific causes, the high rates of AKI in neonates with PDA make this particular NICU sub-population ideal for study of the costs associated with neonatal AKI. By examining this sub-group, we aimed to identify a high rate of AKI to best quantify AKI costs. This pilot study has served to ensure the feasibility of examining costs associated with neonatal AKI in a broader NICU cohort.
To date, very few studies have examined the costs of neonatal AKI; however, studies of adults and pediatric patients in the United States suggest that AKI is independently associated with prolonged hospitalization and excessive hospitalization costs. In adults recovering from a surgical intervention at the University of Florida, AKI was frequent, affecting 39% of >50,000 patients, and those who experienced AKI were more likely to have other postoperative complications along with longer LOS in the intensive care unit (ICU) and the hospital as well as increased mortality [4]. The risk-adjusted average cost of care for patients undergoing surgery was $42,600 for those with AKI compared to $26,700 for those without AKI. Similarly, in a study of adults using the 2012 National Inpatient Sample, AKI was associated with an increase in hospitalization costs of $1795 (95% CI $1692–$1899) and an increase in LOS of 1.1 days (95% CI 3.2–3.3 days) compared to adults without AKI after adjustments for patient and hospital characteristics; the hospital costs associated with AKI in this large study exceeded those of other familiar, high-acuity pathologies including myocardial infarction and gastrointestinal bleeding [2]. AKI was found to be an independent predictor of increased cost (adjusted OR 2.11 (95% CI 1.35–1.90), p < 0.001) in a large pediatric study examining the overall hospital costs in children with congenital heart disease using the 2012 Healthcare Cost and Utilization Project Kid’s Inpatient Database (2012 KID HCUP) [5]. In hospitalized pediatric patients with sickle cell disease, a disease that causes vaso-occlusive crises that frequently require hospitalization, AKI is uncommon (2.5% of admissions were complicated by AKI) but costly [6]. Among those who developed AKI, admission to the ICU was more common (61.9% vs. 5.3% in those without AKI), LOS in the hospital was longer (median 12 days vs. 4 days), and standardized hospital costs were significantly higher (median $58,903 vs. $ 11,589; all p < 0.001) than in those without AKI. To our knowledge, there are no studies examining the economic consequences or the drivers of costs of neonatal AKI itself let alone studies in high-risk sub-populations such as those neonates with PDA.
We acknowledge a number of both strengths and limitations of this retrospective cohort study. As the first examination of economic burden of AKI in an exclusively neonatal population, our study is novel and provides baseline data on which to build. We have also uniquely utilized the Feudtner CCC system as a method to control for severity of illness in our cohort and utilized a sub-population of patients at high risk for AKI to quantify these costs. The PHIS database is an exceptional administrative database that can provide accurate data for cost estimation and allowed us to study a relatively large cohort. However, as an administrative database, clinical information about these patients is limited due to the retrospective nature of these data. Also, as previously mentioned, the AKI rate in our cohort was lower than we expected. Cases of AKI are most certainly missing, which could bias our estimations.
CONCLUSION
In conclusion, in this first ever analysis and pilot study of the economic burden of AKI in critically-ill neonates, we evaluate the hospital costs associated with development of neonatal AKI among NICU patients with PDA, a sub-group known to be at high risk for AKI. We found neonatal AKI was independently associated with increased hospital costs in neonates with PDA in the NICU; These increased costs are most strongly impacted by increased LOS among those with PDA and AKI. Knowledge of these drivers can help in identifying high-value practices for prevention of neonatal AKI and cost-mitigation strategies.
Footnotes
COMPETING INTERESTS
The authors declare no competing interests.
DATA AVAILABILITY
Datasets to be provided should they be requested.
