Abstract
Background
The prognosis of acute respiratory distress syndrome (ARDS) varies with inflammatory responses. ARDS patients with a hyperinflammatory phenotype usually have worse alveolar epithelial injury and vascular endothelial injury than those carrying a hypoinflammatory phenotype. Activated neutrophils recruited and migrated in the lung tissue are responsible for stimulating the progression of ARDS. Interleukin-8 (IL-8), as an inflammatory factor, further aggravates lung damage in ARDS.
Methods
This was a retrospective study involving 135 ARDS children admitted in two pediatric hospitals in northwest China. They were either classified into mild, moderate and severe groups based on the oxygenation index (OI) or oxygenation saturation index (OSI) within 4-h invasive mechanical ventilation on admission, or the survival and non-survival groups based on the 28-day mortality. Demographic and clinical data were analyzed. Risk factors for the prognosis of PARDS were identified by logistic regression. The correlation of IL-8 level with the identified risk factors was analyzed. Prognostic potential of IL-8 was determined by plotting the receiver operating characteristic (ROC) curves.
Results
IL-8, RAGE, Ang-2, ICAM-1 and SP-D were independent risk factors for the mortality of PARDS. They were significantly higher in the non-survival group than the survival group, showing a potential in predicting mortality in PARDS, especially in the combination (P < 0.05). IL-8 was positively correlated with RAGE, Ang-2, ICAM-1 and SP-D in children with ARDS (P < 0.05).
Conclusion
IL-8 is overexpressed in children with ARDS, showing a prognostic potential particularly in combination with RAGE, Ang-2, ICAM-1 and SP-D in PARDS.
Keywords: acute respiratory distress syndrome, biomarkers, interleukin-8, pediatric, receptor for advanced glycation endproducts
1. Introduction
The acute respiratory distress syndrome (ARDS) is a life-threatening condition caused by pathological alterations in the alveolar epithelium and capillary epithelium. It is a heterogeneous syndrome mainly manifested as pulmonary edema, increased capillary permeability and refractory hypoxemia (1–3). Inflammatory factors exert a pivotal role in the lung diseases (4). The severity of inflammatory response predicts the prognosis of ARDS. Biomarkers associated with inflammation response have been proposed to aid in the diagnosis, risk stratification, and classification of ARDS (5). Inflammatory mediators (6, 7), damage-related molecular patterns (8), and endothelial (9–11) and epithelial injury markers are closely linked with adult ARDS (11–13).
Disease heterogeneity is a well concerned issue especially in pediatric intensive care. PARDS is a highly heterogenous condition, presenting varied manifestations with age, causes (pneumonia, sepsis, or trauma), pre-existing comorbid conditions, and baseline immunological state. Classified by the inflammatory subtype, ARDS can be either hyperinflammatory or hypoinflammatory, showing distinct manifestations and outcomes (4, 14). PARDS affects 3% of PICU patients, and accounts for 30% of mortality in those with severe hypoxaemia (15). Specifically, pediatric patients exhibiting high levels of inflammatory responses demonstrate a significantly elevated mortality rate of ARDS.
In the present study, we analyzed clinical data and inflammatory factors in children with ARDS, who were stratified based on the disease severity. Moreover, we specifically explored the role of IL-8 in the hyperinflammatory phenotype of PARDS, aiming to provide references for clinical management of PARDS.
2. Methods
2.1. Study design
This was a retrospective study involving 135 children (28 days to 18 years of age) diagnosed with ARDS in two specialized pediatric hospitals in northwest China, namely the Children's Hospital Affiliated to Xi'an Jiaotong University and Gansu Provincial Maternity and Child Health Hospital from February 2021 to November 2023. Retrospective data study can be exempted from the informed consent.
The study was approved by the Ethics Committee of the Affiliated Children's Hospital of Xi'an Jiaotong University (No.20240022) and Gansu Provincial Maternity and Child Health Hospital, Gansu Provincial Central Hospital (No.20230011). Written informed consent was provided by guardians. This study adhered to principles of the Declaration of Helsinki.
2.2. Participants
According to the Second Pediatric Acute Lung Injury Consensus Conference (PALICC-2) definition of ARDS, a diagnosis of ARDS was established as follows: (I) hypoxemia occurs within 7 days of a clinical insult; (II) new opacities (unilateral or bilateral) consistent with acute pulmonary parenchymal disease that are not explained by atelectasis or pleural effusion; (III) not fully explained by cardiac failure or fluid overload; (IV) hypoxemia essential for respiratory support by mechanical ventilation.
Respiratory support for non-invasively ventilated (NIV) participants was performed using a full-face mask or nasal mask in a continuous positive airway pressure or bilevel positive airway pressure ≥5 cm H2O, achieving the goal of the ratio of partial arterial pressure of oxygen (PaO2) to fractional concentration of inspired oxygen (FiO2) ≤ 300, or the ratio of blood oxygen saturation to FiO2 (SF ratio) ≤ 264. Mechanical ventilation in invasively ventilated participants achieved the following goal: oxygenation index (OI) ≥ 4 or oxygenation saturation index (OSI) ≥ 5.
