Abstract
Background:
Acute kidney injury (AKI) after cardiac surgery (CS) is not uncommon and has serious effects on mortality and morbidity. A majority of patients suffer mild forms of AKI. There is a paucity of Indian data regarding this important complication after CS.
Aims and Objectives:
The primary objective was to study the incidence of AKI associated with CS in an Indian study population. Secondary objectives were to describe the risk factors associated with AKI-CS in our population and to generate outcome data in patients who suffer this complication.
Methods:
Serial patients (n = 400) presenting for adult CS (emergency/elective) at a tertiary referral care hospital in South India from August 2016 to November 2017 were included as the study individuals. The incidence of AKI-CS AKI network (AKIN criteria), risk factors associated with this condition and the outcomes following AKI-CS are described.
Results:
Out of 400, 37 (9.25%) patients developed AKI after CS. AKI associated with CS was associated with a mortality of 13.5% (no AKI group mortality 2.8%, P = 0.001 [P < 0.05]). When AKI was severe enough to need renal replacement therapy, the mortality increased to 75%. Patients with AKI had a mean hospital stay 16.92 ± 12.75 days which was comparatively longer than patients without AKI (14 ± 7.98 days). Recent acute coronary syndrome, postoperative atrial fibrillation, and systemic hypertension significantly predicted the onset of AKI-CS in our population.
Conclusions:
The overall incidence of AKI-CS was 9.25%. The incidence of AKI-CS requiring dialysis (Stage 3 AKIN) AKI-CS was lower (2%). However, mortality risks were disproportionately high in patients with AKIN Stage 3 AKI-CS (75%). There is a need for quality improvement in the care of patients with AKI-CS in its most severe forms since mortality risks posed by the development of Stage 3 AKIN AKI is higher than reported in other index populations from high resource settings.
Keywords: Acute kidney injury, acute kidney injury network criteria, cardiac surgery, mortality, renal failure requiring dialysis, risk stratification
Introduction
Acute kidney injury (AKI) after cardiac surgery (CS) is fairly common with some reports citing a figure close to 30% although the exact incidence varies with definition and based on the numerous scoring systems available. About 1%–2% of patients develop severe renal injury requiring dialysis.[1] AKI after CS is associated with a substantial increase in morbidity and mortality which can exceed 60% among patients requiring dialysis. Even when there is a modest increase in serum creatinine values from baseline values, it is associated with longer hospital stay and increased costs besides adverse prognostication in outcomes.[2] A majority of patients suffer mild forms of AKI; even as knowledge and ability to detect subclinical disease using specific biomarkers evolves for this condition, it is likely that both the estimates of incidence and prognostication will evolve.
AKI-CS is occurs due to combination of preoperative, intra- and post-operative factors. There is no specific pharmacologic strategy to treat AKI. However, it might still be helpful to identify patients at risk of this complication; this could help in triage to focus on amelioration of modifiable risk factors before CS.
The incidence of community-acquired AKI reported in India was 4.14 per 1000 admissions in 1996–2008 with a mortality of 10.98%.[2] There are at present only limited descriptions of the epidemiology of postoperative renal injury after CS.[1] There is also a significant lacuna in our care continuum that there are no national or region-specific databases on the outcomes of treatment of cardiovascular disease, unlike our Western counterparts. As the population in our part of the subcontinent suffers significant cardiovascular disease burden and, as it progressively ages these descriptions will likely be important. This study was therefore planned to describe the risk factors for suffering AKI-CS from a tertiary referral hospital in South India. It additionally attempts to detail the consequences of suffering this complication. It strives to extend the literature on perioperative outcomes in general, and that of CS in the Indian subcontinent.
Materials and Methods
This was an observational prospective study conducted in a tertiary referral hospital in South India (Amrita Institute of Medical Sciences and Research Centre, Kochi, India, from August 2016 to November 2017. Serial adult patients (n = 400) presenting for cardiac surgical procedures (elective and emergency) were recruited into the study after due obtainment of clearance from the Institute Ethics Committee. Informed written consent was also obtained from study individuals or their delegated consent providers when applicable. Patient data were acquired and processed with due respect to confidentiality and in accordance with the information technology policies applicable at the hospital. Data were acquired both prospectively from the physical and electronic medical records of the individuals as also mined from the hospital information system by the study investigators for missing data/accuracy of data acquired from the physical medical record.
