U-Shaped association between platelet-to-lymphocyte ratio and in-hospital mortality in critically ill patients with acute kidney injury requiring continuous renal replacement therapy: A retrospective observational cohort study

Abstract

Background

The platelet-to-lymphocyte ratio (PLR) is a marker of inflammation and predictor of mortality in a variety of diseases. However, the effectiveness of PLR as a predictor of mortality in patients with severe acute kidney injury (AKI) is uncertain. We evaluated the association between PLR and mortality in critically ill patients with severe AKI who underwent continuous renal replacement therapy (CRRT).

Methods

This is a retrospective observational cohort study, and a total of 1044 patients with AKI who underwent CRRT in Kyungpook National University Hospital from 2017 to 2021 were analyzed. The study subjects were divided into quintiles according to the PLR at CRRT initiation. A Cox proportional hazards model was used to investigate the association between PLR and mortality.

Results

PLR was associated with in-hospital mortality in a non-linear manner, showing a higher mortality rate at both ends of the PLR. The Kaplan–Meier curve analysis revealed the highest mortality rates with the first and fifth quintiles, while the lowest mortality rate occurred with the third quintile. Compared with the third quintile (the lowest mortality rate group), the first (adjusted hazard ratio [aHR] 1.94, 95% confidence interval [CI] 1.44–2.62, P < 0.001) and fifth (aHR, 1.60, 95% CI 1.18–2.18, P = 0.002) quintiles of PLR had significantly higher in-hospital mortality. The first and fifth quintiles showed a consistently increased risk of 30-day and 90-day mortality compared with the third quintile. In the subgroup analysis, lower and higher PLRs were predictors of in-hospital mortality in patients with older age, female sex, hypertension, diabetes, and higher Sequential Organ Failure Assessment score.

Conclusion

Both the lower and higher PLRs were independent predictors of in-hospital mortality in critically ill patients with AKI who underwent CRRT. Thus, the PLR may be a useful and easily accessible prognostic indicator for patients with severe AKI.

Background

Acute kidney injury (AKI), which presents more frequently in the intensive care unit (ICU) patients, is associated with poor outcomes (1–4). Several publications have shown that the higher the AKI stage, the worse the outcome (2, 4, 5). In the ICU setting, continuous renal replacement therapy (CRRT) is performed for patients who develop severe AKI requiring dialysis (2). Requiring CRRT implies that a patient has deteriorating medical conditions, such as hemodynamic instability and severe AKI. Given the poor outcomes of patients requiring CRRT, several studies have explored the prognostic factors and identified novel biomarkers of AKI (5–8). However, patient heterogeneity in clinical studies makes it difficult to obtain consistent results. In addition, most biomarkers are neither readily available in clinical practice nor cost-effective (9).

The platelet-to-lymphocyte ratio (PLR) is a systemic inflammatory index that can be calculated easily. PLR has been demonstrated to be a prognostic factor in some diseases such as cancer and myocardial infarction (10–12). Several studies have also shown that PLR is associated with the occurrence of contrast-induced nephropathy in patients with ST-segment elevation myocardial infarction (13, 14).

However, studies on the role of PLR in patients with severe AKI are limited, especially in critically ill patients. We analyzed observational cohort data to elucidate the role of PLR as a prognostic marker in critically ill patients with severe AKI who underwent CRRT.

Methods

Study subjects and data collection

This retrospective cohort study was conducted at Kyungpook National University Hospital between February 2017 and March 2021. Subjects aged ≥ 19 years who underwent CRRT were included in the study while those who had previously undergone maintenance dialysis were excluded. Demographic characteristics and medical data, including comorbidities and clinical information were collected. Laboratory results at the time of CRRT initiation, including complete blood count, creatinine, blood urea nitrogen (BUN), albumin, arterial pH, sodium, and potassium levels, were obtained from the electronic medical records from Kyungpook National University Hospital. The Sequential Organ Failure Assessment (SOFA) score, Acute Physiology and Chronic Health Evaluation II (APACHE II) score, and Charlson Comorbidity Index (CCI) were used to estimate patient severity. This study was approved by the Institutional Review Board (IRB) committee of Kyungpook National University Hospital (2021-07-068) and conducted in accordance with the principles of the 2013 Declaration of Helsinki.

Study outcomes

The primary outcome of this study was in-hospital mortality. The in-hospital morality was also compared in a subgroup analysis. The secondary outcomes were 30-day and 90-day mortality rates.

