Abstract
Background:
To determine the prevalence and severity of acute kidney injury (AKI) at different time frames in relation to gestational age (GA) and birthweight (BW) in extremely low gestational age neonates (ELGAN). Our hypothesis is that ELGAN with lower GA and lower BW have higher AKI rates.
Methods:
923 ELGAN enrolled in the Preterm Erythropoietin Neuroprotection Trial were evaluated from birth until death or hospital discharge. AKI was defined according to kidney disease: improving global outcomes (KDIGO) definition from clinically-derived serum creatinine (SCr) measurements. Severe AKI was defined as stage 2 or higher.
Results:
For the entire cohort, 351/923 (38.0%, CI = 34.8–41.3%) had at least one episode of stage 1 or higher AKI and 168/923 (18.2%, CI = 15.7–20.7%) had at least one episode of severe (stage 2 or higher) AKI. The prevalence of AKI stage 1 or higher for the entire cohort during the early (days 3–7), middle (days 8–14) and late follow-up period (after day 14) was 112/923 (12.1%, CI = 10.0–14.3%), 142/891 (15.9%, CI = 13.5–18.4%) and 249/875 (28.5%, CI = 25.4–31.5%), respectively. The rates of severe AKI during the hospital course were 27.8%, 21.9%, 13.6%, and 9.4% for the 24, 25, 26 and 27 week GA groups respectively. AKI rates were significantly higher with decreasing GA and decreasing BW for stated time trends (all p < 0.01 using tests for trend).
Conclusions:
AKI is relatively common in ELGAN during their initial hospital course, and is associated with lower GA and BW.
Keywords: Acute renal failure, incidence, timing, cystatin c, neonate, premature
Introduction
Single-center studies of premature infants have reported that acute kidney injury (AKI) is common and associated with mortality and prolonged length of stay [1–7]. The Assessment of Worldwide Acute Kidney Injury Epidemiology in Neonates (AWAKEN), a retrospective multi-center study, showed that both early and late AKI are common in extremely low gestational age neonates (ELGAN), and those with AKI had a greater than 3-fold increased odds of death [8]. However, the sample size of these studies are not large enough to make strong inferences on subgroups of ELGAN.
The rates of AKI in very premature neonates approximate those of sick term neonates, and both groups have higher AKI rates compared to mildly premature infants [8]. The AKI etiologies and risk factors differ by GA groups and whether AKI occurs early [9] (in the first postnatal week) and later [10]. Until now, evaluations of AKI in premature neonates describe a relatively broad GA range (e.g. AWAKEN grouped into all who < 32 weeks GA; Carmody et al. reported on 455 very low birth weight infants (birthweight < 1500 grams) [2]. There continue to be knowledge gaps in our understanding of AKI in extremely low GA neonates (ELGAN, born < 28 weeks). Specifically, it is unknown how the degree of prematurity and low birthweight impacts the prevalence, severity and timing of neonatal AKI. Amongst ELGAN, it is possible that the prevalence, risk factors and outcomes ascribed to AKI will differ for even one week differences in GA, and small differences in birthweight, given that one extra week of premature birth and intra-uterine growth restriction can influence predisposing AKI factors, complications, clinical outcomes, and nephron development which continues until 34–36 weeks post GA weeks [11]. A large cohort of ELGAN with robust measurements of serum creatinine, and cystatin C (a marker of glomerular filtration rate, which is not dependent on muscle mass and has no tubular secretion) is needed to fill the gaps in knowledge on the prevalence, severity and timing of AKI by GA and BW during the neonatal intensive care unit (NICU) course.
We evaluate kidney-specific data in neonates enrolled in the Preterm Erythropoietin Neuroprotection Trial (PENUT), a multi-center trial which randomized ELGAN (24–27 weeks gestational age) to erythropoietin (Epo) or placebo. The current study was designed as an ancillary study to the PENUT study, and was supported via an NIH-sponsored R01 ancillary project to existing clinical trials entitled Recombinant Erythropoietin for Protection of Infant Renal Disease (REPaIReD) study. Using SCr values measured as part of clinical care, we compare the prevalence and severity of AKI by specific time frames (first, second, and after the second postnatal week) across four gestational age (GA) categories (24, 25, 26 and 27 weeks). We also report normative values and changes over time for centrally measured SCr and serum Cystatin C on postnatal days 0, 7, 9 and 14. Our primary hypothesis is that the neonatal AKI prevalence and severity will be higher in the younger GA groups and lower BW during all three of the described time frames. Our secondary hypothesis is that SCr and Cystatin C values and trajectories over time vary by GA.
Methods
Patient population
The Preterm Epo Neuroprotection Trial (PENUT Trial) is a randomized, placebo-controlled double-blind clinical trial of Epo in ELGAN who were admitted to 19 NICUs across 13 states in the United States from January 2013 - September 2016 [12]. PENUT enrolled 941 infants who met the following inclusion criteria: 1) inborn patients born between 24 – 0/7 and 27– 6/7 weeks of gestation in participating NICUs, 2) less than 24 hours of age, 3) parental informed consent obtained, and 4) available arterial or venous access. Exclusion criteria included: 1) major life-threatening anomalies (brain, cardiac and chromosomal anomalies), 2) hematologic crises such as DIC or hemolysis due to blood group incompatibility, 3) polycythemia (hematocrit >65%), 4) hydrops fetalis, and 5) known congenital infection. The consort diagram, reasons for exclusion, safety and outcomes of the PENUT study have been published elsewhere [13, 12]. Of note for this study, of the 2,343 infants who were screened for enrollment, 66/2,343 (2.8%) were excluded due to major life-threatening anomalies defined as “fetal diagnosis of brain, cardiac renal malformations or chromosomal anomalies”, and 31/2343 (1.3%) screened subjects were not included due to lack of an umbilical arterial or venous catheter.
Of the 941 subjects enrolled in the study, we excluded four neonates who died prior to receiving study drug and one who was enrolled incorrectly. In addition, we excluded 13 infants who died on days 0, 1 and 2 (since a diagnosis of AKI prior to day 2 is difficult as earlier measures are either reflective of maternal status or we were unable to characterize changes in SCr). Therefore, the final sample of ELGAN for REPaIReD includes the 923 subjects who received study drug and were alive on day 3 (Figure 1).
Fig. 1.