AKI was defined by the AKI network (AKIN) criteria [Table 1].
Table 1.
AKIN criteria
| Stage | Creatinine | Urinary volume |
|---|---|---|
| STAGE 1 | Increase in serum creatinine ≥0.3 mg/dl (or) increase ≥150%-200% | <0.5 ml/kg/hour for >6 h |
| STAGE 2 | Increase in serum creatinine >200%-300% (>2-3 fold) from baseline | <0.5 ml/kg/hour for >12 h |
| STAGE 3 | Increase in serum creatinine >300% (>3 fold from baseline (or) >4 mg/dl (or) requirement of RRT) | <0.3 ml/kg/hour for 24 h or anuria for 12 h |
RRT: Renal replacement therapy, AKIN: Acute Kidney Injury Network
Sample size
The sample size was based on an observed incidence of 30% of AKI-CS in a similar publication (AKI after CS – Focus on Modifiable risk factors – Circulation – 2009; 119: 495–502). The minimum sample size was 225 with 95% confidence limit and 20% allowable error. Recruiting 400 patients was shown to provide a study with an estimated 15% allowable error.
Inclusion criteria
All adult presents presenting for cardiac surgical procedures whether performed on or off cardiopulmonary bypass. An indicative list includes coronary artery bypass grafting, valve replacement/repair, thoracoabdominal aneurysm repair, aortic dissection, septal myectomy for hypertrophic cardiomyopathy, closure of atrial septal defects in adulthood and combined procedures such as valve and coronary bypass together.
Exclusion criteria
Patients with preoperative renal failure requiring hemodialysis
Missing pre-/post-operative creatinine values
Patients who undergo more than one chronologically distinct cardiac surgical procedure during a hospital stay
Baseline serum creatinine >1.5 mg/dl
Patients on extracorporeal membrane oxygenation before surgery
Patients who died in the OR (operation room) or within 24 h after surgical procedure or in whom the surgical procedure was aborted for any reasons.
Variable definitions
Demographic characteristics – age, sex, weight, height, body mass index
Comorbidities – diabetes mellitus, systemic hypertension, dyslipidemia, chronic obstructive pulmonary disease, pulmonary veno-occlusive disease
Euro SCORE II
Recent acute coronary syndrome (ACS)
Baseline serum creatinine – serum creatinine before surgery
Postoperative serum creatinine – highest value in the postoperative period during intensive care unit stay
History of stroke/transient ischemic attack defined by the presence of neurological deficit before surgery
Timing of coronary angiogram (hours) – time from coronary angiogram to the time of surgery
Involvement of the left main coronary artery disease
Cardiac surgical procedure-type, emergency/elective, redo surgery
Preoperative ejection fraction based on echocardiographic reports
The requirement of cardiopulmonary bypass
Need for total circulatory arrest (min)
Need for intra-aortic balloon counterpulsation (intra-aortic balloon pump [IABP]) and duration of IABP (min)
The requirement of blood transfusion (packed red blood cell, platelets, fresh frozen plasma, and cryoprecipitate)
Requirement of inotropes, maximum dose of inotrope postoperatively, total duration of inotropes in minutes
Atrial fibrillation in postoperative period
Hourly urine output.
Outcome variables are defined as follows:
Need for hemodialysis/continuous veno-venous hemofiltration during entire postoperative hospital stay or within 30 days’ postoperatively
Operative mortality – defined as in-hospital mortality (or) 30 days’ mortality
Length of hospital stay is defined from the day of admission until the day of discharge.
Statistical analysis
Statistical analysis was compiled using SPSS 20.0 (SPSS Inc., Chicago, IL, USA). Continuous variables were presented as mean (± standard deviation). Univariate analysis for continuous variables was done by independent samples t-test for normally distributed continuous variables, for nonparametric variables the Mann–Whitney U test was used. Univariate statistical analysis of categorical variables was performed by Chi-square test/Fisher's exact test as appropriate. When sample distributions were small for a risk variable, the population was bootstrapped before determining significance to be entered into the stepwise regression. IABP use was not considered as none of the patients in whom IABP use was reported suffered AKI. The variables which were significant in Univariate analysis were considered for Multivariate logistic regression. Binary stepwise multivariate logistic regression to assess independent correlates of AKI associated with CS and requirement for renal replacement therapy (RRT), AKI associated with hospital stay and mortality. P < 0.19 was considered to be statistically significant. The regression model was evaluated by Hosmer– Lemeshow test-goodness of fit. Odds ratio (OR) for mortality in patients with and without AKI was also calculated.
