Introduction: problem in critical illness. Approximately 5–6% of

 

 

 

Introduction: Acute kidney
injury (AKI) is a significant problem in critical illness. Approximately 5–6%
of all hospitalized adults and 10% of children suffer from varying degrees of
AKI 1. The presence of AKI in critical illness occurs at a rate of 10–15% and
carries a 50% mortality rate in children requiring dialysis 2,3,4. Increasing
AKI severity, characterized by serum creatinine (SCr)- and urine output
(UOP)-based stratifications of AKI, is associated with increased mortality in
adults5 and children.6 Notably, small increases in SCr (0.3 mg/dl) may
reflect significant kidney damage and is associated with poor patient outcomes
7,8.

Consistently effective AKI therapy to prevent or limit the disease
intensity is lacking, potentially due to delayed recognition of existing and/or
ongoing injury. AKI diagnosis is traditionally dependent on changes in serum
creatinine (SCr), a marker with limitations involving time, body habitus, sex,
age, steady-state measurement, and patient condition. Primarily due to the lag
in the rise of SCr, the diagnosis of AKI is often delayed, which creates a
significant barrier to effective early intervention. 9

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Treatment for acute myocardial infarction (MI) was transformed by
the use of troponin I measurements in patients with signs and symptoms of a
cardiac angina. Sensitivity and specificity of troponin elevations and
electrocardiographic changes for MI have allowed practitioners to institute
early and life-saving therapy. However, whereas the novel AKI biomarkers
recently discovered may serve well as a renal troponin equivalent, AKI lacks an
important parallel to MI. Simply put, AKI does not hurt.  In order to optimize the utility of AKI
biomarkers, screening systems are needed to identify patients who are at high
risk of developing AKI.9

Goldstein SL recently proposed the empiric clinical model of renal
angina to identify which critically ill patients would be at the greatest risk
of AKI. Using patient demographic factors and early signs of injury, renal
angina is aimed to delineate patients at risk for subsequent severe AKI (AKI
beyond the period of functional injury) versus those at low risk. 10 In this
study, the concept of renal angina to improve prediction of subsequent severe
AKI has been validated in Indian children admitted in PICU.

Material And
Methods:

Subjects: All children between 1 months-18 years age group admitted in PICU

Duration: one year. Setting: Pediatric
Intensive Care Unit (PICU) of a tertiary care hospital in Ludhiana District,
Punjab. Design: Prospective
observational study

Inclusion Criteria: All critically ill children between 1 months to 18 years of age admitted
to PICU were included in the study.

Exclusion criteria: Children with previously known kidney disease and children with hospital
stay less than 72 hours were be excluded.

The study was approved by the Institutional Ethics committee.
Written consent was obtained from the attendants of the
children.

Data Collection: Day 0 was considered
first day of PICU admission. Day 3 consisted of the time period between 72 and
96 hours after PICU admission. Baseline data at admission included demographic
information including age, sex, primary diagnosis, system involved, Pediatric
Risk of Mortality (PRISM-II) scores 11 within 24 hours of hospital admission,
renal dysfunction using KDIGO (Kidney Disease Improving Global Outcomes)
staging 12, and baseline serum creatinine measurement (SCr).

Calculation of Renal angina index (RAI):
The index calculation for the fulfilment of renal angina is assessed 8-12 h
after a patient is admitted to an intensive care unit and used for prediction
of severe acute kidney injury 72 hours (3 days) later.

Risk factors are
determined as shown and assigned a point value (1, 3, and 5, where 1 denotes
the lowest risk and 5 denotes the highest risk). Mechanical ventilation and
vasoactive support should be used within the 12-h timepoint but are not
required to be simultaneous for a patient to be scored 5 points.

Injury strata was assigned
as depicted to a patient as appropriate.  Percentage fluid overload (FO %) was
calculated by {Fluid in(ml)-fluid out (ml) ÷ Patient Weight (gm)} x 100). GFR
was based on estimated creatinine
clearance (eCrCl) calculated by the Schwartz equation 13, for determination
of the RAI. 

Calculation of Renal
Angina Index (Range 1 to 40) is a multiplication of the risk and injury scores
assigned (Risk score x FO% score OR Risk score x GFR score), whichever is worse
of the two is chosen. The index RAI ?8 was considered fulfillment of renal
angina 14. Fulfillment or the absence of renal angina was denoted ‘RA
positive’ or ‘RA negative’.

