Abstract
Background
The lactate dehydrogenase-to-albumin ratio (LAR), a novel marker reflecting systemic inflammation and nutritional status, was investigated for its association with coronary artery lesions (CALs) in Kawasaki disease (KD).
Methods
A total of 231 pediatric patients with KD were stratified into the CAL group (n=35) and the non-CAL group (n=196). The CAL was defined based on the adjusted Z-score ≥2.0 of the coronary artery inner diameter according to body surface area. Demographic data and pre-treatment laboratory parameters were collected. Univariate analysis was used to screen for potential predictive factors, and multivariate logistic regression was used to analyze the influencing factors of KD complicated with CAL. The predictive performance was evaluated using the receiver operating characteristic (ROC) curve, and the area under the curve (AUC) was calculated.
Results
Univariate analysis revealed that the CAL group exhibited younger age, and significantly elevated levels of LAR and lactate dehydrogenase and higher proportion of incomplete KD compared to the non-CAL group (all P<0.05). Multivariate analysis confirmed LAR [odds ratio (OR) =1.152] and incomplete KD (OR =4.268) were independent predictive factors of CAL in KD. In the subgroup analysis of complete KD, LAR was remained significantly associated with CAL (P<0.05). ROC curve analysis identified the combined AUC of LAR and incomplete KD was 0.719 [95% confidence interval (CI): 0.629–0.810] and an optimal LAR cutoff of 6.97 (AUC =0.671, sensitivity =80.00%, specificity =53.10%). For complete KD, the optimal LAR cutoff for predicting CAL was 7.00, with an AUC of 0.662 (95% CI: 0.557–0.768).
Conclusions
LAR was an independent influencing factor for KD complicated with CAL. LAR could be utilized as an auxiliary diagnostic biomarker for CAL in KD, particularly in complete KD cases, offering a reference for precise KD management.
Keywords: Kawasaki disease (KD), coronary artery lesions (CALs), lactate dehydrogenase-to-albumin ratio (LAR), predictive factors
Highlight box.
Key findings
• Lactate dehydrogenase-to-albumin ratio (LAR) might serve as an auxiliary diagnostic biomarker for coronary artery lesions (CALs) in Kawasaki disease (KD).
What is known and what is new?
• Transthoracic echocardiography demonstrates high sensitivity and specificity in detecting proximal coronary artery abnormalities and remains the preferred method for diagnosing CAL. However, potential predictive factors for early diagnosis of CAL are currently lacking.
• This is the first study to explore the relationship between LAR and CAL among KD cases. LAR is easily obtainable and can assist in the early diagnosis of patients with potential CAL in KD.
What is the implication, and what should change now?
• CAL is the most severe complication of KD. Early prediction is helpful for timely treatment and improving prognosis.
Introduction
Kawasaki disease (KD), an acute systemic vasculitis of unknown etiology primarily affecting small and medium-sized blood vessels, predominantly occurs in children under the age of 5 years. While KD is typically self-limiting, it remains the leading cause of acquired heart disease in children across developed countries (1). Epidemiological studies have consistently shown a higher prevalence of KD in East Asia, particularly in regions surrounding Japan (2). In China, the incidence of KD has been steadily increasing over the past two decades without signs of stabilization (3-5), underscoring its emergence as a significant pediatric public health concern.
Coronary artery lesions (CALs), including coronary artery dilation and aneurysms, represent the most significant complications of KD. Long-term prognosis is closely linked to the extent of initial and ongoing coronary involvement. Without treatment, approximately 25% of patients develop CAL, whereas timely intervention with intravenous immunoglobulin (IVIG) and aspirin reduces this risk to approximately 4% (6). Transthoracic echocardiography has high sensitivity and specificity in detecting abnormalities in the proximal part of the coronary arteries, and is currently the preferred method for diagnosing CAL. However, potential predictive factors for early diagnosis of CAL are currently lacking, highlighting the urgent need for reliable predictors of CAL progression.
The lactate dehydrogenase-to-albumin ratio (LAR), a novel biomarker reflecting systemic inflammation and nutritional status, has demonstrated prognostic value in various diseases, including cardiac (7), malignancies (8), and lower respiratory infections (9). However, its role in predicting outcomes in KD remains largely unexplored. This study investigates the association between LAR and CAL in KD by analyzing demographic characteristics, echocardiographic findings, and pretreatment laboratory data from KD patients (2018–2024), aiming to establish a predictive tool for optimizing clinical management. We present this article in accordance with the TRIPOD reporting checklist (available at https://tp.amegroups.com/article/view/10.21037/tp-2025-aw-704/rc).
Methods
Patients
This retrospective study included 231 KD patients treated at Anhui Medical University Second Affiliated Hospital from January 2018 to December 2024. All participants met the 2017 American Heart Association diagnostic criteria for KD, including both complete and incomplete cases (6). CAL were defined based on Z-scores ≥2.0 for the body surface area-adjusted internal diameters of the left main, left anterior descending, left circumflex, or right coronary arteries (6,10). Outcomes of CAL on admission and the development of new CAL following IVIG therapy in the acute stage of KD. The study population was divided into two groups: the CAL group (n=35) and the non-CAL group (n=196). All patients received standardized therapy: IVIG: 2 g/kg single-dose infusion, aspirin: 30–50 mg/kg/day during acute phase, reduced to 3–5 mg/kg/day post-fever resolution. Selection criteria: inclusion: first-time KD diagnosis meeting clinical criteria, no prior IVIG therapy, acute-phase presentation. Exclusion: incomplete clinical data, pre-admission IVIG administration, pre-existing cardiac conditions, autoimmune disorders.
Ethics consideration
This study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. Ethical approval for this study was granted by the Ethics Committee of Anhui Medical University (No. 81251060). This study was a retrospective analysis, and all personally identifiable information has been de-identified. Therefore, informed consent was waived.