REFERENCES
- 1.Jetton JG, Boohaker LJ, Sethi SK, Wazir S, Rohatgi S, Soranno DE, et al. Incidence and outcomes of neonatal acute kidney injury (AWAKEN): a multicentre, multinational, observational cohort study. Lancet Child Adolesc Health. 2017;1:184–94. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.Silver SA, Long J, Zheng Y, Chertow GM. Cost of acute kidney injury in hospitalized patients. J Hosp Med. 2017;12:70–76. [DOI] [PubMed] [Google Scholar]
- 3.Silver SA, Chertow GM. The Economic consequences of acute kidney injury. Nephron. 2017;137:297–301. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Hobson C, Ozrazgat-Baslanti T, Kuxhausen A, Thottakkara P, Efron PA, Moore FA, et al. Cost and mortality associated with postoperative acute kidney injury. Ann Surg. 2015;261:1207–14. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Faraoni D, Nasr VG, DiNardo JA. Overall Hospital cost estimates in children with Congenital Heart Disease: analysis of the 2012 Kid’s inpatient database. Pediatr Cardiol. 2016;37:37–43. [DOI] [PubMed] [Google Scholar]
- 6.McCormick M, Richardson T, Warady BA, Novelli EM, Kalpatthi R. Acute kidney injury in paediatric patients with sickle cell disease is associated with increased morbidity and resource utilization. Br J Haematol. 2020;189:559–65. [DOI] [PubMed] [Google Scholar]
- 7.International statistical classification of diseases and related health problems. 11th. ed: World Health Organization.; 2019. [Google Scholar]
- 8.Feudtner C, Feinstein JA, Zhong W, Hall M, Dai D. Pediatric complex chronic conditions classification system version 2: updated for ICD-10 and complex medical technology dependence and transplantation. BMC Pediatr. 2014;14:199. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.von Elm E, Altman DG, Egger M, Pocock SJ, Gøtzsche PC, Vandenbroucke JP. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies. Ann Intern Med. 2007;147:573–7. [DOI] [PubMed] [Google Scholar]
- 10.Jetton JG, Guillet R, Askenazi DJ, Dill L, Jacobs J, Kent AL, et al. Assessment of worldwide acute kidney injury epidemiology in neonates: design of a retrospective cohort study. Front Pediatr. 2016;4:68. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Zappitelli M, Ambalavanan N, Askenazi DJ, Moxey-Mims MM, Kimmel PL, Star RA, et al. Developing a neonatal acute kidney injury research definition: a report from the NIDDK neonatal AKI workshop. Pediatr Res. 2017;82:569–73. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Vincent K, Murphy HJ, Ross JR, Twombley KE. Acute kidney injury guidelines are associated with improved recognition and follow-up for neonatal patients. Adv Neonatal Care. 2020;20:269–75. [DOI] [PubMed] [Google Scholar]
- 13.Roy JP, Goldstein SL, Schuh MP. Under-recognition of neonatal acute kidney injury and lack of follow-up. Am J Perinatol. 2022;39:526–31. [DOI] [PubMed] [Google Scholar]
- 14.Starr MC, Chaudhry P, Brock A, Vincent K, Twombley K, Bonachea EM, et al. Improving the identification of acute kidney injury in the neonatal ICU: three centers’ experiences. J Perinatol. 2022;42:243–6. [DOI] [PubMed] [Google Scholar]
- 15.Starr MC, Kula A, Lieberman J, Menon S, Perkins AJ, Lam T, et al. The impact of increased awareness of acute kidney injury in the Neonatal Intensive Care Unit on acute kidney injury incidence and reporting: results of a retrospective cohort study. J Perinatol. 2020;40:1301–7. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Carmody JB, Swanson JR, Rhone ET, Charlton JR. Recognition and reporting of AKI in very low birth weight infants. Clin J Am Soc Nephrol. 2014;9:2036–43. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Schaffzin JK, Dodd CN, Nguyen H, Schondelmeyer A, Campanella S, Goldstein SL. Administrative data misclassifies and fails to identify nephrotoxin-associated acute kidney injury in hospitalized children. Hosp Pediatr. 2014;4:159–66. [DOI] [PubMed] [Google Scholar]
- 18.Velazquez DM, Reidy KJ, Sharma M, Kim M, Vega M, Havranek T. The effect of hemodynamically significant patent ductus arteriosus on acute kidney injury and systemic hypertension in extremely low gestational age newborns. J Matern Fetal Neonatal Med. 2019;32:3209–14. [DOI] [PubMed] [Google Scholar]
- 19.Bömelburg T, Jorch G. Abnormal blood flow patterns in renal arteries of small preterm infants with patent ductus arteriosus detected by Doppler ultrasonography. Eur J Pediatr. 1989;148:660–4. [DOI] [PubMed] [Google Scholar]
- 20.Aygün A, Poryo M, Wagenpfeil G, Wissing A, Ebrahimi-Fakhari D, Zemlin M, et al. Birth weight, Apgar scores and gentamicin were associated with acute kidney injuries in VLBW neonates requiring treatment for patent ductus arteriosus. Acta Paediatr. 2019;108:645–53. [DOI] [PubMed] [Google Scholar]
- 21.Majed B, Bateman DA, Uy N, Lin F. Patent ductus arteriosus is associated with acute kidney injury in the preterm infant. Pediatr Nephrol. 2019;34:1129–39. [DOI] [PubMed] [Google Scholar]
- 22.Guillet R, Selewski DT, Griffin R, Rastogi S, Askenazi DJ, D’Angio CT. Relationship of patent ductus arteriosus management with neonatal AKI. J Perinatol. 2021;41:1441–7. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Vogt BA, Dell KM. The Kidney and Urinary Tract of the Neonate. In: Martin RJ, Fanaroff AA, Walsh MC (eds). Fanaroff & Martin’s Neonatal-Perinatal Medicine: Diseases of the Fetus and Newborn, vol. 10th ed. Elsevier: Philadelphia, PA, 2015, pp 1676–99. [Google Scholar]
- 24.Rhone ET, Carmody JB, Swanson JR, Charlton JR. Nephrotoxic medication exposure in very low birth weight infants. J Matern Fetal Neonatal Med. 2014;27:1485–90. [DOI] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
Datasets to be provided should they be requested.