 

 

Outcomes: The primary outcome was the presence of severe AKI on Day3 (Day3-AKI). Severe AKI was defined by the Kidney
Disease Improving Global Outcomes (KDIGO) AKI classification stage ?2: serum
creatinine of 200% baseline (a decrease in eCrCl of ?50% from baseline) (26). Day3 was chosen since most PICU patients
develop AKI within this timeframe and is a clinically relevant time frame for
AKI management. Secondary outcomes
included use of renal replacement therapy (RRT), need and duration of
mechanical ventilation, length of PICU stay (LOS), and incidence of mortality.

Statistical Analyses

All statistical analyses were
performed using STATA version 12 (StataCorp, College
Station, TX), SAS version 9.3 (SAS Institute, Cary, NC), and R version 2.14.1
(R Development Core Team, Vienna, Austria). An a priori
study sample size of 5250 patients was expected. The continuous data were summarized using
descriptive statistics (mean ± standard deviation). Statistical differences
between the mean values were compared using Student’s t-test. A difference
between the two values was considered to be significant if the P < 0.05. Categorical variables were summarized using frequency and proportion and compared by chi-squared or Fisher's exact tests. An RAI cut-off of ?8 was used to define renal angina fulfillment ANG(+) and this cut-off was used for operative characteristics (20). Simple and multivariable logistic models were used to predict day 3 AKI using RAI. Area under the curve (AUC) values were calculated for the prediction model (RAI) and compared using DeLong's method (27). In all analyses, a P value <0.05 was considered statistically significant. Results:  Of the total ____________ patients admitted during the one year period, 413 (    %) patients were enrolled for study. Number______ could not enrolled for different reasons CKD (n=   ), age less than 2 months (n=______), hospital stay less than 72 hours(n=_______). Approximately one third of patients i.e. 69/413(16.7 %) were RA + on day day 0 of PICU admission. Mean age in RA +ve group was 5.92 ± 5.30 years as compared to RA -ve group 5.88 ± 5.32 years. Age, gender, admitting diagnosis or primary system did not affect RA positivity. Sepsis was the diagnosis in 21 % cases and did not affect RA status. Patients in RA +ve group had higher mean PRISM-II scores (18.62 ± 6.49) compared to RA -ve group (12.74 ± 6.49) (p value < 0.001). Additionally, patients in RA+ group had longer duration of mechanical ventilation (mean 4.94 ± 4.10 days vs mean 1.08 ± 2.68 days) (p value < 0.001), PICU stay (mean  7.19 ± 5.13 days vs mean  4.72 ± 2.71) (p value < 0.001), need for dialysis ( 23.2 % vs 0.6% %, p value < 0.001)  and higher mortality( 31.09 % vs 2 % , p value < 0.001). Prediction of subsequent, severe AKI by Renal Angina Index on admission.  Of the total 413 patients enrolled, 33 patients developed Day3-AKI (8%).  The incidence of Day 3 AKI was significantly higher in patients with RAI ?8 (RA + group) 25 of 69 (36.2 %) versus 8 of 344 (2.3 %); P= <0.001. Day 0 RAI positivity (RAI > 8) predicted Day-3 AKI with an
AUC of 0.883 95% confidence interval (CI) = 0.823-0.943. RAI > 8
positivity had a
high negative predictive value (NPV)
of 97.67% % (95% CI = 95.84-98.7
%), with sensitivity and specificity of  75% and 88.42 % , respectively, and positive
predictive value (PPV) of 35.29% (95% CI = 27.92-43.44 %).

RAI
prediction by GFR criteria and Fluid overload (FO %) criteria

The
predictive value of  RAI was broken down by composite factors
of kidney injury. The predictive value for Day-3 AKI by GFR score alone by AUC values was consistently
superior when compared to
fluid overload score (FO %) AUC 0.877 (95% CI = 0.817-0.936) vs
0.774 (95% CI = 0.685- 0.864).
The AUC for
RAI for Day-3 AKI improved when
RAI incorporated worse of the two scores (GFR score/FO score). (AUC
0.883(95% CI= 0.823-0.943). 

RAI
versus KDIGO stage and PRISM score

Prediction of RA for Day-3 AKI was superior to KDIGO
stage 1 injury at admission;
fulfillment of renal angina demonstrated higher sensitivity (27.27%), PPV of 25%, NPV of 93.63%
and a higher
Youden’s index ( ____________) than KDIGO stage 1,
although specificity was found to be higher with KDIGO stage 1 (92.89%). Similar results were seen when RA was compared to KDIGO stages 2–3 (Youden’s index=_____). When compared directly, RAI outperformed PRISM-II for the
prediction of day 3 AKI. (AUC=0.764)
(95% confidence interval (CI) = 0.672-0.856).

Discussion:  Renal angina index was developed by Goldstein to identify critically
ill patients at greatest risk of AKI.10  In the current study, we operationalize renal
angina index in a tertiary care hospital of a developing country and show that
renal angina index improves prediction of subsequent severe AKI and also
outperforms currently used clinical thresholds for early signs of kidney
injury, or severity of illness scores.