Methodology and data collection
Demographic, echocardiographic, and pretreatment laboratory parameters were systematically recorded. Including age, gender, pre-admission febrile period, days of illness at initial treatment, initial body temperature on admission, Z-scores (Z-scores for the body surface area-adjusted internal diameters of the left main, left anterior descending, left circumflex, or right coronary arteries), alanine aminotransferase (ALT), aspartate aminotransferase (AST), alkaline phosphatase (ALP), gamma-glutamyl transferase (GGT), direct bilirubin (DBil), indirect bilirubin (IBil), albumin-to-globulin ratio (A/G ratio), uric acid (UA), creatinine (Cr), blood urea nitrogen (BUN), magnesium, creatine kinase (CK), creatine kinase-MB (CK-MB), lactate dehydrogenase (LDH), cystatin C (Cys-C), high-sensitivity C-reactive protein (hs-CRP), LAR, iron, mitochondrial aspartate aminotransferase (m-AST), alpha-hydroxybutyrate dehydrogenase (α-HBDH), procalcitonin (PCT), neutrophil count, lymphocyte count, eosinophil count, basophil count, monocyte count, neutrophil percentage, lymphocyte percentage, eosinophil percentage, basophil percentage, monocyte percentage, hemoglobin, platelet count (PLT), globulin, potassium, sodium, chloride, calcium, inorganic phosphate (IP), albumin, white blood cell count (WBC), red blood cell count (RBC), platelet-to-lymphocyte ratio (PLR), neutrophil-to-lymphocyte ratio (NLR). All laboratory analyses were performed by the hospital’s clinical pathology department.
Statistical analysis
Categorical data were presented as numbers (%), and between-group comparisons were conducted using the χ2 test. The normality of continuous variables was assessed using the One-Sample Kolmogorov-Smirnov test. Normally distributed continuous data were expressed as mean ± standard deviation and analyzed using the independent samples t-test. Non-normally distributed continuous data were reported as median (quartile 1–quartile 3) and analyzed using the Mann-Whitney U test. Variables with P<0.1 in univariate analysis were included in the multivariate logistic regression models. Receiver operating characteristic (ROC) curves were constructed, and the area under the curve (AUC) was calculated along with corresponding P values. The optimal cut-off values refer to LAR and incomplete KD, LAR, and LDH corresponding to the maximum Youden index (Youden index = sensitivity + specificity − 1). All statistical analyses were performed using SPSS version 22.0, and a two-tailed P value <0.05 was considered statistically significant.
Results
This study included 231 patients, with 35 (15.15%) diagnosed with CAL. Among these, 202 patients presented with complete KD and 29 with incomplete KD. In the CAL group, the median age was 16.00 (9.50–28.00) months, comprising 25 male cases (71.43%), and 11 cases (31.43%) of incomplete KD. In the non-CAL group, the median age was 22.00 (13.00–43.00) months, including 112 male cases (57.14%), and 18 cases (9.18%) of incomplete KD. The CAL group and the non-CAL group showed significant differences in age, LDH, LAR, and incomplete KD, as shown in Table 1. In the subgroup analysis of complete KD, significant differences were observed between the CAL group and the non-CAL group in levels of GGT and LAR. However, in the incomplete KD subgroup, no significant differences were detected between the CAL and non-CAL groups (Table 2).
Table 1. Comparison of demographic data and laboratory indicators between the CAL and the non-CAL groups in KD.
| Variable | CAL (n=35) | Non-CAL (n=196) | Z/t/χ2 | P |
|---|---|---|---|---|
| Age (months) | 16.00 (9.50–28.00) | 22.00 (13.00–43.00) | 2.086 | 0.04 |
| Pre-admission febrile period (days) | 5.00 (3.00–7.00) | 4.00 (3.00–5.75) | 1.038 | 0.30 |
| Days of illness at initial treatment (days) | 6.00 (5.00–8.00) | 6.00 (6.00–8.00) | 0.284 | 0.78 |
| Initial body temperature on admission (℃) | 39.55 (39.13–40.00) | 39.50 (39.00–40.00) | 0.792 | 0.43 |
| ALT (IU/L) | 50.00 (28.00–119.00) | 36.50 (22.25–77.75) | 1.218 | 0.22 |
| AST (IU/L) | 40.00 (31.00–60.00) | 38.00 (29.00–60.50) | 0.637 | 0.52 |
| ALP (IU/L) | 177.00 (139.00–237.00) | 191.00 (154.00–236.00) | 1.006 | 0.32 |
| GGT (IU/L) | 32.00 (21.00–91.00) | 24.00 (15.00–70.00) | 1.823 | 0.07 |
| DBil (µmol/L) | 2.00 (1.40–3.50) | 2.20 (1.50–3.20) | 0.294 | 0.77 |
| IBil (µmol/L) | 4.60 (3.00–7.70) | 4.70 (3.30–6.80) | 0.352 | 0.73 |