Results
In our study, 37 (9.25%) patients developed AKI after CS. There were no gross differences between the groups with and without AKI in terms of age [Table 1]. Male individuals suffered a higher risk of developing AKI-CS (10.9% of the males patients suffered AKI-CS while only 4.2% of the opposite sex had this complication (P < 0.049)), [Figure 1].
Figure 1.
Gender distribution in patient population
Overall within the cohort that suffered some or the other form of AKI 13.5% of this group died; in stark comparison, in the non-AKI group the overall mortality was only 2.5% showing how even mild forms of the complication have ominous consequences (OR 5.52 95% confidence interval 1.8–17.1) [Figure 2]. Even more dramatically, when AKI-CS was severe enough to warrant RRTs 75% of such patients died [Figure 3]. This result, however, should be tempered by the overall low incidence of this complication since only 9 patients needed RRT, but 6 of these 9 individuals died.
Figure 2.
Mortality risk due to acute kidney injury cardiac surgery (10/353 patients without acute kidney injury cardiac surgery died whereas 5/32 patients with acute kidney injury cardiac surgery died, P < 0.001)
Figure 3.
Renal failure requiring dialysis and mortality
The results of the univariate regression analysis are reported in Tables 2–4. Variables shown to independently predict AKI-CS with AKI are recent ACS, atrial fibrillation and systemic hypertension on stepwise multivariate binary logistic regression. The independent risks of these individual factors are depicted in Table 5.
Table 2.
Comparison between continuous variables and acute kidney injury
| Variable | AKI | t | P | |||||
|---|---|---|---|---|---|---|---|---|
| No (n=363) | Yes (n=37) | |||||||
| n | Mean/median | SD/IQR | n | Mean/median | SD/IQR | |||
| Age | 363 | 59.60 | 11.68 | 37 | 62.14 | 9.49 | 1.275 | 0.203^ |
| Body surface area | 363 | 1.68 | 0.17 | 37 | 1.72 | 0.14 | 1.011 | 0.313^ |
| Time of CAG in hours | 298 | 120 | 48-336 | 34 | 168 | 24-366 | 0.067 | 0.947$ |
| Euro SCORE II (%) | 363 | 1.69 | 1.09-2.82 | 37 | 2.31 | 1.43-4.23 | 2.628 | 0.009$,* |
| Hospital stay | 363 | 11 | 9-15 | 37 | 12 | 8.50-20.50 | 0.557 | 0.578$ |
*P<0.19 significant. Independent samples t-test; $Mann–Whitney U-test P value; ^P<0.19 considered significant for univariate analysis. SD: Standard deviation, IQR: Interquartile range
Table 4.
Association between acute kidney injury and demographic and clinical variables
| Variable | AKI | Chi-square value test | P | |
|---|---|---|---|---|
| No, n (%) | Yes, n (%) | |||
| LMCA category | ||||
| No | 296 (92.5) | 24 (7.5) | 5.837 | 0.016* |
| Yes | 67 (83.8) | 13 (16.2) | ||
| Gender | ||||
| Male | 271 (89.1) | 33 (10.9) | 3.888 | 0.049* |
| Female | 92 (95.8) | 4 (4.2) | ||
| Diabetes mellitus | ||||
| No | 169 (94.4) | 10 (5.6) | 5.180 | 0.023* |
| Yes | 194 (87.8) | 27 (12.2) | ||
| Systemic hypertension | ||||
| No | 114 (97.4) | 3 (2.6) | 8.806 | 0.003* |
| Yes | 249 (88) | 34 (12) | ||