RAI was derived as a composite of risk factors and clinical
signs of AKI. The logic behind the equation dictates that as a patient achieves
higher risk they require less “clinical sign of AKI” early on to fulfill renal
angina. Similarly, if a patient has less risk but shows more overt signs of clinical
AKI signs, renal angina would also be fulfilled.15 RAI derivation was based on available AKI epidemiology
reported in select pediatric populations: children admitted to the ICU carry
increased risk over the general population (4.5–10%),16,17 children receiving bone marrow
transplantation have ~3× risk (11–21%)18, and those who are intubated and on vasopressor support
carry nearly 5× risk versus the general ICU population (51%). 3 The ‘signs of injury’ (i.e.,
kidney pain) in the RAI include GFR and fluid overload.

Troponin measured in patients
who exhibit cardiac angina, a combination of clinical signs and known coronary
disease risk factors, allows practitioners to rule in myocardial infarction. In
this select, risk-stratified population, troponin has great specificity and
PPV. When measured in patients without cardiac angina, troponin loses
performance. Unfortunately, unlike a heart attack, AKI does not carry an easily
identifiable physical prodrome such as cardiac angina. Simply put, a kidney
attack does not ‘hurt’. So clinicians tried to find a novel renal equivalent of
“cardiac angina” so that a suitable biomarker can be applied to select patients
having high risk of AKI.

Renal angina fulfillment identifies children at the highest
risk of suffering subsequent severe AKI. For a clinician, the ability to
predict the presence of severe AKI 3 days in advance carries obvious benefit.

Fluids are the second most
common intervention in acutely ill patients (after oxygen). The benefits of
early fluid resuscitation in patients with shock and acute kidney injury (AKI)
are already accepted. There is evidence that fluid administration beyond the
correction of hypovolaemia is associated with increased morbidity, a longer
hospital stay and mortality. In a recent article in Critical Care, Wang et al.
analysed the data of 2526 patients admitted to 30 intensive care units (ICUs)
in China and showed that even relatively small degrees of fluid overload were
independently associated with an increased risk of AKI and mortality 19.

In the Rajit
Basu etal study,
based on the most optimal Youden’s index (0.49) and highest negative predictive
value (to safely rule out development of subsequent AKI), an RAI > 8 was
taken as cutoff to label Renal Angina positivity.15 Only day 3 AKI was chosen to define outcome as most PICU
patients develop AKI within this time frame and it surpasses the time frame of
functional AKI (prerenal AKI). Also, time frame of 8 h was kept to assess fluid
overload as it was beyond the generally accepted window of ‘early goal-directed
therapy’ (EGDT) of resuscitation. 20

    In our study a
total of 413 patients were included. Day 0 Renal Angina positive was seen in
16.7% patients. Of  renal angina positive
patients 36.2 %  developed subsequent
severe AKI compared to 2.3 % of the other group, which was highly significant
(p<0.001). Performance of the test was also calculated. Sensitivity came to be 75%. Specificity came to be 88.42%. Positive predictive value was low (35.29%) whereas a high negative predictive value of 97.67% was present. AUC for the same came to be 0.877. When the RAI was derived based on either GFR score or Fluid overload alone, it was still able to predict Day-3 AKI. Although FO score did not perform as well as GFR score, FO score was similar to PRISM-II scores for prediction of Day-3 AKI. More importantly, the prediction for Day-3 AKI improved when the worse value of FO or GFR score was used compared to using  GFR score alone. Also, Renal angina outperformed early signs of injury i.e. KDIGO stages I. Our results were similar to those seen in the Rajit Basu et al. study.15 Several AKI biomarkers have demonstrated promising results for the identification and prediction of AKI in children.21 Identifying patients at risk for severe and long-lasting AKI in the PICU is crucial as risk stratification could allow more judicious AKI biomarker assessment to drive therapeutic intervention, thereby increasing their predictive performance and cost-effectiveness. 22 Limitation of the study was that baseline creatinine was calculated from admission serum creatinine and patient height using the Schwartz correction. This was done, as most patients did not have their lowest creatinine value (up to 3 months before PICU admission) to establish a reference value. In our study, to define severe subsequent AKI, estimated creatinine clearance criteria of KDIGO (SCr of 200% baseline or  decrease in eCCl of ?50% from baseline) was take to define primary outcome and urine output criteria was not taken.  Thus, renal angina index could be used as a simple and important bedside tool without the need of any expensive equipment to detect patients at risk of severe AKI. This can allow us to use novel AKI biomarker or therapy trial, which could ultimately guide treatment strategy in critically ill children.