| A/G ratio | 1.30 (1.10–1.80) | 1.40 (1.20–1.70) | 0.381 | 0.70 |
| UA (µmol/L) | 175.00 (141.00–229.00) | 196.00 (161.00–243.25) | 1.505 | 0.13 |
| Cr (µmol/L) | 28.00 (19.00–33.00) | 27.00 (21.00–34.00) | 0.569 | 0.57 |
| BUN (mmol/L) | 2.63 (2.23–3.31) | 2.74 (2.26–3.55) | 0.763 | 0.45 |
| Magnesium (mmol/L) | 0.88 (0.82–0.92) | 0.86 (0.81–0.92) | 1.004 | 0.32 |
| CK (IU/L) | 55.00 (33.00–82.00) | 59.00 (40.25–90.75) | 1.333 | 0.18 |
| CK-MB (IU/L) | 23.00 (17.00–33.00) | 20.00 (15.00–27.00) | 1.641 | 0.10 |
| LDH (IU/L) | 294.00 (257.00–334.00) | 260.00 (222.25–305.75) | 2.345 | 0.02 |
| Cys-C (mg/L) | 0.84 (0.66–1.00) | 0.77 (0.60–0.94) | 1.507 | 0.13 |
| hs-CRP (mg/L) | 62.10 (28.20–91.40) | 55.49 (29.23–86.39) | 0.645 | 0.52 |
| LAR | 8.33 (7.01–9.21) | 6.90 (5.76–8.31) | 3.226 | 0.001 |
| Iron (µmol/L) | 2.20 (1.70–3.15) | 2.40 (1.85–3.40) | 1.075 | 0.28 |
| m-AST (IU/L) | 8.20 (4.35–10.78) | 7.00 (3.95–13.80) | 0.265 | 0.79 |
| α-HBDH (IU/L) | 261.50 (219.00–299.25) | 253.00 (215.50–292.00) | 0.414 | 0.68 |
| PCT (ng/mL) | 0.56 (0.16–1.37) | 0.39 (0.17–1.12) | 0.138 | 0.89 |
| Neutrophil count (×109/L) | 8.74 (6.55–10.97) | 8.35 (5.61–11.21) | 0.296 | 0.77 |
| Lymphocyte count (×109/L) | 3.94 (2.22–5.81) | 3.40 (2.15–5.08) | 1.345 | 0.18 |
| Eosinophil count (×109/L) | 0.29 (0.10–0.79) | 0.25 (0.10–0.48) | 1.065 | 0.29 |
| Basophil count (×109/L) | 0.02 (0.01–0.03) | 0.02 (0.01–0.03) | 0.740 | 0.46 |
| Monocyte count (×109/L) | 1.01 (0.61–1.50) | 0.88 (0.60–1.20) | 0.784 | 0.43 |
| Neutrophil percentage (%) | 56.90 (46.58–73.98) | 63.20 (50.40–73.90) | 0.842 | 0.40 |
| Eosinophil percentage (%) | 2.30 (0.65–4.80) | 2.00 (0.70–3.70) | 0.888 | 0.37 |
| Basophil percentage (%) | 0.10 (0.10–0.20) | 0.10 (0.10–0.20) | 1.564 | 0.12 |
| Monocyte percentage (%) | 7.30 (4.45–9.60) | 6.70 (4.93–8.88) | 0.370 | 0.71 |
| Hemoglobin (g/L) | 113.00 (109.00–118.00) | 113.00 (106.00–119.00) | 0.133 | 0.90 |
| PLT (×109/L) | 339.00 (264.00–455.00) | 340.00 (262.00–410.00) | 0.629 | 0.53 |
| Globulin (g/L) | 27.25±5.94 | 27.70±5.67 | 0.431 | 0.67 |
| Potassium (mmol/L) | 4.48±0.55 | 4.29±0.50 | 1.958 | 0.051 |
| Sodium (mmol/L) | 137.58±2.25 | 136.68±3.72 | 1.932 | 0.057 |
| Chloride (mmol/L) | 99.38±3.10 | 98.73±3.68 | 0.993 | 0.32 |
| Calcium (mmol/L) | 2.23±0.13 | 2.26±0.16 | 1.090 | 0.28 |
| IP (mmol/L) | 1.33±0.34 | 1.32±0.29 | 0.264 | 0.79 |
| Albumin (g/L) | 37.01±4.58 | 38.48±4.86 | 1.667 | 0.10 |
| WBC (×109/L) | 14.83±6.16 | 14.12±5.48 | 0.694 | 0.49 |
| Lymphocyte percentage (%) | 28.80±14.01 | 28.49±14.56 | 0.114 | 0.91 |
| RBC (×1012/L) | 4.29±0.37 | 4.23±0.42 | 0.816 | 0.42 |
| PLR | 89.39 (56.21–153.36) | 107.47 (69.71–146.25) | 1.073 | 0.28 |
| NLR | 1.90 (1.22–3.86) | 2.32 (1.35–4.34) | 0.847 | 0.40 |
| Gender | 2.511 | 0.11 | ||
| Male | 25 (71.43) | 112 (57.14) | ||
| Female | 10 (28.57) | 84 (42.86) | ||
| Incomplete KD | 13.386 | 0.001 | ||
| No | 24 (68.57) | 178 (90.82) | ||
| Yes | 11 (31.43) | 18 (9.18) |
Data were presented as median (quartile 1–quartile 3), mean ± standard deviation or n (%). A/G ratio, albumin-to-globulin ratio; α-HBDH, alpha-hydroxybutyrate dehydrogenase; ALP, alkaline phosphatase; ALT, alanine aminotransferase; AST, aspartate aminotransferase; BUN, blood urea nitrogen; CAL, coronary artery lesion; CK, creatine kinase; CK-MB, creatine kinase-MB; Cr, creatinine; Cys-C, cystatin C; DBil, direct bilirubin; GGT, gamma-glutamyl transferase; hs-CRP, high-sensitivity C-reactive protein; IBil, indirect bilirubin; IP, inorganic phosphate; KD, Kawasaki disease; LAR, lactate dehydrogenase-to-albumin ratio; LDH, lactate dehydrogenase; m-AST, mitochondrial aspartate aminotransferase; NLR, neutrophil-to-lymphocyte ratio; PCT, procalcitonin; PLR, platelet-to-lymphocyte ratio; PLT, platelet count; RBC, red blood cell count; UA, uric acid; WBC, white blood cell count.
Table 2. Comparison of demographic data and laboratory indicators between the CAL and the non-CAL groups in complete KD and incomplete KD.
| Variable | Complete KD | Incomplete KD | |||||||
|---|---|---|---|---|---|---|---|---|---|
| CAL (n=24) | Non-CAL (n=178) | Z/t/χ2 | P | CAL (n=11) | Non-CAL (n=18) | Z/t/χ2 | P | ||
| Age (months) | 18.00 (8.50–26.25) | 22.00 (13.00–43.25) | 1.734 | 0.08 | 13.00 (9.50–29.00) | 25.00 (11.38–36.50) | 0.900 | 0.39 | |