941 subjects were enrolled in the PENUT study. We excluded five infants who were removed from the parent study (4 died prior to receiving study drug, and one who was enrolled incorrectly). Furthermore, we also excluded 13 infants who died on days 0, 1 and 2. Therefore, the final sample of ELGAN for REPaIReD were the 923 who received study drug and were alive on day 3
AKI definitions and time frames of assessments for AKI using clinical SCr data
We used the SCr-based Kidney Disease Improving Global Outcomes (KDIGO) criteria to define neonatal AKI as previously reported [8, 14], using clinically measured SCr values. Each institution measured SCr according to their institution guidelines using the local laboratory methodology available (11 Jaffe, 8 enzymatic). We chose the KDIGO definition because in 2013, an NIH-NIDDK Neonatal AKI definition working group concluded that the KDIGO definition was the best currently available approach to define AKI, and it allows for consistency across studies [14]. AKI is defined as a ≥ 0.3 mg/dl rise within 48 hours or a ≥ 150% SCr rise from baseline.
For the current study, the baseline SCr is defined as the lowest previous value measured (not including any values measured on the birth day or the day after birth). We chose to exclude the SCr measured on the day of birth a priori because this value represents maternal SCr and we excluded the next day because a plateau in SCr does not occur for the next 36–48 hours in ELGAN [15, 16]. The earliest baseline SCr value used to define AKI in this study is on day 2 of life. Thus, it is not until day 3 when the rise in SCr from baseline can be met in this study. We recognize that recent definition of the baseline SCr values in neonates have used the lowest prior value from the time of birth, although other recent quality improvement endeavors to reduce neonatal AKI have removed SCr values in the first days after birth. By choosing to define a baseline SCr, we are conservative in our rates of AKI (as it will be harder for infants to meet a threshold of SCr rise without the lower SCr values that happen in the first days after birth. We provide a comparison of the rates of AKI by both of these baseline SCr definitions in the results.
We define the severity of AKI as the maximum AKI stage (Table 1) using the highest value for SCr achieved during the stated timeframes. We define severe AKI as stage 2 or 3 AKI, as previously described in other multi-center neonatal [8] and pediatric [17] AKI studies.
Table 1:
Neonatal KDIGO AKI definition
| Stage | Serum Creatinine (SCr) |
|---|---|
| No AKI | No change in SCr or rise < 0.3 mg/dL |
| 1 | SCr rise ≥ 0.3 mg/dl within 48 hrs or |
| SCr rise ≥ 1.5– 1.9 X reference SCr* | |
| 2 | SCr rise ≥ 2 to 2.9 X reference SCr* |
| 3 | SCr rise ≥ 3 X reference SCr * or |
| SCr ≥ 2.5 mg/dl or Receipt of dialysis |
reference value is lowest previous value excluding day 0 and 1
In order to better understand the rates of AKI by different timepoints, we evaluated the AKI rates at 3 different timeframes. We chose the first timeframe to be in line with the previous study on early AKI [9]. We chose to define middle AKI to evaluate whether there could be a difference in AKI rates after the second week after birth. We define timing of AKI as follows: day of birth is denoted as day 0. AKI is classified into early (days 3–7), middle (days 8–14) and late (days 15 - discharge or 44 weeks corrected GA, whichever comes first). For these analysis, we included those patients who were alive at the beginning of each timeframe such that we report on 923 infants during the first week, 912 in the middle timeframe (due to 32 deaths between days 3–7), and 875 in the late timeframe (due to 48 deaths between days 3 – 14). In addition, we define anytime AKI as the highest AKI stage during the entire hospital stay.
Serum Creatinine (SCr) and serum cystatin C data measured at the core lab
We report the SCr and Cystatin C levels at a few pre-specified time points, Days 0, 7. 9 and 14, which were chosen according to the blood draws scheduled as part of the parent study. These samples were not intended to help diagnose AKI, instead, they provide normative data on SCR and cystatin C values by GA weeks at pre-specified fixed timepoints on the majority of the cohort, performed at a central laboratory. Blood samples were collected, processed and stored at −80°C on days 0, 7, 9 and 14. SCr concentrations were measured at a core laboratory in Seattle, Washington, using the two-point method with the Vitros 4600 (Ortho Clinical Diagnostic; Raritan, NJ). Cystatin C concentrations were measured from the same blood samples at the same core laboratory using particle-enhanced immunonephelometry using the BN ProSpec System (Simiens Helathineers; Tarrytown, N.Y.). These time points were chosen by the parent study. These values allow us to evaluate kidney function at standardized time points, with samples measured using the same methodology on the same postnatal days for the majority of infants. We report both absolute values and changes in the values over time.
Statistical analysis
Infants were grouped by GA by rounding weeks+days down to the nearest number of weeks. Baseline characteristics were examined by GA. BW was evaluated for every 100 grams birthweight in the regression models. Linear and logistic models were used to test for trends under generalized estimating equation (GEE) structure with clustering by sibship. Similar models were used to determine the association between AKI and severe AKI with GA. Separate models were used for the cross tabulation of severe AKI and at the different timeframes.
The number of clinically measured SCr values available were compared across GA and days since birth. We used logistic regression with a GEE correction (using working independence) to obtain valid standard errors that account for clustering within sibship. The average daily SCr values were compared across gestational age groups using linear regression with a GEE correction.
We report the SCr frequency by site, rates of AKI by center the correlation of these two factors.
We performed sensitivity analysis to evaluate missing data SCr as follows: During the first postnatal week, SCr were missing in 18.9% of days, while in weeks 2, 3, and 4 we find increasing rates of missing daily data (42.2%, 60.5%, and 68.4% respectively). Our primary analysis uses the available clinical measurements taken during hospitalization for all infants, and assumes that if a SCr value was not measured, then the patient did not have AKI during that timeframe. Therefore, the analysis should be appropriately interpreted as the rate of AKI determined by pragmatic measurement of SCr obtained for routine clinical care of ELGAN, and underlying rates of AKI may in fact be higher than if SCr was measured on every neonate on every day. We also performed a sensitivity analysis to determine whether the complete removal of subjects who did not have at least one SCr value measured during a particular follow-up timeframe caused any meaningfully impact to our primary results.
Data management and analysis were conducted using R version 5.3.1 (R Foundation for Statistical Computing, Vienna, Austria).
