Role of Platelet to Albumin Ratio for Predicting Persistent Acute Kidney Injury in Patients Admitted to the Intensive Care Unit

Yuanwei Zhai; Xiaoqiang Liu; Yu Li; Qionghua Hu; Zhengwei Zhang; Tianyang Hu

BMC Anesthesiol. 2023;23(242)

Abstract and Introduction

Abstract

Background: The aim of this study was to investigate the prognostic role of platelet to albumin ratio (PAR) and in persistent acute kidney injury (pAKI) of patients admitted to the intensive care unit (ICU).

Methods: We involved pAKI patients from the Medical Information Mart for Intensive Care-IV (MIMIC-IV) database and eICU Collaborative Research Database (eICU-CRD). Receiver operating curve (ROC) analysis was performed to evaluate the optimal cut-off PAR.

Results: A total of 7,646 patients were finally included in the present study. The optimal cut-off value of PAR was 7.2. The high-PAR group was associated with pAKI (hazard ratio [HR]: 3.25, 95% CI: 2.85–3.72, P < 0.001). We also performed this in the validation cohort, the results further confirmed that the high-PAR group was associated with pAKI (HR: 2.24, 95% CI: 1.86–2.71, P < 0.001). The PAR exhibited good pAKI predictive abilities in the original cohort (C-index: 0.726, 95%CI: 0.714–0.739) and in the validation cohort (C-index: 0.744, 95%CI:0.722–0.766) Moreover, as a systemic inflammatory indicator, PAR depicted better predictive ability compared to other systemic inflammatory indicators.

Conclusion: The present study manifested that elevated PAR could predicts pAKI in patients admitted to ICU. PAR may be an easily obtained and useful biomarker to clinicians for the early identification of pAKI.

Introduction

Acute kidney injury (AKI) is commonly occurs with a high incidence which represents a global public health problem in patients admitted to the intensive care unit (ICU) and is associated with significant morbidity and mortality.^[1–3] Reported mortality in ICU patients with AKI accounts for approximately 36–67% depending on AKI definition.^[2,4] Although efforts have been made to curb AKI progress to chronic kidney disease (CKD) and end-stage kidney disease (ESKD), there remains a considerable proportion of patients presenting to ICU who required renal replacement therapy (RRT).^[5,6] Moreover, the AKI occurrence in ICU increases the length of stay, the need for more vasopressors drugs, and increased the cost of services and health care systems.^[7,8]

Since the 2017 Acute Disease Quality Initiative (ADQI) workgroup proposed standard definitions of transient and persistent AKI (pAKI) based on the potential impact of AKI duration on outcomes,^[9] numerous investigators explored the outcomes of different types of AKI. Previous evidence indicated that two-thirds of patients with AKI resolve their renal dysfunction rapidly and there still almost one-third of patients progress to pAKI. pAKI patients exhibited an increased risk of CKD, ESKD, prone to receive RRT, and reduced survival compared to those transient AKI patients.^[10,11] Considering the important role of pAKI in the prognosis of critically ill patients, early and accurate risk assessment is of critical importance for clinical management in ICU patients to receive early interventions.

Clinicians are seeking clinically meaningful predictors or biomarkers for pAKI in ICU patients. A recent study intended to assess novel candidate biomarkers to predict pAKI in critically ill patients and found that urinary C-C motif chemokine ligand 14 (CCL14) is a predictive biomarker for pAKI in critically ill patients.^[12] Shen et al. reported that 24-h procalcitonin change is a good predictor of pAKI in critical patients.^[13] However, these biomarkers are not easily obtained upon admission to clinical. A simple and easily accessible prognostic biomarker for early risk stratification of pAKI in patients admitted to ICU is needed.

Platelet to albumin ratio (PAR) is a widely used biomarker clinically based on routine laboratory tests which reflect the systemic inflammatory state and nutrition status, has been reported to predict several disease settings.^[14,15] However, limited data have been presented on the relationship between PAR and pAKI in critically ill patients. This study sought to investigate the role of PAR in predicting pAKI in patients admitted to ICU.