A total of 158 children diagnosed with ARDS and admitted to the hospital were initially screened. Of these, 16 were excluded due to incomplete clinical data, and an additional 7 were excluded—4 who died within 24 h of admission and 3 whose legal guardians declined participation in the study. 135 eligible children with ARDS were classified into mild (4 ≤ OI < 8 or 5 ≤ OSI < 7.5), moderate (8 ≤ OI < 16 or 7.5 ≤ OSI <12.3) and severe groups (OI ≥ 16 or OSI≥12.3) based on the OI or OSI within 4-h invasive mechanical ventilation on admission. NIV patients were included in the mild group. Based on the 28-day mortality, participants were assigned into survival group (n = 102) and non-survival group (n = 33) (Figure 1).
Figure 1.
A flowchart of the study design.
2.3. Data collection
Biologically banked blood specimens of each participant were subjected to measurements of angiopoietin-2 (Ang-2), von Willebrand factor (vWF), D-dimer, blood cell analysis parameters, intracellular adhesion molecule-1 (ICAM-1), receptor for advanced glycation endproducts (RAGE), surfactant protein D (SP-D), and inflammatory factors in duplicates.
Demographic data, etiological factors, cause of ARDS, use of extracorporeal membrane oxygenation (ECMO), use of mechanical ventilation, the Lung Injury Score (LIS), complications, treatment process and 28-day mortality were retrospectively collected as well.
2.4. Statistical analysis
Statistical analysis was performed using SPSS 21.0. Continuous variables in a normal distribution were expressed as mean ± standard deviation (SD), and compared between groups by the independent samples t-test; otherwise, they were expressed as median and interquartile range (IQR), and compared by the Mann–Whitney U-test. Categorical variables were compared by the Chi-square test. Risk factors were identified by binary logistic regression, and correlation of two variables was determined by a linear regression. The receiver operating characteristic (ROC) curves were plotted to examine the diagnostic potential. P < 0.05 suggested a significant difference.
3. Results
3.1. Baseline characteristics of children with ARDS
Totally 135 children with ARDS were assigned into the mild group (n = 24), moderate group (n = 57) and severe group (n = 54). No significant differences were detected in the gender and age among the three groups (P > 0.05). There were no statistically significant differences among the three patient groups with respect to the distribution of etiological factors in infection-associated pneumonia [10[41,67] vs. 32[56.14] vs. 38[70.37]], non-pulmonary sepsis [6[25] vs. 10[17.54] vs. 7[12.95]], drowning [0 vs. 2 [3.51] vs. 3[5.56]] and pancreatitis [0 vs. 3[5.27] vs. 3[5.56]]. A significant difference was only detected in the proportion of aspiration pneumonia [8[33.33] vs. 10[17.54] vs. 3[5.56]] among the three groups (P < 0.05). The pathogen of viral infection in the mild group [3(12.5)] was lower than that in the moderate group [24 (42.11)] and severe group [20 (37.04)] (P < 0.05). However, no statistically significant difference was found between the moderate and severe groups.
Compared with those of mild group, we defected significantly higher LIS, proportions of pneumothorax, use of ECMO, mechanical ventilation, multiple organ disfunction syndrome (MODS) and adjuvant therapies (renal replacement, use of inhaled nitric oxide, neuromuscular blockade and use of corticosteroids), and 28-day mortality in moderate and severe groups (P < 0.05, Table 1).
Table 1.
General clinical characteristics of the three study groups (n = 135).