Results
Of the 923 neonates included in this analysis, 51.9% were male, the average birthweight was 801 grams, and most (91.6%) received prenatal steroids. Demographic and delivery room intervention differences by GA group are shown in Table 2. Infants who were of lower GA had lower BW, shorter length, smaller head circumference, lower APGAR scores, and had more interventions for resuscitation in the delivery room (all p< 0.05 using test for trends).
Table 2:
Demographic characteristics by gestational age
| Gestational Age at birth | ||||||
|---|---|---|---|---|---|---|
| All | 24 weeks | 25 weeks | 26 weeks | 27 weeks | p-value | |
| N | 923 | 227 | 242 | 220 | 234 | |
| Male, n (%) | 479 (51.9%) | 121 (53.3%) | 122 (50.4%) | 114 (51.8%) | 122 (52.1%) | 0.90 |
| Birth weight (g), mean (SD) | 801.1 (187.9) | 656.1 (117.4) | 754.6 (131.6) | 862.6 (172.0) | 932.2 (192.5) | <0.01 |
| Birth length (cm), mean (SD) | 32.9 (2.9) | 30.9 (2.2) | 32.1 (2.4) | 33.9 (2.6) | 34.8 (2.7) | <0.01 |
| Size for Gestational Age | ||||||
| Large, n (%) | 104 (11.3%) | 30 (13.2%) | 25 (10.3%) | 33 (15.0%) | 16 (6.8%) | 0.03 |
| Average, n (%) | 739 (80.1%) | 178 (78.4%) | 202 (83.5%) | 169 (76.8%) | 190 (81.2%) | -- |
| Small, n (%) | 80 (8.7%) | 19 (8.4%) | 15 (6.2%) | 18 (8.2%) | 28 (12.0%) | -- |
| Apgar 1 min, median (IQR) | 4 (2, 6) | 3 (2, 5) | 3 (2, 5.75) | 4 (2, 6) | 5 (3, 6) | <0.01 |
| Apgar 5 min, median (IQR) | 7 (5, 8) | 6 (4, 7) | 7 (4, 7) | 7 (6, 8) | 7 (6, 8) | <0.01 |
| OFC (cm), mean (SD) | 23.1 (1.9) | 21.5 (1.2) | 22.7 (1.7) | 23.7 (1.7) | 24.5 (1.5) | <0.01 |
| Number of fetuses, median (IQR) | 1 (1, 2) | 1.3 (0.7) | 1.3 (0.5) | 1.2 (0.4) | 1.3 (0.5) | 0.56 |
| Prenatal steroids, n (%) | 831 (91.6%) | 204 (91.5%) | 225 (93.4%) | 195 (91.1%) | 207 (90.4%) | 0.55 |
| Steroid doses, median (IQR) | 2 (2, 2) | 2 (2, 2) | 2 (2, 2) | 2 (1.75, 2) | 2 (2, 2) | 0.01 |
| Delivery room resuscitation, n (%) | ||||||
| Any | 896 (97.1%) | 223 (98.2%) | 239 (98.8%) | 214 (97.3%) | 220 (94.0%) | 0.01 |
| Oxygen | 738 (80.0%) | 185 (81.5%) | 199 (82.2%) | 171 (77.7%) | 183 (78.2%) | 0.26 |
| Positive pressure | 797 (86.3%) | 194 (85.5%) | 209 (86.4%) | 189 (85.9%) | 205 (87.6%) | 0.58 |
| Intubation | 748 (81.0%) | 216 (95.2%) | 214 (88.4%) | 173 (78.6%) | 145 (62.0%) | <0.01 |
| Surfactant | 480 (52.0%) | 138 (60.8%) | 138 (57.0%) | 113 (51.4%) | 91 (38.9%) | <0.01 |
| Chest compression | 72 (7.8%) | 23 (10.1%) | 21 (8.7%) | 18 (8.2%) | 10 (4.3%) | 0.02 |
| Resuscitation drugs | 32 (3.5%) | 10 (4.4%) | 9 (3.7%) | 8 (3.6%) | 5 (2.1%) | 0.19 |
NOTE: All p-values represent test for trends. GEE with either linear, logistic or ordinal regression depending on variable type.
SCr was measured clinically in over 80% of infants in each of the first 7 postnatal days, and measurement frequency decreased over time during the hospitalization. Figure 2 displays the SCr counts over time (moving 3-day window) by GA weeks which demonstrates that SCr was measured more frequently in subjects with lower GA (p<0.01 from a test of equality of time trends). Figure 3 shows the mean SCr levels over a 7-day window by GA weeks which demonstrates that ELGAN of lower GA had higher mean SCr values over time (p<0.01 from a test of equality of time trends).
Fig. 2.
Creatinine counts over time (moving 3-day window) by GA weeks
Fig. 3.
Mean creatinine levels over rolling 7-day window by GA weeks
The prevalence rates for AKI in the entire cohort and for each of the four gestational age groups for early, middle, late and anytime are shown in Table 3. For the entire cohort, 351/923 (38.0%, CI = 34.8 – 41.3%) had at least one episode of stage 1 or higher AKI and 168/923 (18.2%, CI = 15.7 – 20.7%) had severe (stage 2 or 3) AKI anytime. The prevalence of stage 1 or higher for the entire cohort during the early, middle and late period was 112/923 (12.1%, CI = 10.0 – 14.3%), 142/891 (15.9%, CI = 13.5 – 18.4%) and 249/875 (28.5%, CI = 25.4 – 31.5%), respectively. The rates of any AKI, across each of the 3 timeframes were higher with decreasing GA weeks (all p<0.01 using test for trends). For example, the rates of severe AKI during the hospital course were 27.8% (CI = 22.0 – 33.5%), 21.9% (CI = 16.6 – 27.2%), 13.6% (CI = 9.2 – 18.1%), and 9.4% (CI = 5.5 – 13.3%) for the 24, 25, 26 and 27 week GA groups, respectively. The range of severe AKI varied by site = 0 to 45.6%; range of SCr mean per subject by site = 3.2 to 20.1, correlation coefficient = 0.17; p=0.07.