| Pre-admission febrile period (days) | 4.00 (2.25–5.00) | 4.00 (3.00–5.00) | 0.307 | 0.76 | 5.73±1.68 | 4.50±2.23 | 1.570 | 0.13 | |
| Days of illness at initial treatment (days) | 6.00 (5.00–7.00) | 6.00 (6.00–7.00) | 1.446 | 0.15 | 8.00 (6.00–9.00) | 8.00 (6.00–9.00) | 0.092 | 0.95 | |
| Initial body temperature on admission (℃) | 39.60 (39.20–40.00) | 39.50 (39.00–40.00) | 1.115 | 0.27 | 39.36±0.94 | 39.39±0.52 | 0.100 | 0.92 | |
| ALT (IU/L) | 58.00 (28.25–135.25) | 36.50 (22.75–80.75) | 1.603 | 0.11 | 42.00 (20.00–59.00) | 34.50 (21.00–48.25) | 0.382 | 0.71 | |
| AST (IU/L) | 44.50 (32.25–66.75) | 37.50 (29.75–59.50) | 0.934 | 0.35 | 38.00 (29.00–47.00) | 45.50 (20.50–70.50) | 0.225 | 0.84 | |
| ALP (IU/L) | 184.50 (145.50–274.75) | 192.00 (156.00–237.50) | 0.084 | 0.93 | 151.18±72.83 | 180.22±59.84 | 1.168 | 0.25 | |
| GGT (IU/L) | 64.00 (23.25–127.00) | 24.00 (15.00–68.50) | 2.287 | 0.02 | 26.00 (14.00–61.00) | 20.50 (13.75–108.00) | 0.045 | 0.98 | |
| DBil (µmol/L) | 2.40 (1.60–4.18) | 2.30 (1.50–3.20) | 0.775 | 0.44 | 1.50 (1.10–2.50) | 1.85 (1.28–2.70) | 0.968 | 0.34 | |
| IBil (µmol/L) | 5.45 (3.60–8.28) | 5.00 (3.45–6.95) | 1.141 | 0.25 | 2.90 (1.70–5.10) | 3.70 (2.95–5.18) | 1.327 | 0.19 | |
| A/G ratio | 1.30 (1.10–1.70) | 1.40 (1.20–1.70) | 0.587 | 0.56 | 1.49±0.52 | 1.52±0.56 | 0.149 | 0.88 | |
| UA (µmol/L) | 174.00 (142.00–226.75) | 194.50 (160.75–241.75) | 1.040 | 0.30 | 185.64±59.57 | 219.72±55.35 | 1.564 | 0.13 | |
| Cr (µmol/L) | 26.50 (19.00–34.00) | 27.50 (21.00–34.25) | 0.810 | 0.42 | 28.82±8.62 | 29.50±12.48 | 0.159 | 0.88 | |
| BUN (mmol/L) | 2.56 (2.04–3.07) | 2.74 (2.26–3.56) | 1.412 | 0.16 | 3.26±1.43 | 3.05±1.36 | 0.390 | 0.70 | |
| Magnesium (mmol/L) | 0.87 (0.82–0.92) | 0.86 (0.81–0.92) | 0.577 | 0.56 | 0.89±0.11 | 0.89±0.13 | 0.016 | 0.99 | |
| CK (IU/L) | 52.50 (30.75–80.75) | 59.00 (40.75–90.00) | 1.410 | 0.16 | 63.36±36.00 | 68.72±44.43 | 0.337 | 0.74 | |
| CK-MB (IU/L) | 22.00 (15.25–27.75) | 20.00 (15.00–27.00) | 0.521 | 0.60 | 32.55±18.22 | 22.94±11.92 | 1.721 | 0.10 | |
| LDH (IU/L) | 295.50 (257.25–321.50) | 260.00 (222.75–305.25) | 1.841 | 0.07 | 284.00 (257.00–350.00) | 254.00 (219.25–317.00) | 1.371 | 0.17 | |
| Cys-C (mg/L) | 0.88 (0.60–1.06) | 0.76 (0.60–0.94) | 1.438 | 0.15 | 0.82 (0.70–1.00) | 0.80 (0.53–0.96) | 0.542 | 0.61 | |
| hs-CRP (mg/L) | 63.90 (42.63–91.75) | 55.49 (30.95–86.75) | 1.109 | 0.27 | 41.30 (16.17–91.40) | 49.80 (17.20–85.83) | 0.090 | 0.95 | |
| LAR | 8.36 (7.01–9.12) | 6.91 (5.78–8.51) | 2.582 | 0.01 | 7.73 (6.99–9.21) | 6.72 (5.49–7.72) | 1.888 | 0.06 | |
| Iron (µmol/L) | 2.20 (1.60–3.30) | 2.40 (1.80–3.30) | 0.647 | 0.52 | 2.10 (1.70–2.95) | 2.70 (2.00–7.25) | 1.608 | 0.11 | |
| m-AST (IU/L) | 7.70 (4.40–13.40) | 7.10 (4.00–13.80) | 0.294 | 0.77 | 8.40 (4.20–10.30) | 6.35 (2.60–14.43) | 0.270 | 0.81 | |
| α-HBDH (IU/L) | 247.00 (208.00–293.00) | 259.00 (216.00–292.00) | 0.424 | 0.67 | 266.00 (240.00–324.00) | 225.50 (206.00–285.75) | 1.618 | 0.11 | |
| PCT (ng/mL) | 0.57 (0.21–1.28) | 0.41 (0.17–1.22) | 0.481 | 0.63 | 0.16 (0.08–2.06) | 0.26 (0.15–0.73) | 0.360 | 0.74 | |
| Neutrophil count (×109/L) | 8.28 (5.54–11.04) | 8.36 (5.65–11.56) | 0.013 | 0.99 | 8.76±1.33 | 7.39±3.28 | 1.558 | 0.13 | |
| Lymphocyte count(×109/L) | 3.91 (2.00–5.14) | 3.39 (2.16–5.09) | 0.592 | 0.55 | 5.55±3.54 | 3.83±1.98 | 1.662 | 0.11 | |
| Eosinophil count (×109/L) | 0.29 (0.05–0.57) | 0.23 (0.10–0.48) | 0.468 | 0.64 | 0.54 (0.14–1.14) | 0.31 (0.19–0.69) | 0.301 | 0.79 | |
| Basophil count (×109/L) | 0.01 (0.01–0.02) | 0.02 (0.01–0.03) | 1.448 | 0.15 | 0.02 (0.02–0.04) | 0.02 (0.01–0.04) | 0.615 | 0.57 | |
| Monocyte count (×109/L) | 0.90 (0.59–1.47) | 0.87 (0.60–1.15) | 0.331 | 0.74 | 1.15 (0.76–1.55) | 1.20 (0.57–1.55) | 0.100 | 0.94 | |
| Neutrophil percentage (%) | 57.90 (46.33–75.38) | 63.40 (50.83–74.60) | 0.300 | 0.76 | 52.40±20.06 | 56.08±16.70 | 0.514 | 0.61 | |
| Lymphocyte percentage (%) | 27.95±15.39 | 28.24±14.68 | 0.088 | 0.93 | 30.83±10.41 | 31.07±13.37 | 0.049 | 0.96 | |
| Eosinophil percentage (%) | 2.00 (0.50–4.80) | 1.80 (0.60–3.70) | 0.464 | 0.64 | 3.15 (1.38–5.55) | 2.40 (1.70–4.80) | 0.050 | 0.98 | |
| Basophil percentage (%) | 0.10 (0.10–0.20) | 0.10 (0.10–0.20) | 1.739 | 0.08 | 0.15 (0.10–0.20) | 0.20 (0.10–0.30) | 0.445 | 0.68 | |
| Monocyte percentage (%) | 5.50 (4.20–9.70) | 6.40 (4.90–8.60) | 0.416 | 0.68 | 7.90 (6.53–10.98) | 8.80 (5.45–10.95) | 0.075 | 0.94 | |