| Dyslipidemia | ||||
| No | 171 (95.5) | 8 (4.5) | 8.821 | 0.003* |
| Yes | 192 (86.9) | 29 (13.1) | ||
| Recent ACS | ||||
| No | 216 (95.2) | 11 (4.8) | 12.128 | 0.0001* |
| Yes | 147 (85) | 26 (15) | ||
| Ejection fraction (%) | ||||
| <50 | 111 (85.4) | 19 (14.6) | 6.605 | 0.010* |
| >50 | 252 (93.3) | 18 (6.7) | ||
| NYHA Class | ||||
| NYHA Class I and II | 264 (90.1) | 29 (9.9) | 0.548 | 0.828a |
| NYHA Class III and IV | 99 (92.52) | 8 (7.47) | ||
| Redo | ||||
| No | 345 (90.8) | 35 (9.2) | 0.014 | 0.706a |
| Yes | 18 (90.0) | 2 (10.0) | ||
| Emergency | ||||
| No | 354 (91.5) | 35 (9.2) | 7.412 | 0.024a,* |
| Yes | 9 (69.2) | 4 (30.8) | ||
| CABG | ||||
| No | 121 (92.4) | 10 (7.6) | 0.606 | 0.436 |
| Yes | 242 (90) | 27 (10) | ||
| CABG + valve | ||||
| No | 343 (91.2) | 33 (8.8) | 1.673 | 0.262a |
| Yes | 20 (83.3) | 4 (16.7) | ||
| Valve replacement/repair | ||||
| No | 271 (89.1) | 33 (10.9) | 3.888 | 0.049* |
| Yes | 92 (95.8) | 4 (4.2) | ||
| Others | ||||
| No | 352 (91) | 35 (9) | 0.602 | 0.342a,* |
| Yes | 11 (84.6) | 2 (15.4) | ||
| Reintubation | ||||
| No | 338 (91.8) | 30 (8.2) | 6.604 | 0.020a* |
| Yes | 25 (78) | 7 (21.9) | ||
| Stroke | ||||
| No | 345 (91.5) | 32 (8.5) | 4.534 | 0.050a,* |
| Yes | 18 (78.3) | 5 (21.7) | ||
| IABP | ||||
| No | 359 (90.7) | 37 (9.3) | 0.412 | 1.000a |
| Yes | 4 (100.0) | 0 | ||
| CPB | ||||
| No | 235 (90.7) | 24 (9.3) | 0.0001 | 0.988 |
| Yes | 128 (90.8) | 13 (9.2) | ||
| History of prior PTCA | ||||
| No | 313 (89.9) | 35 (10.1) | 0.007 | 1.000a |
| Yes | 50 (96.2) | 2 (3.8) | ||
| Atrial fibrillation | ||||
| No | 299 (93.4) | 21 (6.6) | 13.767 | 0.0001* |
| Yes | 64 (80) | 16 (20) | ||
| Re exploration | ||||
| No | 355 (90.8) | 36 (9.2) | 0.038 | 0.586a |
| Yes | 8 (88.9) | 1 (11.1) | ||
| PRBC | ||||
| No | 187 (89) | 23 (11) | 1.526 | 0.217 |
| Yes | 176 (92.6) | 14 (7.4) | ||
| FFP | ||||
| No | 342 (90.2) | 37 (9.8) | 2.259 | 0.241a |
| Yes | 21 (100.0) | 0 | ||
| Platelet | ||||
| No | 342 (90.5) | 36 (9.5) | 0.614 | 0.708a |
| Yes | 21 (95.5) | 1 (4.5) | ||
| Cryoprecipitate | ||||
| No | 352 (90.7) | 36 (9.3) | 0.012 | 1.000a |
| Yes | 11 (91.7) | 1 (8.3) | ||
aFisher's exact test value. *P<0.19 significant. LMCA: Left main coronary artery, ACS: Acute coronary syndrome, AKI: acute kidney injury, FFP: Fresh frozen plasma, PRBC: Packed red blood cell, PTCA: Percutaneous transluminal coronary angioplasty, IABP: Intra aortic balloon counter pulsation, CPB: Cardiopulmonary bypass, CABG: Coronary artery bypass, NYHA: New York Heart Association
Table 5.
Multivariate binary logistic regression analysis with respect to acute kidney injury
| Variable | OR | 95% confidence limit | P | |
|---|---|---|---|---|
| Lower | Upper | |||
| Systemic hypertension | 4.002 | 1.177 | 13.603 | 0.026* |
| Recent ACS | 3.340 | 1.553 | 7.184 | 0.002* |
| Atrial fibrillation | 3.845 | 1.837 | 8.048 | 0.0001* |
*P<0.05 significant, P<0.001 statistically highly significant.
OR: Odds ratio, ACS: Acute coronary syndrome
Table 3.