CRRT protocol

In our hospital, CRRT is performed when azotemia, volume overload, electrolyte imbalance, metabolic abnormality, oliguria, and other indications occur, as deemed necessary by the responsible nephrologists. Details of the CRRT protocol at our hospital have been described previously (15).

Statistical analysis

Continuous variables are expressed as mean ± standard deviation or median (interquartile range), while categorical variables are expressed as numbers (percentages). Restricted cubic spline regression model was used to explore the association between PLR as a continuous variable and in-hospital mortality. Since there was a non-linear association between PLR and in-hospital mortality (Fig. 1), subjects were divided into quintiles according to their PLR. Analysis of variance was performed to evaluate the differences between baseline characteristics and in-hospital information by quintiles. Cumulative survival according to PLR quintiles was analyzed using the Kaplan–Meier method and compared using the log-rank test. Multivariable Cox regression analysis was used to adjust for confounding variables. We selected age, sex, and variables with P < 0.10 in univariable analysis as adjustment factors. Hazard ratios (HRs) and 95% confidence intervals (CIs) were measured from the Cox proportional hazards regression model. Subgroup analyses were performed to assess differences according to the baseline characteristics. A P < 0.05 indicates statistical significance. Statistical analyses were performed using SAS for Windows, version 9.4 (SAS Institute Inc., Cary, NC, USA) and R (R Foundation for Statistical Computing, Vienna, Austria; www.r-project.org).

Results

Abbreviations: PLR platelet-to-lymphocyte ratio; ICU intensive care unit; BMI body mass index; CCI Charlson Comorbidity Index; AKI acute kidney injury; SOFA Sequential Organ Failure Assessment; APACHE II Acute Physiology and Chronic Health Evaluation II; WBC white blood cell; BUN blood urea nitrogen. 

In-hospital mortality outcomes

Among patients treated using CRRT, 651 (62.4%) died during the follow-up period. The mean length of hospital stay was 26.1 days (range, 5–32 days). Patients were admitted to the ICU for an average of 12.5 days and received CRRT treatment for approximately 4.3 days. Overall, PLR (the outcomes of this study) as a continuous variable, showed a U-shaped relationship in the cubic spline regression model (Fig. 1). In-hospital mortality and other in-hospital information according to PLR quintiles are presented in Table 2. Briefly, we observed significantly higher in-hospital mortality rates in the first [157 (75.5%)] and fifth [148 (70.8%)] quintile groups than in the third quintile group [93 (44.5%)], which had the lowest mortality rate. Furthermore, the 30-day and 90-day mortality rates showed a significant increase at both ends of the quintiles (Table 2). The ratio of patients who received mechanical ventilation and used vasopressors differed significantly by quintile; with the highest and lowest rates in the first and fifth quintiles, respectively (both P < 0.05).

Table 2. In-hospital information of PLR quintile groups

Data are presented as mean ± standard deviation or number (%)

Abbreviation: CRRT continuous renal replacement therapy; ICU intensive care unit

Correlation between PLR ratio and mortality

Kaplan-Meier curves showed a significant difference in cumulative survival according to PLR quintiles (Fig. 2). The first and fifth quintiles had the highest mortality rates, whereas the third quintile had the lowest mortality rate. Similar differences were observed in the 30-day and 90-day mortality rates (all P < 0.05; Fig. 2). In model 4, after adjusting for various factors, including age, sex, comorbidities, and severity indicators, compared with the third quintile of PLR (reference group), the lowest (adjusted HR [aHR] 1.94, 95% CI 1.44–2.62, P < 0.001) and highest (aHR 1.60, 95% CI 1.18–2.18; P = 0.002) quintiles had significantly greater in-hospital mortality (Table 3). Figure 3 shows the model 4’s aHRs of the 30-day (quintile 1: aHR 1.93, 95% CI 1.43–2.61, P < 0.001; quintile 5: aHR 1.63, 95% CI 1.20–2.22, P = 0.002), 90-day (quintile 1: aHR 1.97, 95% CI 1.47–2.65, P < 0.001; quintile 5: aHR 1.70, 95% CI 1.26–2.30, P < 0.001), and in-hospital mortality, showing U-shaped aHRs across the PLR quintiles. Supplementary Table 1 presents the detailed results of the Cox regression analysis for 30-day and 90-day mortality across the PLR quintiles (see Additional file 1).

Table 3. Cox regression analyses for in-hospital mortality in PLR quintile groups

Model 1: unadjusted

Model 2: adjusted for age, sex, and body weight

Model 3: adjusted for age, sex, body weight, CCI, hypertension, and malignancy.