| Hemoglobin (g/L) | 112.50 (109.00–115.75) | 113.00 (106.00–119.00) | 0.049 | 0.96 | 113.91±11.27 | 113.22±12.30 | 0.150 | 0.88 | |
| PLT (×109/L) | 327.00 (263.25–461.00) | 337.00 (258.00–408.00) | 0.467 | 0.64 | 378.18±168.54 | 372.39±115.02 | 0.110 | 0.91 | |
| Globulin (g/L) | 27.25±5.86 | 27.64±5.51 | 0.323 | 0.75 | 27.25±6.40 | 28.34±7.25 | 0.408 | 0.69 | |
| Potassium (mmol/L) | 4.44±0.57 | 4.29±0.51 | 1.372 | 0.17 | 4.57±0.52 | 4.35±0.43 | 1.200 | 0.24 | |
| Sodium (mmol/L) | 137.36±2.32 | 136.51±3.57 | 1.131 | 0.26 | 138.00 (137.10–139.00) | 137.05 (135.58-139.65) | 0.854 | 0.41 | |
| Chloride (mmol/L) | 99.10±2.89 | 98.73±3.75 | 0.468 | 0.64 | 100.00±3.57 | 98.72±2.99 | 1.038 | 0.31 | |
| Calcium (mmol/L) | 2.23±0.11 | 2.27±0.15 | 1.376 | 0.18 | 2.32 (2.08–2.37) | 2.26 (2.13–2.34) | 0.336 | 0.76 | |
| IP (mmol/L) | 1.29±0.33 | 1.32±0.28 | 0.362 | 0.72 | 1.51 (1.36–1.63) | 1.38 (1.07–1.52) | 1.259 | 0.22 | |
| Albumin (g/L) | 36.72±4.33 | 38.39±4.91 | 1.589 | 0.11 | 37.65±5.25 | 39.41±4.44 | 0.967 | 0.34 | |
| WBC (×109/L) | 14.48±6.30 | 14.24±5.57 | 0.194 | 0.85 | 15.58±6.07 | 12.84±4.40 | 1.408 | 0.17 | |
| RBC (×1012/L) | 4.26±0.35 | 4.23±0.42 | 0.360 | 0.72 | 4.37±0.44 | 4.26±0.33 | 0.777 | 0.44 | |
| PLR | 92.00 (64.37–155.77) | 108.73 (70.24–143.85) | 0.342 | 0.73 | 60.83 (48.06–134.39) | 101.43 (66.86–169.91) | 1.342 | 0.19 | |
| NLR | 1.97 (1.23–4.13) | 2.37 (1.38–4.57) | 0.566 | 0.57 | 1.72 (1.16–3.24) | 1.75 (1.15–3.26) | 0.096 | 0.94 | |
| Gender | 1.599 | 0.21 | 0.855 | 0.36 | |||||
| Male | 17 (70.83) | 102 (57.30) | 8 (72.73) | 10 (55.56) | |||||
| Female | 7 (29.17) | 76 (42.70) | 3 (27.27) | 8 (44.44) | |||||
Data were presented as median (quartile 1–quartile 3), mean ± standard deviation or n (%). A/G ratio, albumin-to-globulin ratio; α-HBDH, alpha-hydroxybutyrate dehydrogenase; ALP, alkaline phosphatase; ALT, alanine aminotransferase; AST, aspartate aminotransferase; BUN, blood urea nitrogen; CAL, coronary artery lesion; CK, creatine kinase; CK-MB, creatine kinase-MB; Cr, creatinine; Cys-C, cystatin C; DBil, direct bilirubin; GGT, gamma-glutamyl transferase; hs-CRP, high-sensitivity C-reactive protein; IBil, indirect bilirubin; IP, inorganic phosphate; KD, Kawasaki disease; LAR, lactate dehydrogenase-to-albumin ratio; LDH, lactate dehydrogenase; m-AST, mitochondrial aspartate aminotransferase; NLR, neutrophil-to-lymphocyte ratio; PCT, procalcitonin; PLR, platelet-to-lymphocyte ratio; PLT, platelet count; RBC, red blood cell count; UA, uric acid; WBC, white blood cell count.
Variables with a P<0.1 identified from the univariate analysis were incorporated into the multivariate logistic regression model (with CAL =1 and non-CAL =0, male =1 and female =0, complete KD =1 and incomplete KD =2). In overall data, the results demonstrated that LAR [odds ratio (OR) = 1.152; 95% confidence interval (CI): 1.026–1.294; P=0.02] and incomplete KD (OR =4.268; 95% CI: 1.737–10.490; P=0.002) were independent predictors of CAL. LAR and incomplete KD were still associated with CAL in KD cases after adjusting for age. When LAR was excluded from the analysis, LDH and incomplete KD emerged as independent predictors of CAL in both unadjusted and adjusted models. In the subgroup analysis of complete KD, LAR remained significantly associated with CAL in both unadjusted and adjusted models, as detailed in Table 3. The univariate analysis between complete and incomplete KD groups revealed significant differences in days of illness at initial treatment (Table 4).
Table 3. Multivariable analysis for independent predictive factors of CAL among KD cases.
| Variable | OR | 95% CI | P |
|---|---|---|---|
| Overall | |||
| Unadjusted | |||
| LAR | 1.152 | 1.026–1.294 | 0.02 |
| Incomplete KD | 4.268 | 1.737–10.490 | 0.002 |
| Adjusted model | |||
| LAR | 1.143 | 1.022–1.279 | 0.02 |
| Incomplete KD | 4.293 | 1.718–10.732 | 0.002 |
| Removed LAR | |||
| Unadjusted | |||
| LDH | 1.003 | 1.000–1.006 | 0.04 |
| Incomplete KD | 4.114 | 1.685–10.048 | 0.002 |
| Adjusted model | |||
| LDH | 1.003 | 1.000–1.006 | 0.047 |
| Incomplete KD | 4.153 | 1.673–10.308 | 0.002 |
| Complete KD | |||
| Unadjusted | |||
| LAR | 1.145 | 1.011–1.296 | 0.03 |
| Adjusted model | |||
| LAR | 1.140 | 1.010–1.286 | 0.03 |
CAL, coronary artery lesion; CI, confidence interval; KD, Kawasaki disease; LAR, lactate dehydrogenase-to-albumin ratio; LDH, lactate dehydrogenase; OR, odds ratio.