Table 3:
AKI status by gestational age
| Gestational age at birth | ||||||
|---|---|---|---|---|---|---|
| All | 24 weeks | 25 weeks | 26 weeks | 27 weeks | p-values | |
| n | 923 | 227 | 242 | 220 | 234 | |
| AKI Max Anytime, n (%) | <0.01 | |||||
| No AKI | 572 (62.0%) | 96 (42.3%) | 141 (58.3%) | 158 (71.8%) | 177 (75.6%) | |
| Stage 1 | 183 (19.8%) | 68 (30.0%) | 48 (19.8%) | 32 (14.5%) | 35 (15.0%) | |
| Stage 2 | 108 (11.7%) | 48 (21.1%) | 33 (13.6%) | 13 (5.9%) | 14 (6.0%) | |
| Stage 3 | 60 (6.5%) | 15 (6.6%) | 20 (8.3%) | 17 (7.7%) | 8 (3.4%) | |
| Severe AKI max anytime, n (%) | <0.01 | |||||
| No (stage 0 or 1) | 755 (81.8%) | 164 (72.2%) | 189 (78.1%) | 190 (86.4%) | 212 (90.6%) | |
| Yes (stage 2 or 3) | 168 (18.2%) | 63 (27.8%) | 53 (21.9%) | 30 (13.6%) | 22 (9.4%) | |
| AKI Timing (Max SCr) | ||||||
| Early, n (%) | <0.01 | |||||
| No AKI | 811 (87.9%) | 179 (78.9%) | 216 (89.3%) | 201 (91.4%) | 215 (91.9%) | |
| Stage 1 | 92 (10.0%) | 43 (18.9%) | 17 (7.0%) | 15 (6.8%) | 17 (7.3%) | |
| Stage 2 | 11 (1.2%) | 4 (1.8%) | 6 (2.5%) | 0 (0.0%) | 1 (0.4%) | |
| Stage 3 | 9 (1.0%) | 1 (0.4%) | 3 (1.2%) | 4 (1.8%) | 1 (0.4%) | |
| Middle , n (%)* | <0.01 | |||||
| No AKI | 749 (84.1%) | 152 (72.4%) | 192 (82.1%) | 196 (90.7%) | 209 (90.5%) | |
| Stage 1 | 90 (10.1%) | 40 (19.0%) | 26 (11.1%) | 11 (5.1%) | 13 (5.6%) | |
| Stage 2 | 41 (4.6%) | 18 (8.6%) | 13 (5.6%) | 4 (1.9%) | 6 (2.6%) | |
| Stage 3 | 11 (1.2%) | 0 (0.0%) | 3 (1.3%) | 5 (2.3%) | 3 (1.3%) | |
| Late, n (%)** | <0.01 | |||||
| No AKI | 626 (71.5%) | 108 (52.2%) | 155 (68.6%) | 168 (79.2%) | 195 (84.8%) | |
| Stage 1 | 117 (13.4%) | 45 (21.7%) | 33 (14.6%) | 20 (9.4%) | 19 (8.3%) | |
| Stage 2 | 84 (9.6%) | 40 (19.3%) | 21 (9.3%) | 12 (5.7%) | 11 (4.8%) | |
| Stage 3 | 48 (5.5%) | 14 (6.8%) | 17 (7.5%) | 12 (5.7%) | 5 (2.2%) | |
Early (days 3–7); Middle (days 8–14); Late (days 15 - discharge or 44 weeks whichever occurred first).
32 patients not in reported due to death on days 3–7;
48 patients not reported due to death on days 3–14.
NOTE: All p-values represent test for trends. GEE with either linear, logistic or ordinal regression depending on variable type.
The 23 neonates without any SCr are imputed as No AKI.
We performed a sensitivity analysis to determine how the rates of AKI would have changed, had we chosen a baseline SCr defined as the lowest SCr measured any time (including on the day of birth (day 0) or the following day (day 1)). We found that of the 923 subjects, 260 had a SCr on day 0 and 771 had a SCr on day 1. If we would have used the lowest prior SCr to define the baseline value, 33 infants would have had a higher AKI stage as follows: 23 would move from no AKI to stage 3 AKI, 6 would move from no AKI to stage 2 AKI, 3 from stage 1 to stage 2 AKI, and 2 from stage 2 to stage 3 AKI.
Using the GEE models, clustered by birth mother, we found that AKI was more common in lower GAs for early, middle, late and anytime AKI and for No or Stage 1 AKI vs. severe AKI (Table 4a). The odds ratios for AKI associated with a 1-week decrease in GA ranged between 1.34 and 1.66. Similarly, using the GEE models, clustered by birth mother, we found that AKI was more common for 100 gram decrease in BW for early, middle, late and anytime AKI and No or Stage 1 AKI vs. severe AKI (Table 4b). The odds ratios for AKI associated with a 100 gram decrease in BW ranged between 1.15 and 1.35. GA was independently associated with AKI even after controlling for BW (Table 4c). BW was independently associated with AKI even after controlling for GA (Table 4d). The interaction term between BW and GA was not statistically significant. Although not all of the stratified analyses are statistically significant, they all had estimated trends consistent with our hypothesis.
Table 4a:
GEE model estimates for AKI by Gestational Age Only
| OR (95% CI) | ||
|---|---|---|
| NO AKI vs. Any AKI | No or stage 1 vs. Severe (Stage 2/3) | |
| Early | 1.49 (1.21, 1.82) | 1.34 (0.94, 1.90) |
| Middle | 1.63 (1.35, 1.95) | 1.36 (1.03, 1.79) |
| Late | 1.74 (1.51, 2.02) | 1.66 (1.40, 1.99) |
| Any | 1.56 (1.33, 1.83) | 1.56 (1.33, 1.83) |
Table 4b:
GEE model estimates for AKI by Birthweight Only
| Early | 1.14 (1.02, 1.28) | 1.30 (1.01, 1.68) |
| Middle | 1.19 (1.08, 1.31) | 1.15 (0.99, 1.33) |
| Late | 1.30 (1.20, 1.42) | 1.35 (1.22, 1.50) |
| Any | 1.26 (1.08, 1.48) | 1.33 (1.20, 1.46) |
Table 4c:
GEE model estimates for AKI by Gestational Age Controlling for Birthweight *
| Early | 1.48 (1.16, 1.90) | 1.27 (0.94, 1.72) |
| Middle | 1.59 (1.26, 2.00) | 1.06 (0.86, 1.30) |
| Late | 1.56 (1.31, 1.85) | 1.22 (1.07, 1.39) |
| Any | 1.51 (1.29, 1.77) | 1.22 (1.09, 1.37) |
Table 4d:
GEE model estimates for AKI by Birthweight Controlling for Gestational Age *
| Early | 1.00 (0.87, 1.16) | 1.09 (0.72, 1.66) |
| Middle | 1.02 (0.90, 1.17) | 1.29 (0.90, 1.84) |
| Late | 1.13 (1.02, 1.26) | 1.40 (1.14, 1.72) |
| Any | 1.11 (1.00, 1.22) | 1.31 (1.09, 1.57) |
In sensitivity analyses that removed the 23 subjects with no SCr data available, we found small changes in the estimated rates of AKI compared to the analysis with all 923 subjects (Table 4e). There continued to be an association between GA weeks and AKI rates for each of the three follow-up timeframes (all p<0.01 using a test for trend). In the GEE models, all point estimates showed similar odds ratios for a 1-week difference in GA, suggesting that our finding of the association between lower GA and higher AKI rates remained true regardless of whether or not subjects without SCr were treated as no AKI (Table 4a) or excluded from the analysis (Table 4b).