| Mild group (n = 24) |
Moderate group (n = 57) |
Severe group (n = 54) |
|
|---|---|---|---|
| Male (n, %) | 14 (58.33) | 27 (47.37) | 25 (46.30) |
| Age (n, %) | |||
| ≥28 days, <3 yrs | 5 (20.83) | 8 (14.04) | 7 (12.96) |
| ≥3 yrs, <6 yrs | 8 (33.33) | 16 (28.07) | 17 (31.49) |
| ≥6 yrs, < 18 yrs | 11 (45.84) | 33 (57.89) | 30 (55.55) |
| Etiology (n, %) | |||
| Infection-associated pneumonia | 10 (41.67) | 32 (56.14) | 38 (70.37) |
| Aspiration pneumonia | 8 (33.33) | 10 (17.54) | 3 (5.56)£& |
| Non-pulmonary sepsis | 6 (25) | 10 (17.54) | 7 (12.95) |
| Drowning | 0 | 2 (3.51) | 3 (5.56) |
| Pancreatitis | 0 | 3 (5.27) | 3 (5.56) |
| Pathogen (n, %) | |||
| Bacteria | 8 (33.33) | 11 (19.29) | 21 (38.88) |
| Virus | 3 (12.5) | 24 (42.11) | 20 (37.04)£ |
| Mycosis | 2 (8.33) | 7 (12.28) | 5 (9.26) |
| Others | 1 (4.17) | 5 (8.77) | 2 (3.7) |
| LIS (median, points) | 2 (1, 2.5) | 3 (2, 4.5) | 5 (3.5, 7.5)£& |
| Pneumothorax (n, %) | 1 (4.17) | 6 (10.53) | 18 (33.33)£& |
| Adjuvant therapies (n, %) | |||
| Renal replacement | 2 (8.33) | 9 (15.79) | 16 (26.93)£& |
| Use of Inhaled nitric oxide | 3 (12.5) | 17 (29.82) | 28 (51.85)£& |
| Neuromuscular blockade | 2 (8.33) | 25 (43.86) | 26 (48.15)£& |
| Use of corticosteroids | 3 (12.5) | 12 (21.05) | 26 (48.15)£& |
| Use of ECMO (n, %) | 0 | 8 (14.03) | 19 (35.19)£& |
| Mechanical ventilation (n, %) | 15 (62.5) | 57 (100) | 54 (100)£ |
| Blood cell analysis | |||
| Platelet count (×109/L) | 167 ± 56 | 121 ± 34 | 68 ± 32£& |
| Leukocyte count (×109/L) | 3.5 (2.32, 4.91) | 4.7 (2.55, 7.54) | 7.5 (3.35, 14.65) |
| Neutrophils (%) | 57 ± 28 | 45 ± 32 | 53 ± 21 |
| ymphocytes (%) | 33 ± 12 | 36 ± 19 | 34 ± 15 |
| Hb (g/dL) | 143 ± 37 | 123 ± 41 | 76 ± 29 |
| Inflammatory factors | |||
| CRP (mg/L) | 45 ± 23 | 67 ± 31 | 49 ± 22 |
| PCT (mg/L) | 4 ± 3 | 6 ± 5 | 6 ± 5 |
| IL-8 (pg/mL) | 21 ± 11 | 42 ± 8 | 74 ± 11£& |
| TNF-α (pg/mL) | 45 ± 12 | 41 ± 9 | 55 ± 6 |
| Lung injury biomark | |||
| D-dimer (×109/L) | 5.52 ± 2.67 | 9.56 ± 6.75 | 15.78 ± 7.98£& |
| vWF (mg/L) | 321 ± 119 | 564 ± 267 | 774 ± 116£& |
| RAGE (pg/L) | 1,354 ± 354 | 1,895 ± 123 | 2,235 ± 334£& |
| Ang-2 (pg/L) | 43 ± 12 | 66 ± 21 | 89 ± 13£& |
| ICAM-1 (ng/mL) | 798 ± 145 | 1,456 ± 321 | 1,973 ± 434£& |
| SP-D (pg/mL) | 11 ± 6 | 18 ± 4 | 27 ± 11£& |
| Outcomes | |||
| MODS (n, %) | 2 (8.33) | 13 (22.81) | 21 (38.89)£& |
| 28-day mortality | 2 (8.33) | 12 (21.05) | 19 (35.19)£& |
3.2. Clinical features of children with PARDS
There were significant differences in the D-dimer, vWF, platelet count, RAGE, Ang-2, ICAM-1 and SP-D levels among the three groups (P < 0.05, Table 1). Notably, IL-8 was an inflammatory marker showing a significant difference in children with ARDS stratified by the severity (P < 0.05).
3.3. Risk factors for the mortality of PARDS
The univariate logistic regression analysis revealed that vWF, IL-8, RAGE, Ang-2, ICAM-1 and SP-D were significantly associated with the mortality of PARDS (all OR > 1 and P < 0.05). The multivariate logistic regression analysis further demonstrated that IL-8, RAGE, Ang-2, ICAM-1 and SP-D were independent risk factors for the prognosis of PARDS (all OR > 1 and P < 0.05, Table 2). Compared with those of survival group, children with ARDS in the non-survival group presented significantly higher levels of ICAM-1 (1,438 ± 622 ng/mL vs. 2,126 ± 421 ng/mL, Figure 2A), RAGE (1,498 ± 322 pg/L vs. 2,131 ± 224 pg/L, Figure 2B), Ang-2 (8 ± 20 pg/L vs. 77 ± 21 pg/L, Figure 2C), SP-D (19 ± 6 pg/mL vs. 29 ± 10 pg/mL, Figure 2D), IL-8 (32 ± 16 pg/mL vs. 72 ± 21 pg/mL, P < 0.05; Figure 2E).
Table 2.