Table 4. Comparison of clinical features on admission between the complete KD and incomplete KD.
| Variable | Complete KD (n=202) | Incomplete KD (n=29) | Z/t/χ2 | P |
|---|---|---|---|---|
| Age (months) | 21.00 (12.00–40.50) | 22.00 (10.50–33.00) | 0.462 | 0.64 |
| Pre-admission febrile period (days) | 4.00 (3.00–5.00) | 5.00 (3.50–7.00) | 1.820 | 0.07 |
| Days of illness at initial treatment (days) | 6.00 (6.00–7.00) | 8.00 (6.00–9.00) | 3.927 | <0.001 |
| Initial body temperature on admission (℃) | 39.50 (39.00–40.00) | 39.40 (39.00–39.95) | 0.778 | 0.44 |
| Gender | 0.105 | 0.75 | ||
| Male | 119 (58.90) | 18 (62.10) | ||
| Female | 83 (41.10) | 11 (37.90) |
Data were presented as median (quartile 1–quartile 3) or n (%). KD, Kawasaki disease.
ROC analysis demonstrated that combined AUC of LAR and incomplete KD was 0.719 (95% CI: 0.629–0.810), with a sensitivity of 71.40% and specificity of 66.80%. The optimal LAR cutoff for predicting CAL was 6.97 (Youden index: 0.331), yielding an AUC of 0.671 (95% CI: 0.583–0.759), sensitivity of 80.00%, and specificity of 53.10%. The AUC of incomplete KD was 0.611 (95% CI: 0.500–0.722). For LDH, the optimal predictive cutoff was 256.00 IU/L (Youden index: 0.269), with an AUC of 0.624 (95% CI: 0.532–0.717), sensitivity of 80.00%, and specificity of 46.90%. For complete KD, the optimal LAR cutoff for predicting CAL was 7.00 (Youden index: 0.325), yielding an AUC of 0.662 (95% CI: 0.557–0.768), sensitivity of 79.20%, and specificity of 53.40%. Detailed results are presented in Table 5 and Figures 1,2.
Table 5. The predictive value of LAR and incomplete KD, LAR, incomplete KD, and LDH for CAL in KD cases.
| Variable | AUC | 95% CI | Sensitivity (%) | Specificity (%) | Cutoff | P | Youden index |
|---|---|---|---|---|---|---|---|
| Overall | |||||||
| LAR and incomplete KD | 0.719 | 0.629–0.810 | 71.40 | 66.80 | 0.12 | <0.001 | 0.383 |
| LAR | 0.671 | 0.583–0.759 | 80.00 | 53.10 | 6.97 | 0.001 | 0.331 |
| Incomplete KD | 0.611 | 0.500–0.722 | – | – | – | 0.04 | – |
| LDH | 0.624 | 0.532–0.717 | 80.00 | 46.90 | 256.00 IU/L | 0.02 | – |
| Complete KD | |||||||
| LAR | 0.662 | 0.557–0.768 | 79.20 | 53.40 | 7.00 | 0.01 | 0.325 |
| LDH | 0.615 | 0.506–0.726 | – | – | – | 0.07 | – |
AUC, area under the curve; CAL, coronary artery lesion; CI, confidence interval; KD, Kawasaki disease; LAR, lactate dehydrogenase-to-albumin ratio; LDH, lactate dehydrogenase.
Figure 1.
ROC analysis of the predictive effect of LAR and incomplete KD, LAR, incomplete KD, and LDH on CAL among KD cases. AUC, area under the curve; CAL, coronary artery lesion; KD, Kawasaki disease; LAR, lactate dehydrogenase-to-albumin ratio; LDH, lactate dehydrogenase; ROC, receiver operating characteristic.
Figure 2.
ROC analysis of the predictive effect of LAR and LDH on CAL among complete KD cases. AUC, area under the curve; CAL, coronary artery lesion; KD, Kawasaki disease; LAR, lactate dehydrogenase-to-albumin ratio; LDH, lactate dehydrogenase; ROC, receiver operating characteristic.
Discussion
This study revealed a CAL proportion of 15.15%, which was consistent with domestic recent research findings (13.88% and 14.7%) (11,12), but higher than the Shanghai 2013–2017 survey data (5). The discrepancy likely stemmed from differing CAL assessment methods: the prior studies utilized Z-scores (accounting for body size), whereas the 2013–2017 reports relied solely on two-dimensional echocardiography to measure internal cavity diameter, neglecting body size effects and potentially leading to missed diagnoses (5). Callinan et al. reported that IVIG treatment administered within 5 days of symptom onset reduced CAL incidence in children with KD (13). In this study, the median time from fever onset to medical consultation in the CAL group was 5 days, which likely exceeded the optimal IVIG treatment window. Consequently, enhancing public education on KD and improving parental awareness of early medical seeking were deemed necessary.
This study demonstrated that LAR and the proportion of incomplete KD in the CAL group were significantly higher than that in the non-CAL group. Multivariate Logistic regression revealed that LAR and incomplete KD were independent predictors of KD complicated with CAL, and the optimal cutoff value of LAR for predicting CAL in KD was 6.97, the AUC was 0.671 The combined AUC of LAR and incomplete KD was 0.719. In the subgroup analysis of complete KD, LAR was still an independent predictor of CAL. However, such relationship was not observed in incomplete KD cases, which may be attributed to smaller sample size, and further research is required to investigate this issue. To our knowledge, this is the first study to investigate the correlation between LAR and CAL among KD cases. LAR, as a new prognostic indicator for diseases, is easily obtainable, cost-effective, highly applicable, and readily implementable in clinical practice. An increase in LAR is associated with an increase in LDH or (and) a relative decrease in albumin, providing more comprehensive prognostic information than LDH or albumin alone (14). This study showed that LAR had a higher predictive value compared with LDH alone, and LAR could be used as a potential predictor of KD complicated with CAL, especially in complete KD.
Incomplete KD has been reported as a predictive factor for CAL in children with KD (15-17). Tsai et al. reported the OR for incomplete KD in predicting CAL in KD patients was 1.968 (95% CI: 1.064–3.639, P=0.031) (15). Additionally, another study reported the OR for complete KD in predicting CAL in KD patients was 0.226 (95% CI: 0.080–0.640, P=0.005) (16). These findings were consistent with the results of this research. Due to atypical symptoms on admission, clinical diagnosis of incomplete KD is frequently delayed. This study revealed that the median time to initial treatment in incomplete KD patients was 8 days, significantly longer than that in children with complete KD (6 days, P<0.001), aligning with prior research findings (17). Delayed treatment may serve as an important intermediary mechanism contributing to the elevated CAL risk in incomplete KD patients.