Model 4: adjusted for age, sex, body weight, CCI, hypertension, malignancy, SOFA score, APACHE II score, mechanical ventilator use, and vasopressor use.

Abbreviation: PLR platelet-to-lymphocyte ratio; HR hazard ratio; aHR adjusted hazard ratio; CI confidence interval; CCI Charlson Comorbidity Index; SOFA Sequential Organ Failure Assessment; APACHE II Acute Physiology and Chronic Health Evaluation II.

Subgroup analysis

We divided the patients into subgroups according to age, sex, body mass index, comorbidities (hypertension and diabetes), SOFA and APACHE II scores. The first and fifth quintiles showed significant associations with increased in-hospital mortality in most subgroups including those with older age, female sex, hypertension, diabetes, and higher SOFA score (Table 4).

Table 4. Subgroup analyses for in-hospital mortality in PLR quintile groups

^aP <0.05; ^bP <0.01; ^cP <0.001.

The statistical values are based on the multivariable Cox regression model 4 except for the variables corresponding to each subgroup.

Abbreviations: PLR platelet-to-lymphocyte ratio; aHR adjusted hazard ratio; CI confidence interval; BMI body mass index; DM diabetes mellitus; SOFA Sequential Organ Failure Assessment; APACHE II Acute Physiology and Chronic Health Evaluation II.

Discussion

The current study evaluated PLR as a prognostic factor by investigating the mortality rate according to PLR quintiles in critically ill patients with AKI who underwent CRRT. In-hospital mortality was lowest in the third quintile of PLR and significantly higher in the first and fifth quintiles. We also observed a U-shaped correlation between in-hospital mortality and PLR quintiles, with similar results for 30- and 90-day mortality patterns along the PLR quintiles. This is the first study to demonstrate PLR as a predictor of mortality in critically ill patients who underwent CRRT.

Zheng et al. demonstrated the predictive value of PLR on mortality in critically ill patients with mild-to-moderate AKI (16). They reported an increased risk of 90-day mortality in the lower and higher PLR groups compared with the reference median PLR group, and the results were similar when patients were divided into quintiles of PLR (16). The patients in our study had a much higher SOFA score than those in the previous study, and all had severe AKI that required CRRT, which indicated high severity. Nevertheless, PLR was an independent predictor of mortality, and both low and high PLR quintiles were associated with poor prognosis. Therefore, PLR can be an effective predictor of mortality in critically ill patients with AKI irrespective of the degree of AKI.

The value of PLR as a prognostic marker has been demonstrated in several studies. As PLR is considered a systemic inflammatory indicator, previous studies have mainly focused on cancer, autoimmune disease, and cardiovascular disease (17-23). In addition, PLR contributes to predicting prognosis in acute inflammatory episodes because PLR increases along with other inflammatory indicators, such as C-reactive protein (CRP) and procalcitonin, and predicts patient mortality in sepsis (24). Recent studies have reported that PLR is independently associated with all-cause mortality in patients with end-stage kidney disease (ESKD) on either hemodialysis or peritoneal dialysis (25, 26). Patients with ESKD are continuously exposed to chronic inflammation, and PLR positively correlates with inflammatory markers such as CRP. Therefore, a high PLR might indicate an increased inflammatory state and could be a predictor of mortality in patients with ESKD. In the present study, sepsis was the major etiology of AKI in the fifth quintile group. Despite the relatively low severity of organ failure, the high mortality rate in the fifth quintile could be explained by the association between increased PLR and severe inflammation.

In addition, the high mortality in the highest PLR quintile group may also be associated with the patients’ baseline characteristics. The highest quintile group tended to be older, have lower body weight and albumin levels, and have more comorbidities with malignancy. Frailty could not be assessed in the present study because of the severity of illness; however, the higher PLR group seemed to have high frailty considering their age and nutritional parameters. Maintenance hemodialysis patients show a positive correlation between frailty and PLR, with increased mortality in the frailty group (29). The high PLR might be associated with these different baseline characteristics, presumed to be present before hospitalization, and may explain the increased mortality in the fifth quintile regardless of the severity of illness. Patients with cancer also show higher PLR than the healthy population, and increased PLR is a well-known predictive marker associated with poor patient outcomes (17-20, 30, 31).