Logistic regression analysis of risk factors for the prognosis of PARDS.
| Univariate logistic | Multivariate logistic | |||
|---|---|---|---|---|
| Adjusted OR (95% CI) | P value | Adjusted OR (95% CI) | P value | |
| D-dimer (×109/L) | 2.67 (1.51, 3.56) | 0.011 | 1.62 (1.33, 1.79) | 0.053 |
| vWF (mg/L) | 2.34 (1.18, 3.46) | 0.000 | 1.64 (0.91, 2.71) | 0.056 |
| Blood cell analysis | ||||
| Platelet count (×109/L) | 0.54 (0.32, 0.98) | 0.052 | ||
| Leukocyte count (×109/L) | 1.03 (0.67, 1.29) | 0.318 | ||
| Neutrophils (%) | 0.98 (0.45, 1.05) | 0.334 | ||
| Lymphocytes (%) | 1.11 (0.76, 1.35) | 0.246 | ||
| Hb (×109/L) | 0.95 (0.76, 1.05) | 0.316 | ||
| Inflammatory factors | ||||
| CRP (mg/L) | 1.13 (0.98, 1.19) | 0.221 | ||
| PCT (mg/L) | 1.32 (0.87, 1.81) | 0.312 | ||
| IL-8 (pg/mL) | 2.78 (1.49, 4.12) | 0.000 | 2.12 (1.34, 3.11) | 0.023 |
| TNF-α (pg/mL) | 1.14 (0.96, 1.59) | 0.113 | ||
| RAGE (pg/L) | 2.69 (1.54, 3.95) | 0.000 | 1.55 (1.21, 2.34) | 0.036 |
| Ang-2 (pg/L) | 3.01 (1.94, 3.89) | 0.000 | 1.98 (1.49, 2.63) | 0.039 |
| ICAM-1 (ng/mL) | 2.67 (1.95, 3.03) | 0.002 | 1.35 (1.04, 2.01) | 0.044 |
| SP-D (pg/mL) | 2.11 (1.43, 3.01) | 0.014 | 1.49 (1.14, 2.43) | 0.041 |
vWF, von Willebrand factor; Hb, hemoglobin; CRP, C-reactive protein; PCT, procalcitonin; IL-8, interleukin 8; TNF-α, tumor necrosis factor alpha; RAGE, receptor for advanced glycation endproducts; Ang-2, angiopoietin-2; ICAM-1, intracellular adhesion molecule-1; SP-D, surfactant protein D.
Figure 2.
Distribution of risk factors for the prognosis of PARDS. Relative levels of ICAM-1 (A), RAGE (B), Ang-2 (C), SP-D (D) and IL-8 (E) in children with ARDS of the survival group and non-survival group.
3.4. Predictive potential in mortality of ICAM-2, RAGE, Ang-2 and SP-D in PARDS
ROC curves were plotted to illustrate the predictive potential of the above risk factors in discriminating PARDS. The area under the curve (AUC) of ICAM-1 (sensitivity = 75.45%, specificity = 73.34%, Figure 3A), RAGE (sensitivity = 81.21%, specificity = 76.15%, Figure 3B), Ang-2 (sensitivity = 76.54%, specificity = 75.45%, Figure 3C) and SP-D (sensitivity = 72.12%, specificity = 73.41%, Figure 3D) in distinguishing PARDS was 0.754, 0.778, 0.787 and 0.732, respectively. All of them presented acceptable performances in diagnosing PARDS. They demonstrated a strong predictive performance in assessing the mortality of PARDS.
Figure 3.
ROC curves of ICAM-1 (A), RAGE (B), Ang-2 (C), SP-D (D) and IL-8 in regressive prognosis (E) and prediction (F) in PARDS.
3.5. IL-8 is a prognostic factor for PARDS
A significantly higher level of IL-8 was detected in children with ARDS of the non-survival group than survival group. Notably, the AUC of IL-8 in discriminating PARDS was up to 0.898, with the cut-off value of 61.7 pg/mL, sensitivity of 88.12% and specificity of 83.45% (Figures 3E,F).
3.6. Correlation of IL-8 with the risk factors of mortality for PARDS
IL-8 levels in children with ARDS were positively correlated with ICAM-1 (R2 = 0.652, P = 0.035, Figure 4A), RAGE (R2 = 0.681, P = 0.029, Figure 4B), Ang-2 (R2 = 0.729, P = 0.022, Figure 4C) and SP-D (R2 = 0.824, P = 0.018, Figure 4D). Considering the importance of IL-8 and the identified risk factors in PARDS, we investigated the potential of their combination in predicting mortality of PARDS. The AUC of IL-8 combined with ICAM-1, RAGE, Ang-2 and SP-D in predicting mortality was as high as 0.967, with the sensitivity of 94.12% and specificity of 88.23% (Figure 5).
Figure 4.
Correlation of IL-8 with ICAM-1 (A), RAGE (B), Ang-2 (C) and SP-D (D) in children with ARDS.
Figure 5.
ROC curves of IL-8 combined with ICAM-1, RAGE, Ang-2 and SP-D in distinguishing PARDS.
4. Discussion
For more than half a century, ARDS has still been blamed for its relatively high morbidity and mortality rates, posing a great threat to the health of children and adults (15–17). The PALICC-2 guidelines offer pediatricians with more objective and effective efforts for diagnosing and treating ARDS; moreover, ongoing research is paying an increasing attention on the impact of ARDS phenotypes on patient prognosis. At present, inflammatory phenotypes have been highlighted for their significance in adults and children with lung diseases. The correlation of the hyperinflammatory state with the prognosis of ARDS has been growingly concerned, especially since after the global epidemic of the COVID-19 (18, 19).