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Next Section

Abstract and Introduction
Methods
Results
Discussion
Conclusions
References

Table 1. Comparisons of baseline characteristics in all cohorts
Covariates	Original cohort			Validation cohort
Covariates	Low PAR	High PAR	P	Low PAR	High PAR	p
N	3533	1791	-	1489	833	-
Age, years	65.2 (15.9)	65.2 (16.0)	0.992	65.0 (15.5)	64.5 (14.9)	0.516
Gender, male, n (%)	2243 (63.5)	933 (52.1)	< 0.001	842 (56.5)	403 (48.4)	< 0.001
Weight, kg	27.8 (7.9)	28.0 (8.8)	0.688	30.4 (8.4)	28.6 (8.2)	0.318
Ethnicity, n (%)			0.167			0.579
White	2250 (63.7)	1186(66.2)		1182 (79.4)	671 (80.6)
Black	481 (13.6)	234 (13.1)		170 (11.4)	96 (11.5)
Other	802 (22.7)	371 (20.7)		25 (16.2)	19 (29.2)
Interventions, n (%)
MV use	2251 (63.7)	1130(63.1)	0.679	839 (56.3)	497 (59.7)	0.132
RRT use	386 (10.9)	216 (12.1)	0.234	119 (8.0)	81 (9.7)	0.177
Drugs usage, n (%)
ACEI/ARB	1028 (29.1)	532 (29.7)	0.669	392 (26.3)	214 (25.7)	0.775
βblockers	2454 (69.5)	1278 (71.4)	0.162	916 (61.5)	506 (60.7)	0.747
CCB	882 (25.0)	431 (24.1)	0.493	324 (21.8)	188 (22.6)	0.690
Diuretic	2730 (77.3)	1368 (76.4)	0.488	1087 (73.0)	594 (71.3)	0.408
Statin	1527 (43.2)	770 (43.0)	0.897	606 (40.7)	340 (40.8)	0.991
Aspirin	1779 (50.4)	940 (52.5)	0.150	695 (46.7)	396 (47.5)	0.721
PPI	2292 (64.9)	1230 (68.7)	0.006	758 (50.9)	429 (51.5)	0.817
Score system, points
SOFA	3.9 (1.1)	4.5 (1.6)	< 0.001	6.1 (3.6)	8.1 (3.1)	< 0.001
OASIS	38.4 (9.6)	38.2 (9.5)	0.435	29.8 (10.7)	30.4 (10.6)	0.141
APSIII	68.7 (27.6)	67.7 (26.7)	0.192	65.7 (25.1)	67.1 (25.2)	0.206
Comorbidities, n (%)
Hypertension	1173 (33.2)	636 (35.5)	0.099	841 (56.5)	484 (58.1)	0.475
Diabetes	1220 (34.5)	662 (37.0)	0.085	554 (37.2)	343 (41.2)	0.066
CKD	1122 (31.8)	601 (33.6)	0.195	363 (24.4)	194 (23.3)	0.590
Myocardial infarct	670 (19.0)	386 (21.6)	0.028	149 (10.0)	65 (7.8)	0.092
CHF	1269 (35.9)	682 (38.1)	0.130	302 (20.3)	153 (18.4)	0.289
COPD	240 (6.8)	137 (7.6)	0.274	243 (16.3)	146 (17.5)	0.491