Table 4e:
GEE model estimates for AKI by Gestational Age - Sensitivity Analysis **
| Early | 1.46 (1.19, 1.79) | 1.32 (0.93, 1.87) |
| Middle | 1.52 (1.26, 1.82) | 1.27 (0.96, 1.67) |
| Late | 1.57 (1.35, 1.83) | 1.50 (1.25, 1.80) |
| Any | 1.63 (1.43, 1.87) | 1.54 (1.31, 1.81) |
Models are clustered by birth mother.
Gestational age weeks evaluated as a continuous variable for every one week.
Birthweight is evaluated as a continuous variable for every 100 grams.
The interaction term of GA x Birthweight was not significant.
Evaluated only the 900 SCr with ample SCr values.
The SCr and the cystatin C values measured at the core-laboratory on postnatal days 0, 7, 9 and 14 are reported by GA weeks in Table 5 as means, standard deviation and sample size for all timepoints reported. They are also depicted in Figure 4a and 4b respectively. There was no difference in the day 0 SCr values by GA groups; however, the SCr values on day 7, 9 and 14 were higher in those with lower GA (p<0.01 using a test for trend). The changes in SCr from day 0 to 7, day 0 to 9, and day 0 to 14 were different (p<0.01 using a test for trend) across GA groups, but changes in SCr from days 7 to 9 were not different between groups.
Table 5:
Core laboratory SCr and cystatin C values by gestational age.
| Gestational age at birth | ||||||
|---|---|---|---|---|---|---|
| All | 24 weeks | 25 weeks | 26 weeks | 27 weeks | ||
| n | 624 | 158 | 172 | 145 | 149 | |
| mean (sd) [n] | ||||||
| SCr | p-values | |||||
| Day 0 | 0.85 (0.20) [551] | 0.83 (0.25) [140] | 0.85 (0.20) [153] | 0.86 (0.16) [128] | 0.85 (0.15) [130] | 0.33 |
| Day 7 | 0.79 (0.23) [514] | 0.83 (0.24) [119] | 0.82 (0.26) [145] | 0.77 (0.23) [121] | 0.73 (0.17) [129] | <0.01 |
| Day 9 | 0.74 (0.23) [506] | 0.77 (0.21) [123] | 0.79 (0.28) [135] | 0.72 (0.23) [120] | 0.67 (0.16) [128] | <0.01 |
| Day 14 | 0.68 (0.23) [457] | 0.75 (0.25) [108] | 0.74 (0.27) [122] | 0.64 (0.20) [107] | 0.60 (0.16) [120] | <0.01 |
| Max | 0.92 (0.25) [621] | 0.95 (0.28) [158] | 0.94 (0.29) [172] | 0.90 (0.22) [144] | 0.86 (0.18) [147] | <0.01 |
| Change Day 0 to 7 | −0.06 (0.28) [473] | −0.01 (0.35) [110] | −0.06 (0.27) [133] | −0.06 (0.27) [112] | −0.12 (0.19) [118] | <0.01 |
| Change Day 0 to 9 | −0.11 (0.27) [450] | −0.05 (0.27) [106] | −0.08 (0.32) [120] | −0.12 (0.26) [107] | −0.18 (0.19) [117] | <0.01 |
| Change Day 0 to 14 | −0.17 (0.28) [430] | −0.08 (0.37) [101] | −0.15 (0.27) [113] | −0.20 (0.22) [102] | −0.25 (0.20) [114] | <0.01 |
| Change Day 7 to 9 | −0.05 (0.15) [441] | −0.05 (0.18) [100] | −0.04 (0.16) [121] | −0.05 (0.14) [107] | −0.06 (0.10) [113] | 0.57 |
| Change Day 7 to 14 | −0.10 (0.21) [413] | −0.07 (0.26) [94] | −0.08 (0.21) [114] | −0.13 (0.18) [97] | −0.12 (0.16) [108] | 0.03 |
| Cystatin C Day 0 | 1.27 (0.23) [537] | 1.24 (0.25) [140] | 1.29 (0.23) [144] | 1.26 (0.20) [124] | 1.30 (0.23) [129] | 0.13 |
| Day 7 | 1.38 (0.43) [505] | 1.31 (0.29) [116] | 1.43 (0.67) [144] | 1.40 (0.27) [118] | 1.39 (0.27) [127] | 0.19 |
| Day 9 | 1.41 (0.56) [502] | 1.40 (0.72) [123] | 1.46 (0.74) [133] | 1.39 (0.30) [120] | 1.40 (0.27) [126] | 0.73 |
| Day 14 | 1.42 (0.29) [454] | 1.44 (0.35) [109] | 1.45 (0.35) [121] | 1.40 (0.22) [104] | 1.38 (0.23) [120] | 0.06 |
| Max | 1.54 (0.51) [621] | 1.55 (0.65) [157] | 1.58 (0.67) [171] | 1.50 (0.28) [144] | 1.51 (0.26) [149] | 0.27 |
| Change Day 0 to 7 | 0.10 (0.44) [452] | 0.05 (0.26) [109] | 0.12 (0.73) [124] | 0.13 (0.28) [105] | 0.10 (0.23) [114] | 0.22 |
| Change Day 0 to 9 | 0.13 (0.59) [433] | 0.16 (0.75) [107] | 0.15 (0.82) [112] | 0.11 (0.28) [102] | 0.11 (0.27) [112] | 0.42 |
| Change Day 0 to 14 | 0.13 (0.31) [414] | 0.20 (0.37) [102] | 0.15 (0.32) [108] | 0.12 (0.25) [94] | 0.07 (0.27) [110] | <0.01 |
| Change Day 7 to 9 | 0.02 (0.24) [431] | 0.03 (0.26) [99] | 0.03 (0.27) [118] | 0.01 (0.24) [104] | 0.02 (0.21) [110] | 0.57 |
| Change Day 7 to 14 | 0.03 (0.49) [402] | 0.13 (0.35) [92] | 0.00 (0.79) [112] | −0.03 (0.27) [91] | 0.00 (0.25) [107] | 0.02 |
NOTE: All p-values represent test for trends. GEE with linear regression.