In direct ARDS, acute damages to the alveolar epithelium and capillary endothelium results in the disruption of the endothelial barrier, fluid leakage and pulmonary oedema (20–22). During the pathological process of ARDS, pro-inflammatory factors are responsible for activating platelets and cytokines, and recruiting harmful substances within lung tissues (23). A hyperinflammatory state is typically characterized by severe and uncontrolled inflammatory response involving multiple organs and systems. In comparison to the hypoinflammatory state, the hyperinflammatory phenotype of ARDS usually links with more severe inflammatory responses and worse prognosis.
ICAM-1 is an established regulator of inflammation and vascular injury via mediating endothelial and epithelial barrier function. It is significantly correlated with the severity of pulmonary exudation, oxygenation dysfunction and 28-day mortality in adult ARDS (24–26). Ang-2 is an endogenous ligand for the tyrosine kinase receptor expressed on the surface of endothelial cells, acting as a trigger of increased permeability of endothelial cells (27). Serum Ang-2 is found significantly higher in patients with severe sepsis than those with a milder condition, which is also positively correlated with arterial hypoxemia. Bhandari et al. (28) detected higher Ang-2 levels in plasma and pulmonary edema fluid of ARDS patients than those with hydrostatic pulmonary edema. RAGE is a receptor for transmembrane immunoglobulins and expressed on the basal surface of alveolar type I (ATI) cells (29). It is usually overexpressed in ARDS models, presenting a correlation with the severity of hypoxia (12, 30–32). The damage to alveolar endothelium impairs a normal clearance of alveolar exudate materials, and their accumulation eventually induces pulmonary edema and increases alveolar surface tension (12, 33). SP-D level increases in response to alveolar cell damages. Overexpression of SP-D not only causes oxygenation dysfunction and ventilator-induced lung injury, but also increases the mortality (34–36). In the present study, RAGE, Ang-2, ICAM-1 and SP-D were independent risk factors for the mortality of PARDS, which were significantly higher in non-survived children with ARDS than those of survivors. Our data confirmed that alveolar damage worsened the prognosis of ARDS.
Previous data have confirmed that neutrophils are recruited, migrated, and activated in lung tissue, playing a pivotal role in lung injury. In this process, IL-8 plays a crucial role in transmitting inflammatory signals and activating inflammation, thereby further enhancing the recruitment of inflammatory cells to the affected tissue and exacerbating associated damage (37–39). Overexpression of IL-8 is found as a vital biomarker for predicting a poor prognosis in PARDS. Moreover, upregulated IL-8 exacerbates oxygenation impairment and prolongs the duration of ventilator therapy in severe PARDS (39). Overexpressed IL-8 is considered to cause a hyperinflammatory state, leading to the damages to alveolar epithelial and endothelial cells. Meanwhile, severe pulmonary inflammatory exudation is noted (37, 39–41).
Here, a significant difference was detected in IL-8 levels among children with mild, moderate and severe ARDS. Its level was significantly higher in non-survival group than the survival group. Moreover, IL-8 was positively correlated with RAGE, Ang-2, ICAM-1 and SP-D levels in PARDS. Compared with a single detection, a combination detection of IL-8 with RAGE, Ang-2, ICAM-1 and SP-D presented an extraordinary performance in predicting the mortality of PARDS. In the future, non-invasive measurements of IL-8, RAGE, Ang-2, ICAM-1 and SP-D are believed as a promising approach to identify high-risk population of PARDS.
Several limitations should be concerned. First of all, this was a retrospective study conducted in two pediatric hospitals in northwest China. Totally, 16 patients were excluded due to incomplete key data, which may have influenced the study outcomes. This limitation should be objectively acknowledged as a potential source of bias in the results. Our research needs to be further clinically validated in PARDS patients in other regions. Second, the potential mechanisms underlying the role of IL-8 in ARDS remain unclear. Third, clinical benefits of anti-IL-8 autoantibodies to PARDS are the future spotlight to be deeply mined. In future research on PARDS, prospective cohort studies should be implemented to rigorously address the heterogeneity associated with PARDS and to generate more robust scientific evidence for informing clinical diagnosis and treatment strategies.
5. Conclusion
IL-8 is overexpressed in children with ARDS, showing a prognostic potential particularly in combination with RAGE, Ang-2, ICAM-1 and SP-D in PARDS.
Funding Statement
The author(s) declared that financial support was received for this work and/or its publication. This research was funded by Shaanxi Provincial Natural Science Research Project (No.2021JM-560), Xi’an Basic Research Project (No.2023ms10), Xi’an Children’s Hospital Research Project (No.2022E05) and Gansu Province Major Science and Technology Special Projects (No.22ZD6FA034).