Interestingly, both high and low PLR were associated with poor prognosis in our study. The relationship between a low PLR and poor prognosis is not well understood; however, a low PLR was a consistent predictor of poor prognosis in our study after adjusting for various factors. Although it was difficult to clarify the causal relationship in this study, we suggest an interpretation based on thrombocytopenia, because a low PLR results from low platelet counts. Thrombocytopenia is a coagulation disorder frequently encountered in patients admitted to the ICU (32). Common causes of thrombocytopenia in the ICU population include sepsis, disseminated intravascular coagulation, and major trauma (33). Unsurprisingly, a low platelet count reflects the severity of disease and worsens outcomes in patients with AKI (34-36). The first quintile group had the highest SOFA and APACHE II scores among the quintiles. Hence, the higher mortality in the low PLR group might be associated with the highest severity of illness.

Although the predictive role of the PLR in various diseases has been demonstrated, the underlying mechanism remains unknown. Recent studies have focused on the bidirectional relationship between AKI and inflammation (37, 38). Noninfectious causes can promote inflammation during AKI (39). Conversely, AKI can also affect the immune system by interfering with cytokine clearance and causing immune cell dysfunction (37, 40). Various immune cells and mediators are involved in AKI pathophysiology. Platelets and lymphocytes, which are components of the PLR index, may play important roles in this pathophysiological mechanism. First, platelets play an important role in hemostasis and inflammation. Once endothelial cell damage occurs, platelets are activated, releasing various cytokines and chemokines. In experimental studies, markers appearing in activated platelets, such as P-selectin, thromboxane A2, CC-chemokine ligand 5, and platelet factor 4, have been reported in the AKI model (41). Second, lymphocytes are components of adaptive immunity while T cells are emerging mediators involved in the development and recovery of AKI (38, 42, 43). Further studies are required to determine the specific roles of platelets and lymphocytes in AKI.

We demonstrated that the PLR index is an easily measurable and cost-effective marker for predicting mortality in patients with severe AKI who underwent CRRT. However, some limitations of our study must be considered. First, there may have been some bias due to the retrospective nature of this study. However, we evaluated the association of PLR by adjusting for various variables in various models to minimize the effects of possible confounding factors. Second, we obtained PLR values at the time of initiation of CRRT, therefore we could not assess the impact of serial changes of PLR in mortality. Third, the enrolled patients showed clinical heterogeneity, including the underlying disease or cause of AKI. Therefore, the number of patients was relatively small to contemplate variability in patient characteristics. Further large-scale, prospective, and longitudinal studies are required to validate the results of this study.

Conclusions

In summary, this is the first study to provide a prognostic analysis according to PLR in patients with severe AKI who underwent CRRT in the ICU. We confirm a U-shaped relationship between PLR and mortality, underlining the need for special attention in these high-risk groups. Further studies are needed to validate the PLR index as a predictor of mortality and understand the mechanisms of the immune system involved.

Abbreviations

aHR, adjusted hazard ratio; AKI, acute kidney injury; APACHE II, Acute Physiology and Chronic Health Evaluation II; BUN, blood nitrogen urea; CCI, Charlson Comorbidity Index; CI, confidence interval; CRP, C-reactive protein; CRRT, continuous renal replacement therapy; ESKD, end-stage kidney disease; HR, hazard ratio; ICU, intensive care unit; IRB, institutional review board; PLR, platelet-to-lymphocyte ratio; SOFA, Sequential Organ Failure Assessment

Declarations

Ethics approval and consent to participate

The Institutional Review Board (IRB) of Kyungpook National University Hospital approved the study (2021-07-068). The requirement for informed consent was waived by the IRB because all patient information was anonymized.

Consent for publication

Not applicable.

Availability of data and materials

The datasets used and analyzed during the current study are available from the corresponding authors upon reasonable request.

Competing interests

The authors declare that they have no competing interests.

Funding

This research was supported by a grant from the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI), funded by the Ministry of Health & Welfare, Republic of Korea (HI15C0001), and by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (2021R1I1A3059702 and 2021R1I1A3047973).

Authors’ contributions

YHJ analyzed and interpreted the data and drafted the manuscript. YJ performed the statistical analyses and created the figures and tables. HJ collected and analyzed the data and reviewed the manuscript. JC collected and analyzed the data and reviewed the manuscript. SP interpreted data and reviewed the manuscript. CK interpreted data and reviewed the manuscript. YK analyzed and interpreted the data and reviewed the manuscript. JC designed and supervised the study, analyzed and interpreted the data, obtained funding, and revised the manuscript. JL designed and conducted the study; collected, analyzed, and interpreted the data; and drafted the manuscript. All authors have read and approved the final manuscript.

Acknowledgements

Not applicable.

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