Fig. 4.
a Core laboratory SCr (median and IQR) by day and GA weeks on days 0, 7, 9 and 14 after birth b Core Laboratory Serum Cystatin C (median and IQR) by day and GA weeks on days 0, 7, 9 and 14 after birth
In contrast, the cystatin C values did not differ on days 0, 7 and 9 by GA. There was a trend (although not statistically significant (p=0.06)) for higher cystatin C on day 14 in those with lower GA. Only the changes in cystatin C from day 0 to 14 were higher with decreasing GA (p<0.02 using a test for trend).
Discussion
We describe the prevalence and severity of AKI by GA and BW during three timeframes using a contemporary definition of neonatal AKI with data from a large prospective multicenter ELGAN cohort. We found that approximately 38.0% (CI = 34.8 – 41.3%) of the cohort developed at least one episode of stage 1 or higher AKI, and that 18.2% (CI = 15.7 – 20.7%) had at least one episode of stage 2 or higher AKI. Furthermore, AKI is not restricted to the first postnatal week but occurs frequently throughout the NICU stay. The difference in rates of AKI by GA in ELGAN is robust as 24 week GA neonates have twice and triple the rates of severe AKI compared to 26 and 27 week GA infants respectively. Understanding these differences is important to clinicians who care for infants, those who follow them into childhood, and to researchers as they design interventions aimed at reducing AKI and its sequelae.
The overall prevalence of AKI in this cohort is similar to other studies in premature neonates [2, 8]. Having a large sample size within a subset of infants (ELGAN) has allowed us to better characterize AKI for smaller GA increments and at several different time frames. One difference between this study and others is the way we define the baseline SCr. We chose to eliminate the SCr on days 0, 1 and 2 as part of the baseline value for the following reasons: a) we recognize that in there is a natural rise in the SCr over the coming days in the majority of ELGAN (i.e. in the manuscript by Bateman et al. 2014 [16], the mean SCr of 25–27 week neonates increased from 0.79 to 0.95 mg/dl from birth to day 2), b) previous studies in ELGAN which used the definition of baseline as any SCr since birth makes the rate of AKI very high (likely higher than is true). For example, the study by Carmody et.al. 100% of infants < 24 weeks, and 79% of neonates less than 26 weeks GA had AKI, c) there is now precedent to remove the first few postnatal days’ SCr to define baseline SCr (i.e. a quality improvement program to reduce AKI in neonates exposed to nephrotoxic medications (for example the Solution for Patient Safety NICU Nephrotoxic AKI initiative) and d) choosing a baseline SCr after day 2 would make the diagnosis of AKI more difficult (as the baseline SCr would be higher) which keeps the estimates of the prevalence of AKI more conservative. Thus, we believe that ELGAN have a natural SCr rise over the first postnatal days as the neonate finds it’s new “steady state SCr” in context of a new set of creatinine generation/excretion variables once it is no longer part of the maternal system. We show that if we would have used the lowest prior SCr to define the baseline SCr only 33 neonates would have had higher AKI stage.
Using the KDIGO AKI definition, AKI prevalence rates in this cohort are comparable to multi-center pediatric and adult critically ill cohorts. In the AKI-EPI study, a multi-center adult ICU cohort study involving 1,905 patients from 33 countries, the rate of any and severe AKI reported in adult critically ill patients was 57.3% and 34.7% respectively. The AWARE study, a multi-center pediatric ICU study involving 4,683 patients from 32 ICUs reported the rate of any and severe AKI of 26.9% and 11.6% respectively. These comparisons need to be taken in context of the longer ICU stay in ELGAN (the AKI-EPI study and the AWARE study report the rates of AKI over the first week of ICU stay).
Although we only had access to research blood at 4 time points after birth, we were able to measure the cystatin C and SCr values systematically on the majority of neonates at a central laboratory. As expected, there was no difference by GA in the day 0 SCr or cystatin C values (which reflects maternal values and should be similar for all infants regardless of GA). We found significant SCr changes by GA weeks at days 7, 9 and 14; however, cystatin C changes by GA were only apparent at day 14. Although our analysis does not have the data to fully evaluate the reasons for the unexpected finding that cystatin C did not differ by GA on days 7 and 9, while SCr values did, we offer a few possible explanations. First, cystatin C values can be affected by thyroid levels and use of steroids [18], both of which differ by GA. Alternatively, cystatin C may be less affected by variables known to affect SCr (muscle mass, variations fluid status, or secretion by the kidneys). Additional data at multiple timeframes will be needed to understand these findings.
There are several interesting comparisons between our SCr normative data and data previously published by Bateman et al. [16] and Go et al. [19]. First, the mean day 0 SCr in the Bateman cohort was very similar to the data in our cohort (around 0.8 mg/dL) but was different from the data in the Go cohort (around 0.5 mg/dL). This is likely because the SCr values on day 0 reflect the maternal SCr values, and the population in the Go, et al. article is from a cohort in Japan where women have smaller muscle mass than women in the United States. Second, the day 7 SCr was the same in all 3 cohorts (around 0.9 mg/dL). Third, in our cohort, the SCr values on day 14 were lower (around 0.7 mg/dL) compared to the Bateman et al. cohort (around 1.0 mg/dL) and the Go et al. article (around 0.9 mg/dL). Possible explanations for these findings include difference in fluid balance, and different rates of AKI, among other reasons.