The data from this study also revealed that serum LDH levels were significantly higher in the CAL group compared to the non-CAL group. However, in overall data, LDH was not identified as an independent predictor, probably attributable to the collinearity between LAR and LDH. Given that LAR integrates both LDH and albumin in its calculation, this precludes their simultaneous inclusion in the multivariate model. LDH, a cytoplasmic enzyme widely distributed in tissues such as myocardium, red blood cells, and skeletal muscle, plays a pivotal role in the glycolytic pathway. Following ischemia-hypoxia-induced tissue injury, LDH is rapidly released into peripheral blood, serving as a biomarker for cellular damage (18). Additionally, during ischemia and hypoxia, LDH catalyzes the conversion of pyruvate to lactic acid (19), leading to a decrease in microenvironmental pH and affecting the outcome of cells (20). It is worth noting that LDH also plays a crucial role in inflammation by promoting the effector function of T cells (21). KD complicated with CAL may cause myocardial ischemia-hypoxia in patients, resulting in abnormally elevated LDH levels. A recent study was consistent with findings from ours (22). However, the study did not identify LDH as an independent predictor. Another study reported that there was no relationship between LDH and CAL in KD (23). It is noteworthy that a study presented opposite result, and there was no report on whether LDH was an independent predictor (24). The inconsistency of the results could be attributed to differences in CAL diagnostic standards and the period when CAL imaging data were obtained. Further research is required to investigate the relationship between LDH and CAL in KD.
Simultaneously, this study observed a downward trend in serum albumin levels in the CAL group, although this difference did not reach statistical significance (P=0.10). This phenomenon warrants further investigation. Albumin, the most critical plasma protein synthesized by the liver, maintains colloid osmotic pressure and possesses strong antioxidant capacity due to its disulfide bonds and free thiol groups (25). Experimental evidence confirms that albumin alleviates oxidative stress-induced endothelial cell damage by binding to substances such as nitric oxide and bilirubin (26). Moreover, as an important regulator of the immune microenvironment, reduced albumin levels may impair immune cell function (20). Despite the lack of significant differences in the current results, considering the long half-life of albumin (approximately 17 days) (27), changes in its levels may lag behind acute phase responses. Studies reported that albumin serves as an independent predictor for KD complicated with CAL, with OR for predicting CAL in KD of 0.926 (95% CI: 0.858–0.998, P=0.045), 0.886 (95% CI: 0.805–0.975, P=0.014), and 0.946 (95% CI: 0.919–0.973, P<0.001), respectively (23,28,29). These results suggest that LAR may hold some predictive value, as it is associated with changes in albumin levels. Further studies are needed to validate these findings.
While this study provided valuable insights into factors that may potentially predict CAL in KD, its findings should be interpreted in light of several limitations. First, in this study, LAR demonstrated moderate sensitivity (80%), but its relatively low specificity (53.1%) and an AUC of 0.671 suggest that it might miss some true positive CAL cases or generate false positives, thereby limiting its clinical utility as a standalone diagnostic tool. However, its moderate sensitivity indicates that it could still serve as an auxiliary biomarker for CAL in KD when used alongside other predictors. Second, the single-center design may introduce selection bias. This could limit the generalizability of results to broader populations. Additionally, the relatively small sample size may have reduced statistical power to detect. Finally, in this study, LAR only predicts CAL in the acute stage of KD, so it may not be applicable to other phases. Future multi-center studies with larger sample sizes are needed to overcome these limitations and to verify our research findings.
Conclusions
In summary, this study concluded that LAR was an independent influencing factor for KD complicated with CAL. LAR could be utilized as an auxiliary diagnostic biomarker for CAL in KD, especially in complete KD, offering a reference for precise KD management. Investigating CAL risk factors and early warning signs in KD enables timely intervention and better patient outcomes.
Supplementary
The article’s supplementary files as
Acknowledgments
None.
Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. This study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. Ethical approval for this study was granted by the Ethics Committee of Anhui Medical University (No. 81251060). This study was a retrospective analysis, and all personally identifiable information has been de-identified. Therefore, informed consent was waived.
Footnotes
Reporting Checklist: The authors have completed the TRIPOD reporting checklist. Available at https://tp.amegroups.com/article/view/10.21037/tp-2025-aw-704/rc
Funding: This study was supported by the University Research Fund of Anhui Medical University (No. 2022xkj017).
Conflicts of Interest: Both authors have completed the ICMJE uniform disclosure form (available at https://tp.amegroups.com/article/view/10.21037/tp-2025-aw-704/coif). The authors have no conflicts of interest to declare.