Ionotrope requirement and aortic occlusion time in patient population
| Variable | AKI | t | P | |||||
|---|---|---|---|---|---|---|---|---|
| No | Yes | |||||||
| n | Mean/median | SD/IQR | n | Mean/median | SD/IQR | |||
| Noradrenaline (mcg/kg/min) | 267 | 0.04 | 0.02-0.06 | 34 | 0.04 | 0.02-0.065 | 0.109 | 0.913$ |
| Adrenaline (mcg/kg/min) | 116 | 0.03 | 0.02-0.06 | 20 | 0.035 | 0.02-0.05 | 0.060 | 0.952$ |
| Dobutamine (mcg/kg/min) | 78 | 4.38 | 2.5-5.0 | 1 | 10 | 10-10 | 1.723 | 0.085$,* |
| Milrinone (mcg/kg/min) | 49 | 0.3 | 0.23-0.4 | 8 | 0.27 | 0.23-0.3 | 0.231 | 0.817$ |
| Levosimendan (mcg/kg/min) | 16 | 0.10 | 0.06-0.1 | 5 | 0.10 | 0.05-0.2 | 0.667 | 0.505$ |
| Vasopressin (units/kg/min) | 16 | 0.0003 | 0.0002-0.0004 | 6 | 0.00045 | 0.0002-0.0007 | 1.161 | 0.246$ |
| DOPA (mcg/kg/mins) | 6 | 2.50 | 2.0-4.0 | 2 | 5.60 | 2.5-8.7 | 1.031 | 0.302$ |
| Ionotrope usage (mins) | 300 | 2130 | 1320-3131.3 | 35 | 2410 | 1005-4882 | 0.581 | 0.561$ |
| Aortic occlusion time (mins) | 126 | 104.01 | 39.72 | 13 | 119.62 | 54.34 | 1.300 | 0.196^ |
*P<0.19 significant. Independent samples t-test; $Mann–Whitney U-test P value; ^P<0.19 considered significant for univariate analysis. Dobutamine, Milrinone, Levosimendan, Vasopressin, and DOPA are presented with bootstrap median due to insufficient sample size. SD: Standard deviation, IQR: Interquartile range, AKI: Acute kidney injury, DOPA: Dopamine
Discussion
We successively recruited four hundred patients presenting to our center for elective/emergency CS during August 2016–October 2017. The overall incidence of AKI in this cohort was 9.25%. This is lower than the reported incidence in a meta-analysis of the literature which cites the overall incidence of this complication to be about 22%.[3] Most of the AKI reported, however, was deemed mild and therefore of less consequence. However, it should be pointed out that a majority of our patients underwent coronary artery revascularization (270/400); it is usual to perform this in centers such as ours without the use of cardiopulmonary bypass. The overall incidence of this complication is, therefore, closer to that reported in this population.[4] It should, however, be pointed out that the complication rate can, however, be as high as 14%–15% in this limited population as well.[5,6] It is, also a matter of current debate, a matter of current debate whether or not off-pump coronary artery bypass (OPCAB) revascularization is inferior to on-pump coronary artery bypass (ONCAB) in the mid/long term as opposed to short-term outcomes.[7] In the coronary trial which was a randomized controlled trial of ONCAB versus OPCAB with a study population across 16 countries, OPCAB was clearly beneficial in preventing AKIN Stage I AKI-CS with a strong trend toward preventing AKIN Stages 2/3 at 30 days.[8] However, there was no protection from renal failure requiring dialysis either in the short or intermediate term.[8] Further, in all prevalence studies of AKI-CS, there is divergence on account of patient enrolment and definitions of the condition, the nature and types of surgery which the individuals underwent. It is also questionable as to what should be the real outcome of interest considering that AKIN Stage I AKI-CS is less devastating, reversible, and therefore, probably of less clinical import than other more advanced forms of renal injury at least in the intermediate term.[9]
It is widely regarded that inotrope use or a compromised hemodynamic state is an important substrate in the causation of AKI-CS.[10] In our cohort, dobutamine use was associated with AKI in initial univariate analysis, but this risk was found to be insignificant on multivariate regression. On further univariate analysis, it was also determined that recent acute coronary events and emergent surgery were significantly more common in the adverse event group; these index risks advert to perturbations in hemodynamics not adequately captured in the enumerated data and to that extent, undermine the conclusions of the study. It should, however, be moot to point out, that, in any case, observational studies do not and should not attempt to hint at or prove causation.