The strengths of this study are the size of the cohort and the robust number of SCr measurements available, which has allowed us to better characterize the AKI rates within the ELGAN population. Despite these strengths, we acknowledge the following limitations. First, not all infants had SCr captured every day during the hospitalization; therefore, it is possible that the true AKI rate could be higher. Second, as we describe the rates of AKI, the SCr values we report were those measured as part of clinical care, which were performed at local institutions that do not all use the same methodology for SCr determination. As the AKI definition is dependent on changes in SCr over time, this is not likely to affect our study conclusions given that the comparison of the differences in SCr were from samples measured in the same manner from each institution. Finally, we acknowledge that although the definition we used is currently the most accepted neonatal AKI definition, this definition may need to be refined over time.
In conclusion, this analysis shows that AKI is common in ELGAN throughout their hospital course, and AKI is more common in the most premature infants. Other studies of this database are underway which will answer multiple questions, including the potential protective effect of erythropoietin on the kidney, the impact of neonatal AKI on hospital outcomes, and the long-term risk factors on 2-year kidney outcomes.
Acknowledgements
We would like to thank Lynn Dill, RN, and Emily Pao for their assistance in coordinating the REPaIReD study.
We would like to thank the investigators, clinicians, research personnel, study teams and families who participated in the PENUT Trial.
Conflict of interest disclosures
For full disclosure, we provide here an additional list of other author’s commitments and funding sources that are not directly related to this study:
David J Askenazi serves on the speaker board for Baxter (Baxter, USA), and the Acute Kidney Injury (AKI) Foundation (Cincinnati, OH, USA). He is consultant for Baxter, CHF solutions, and Medtronic. He also receives grant funding for studies not related to this project from Baxter, CHF solutions, and National Institutes of Health (R01 FD005092, U34 KD117128) and the Pediatric and Infant Center for Acute Nephrology (PICAN). PICAN is part of the Department of Pediatrics at the University of Alabama at Birmingham (UAB), and is funded by Children’s of Alabama Hospital, the Department of Pediatrics, UAB School of Medicine, and UAB’s Center for Clinical and Translational Sciences (CCTS, NIH grant UL1TR001417).
Dr. Goldstein reports personal fees from and a position as a consultant to CHF Solutions Inc., Renibus, ExThera, Reata and Medtronic Inc. Dr. Goldstein receives grant funding from and serves as a consultant and on a Speaker’s Bureau for Baxter Healthcare, Inc.
Dr Goldstein receives grant funding and serves as a consultant for BioPorto, Inc. Dr. Goldstein serves on a Speaker’s Bureau for Fresenius Medical Corporation.
Mr. Schmicker receives grant funding for studies not related to this project from NHLBI and PCORI.
Funding Sources
Recombinant Erythropoietin for Protection of Infant Renal Disease (REPaIReD) Study is an NIH NIDDK funded (R01 DK103608) ancillary study designed to look at kidney outcome in patients enrolled in the Preterm Erythropoietin Neuroprotection Trial (PENUT Trial) which is an NIH NINDS funded (U01 NS077953, U01 NS077955) trial. The clinicaltrials.gov identifier is NCT01378273.
Role of funding sources
Funding sources for this study had no role in study design, data collection, data analysis, data interpretation, or writing of the report
Prior Presentations
Some data presented in this study was previously presented as oral presentations to the 23rd AKI/CRRT meeting (March 2018) and the Pediatric Academic Society meeting (May 2018).
List of Abbreviations:
- AKI
acute kidney injury
- NICU
neonatal intensive care unit
- SCr
serum creatinine
- PENUT
Preterm Epo Neuroprotection Trial
- ELGAN
Extreme low gestational age neonates
- REPaIReD
Recombinant Erythropoietin for Protection of Infant Renal Disease
- GA
gestational age
- Epo
erythropoietin
- GEE
general estimating equations
- AWAKEN
Awareness of Worldwide Acute Kidney Epidemiology in Neonates
APPENDIX
PENUT Primary Investigators
Sandra E. Juul1, Bryan A. Comstock1, Rajan Wadhawan2; Dennis E. Mayock1, Sherry E. Courtney3; Tonya Robinson4; Kaashif A. Ahmad5; Ellen Bendel-Stenzel6; Mariana Baserga7; Edmund F. LaGamma8; L. Corbin Downey9; Raghavendra Rao10; Nancy Fahim10; Andrea Lampland11; Ivan D. Frantz, III12; Janine Y. Khan13; Michael Weiss14; Maureen M. Gilmore15; Robin Ohls16; Nishant Srinivasan17; Jorge E. Perez18; Victor McKay19; Phuong T. Vu1; Patrick J. Heagerty1; and the PENUT Trial Consortium
PENUT Co-Investigators
Billy Thomas3, Nahed Elhassan3, Sarah Mulkey3, Philip Dydynski4, Vivek K. Vijayamadhavan5, Neil Mulrooney6, Bradley Yoder7, Jordan S. Kase8, Jennifer Check9, Semsa Gogcu9, Erin Osterholm10, Sara Ramel10, Catherine Bendel10, Cheryl Gale10, Thomas George10, Michael Georgieff10, Tate Gisslen10, Sixto Guiang III10, Anne Hall10, Dana Johnson10, Katie Pfister10, Heather Podgorski10, Kari Roberts10, Erin Stepka10, Melissa Engel10, Heidi Kamrath10, Johannah Scheurer10, Angela Hanson10, Katherine Satrom10, Susan Pfister10, Ann Simones10, Erin Plummer10, Elizabeth Zorn10, Camilia R. Martin12, Deirdre O’Reilly12, Nicolas Porta13, Catalina Bazacliu14, Jonathan Williams14, Dhanashree Rajderkar14, Frances Northington15, Raul Chavez Valdez15, Sandra Beauman16, Patel Saurabhkumar17, Magaly Diaz-Barbosa18, Arturo Serize18, Jorge Jordan18
PENUT Research Coordinators