Liver disease	948 (26.8)	280 (15.6)	< 0.001	90 (6.0)	22 (2.6)	< 0.001
CCI, points	6.4 (2.8)	6.5 (3.2)	0.486	4.5 (1.8)	4.2 (1.6)	0.080
Vital signs
MAP, mmHg	106.8 (30.3)	107.7 (31.1)	0.333	85.6 (25.0)	86.2 (24.0)	0.565
Heart rate, bpm	106.6 (21.8)	111.2 (24.1)	< 0.001	106.5 (29.1)	110.5 (27.2)	0.001
RR, bpm	28.8 (6.8)	29.7 (7.0)	< 0.001	25.6 (9.1)	26.1 (9.3)	0.205
Laboratory results
WBC, × 10⁹/L	15.4 (5.7)	18.6 (6.9)	< 0.001	13.8 (5.4)	17.3 (8.3)	< 0.001
HGB, g/dL	9.6 (2.3)	9.4 (2.1)	0.001	10.9 (2.3)	10.5 (2.1)	< 0.001
PLT, × 10⁹/L	164.5 (67.6)	331.0(94.8)	< 0.001	150.0 (64.4)	311.9 (109.6)	< 0.001
HCT, %	34.6 (7.6)	34.5 (6.6)	0.819	33.0 (6.8)	32.3 (6.1)	0.010
Albumin, g/dL	3.9 (0.9)	3.0 (1.0)	< 0.001	3.5 (0.8)	2.9 (0.8)	< 0.001
PAR	4.3 (1.6)	12.0 (5.1)	< 0.001	54.3 (1.7)	11.4 (5.0)	< 0.001
Bilirubin, mmol/L	3.3 (1.9)	2.2 (1.4)	< 0.001	1.7 (0.9)	1.1 (0.7)	< 0.001
Anion gap, mEq/L	18.3 (5.4)	18.7 (5.8)	< 0.001	13.2 (5.9)	13.4 (6.2)	0.393
Bicarbonate, mEq/L	23.6 (4.6)	23.7 (4.7)	0.683	22.8 (5.9)	23.6 (6.4)	0.003
BUN, mg/dL	38.8 (7.5)	39.1 (10.3)	0.742	38.6 (8.1)	38.4 (10.7)	0.002
Glucose, mg/dL	186.9 (77.8)	202.1(95.0)	< 0.001	166.9 (80.0)	183.9 (86.9)	0.004
Lactate, mmol/L	3.5 (1.5)	3.5 (1.8)	0.473	2.9 (0.9)	2.5 (0.8)	< 0.001
Potassium, mmol/L	4.8 (0.9)	4.9 (1.0)	< 0.001	4.2 (0.7)	4.2 (0.7)	0.670
Sodium, mmol/L	139.8 (5.7)	139.6 (5.7)	0.263	137.6 (5.7)	137.4 (5.5)	0.247
Calcium, mg/dL	8.6 (1.7)	8.6 (1.1)	0.290	8.5 (1.1)	8.6 (1.1)	0.123
Chloride, mmol/L	105.8 (7.3)	105.6 (7.4)	0.252	101.4 (7.8)	100.3 (7.7)	0.002
PT, s	19.9 (5.4)	19.0 (6.8)	0.024	18.9 (8.4)	18.1 (7.0)	0.019
APTT, s	50.7 (13.2)	50.0 (14.6)	0.497	38.0 (10.5)	38.0 (10.9)	0.992
INR	1.9 (0.7)	1.8 (0.8)	0.010	1.7 (0.8)	1.6 (0.7)	0.009
AKI stage, n (%)			0.002			0.085
Stage I	2760 (78.1)	1322 (73.8)		1205 (80.9)	649 (77.9)
Stage II	410 (11.6)	253 (14.1)		97 (6.5)	61 (7.3)
Stage III	363 (10.3)	216 (12.1)		187 (12.6)	123 (14.8)
Clinical outcome
pAKI, n (%)	753 (21.3)	787 (43.9)	< 0.001	300 (20.1)	301 (36.1)	< 0.001