Footnotes
Edited by: Georgia Damoraki, National and Kapodistrian University of Athens, Greece
Reviewed by: Qalab Abbas, Aga Khan University, Pakistan
Konstantinos Louis, University General Hospital Attikon, Greece
Data availability statement
The original contributions presented in the study are included in the article/Supplementary Material, further inquiries can be directed to the corresponding author.
Ethics statement
The studies involving humans were approved by The study was approved by the Ethics Committee of the Affiliated Children's Hospital of Xi'an Jiaotong University (No.20240022) and Gansu Provincial Maternity and Child Health Hospital, Gansu Provincial Central Hospital (No.20230011). The studies were conducted in accordance with the local legislation and institutional requirements. Written informed consent for participation in this study was provided by the participants' legal guardians/next of kin.
Author contributions
YW: Writing – original draft, Conceptualization, Investigation, Methodology, Project administration, Supervision. WW: Conceptualization, Investigation, Methodology, Supervision, Writing – original draft. ZL: Conceptualization, Investigation, Methodology, Writing – review & editing. HW: Conceptualization, Investigation, Methodology, Writing – review & editing. HZ: Conceptualization, Investigation, Methodology, Writing – review & editing. YW: Conceptualization, Investigation, Methodology, Writing – review & editing. YZ: Formal analysis, Investigation, Methodology, Visualization, Writing – review & editing. ZG: Formal analysis, Investigation, Methodology, Visualization, Writing – review & editing. JL: Formal analysis, Methodology, Validation, Writing – review & editing. LM: Formal analysis, Methodology, Validation, Writing – review & editing. DY: Conceptualization, Formal analysis, Investigation, Writing – review & editing. TZ: Formal analysis, Investigation, Methodology, Writing – review & editing. YD: Formal analysis, Investigation, Methodology, Writing – review & editing. LL: Conceptualization, Supervision, Writing – review & editing.
Conflict of interest
The author(s) declared that this work was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
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References
- 1.Matthay MA, McAuley DF, Ware LB. Clinical trials in acute respiratory distress syndrome: challenges and opportunities. Lancet Respir Med. (2017) 5(6):524–34. 10.1016/S2213-2600(17)30188-1 [DOI] [PubMed] [Google Scholar]
- 2.Fan E, Brodie D, Slutsky AS. Acute respiratory distress syndrome: advances in diagnosis and treatment. JAMA. (2018) 319(7):698–710. 10.1001/jama.2017.21907 [DOI] [PubMed] [Google Scholar]
- 3.Wong HR, Marshall JC. Leveraging transcriptomics to disentangle sepsis heterogeneity. Am J Respir Crit Care Med. (2017) 196(3):258–60. 10.1164/rccm.201701-0143ED [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Calfee CS, Delucchi KL, Sinha P, Matthay MA, Hackett J, Shankar-Hari M, et al. Acute respiratory distress syndrome subphenotypes and differential response to simvastatin: secondary analysis of a randomised controlled trial. Lancet Respir Med. (2018) 6(9):691–8. 10.1016/S2213-2600(18)30177-2 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Terpstra ML, Aman J, van Nieuw Amerongen GP, Groeneveld AB. Plasma biomarkers for acute respiratory distress syndrome: a systematic review and meta-analysis*. Crit Care Med. (2014) 42(3):691–700. 10.1097/01.ccm.0000435669.60811.24 [DOI] [PubMed] [Google Scholar]
- 6.Ware LB. Prognostic determinants of acute respiratory distress syndrome in adults: impact on clinical trial design. Crit Care Med. (2005) 33(3 Suppl):S217–22. 10.1097/01.ccm.0000155788.39101.7e [DOI] [PubMed] [Google Scholar]
- 7.Nakos G, Kitsiouli E, Hatzidaki E, Koulouras V, Touqui L, Lekka ME. Phospholipases A2 and platelet-activating-factor acetylhydrolase in patients with acute respiratory distress syndrome. Crit Care Med. (2005) 33(4):772–9. 10.1097/01.ccm.0000158519.80090.74 [DOI] [PubMed] [Google Scholar]