Debbie Ott1, Ariana Franco Mora1, Pamela Hedrick1, Vicki Flynn1, Amy Silvia2, Bailey Clopp2, John B. Feltner2, Isabella Esposito2, Stephanie Hauge2, Samantha Nikirk2, Andrea Purnell3, Emilie Loy3, Natalie Sikes3, Melanie Mason3, Jana McConnell3, Tiffany Brown3, Henry Harrison3, Denise Pearson3, Tammy Drake3, Jocelyn Wright3, Debra Walden3, Annette Guy3, Jennifer Nason4, Morgan Talbot4, Kristen Lee4, Sarah Penny4, Terri Boles4, Melanie Drummond5, Katy Kohlleppel5, Charmaine Kathen5, Brian Kaletka6, 11, Shania Gonzales6, 11, Cathy Worwa6, 11, Molly Fisher, 11, Tyler Richter6, 11, Alexander Ginder6, 11, Brixen Reich7, Carrie Rau7, Manndi Loertscher7, Laura Bledsoe7, Kandace McGrath7, Kimberlee Weaver Lewis7, Jill Burnett7, Susan Schaefer7, Karie Bird7, Clare Giblin8, Rita Daly8, Kristi Lanier9, Kelly Warden9, Jenna Wassenaar10, Jensina Ericksen10, Bridget Davern10, Mary Pat Osborne10, Brittany Gregorich10, Neha Talele12, Evelyn Obregon12, Tiglath Ziyeh12, Molly Clarke12, Rachel E Wegner12, Palak Patel12, Molly Schau13, Annamarie Russow13, Kelly Curry14, Susan Sinnamon14, Lisa Barnhart14, Charlamaine Parkinson15, Sandra Beauman16, Mary Hanson16, Elizabeth Kuan16, Conra Backstrom Lacy16, Edshelee M. Galvis18, Susana Bombino18, Denise Martinez19, Suzi Bell19, Corrie Long19
PENUT Follow-Up Personnel
Cathy Longa2, Michael Westerveld2, Stacy McConkey2, Anne Hay1, Niranjana Natarajan1, Shari Gaudette3, Sarah Cobb3, Gregory Sharp3, Elizabeth Schumacher4, Leslie Schuschke4, Charlotte Frey5, Mario Fierro5, Lois Gilmore6, Pamela Lundequam6, Ronald Hoekstra6, Anastasia Ketko6, Nina Perdue6, Sean Cunningham7, Kelly Stout7, Becky Hall7, Galina Morshedzadeh7, Betsy Ostrander7, Sarah Winter7, Lauren Cox8, Jordan S. Kase8, Matthew A. Rainaldi8, Sarah Hensley9; Melissa Morris9, Dia Roberts9, Semsa Gogcu9, Melissa Tuttle9; Christopher Boys10, Solveig Hultgren10, Elizabeth I. Pierpont10, Nancy Fahim10, Tom George10, Erin Osterholm10, Michael Georgieff10, Kelly E. King10, Katherine Bataglia11, Cathy Neis11, Mark Bergeron11, Cristina Miller11, Cara Accomando12, Jennifer Anne Gavin12, Elizabeth Maczek12, Susan Marakovitz12, Aimee Knorr12, Vincent C. Smith12, Jane E. Stewart12, Marie Weissbourd13, Raye-Ann deRegnier13, Nana Matoba13, Shelly C. Heaton12, Erika M. Cascio12, Janet Brady14, Suman Ghosh14, Jessica Ditto15, Mary Leppert15, Jean Lowe16, Janell Fuller16, Tara DuPont16, Robin Ohls16, Pamela Kloska17, Saurabh Patel17, Lauren Carbonell18, Anna Maria Patino-Fernandez18 Carmen de Lerma18, Susana Bombino18, Arturo Serize18, Kelly McDonough18, Maiana De Cortada18, Lacy Chavis19, Jane Shannon19
University of Washington Data Coordinating Center
Bryan A. Comstock1, Patrick J. Heagerty1, Mark A. Konodi1, Christopher Nefcy1, Phuong T. Vu1
PENUT Follow-Up Committee
Karl C. K. Kuban20, Jean R. Lowe16, T. Michael O’Shea21
Radiology Committee
Manjiri Dighe1, Todd Richards1, Dennis W. W. Shaw1, Colin Studholme1, Christopher M. Traudt1
PENUT Executive Committee
Roberta Ballard22, Bryan A. Comstock1, Adam Hartman23, Scott Janis23, Sandra E. Juul1, Dennis E. Mayock1, T. Robin Ohls16, Michael O’Shea21
DSMB
Ronnie Guillet 24, M. Bethany Ball25, Hannah Glass22, Ben Saville26, Michael Schreiber27
1. University of Washington (Seattle, Washington)
2. AdventHealth for Children, (Orlando, Florida)
3. University of Arkansas for Medical Sciences (Little Rock, Arkansas)
4. University of Louisville, (Louisville, Kentucky)
5. Methodist Children’s Hospital (San Antonio, Texas)
6. Children’s Hospital and Clinics of Minnesota (Minneapolis, Minnesota)
7. University of Utah (Salt Lake City, Utah)
8. Maria Fareri Children’s Hospital at Westchester Medical Center (Valhalla, New York)
9. Wake Forest School of Medicine (Winston-Salem, North Carolina)
10. University of Minnesota Masonic Children’s Hospital (Minneapolis, Minnesota)
11. Children’s Minnesota (St. Paul, Minnesota)
12. Beth Israel Deaconess Medical Center (Boston, Massachusetts)
13. Prentice Women’s Hospital (Chicago, Illinois)
14. University of Florida (Gainesville, Florida)
15. Johns Hopkins University (Baltimore, Maryland)
16. University of New Mexico (Albuquerque, New Mexico)
17. Children’s Hospital of the University of Illinois (Chicago, Illinois)
18. South Miami Hospital (South Miami, Florida)
19. Johns Hopkins All Children’s Hospital (St. Petersburg, Florida)
20. Boston University Medical Center (Boston, Massachusetts)
21. University of North Carolina School of Medicine (Chapel Hill, North Carolina)
22. University of California San Francisco School of Medicine (San Francisco, California)
23. National Institute of Neurological Disorders and Stroke
24. University of Rochester Medical Center (Rochester, New York)
25. Stanford University and Lucile Packard Children’s Hospital (Palo Alto, California)
26. Vanderbilt University Medical Center (Nashville, Tennessee)
27. University of Chicago (Chicago, Illinois)
Footnotes
Compliance with Ethical Standards
Financial Disclosure Statement:
All authors declare no real or perceived conflicts of interest that could affect the study design, collection, analysis and interpretation of data, writing of the report, or the decision to submit for publication.
Ethics Committee Approval
The University of Washington Institutional Review Board (IRB) approved this collaborative study, and each center received approval from their respective IRBs.
Publisher's Disclaimer: This Author Accepted Manuscript is a PDF file of a an unedited peer-reviewed manuscript that has been accepted for publication but has not been copyedited or corrected. The official version of record that is published in the journal is kept up to date and so may therefore differ from this version.
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