PAR, platelet-to-albumin ratio, MV, mechanical ventilation, RRT, renal replacement therapy, ACEI/ARB, Angiotensin converting enzyme inhibitors/Angiotensin receptor blockers, CCB, Calcium calcium blockers, NSAID, nonsteroidal anti-inflammatory drug, PPI, proton pump inhibitor, SOFA, sequential organ failure assessment, OASIS, oxford acute severity of illness score, APSIII, acute physiology score III, CKD, chronic kidney disease, CHF, congestive heart failure, COPD, chronic obstructive pulmonary disease, CCI, charlson comorbidity index, AKI, acute kidney injury, MAP, mean arterial pressure, RR, respiratory rate, WBC, white blood cell, HGB, hemoglobin, PLT, platelet, HCT, hematocrit, ALP, alkaline phosphatase, BUN, blood urea nitrogen, PT, prothrombin time, APTT, activated partial thromboplastin time, INR, international normalized ratio, AKI, acute kidney injury, pAKI, persistent AKI.

Table 2. Change in serum creatinine before and after the diagnosis of AKI
Variables	Values
Original cohort
Serum creatinine at ICU admission, mean ± SD	1.63 ± 0.94
Serum creatinine at ICU admission, median (IQR)	1.00 (0.70, 1.80)
Serum creatinine at first AKI diagnosis, mean ± SD	2.40 ± 1.04
Serum creatinine at first AKI diagnosis, median (IQR)	1.70 (1.20–2.90)
Serum creatinine at 48 h after AKI diagnosis, mean ± SD	2.12 ± 1.02
Serum creatinine at 48 h after AKI diagnosis, median (IQR)	1.50 (0.93–2.68)
Positive changes of serum creatinine, n (%)	1193 (22.4)
Δserum creatinine, mean ± SD	0.86 ± 0.73
Negative or static change of serum creatinine, n (%)	4131 (77.6)
Δserum creatinine, mean ± SD	-0.63 ± 0.51
Validation cohort
Serum creatinine at ICU admission, mean ± SD	1.53 ± 0.52
Serum creatinine at ICU admission, median (IQR)	1.08 (0.72, 1.90)
Serum creatinine at first AKI diagnosis, mean ± SD	2.74 ± 1.04
Serum creatinine at first AKI diagnosis, median (IQR)	2.10 (1.38, 3.49)
Serum creatinine at 48 h after AKI diagnosis, mean ± SD	2.12 ± 1.02
Serum creatinine at 48 h after AKI diagnosis, median (IQR)	1.50 (0.93, 2.68)
Positive changes of serum creatinine, n (%)	333 (14.3)
Δserum creatinine, mean ± SD	0.53 ± 0.42
Negative or static change of serum creatinine, n (%)	1989 (85.7)
Δserum creatinine, mean ± SD	-0.81 ± 0.67

ICU, intensive care unit, SD, standard deviation, IQR, interquartile range, AKI, acute kidney injury

Table 3. Summary of results of primary outcome and sensitivity analysis
	Original cohort		Validation cohort
	HR (95%CI)	P value	HR (95%CI)	P value
Unadjusted	2.89 (2.56–3.27)	< 0.001	2.24 (1.86–2.71)	< 0.001
Model 1	2.93 (2.59–3.32)	< 0.001	2.30 (1.90–2.79)	< 0.001
Model 2	3.12 (2.74–3.54)	< 0.001	2.36 (1.94–2.87)	< 0.001
Model 3	3.31 (2.91–3.78)	< 0.001	2.55 (2.05–3.16)	< 0.001
Model 4	3.45 (3.02–3.95)	< 0.001	2.77 (2.13–3.60)	< 0.001

Model 1 adjusted for age, gender, weight, ethnicity. Model 2 adjusted for model 1 plus comorbidities and charlson comorbidity index. Model 3 adjusted for model 2 plus score systerm, interventions, and drug usage. Model 4 adjusted for model 3 plus vital signs and laboratory results except for platelets and serum albumin

Table 4. Receiver operating curve analysis
Variable	Sensitivity	Specificity	AUC (95%CI)	P value
Original cohort
PAR	60.3	74.3	0.726 (0.714–0.739)
NLR	12.3	90.8	0.504 (0.486–0.519)	< 0.001
PLR	37.5	76.6	0.603 (0.589–0.616)	< 0.001
MLR	28.2	74.3	0.501 (0.488–0.515)	< 0.001
SII	43.4	79.5	0.615 (0.601–0.628)	0.004
Validation cohort
PAR	70.7	69.7	0.744 (0.722–0.766)
NLR	48.3	56.4	0.507 (0.485–0.529)	< 0.001
PLR	80.4	28.6	0.602 (0.580–0.624)	< 0.001
MLR	54.0	48.6	0.503 (0.481–0.525)	< 0.001
SII	49.3	62.2	0.507 (0.485–0.529)	< 0.001

PAR, platelet to serum albumin ratio, NLR, neutrophil-lymphocyte ratio, PLR, platelet-lymphocyte ratio, MLR, monocyte-lymphocyte ratio, SII, systemic immune-inflammation index, area under the receiver operating curve