Data Sharing Statement
Available at https://tp.amegroups.com/article/view/10.21037/tp-2025-aw-704/dss
References
- 1.Jone PN, Tremoulet A, Choueiter N, et al. Update on Diagnosis and Management of Kawasaki Disease: A Scientific Statement From the American Heart Association. Circulation 2024;150:e481-500. 10.1161/CIR.0000000000001295 [DOI] [PubMed] [Google Scholar]
- 2.Xu L, Zhang J, Dong J, et al. A bibliometric analysis of Kawasaki disease from 1974 to 2022. Heliyon 2024;10:e27290. 10.1016/j.heliyon.2024.e27290 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Zhang X, Liang Y, Feng W, et al. Epidemiologic survey of Kawasaki disease in Inner Mongolia, China, between 2001 and 2013. Exp Ther Med 2016;12:1220-4. 10.3892/etm.2016.3393 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Chen JJ, Ma XJ, Liu F, et al. Epidemiologic Features of Kawasaki Disease in Shanghai From 2008 Through 2012. Pediatr Infect Dis J 2016;35:7-12. 10.1097/INF.0000000000000914 [DOI] [PubMed] [Google Scholar]
- 5.Xie LP, Yan WL, Huang M, et al. Epidemiologic Features of Kawasaki Disease in Shanghai From 2013 Through 2017. J Epidemiol 2020;30:429-35. 10.2188/jea.JE20190065 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.McCrindle BW, Rowley AH, Newburger JW, et al. Diagnosis, Treatment, and Long-Term Management of Kawasaki Disease: A Scientific Statement for Health Professionals From the American Heart Association. Circulation 2017;135:e927-99. 10.1161/CIR.0000000000000484 [DOI] [PubMed] [Google Scholar]
- 7.Baris O, Holat CM, Tosun ME, et al. Assessing the Predictive Impact of Preoperative Lactate Dehydrogenase to Albumin Ratio on Outcomes Following Coronary Artery Bypass Graft Surgery. J Clin Med 2025;14:554. 10.3390/jcm14020554 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Wang X, Ji X. Effect of Preoperative Serum Lactate Dehydrogenase-to-Albumin Ratio on the Survival of Oral Cancer: A Retrospective Study. J Inflamm Res 2024;17:5129-38. 10.2147/JIR.S472041 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Lee BK, Ryu S, Oh SK, et al. Lactate dehydrogenase to albumin ratio as a prognostic factor in lower respiratory tract infection patients. Am J Emerg Med 2022;52:54-8. 10.1016/j.ajem.2021.11.028 [DOI] [PubMed] [Google Scholar]
- 10.Kobayashi T, Fuse S, Sakamoto N, et al. A New Z Score Curve of the Coronary Arterial Internal Diameter Using the Lambda-Mu-Sigma Method in a Pediatric Population. J Am Soc Echocardiogr 2016;29:794-801.e29. 10.1016/j.echo.2016.03.017 [DOI] [PubMed] [Google Scholar]
- 11.Na W, Chen S, Xiao T, et al. Epidemiologic trends of Kawasaki Disease and the potential impact of COVID-19 pandemic in Shanghai from 2018 through 2022. Chin Med J (Engl) 2025. [Epub ahead of print]. doi: . 10.1097/CM9.0000000000003901 [DOI] [PubMed] [Google Scholar]
- 12.Yin H, Su R, Liu D, et al. Development of a predictive model for the progression of Kawasaki disease: a retrospective analysis of clinical and echocardiographic data. Eur J Pediatr 2025;184:355. 10.1007/s00431-025-06181-x [DOI] [PubMed] [Google Scholar]
- 13.Callinan LS, Tabnak F, Holman RC, et al. Kawasaki syndrome and factors associated with coronary artery abnormalities in California. Pediatr Infect Dis J 2012;31:894-8. 10.1097/INF.0b013e31825c4d7c [DOI] [PubMed] [Google Scholar]
- 14.Wu W, Miao L, Zhao L, et al. Prognostic value of lactate dehydrogenase, serum albumin and the lactate dehydrogenase/albumin ratio in patients with diffuse large B-cell lymphoma. Hematology 2024;29:2293514. 10.1080/16078454.2023.2293514 [DOI] [PubMed] [Google Scholar]
- 15.Tsai CM, Yu HR, Tang KS, et al. C-Reactive Protein to Albumin Ratio for Predicting Coronary Artery Lesions and Intravenous Immunoglobulin Resistance in Kawasaki Disease. Front Pediatr 2020;8:607631. 10.3389/fped.2020.607631 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Wang L, Zeng X, Chen B. Clinical manifestations and risk factors of coronary artery lesions in children with Kawasaki disease. Medicine (Baltimore) 2023;102:e34939. 10.1097/MD.0000000000034939 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Shi H, Qiu H, Jin Z, et al. Coronary artery lesion risk and mediating mechanism in children with complete and incomplete Kawasaki disease. J Investig Med 2019;67:950-6. 10.1136/jim-2018-000898 [DOI] [PubMed] [Google Scholar]
- 18.Ye L, Lu J, Yuan M, et al. Correlation between Lactate Dehydrogenase to Albumin Ratio and the Prognosis of Patients with Cardiac Arrest. Rev Cardiovasc Med 2024;25:65. 10.31083/j.rcm2502065 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Carpenter KL, Jalloh I, Gallagher CN, et al. (13)C-labelled microdialysis studies of cerebral metabolism in TBI patients. Eur J Pharm Sci 2014;57:87-97. 10.1016/j.ejps.2013.12.012 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Luo M, Wei H, Qiu M, et al. Prognostic value of the lactate dehydrogenase to albumin ratio in advanced non-small cell lung cancer patients treated with the first-line PD-1 checkpoint inhibitors combined with chemotherapy. Front Immunol 2025;16:1473962. 10.3389/fimmu.2025.1473962 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Certo M, Tsai CH, Pucino V, et al. Lactate modulation of immune responses in inflammatory versus tumour microenvironments. Nat Rev Immunol 2021;21:151-61. 10.1038/s41577-020-0406-2 [DOI] [PubMed] [Google Scholar]
- 22.Zhu G, Zhang P. Retrospective Analysis of Risk Factors Impacting the Severity of Coronary Artery Lesions in Kawasaki Disease. Br J Hosp Med (Lond) 2025;86:1-12. 10.12968/hmed.2025.0047 [DOI] [PubMed] [Google Scholar]
- 23.Yang X, Zou J, Nie H, et al. Identification of clinical risk factors for coronary artery lesions in children with Kawasaki disease: a retrospective cohort study. Cardiol Young 2024. [Epub ahead of print]. doi: . 10.1017/S1047951124000829 [DOI] [PubMed] [Google Scholar]
- 24.Li L, Wan Y, Li GA, et al. Predictive value of the combined evaluation of the neutrophil-to-lymphocyte ratio and lactate dehydrogenase level for coronary artery lesions in patients with acute Kawasaki disease. Ital J Pediatr 2025;52:1. 10.1186/s13052-025-02165-7 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.Manolis AA, Manolis TA, Melita H, et al. Low serum albumin: A neglected predictor in patients with cardiovascular disease. Eur J Intern Med 2022;102:24-39. 10.1016/j.ejim.2022.05.004 [DOI] [PubMed] [Google Scholar]
- 26.Kremer H, Baron-Menguy C, Tesse A, et al. Human serum albumin improves endothelial dysfunction and survival during experimental endotoxemia: concentration-dependent properties. Crit Care Med 2011;39:1414-22. 10.1097/CCM.0b013e318211ff6e [DOI] [PubMed] [Google Scholar]
- 27.Arques S. Human serum albumin in cardiovascular diseases. Eur J Intern Med 2018;52:8-12. 10.1016/j.ejim.2018.04.014 [DOI] [PubMed] [Google Scholar]
- 28.Xuan W, Yao Y, Wang Y, et al. A nomogram for predicting coronary artery lesions in patients with Kawasaki disease. Medicine (Baltimore) 2024;103:e40428. 10.1097/MD.0000000000040428 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.Hua W, Ma F, Wang Y, et al. A new scoring system to predict Kawasaki disease with coronary artery lesions. Clin Rheumatol 2019;38:1099-107. 10.1007/s10067-018-4393-7 [DOI] [PubMed] [Google Scholar]