Lower ejection fractions, the presence of long-standing diabetes and hypertension expectedly were markedly more prevalent in the group suffering AKI-CS. However, the time interval between angiography and procedure was not significant in risk for AKI-CS, and there is an ongoing debate about the attributable risk owing to radiocontrast agents outside the domain of CS.[11] The use of blood products has increasingly been a point of focus in perioperative care (Farmer et al. 2017)[12] with a proven reduction in both costs and complications. There have however been contrarian thoughts from the specialty of CS highlighting the role of anemia in aggravating renal injury[13] and transfusion in improving more global outcome,[14] our study could not demonstrate any association between blood component use and AKI-CS.
On multivariate regression analysis of the univariate predictors of AKI-CS only the following three predictors were found significant: systemic hypertension, recent ACS, and postoperative atrial fibrillation. We surmise that this is on account of a coalescence of the extremely deleterious risks that atrial fibrillation has on systemic hemodynamics in the presence of diastolic dysfunction. It is already well known that this combined risk of undermanaged hypertension and diastolic dysfunction has independent effects on mortality.[15] More specifically there is now further clear evidence from other investigators of the deleterious effects of heart failure with preserved ejection fraction (HFpEF) on renal outcomes, both in the community[16] and after coronary artery bypass.[3]
Our study is lacking in that specific indices of diastolic function were not systematically studied or enumerated in the risk assessment of CS-AKI. Nevertheless, we suggest that we extend the literature in our cohort and our results will also make a compelling case for both systematic study and specific measures to target HFpEF in patients presenting for CS. The risks of diabetes were however not sustained on multivariate regression. It is interesting that multivariate regression shows that dopamine was actually a risk factor for AKI-CS. Therefore, it is likely that this was rather the effect than the cause of AKI-CS and a misinformed attempt to treat this entity. Recent ACS as presentation also substantially increased the risk of AKI-CS; this likely is a surrogate for the compromised hemodynamic profile of these patients. However, other surrogates of hemodynamic compromise such as extended vasoactive drug use or use of the IABP were not shown to be independent predictors of this complication. A detailed explanation is suggested vide supra.
In the group which suffered AKI-CS of any degree hospital stay was marginally but not significantly increased. The adverse outcome group also had higher mortality overall than in the group which did not suffer AKI-CS (97% survival vs. 86.5% survival). The starkest data was from the small group of patients who suffered AKI-CS requiring dialysis; an overwhelming, 75% of the patients who suffered this degree of AKI died. This is considerably higher than the benchmark mortality rates approaching 50%–60% in the previously reported literature.[17,18] It may be evidence of how renal intensive care in low- and middle-income settings such as ours does not yet meet international benchmarks of care and that a conscious effort to improve the overall quality of evaluating and delivering RRTs in acute care after CS needs a conscious revisit.
Overall, we suggest that we extend the rather limited description of AKI-CS from limited resource healthcare. While heartening that the overall incidence of AKI-CS, we report is lower than most other reports in the literature the extraordinary risks of mortality that result from the severest forms of the condition warrant purposive and conscious quality improvement. There should be country specific registry data listing major perioperative outcomes; they will allow clinical practice guidelines based on local data. Single center, observational studies such as ours can be lamps but cannot be the beacon.
Conclusions
The overall incidence of AKI-CS was 9.25%. The incidence of AKI-CS requiring dialysis (Stage 3 AKIN) AKI-CS was lower (2%). However, mortality risks were disproportionately high in patients with AKIN Stage 3 AKI-CS (75%). Despite this study showing that the predominant severity of AKI- CS was mild mortality risks were disproportionately higher (2.8% vs 13.5%, Figure 2).
In multivariate logistic regression atrial fibrillation, systemic hypertension, recent ACS independently predict the risk of CS-AKI in our population. Systemic hypertension and occult diastolic heart failure could be linked to hemodynamic compromise secondary to onset of postoperative atrial fibrillation. Since observational studies do not prove causation, this can only be considered hypothesis generating.
There is a need for quality improvement in the care of patients with CS AKI in its most severe forms since mortality risks posed by the development of Stage 3 AKIN AKI is higher than reported in other index populations from high-resource settings.
Financial support and sponsorship
Nil.
Conflicts of interest
There are no conflicts of interest.
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