- 8.Abrams ST, Zhang N, Manson J, Liu T, Dart C, Baluwa F, et al. Circulating histones are mediators of trauma-associated lung injury. Am J Respir Crit Care Med. (2013) 187(2):160–9. 10.1164/rccm.201206-1037OC [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Ong T, McClintock DE, Kallet RH, Ware LB, Matthay MA, Liu KD. Ratio of angiopoietin-2 to angiopoietin-1 as a predictor of mortality in acute lung injury patients. Crit Care Med. (2010) 38(9):1845–51. 10.1097/CCM.0b013e3181eaa5bf [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Calfee CS, Gallagher D, Abbott J, Thompson BT, Matthay MA, NHLBI ARDS Network. Plasma angiopoietin-2 in clinical acute lung injury: prognostic and pathogenetic significance. Crit Care Med. (2012) 40(6):1731–7. 10.1097/CCM.0b013e3182451c87 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Calfee CS, Janz DR, Bernard GR, May AK, Kangelaris KN, Matthay MA, Ware LB, et al. Distinct molecular phenotypes of direct vs indirect ARDS in single-center and multicenter studies. Chest. (2015) 147(6):1539–48. 10.1378/chest.14-2454 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Eisner MD, Parsons P, Matthay MA, Ware L, Greene K. Acute respiratory distress syndrome network. Plasma surfactant protein levels and clinical outcomes in patients with acute lung injury. Thorax. (2003) 58(11):983–8. 10.1136/thorax.58.11.983 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Finigan JH, Mishra R, Vasu VT, Silveira LJ, Nethery DE, Standiford TJ, et al. Bronchoalveolar lavage neuregulin-1 is elevated in acute lung injury and correlates with inflammation. Eur Respir J. (2013) 41(2):396–401. 10.1183/09031936.00004912 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Dahmer MK, Yang G, Zhang M, Quasney MW, Sapru A, Weeks HM, et al. Identification of phenotypes in paediatric patients with acute respiratory distress syndrome: a latent class analysis. Lancet Respir Med. (2022) 10(3):289–97. 10.1016/S2213-2600(21)00382-9 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Khemani RG, Smith L, Lopez-Fernandez YM, Kwok J, Morzov R, Klein MJ, et al. Paediatric acute respiratory distress syndrome incidence and epidemiology (PARDIE): an international, observational study. Lancet Respir Med. (2019) 7(2):115–28. 10.1016/S2213-2600(18)30344-8 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Ashbaugh DG, Bigelow DB, Petty TL, Levine BE. Acute respiratory distress in adults. Lancet. (1967) 2(7511):319–23. 10.1016/s0140-6736(67)90168-7 [DOI] [PubMed] [Google Scholar]
- 17.ARDS Definition Task Force, Ranieri VM, Rubenfeld GD, Thompson BT, Ferguson ND, Caldwell E, et al. Acute respiratory distress syndrome: the Berlin definition. JAMA. (2012) 307(23):2526–33. 10.1001/jama.2012.5669 [DOI] [PubMed] [Google Scholar]
- 18.Lamers MM, Haagmans BL. SARS-CoV-2 pathogenesis. Nat Rev Microbiol. (2022) 20(5):270–84. 10.1038/s41579-022-00713-0 [DOI] [PubMed] [Google Scholar]
- 19.Bonaventura A, Vecchié A, Dagna L, Martinod K, Dixon DL, Van Tassell BW, et al. Endothelial dysfunction and immunothrombosis as key pathogenic mechanisms in COVID-19. Nat Rev Immunol. (2021) 21(5):319–29. 10.1038/s41577-021-00536-9 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Thompson BT, Chambers RC, Liu KD. Acute respiratory distress syndrome. N Engl J Med. (2017) 377(6):562–72. 10.1056/NEJMra1608077 [DOI] [PubMed] [Google Scholar]
- 21.Bhattacharya J, Matthay MA. Regulation and repair of the alveolar-capillary barrier in acute lung injury. Annu Rev Physiol. (2013) 75:593–615. 10.1146/annurev-physiol-030212-183756 [DOI] [PubMed] [Google Scholar]
- 22.Matthay MA. Resolution of pulmonary edema. Thirty years of progress. Am J Respir Crit Care Med. (2014) 189(11):1301–8. 10.1164/rccm.201403-0535OE [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Matthay MA, Ware LB, Zimmerman GA. The acute respiratory distress syndrome. J Clin Invest. (2012) 122(8):2731–40. 10.1172/JCI60331 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Conner ER, Ware LB, Modin G, Matthay MA. Elevated pulmonary edema fluid concentrations of soluble intercellular adhesion molecule-1 in patients with acute lung injury: biological and clinical significance. Chest. (1999) 116(1 Suppl):83S–4. 10.1378/chest.116.suppl_1.83s [DOI] [PubMed] [Google Scholar]
- 25.Calfee CS, Eisner MD, Parsons PE, Thompson BT, Conner ER, Matthay MA, et al. Soluble intercellular adhesion molecule-1 and clinical outcomes in patients with acute lung injury. Intensive Care Med. (2009) 35(2):248–57. 10.1007/s00134-008-1235-0 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.Kaur S, Hussain S, Kolhe K, Kumar G, Tripathi DM, Tomar A, et al. Elevated plasma ICAM1 levels predict 28-day mortality in cirrhotic patients with COVID-19 or bacterial sepsis. JHEP Rep. (2021) 3(4):100303. 10.1016/j.jhepr.2021.100303 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27.Parikh SM, Mammoto T, Schultz A, Yuan HT, Christiani D, Karumanchi SA, et al. Excess circulating angiopoietin-2 may contribute to pulmonary vascular leak in sepsis in humans. PLoS Med. (2006) 3(3):e46. 10.1371/journal.pmed.0030046 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Bhandari V, Choo-Wing R, Lee CG, Zhu Z, Nedrelow JH, Chupp GL, et al. Hyperoxia causes angiopoietin 2-mediated acute lung injury and necrotic cell death. Nat Med. (2006) 12(11):1286–93. 10.1038/nm1494 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.Ware LB, Matthay MA. Alveolar fluid clearance is impaired in the majority of patients with acute lung injury and the acute respiratory distress syndrome. Am J Respir Crit Care Med. (2001) 163(6):1376–83. 10.1164/ajrccm.163.6.2004035 [DOI] [PubMed] [Google Scholar]
- 30.Lewis JF, Jobe AH. Surfactant and the adult respiratory distress syndrome. Am Rev Respir Dis. (1993) 147(1):218–33. 10.1164/ajrccm/147.1.218 [DOI] [PubMed] [Google Scholar]
- 31.Greene KE, Wright JR, Steinberg KP, Ruzinski JT, Caldwell E, Wong WB, et al. Serial changes in surfactant-associated proteins in lung and serum before and after onset of ARDS. Am J Respir Crit Care Med. (1999) 160(6):1843–50. 10.1164/ajrccm.160.6.9901117 [DOI] [PubMed] [Google Scholar]
- 32.de Souza Xavier Costa N, da Costa Sigrist G, Schalch AS, Belotti L, Dolhnikoff M, da Silva LFF. Lung tissue expression of epithelial injury markers is associated with acute lung injury severity but does not discriminate sepsis from ARDS. Respir Res. (2024) 25(1):129. 10.1186/s12931-024-02761-x [DOI] [PMC free article] [PubMed] [Google Scholar]
- 33.Atmowihardjo LN, Heijnen N, Smit MR, Hagens LA, Filippini D, Zimatore C, et al. Biomarkers of alveolar epithelial injury and endothelial dysfunction are associated with scores of pulmonary edema in invasively ventilated patients. Am J Physiol Lung Cell Mol Physiol. (2023) 324(1):L38–47. 10.1152/ajplung.00185.2022 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 34.Uchida T, Shirasawa M, Ware LB, Kojima K, Hata Y, Makita K, et al. Receptor for advanced glycation end-products is a marker of type I cell injury in acute lung injury. Am J Respir Crit Care Med. (2006) 173(9):1008–15. 10.1164/rccm.200509-1477OC [DOI] [PMC free article] [PubMed] [Google Scholar]
- 35.McNeil JB, Shaver CM, Kerchberger VE, Russell DW, Grove BS, Warren MA, et al. Novel method for noninvasive sampling of the distal airspace in acute respiratory distress syndrome. Am J Respir Crit Care Med. (2018) 197(8):1027–35. 10.1164/rccm.201707-1474OC [DOI] [PMC free article] [PubMed] [Google Scholar]
- 36.Sato A, Whitsett JA, Scheule RK, Ikegami M. Surfactant protein-d inhibits lung inflammation caused by ventilation in premature newborn lambs. Am J Respir Crit Care Med. (2010) 181(10):1098–105. 10.1164/rccm.200912-1818OC [DOI] [PMC free article] [PubMed] [Google Scholar]
- 37.Donnelly SC, Strieter RM, Kunkel SL, Walz A, Robertson CR, Carter DC, et al. Interleukin-8 and development of adult respiratory distress syndrome in at-risk patient groups. Lancet. (1993) 341(8846):643–7. 10.1016/0140-6736(93)90416-e [DOI] [PubMed] [Google Scholar]
- 38.Famous KR, Delucchi K, Ware LB, Kangelaris KN, Liu KD, Thompson BT, et al. Acute respiratory distress syndrome subphenotypes respond differently to randomized fluid management strategy. Am J Respir Crit Care Med. (2017) 195(3):331–8. 10.1164/rccm.201603-0645OC [DOI] [PMC free article] [PubMed] [Google Scholar]
- 39.Mikacenic C, Price BL, Harju-Baker S, O'Mahony DS, Robinson-Cohen C, Radella F, et al. A two-biomarker model predicts mortality in the critically ill with sepsis. Am J Respir Crit Care Med. (2017) 196(8):1004–11. 10.1164/rccm.201611-2307OC [DOI] [PMC free article] [PubMed] [Google Scholar]
- 40.Sinha P, Delucchi KL, McAuley DF, O'Kane CM, Matthay MA, Calfee CS. Development and validation of parsimonious algorithms to classify acute respiratory distress syndrome phenotypes: a secondary analysis of randomised controlled trials. Lancet Respir Med. (2020) 8(3):247–57. 10.1016/S2213-2600(19)30369-8 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 41.Lawler PR, Fan E. Heterogeneity and phenotypic stratification in acute respiratory distress syndrome. Lancet Respir Med. (2018) 6(9):651–3. 10.1016/S2213-2600(18)30287-X [DOI] [PubMed] [Google Scholar]
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Data Availability Statement
The original contributions presented in the study are included in the article/Supplementary Material, further inquiries can be directed to the corresponding author.