Daily Ards Research Analysis
Analyzed 7 papers and selected 3 impactful papers.
Summary
Three ARDS studies stand out today: an EHR-based computable ARDS classifier enabling genomic discovery with an age-dependent MUC5B association; a multicenter ECMO registry analysis showing low PEEP at initiation is linked to lower ECMO liberation; and a pragmatic oxygenation index (S/F*P) that integrates PEEP and SpO2 to improve severity assessment. Together, they advance phenotyping, management, and noninvasive monitoring in ARDS.
Research Themes
- ECMO management strategies in severe ARDS
- EHR-driven ARDS phenotyping and genomics
- Noninvasive oxygenation indices incorporating PEEP
Selected Articles
1. A Computable Electronic Health Record ARDS Classifier and the Association Between the
An EHR-based algorithm combining billing codes, laboratory values, and chest radiograph text identified ARDS with moderate agreement versus investigator-adjudicated ARDS across two cohorts. The approach enabled genomic analyses, revealing an age-dependent association between the MUC5B promoter variant (rs35705950) and ARDS risk among older patients.
Impact: This work operationalizes a scalable computable ARDS phenotype and links it to genetic risk, opening avenues for large-scale ARDS genomics and risk stratification.
Clinical Implications: Computable phenotyping could enable population-scale ARDS surveillance, pragmatic trials, and discovery of genetic risk markers; however, genotype-informed bedside decisions are premature.
Key Findings
- EHR-ARDS showed moderate agreement with adjudicated ARDS in VALID (sensitivity 0.86, specificity 0.70, PPV 0.49, NPV 0.93, κ 0.45).
- Performance was higher in BioVU (sensitivity 0.94, specificity 0.81, PPV 0.66, NPV 0.97, κ 0.67).
- A significant age-gene interaction was observed: among older patients, rs35705950 (MUC5B promoter) increased EHR-ARDS risk (OR 1.37, 95% CI 1.05-1.78).
Methodological Strengths
- Development and external validation across two independent cohorts (VALID and BioVU).
- Multimodal EHR features including billing codes, laboratory data, and radiography report text.
Limitations
- EHR-based case identification risks misclassification relative to gold-standard Berlin adjudication.
- Genetic findings are based on EHR-ARDS and require replication and functional validation.
Future Directions: Prospective validation of the computable phenotype across diverse health systems, refinement with additional physiologic data, and replication/functional studies of the age-dependent MUC5B signal.
BACKGROUND: Large population-based DNA biobanks linked to electronic health records (EHRs) may provide novel opportunities to identify genetic drivers of ARDS. RESEARCH QUESTION: Can a computerized algorithm identify ARDS in a large EHR biobank database, and can this be used to identify ARDS genetic risk factors? STUDY DESIGN AND METHODS: We developed a classifier algorithm to identify a diagnosis of ARDS as identified from the electronic health record (EHR-ARDS) using diagnostic billing codes, laboratory test results, and chest radiography report text. The classifier model performance was evaluated against investigator-adjudicated ARDS using standard classification metrics including sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and the Cohen κ value. After confirming acceptable classifier performance, we evaluated the association between EHR-ARDS and the RESULTS: We included 2,795 patients from VALID and 9,025 hospitalized participants from BioVU. EHR-ARDS showed moderate agreement with investigator-adjudicated ARDS (VALID: sensitivity, 0.86; specificity, 0.70; PPV, 0.49; NPV, 0.93; and k, 0.45; BioVU: sensitivity, 0.94; specificity, 0.81; PPV, 0.66; NPV, 0.97; and k, 0.67). We observed a significant age-gene interaction effect for EHR-ARDS in VALID: among older patients, rs35705950 was associated with increased EHR-ARDS risk (OR, 1.37; 95% CI, 1.05-1.78; INTERPRETATION: The
2. Association Between Positive End-Expiratory Pressure at Venovenous Extracorporeal Membrane Oxygenation Initiation and Liberation Outcomes in Acute Respiratory Distress Syndrome: A Multicenter Retrospective Study.
In a 24-center registry of 683 severe ARDS patients on VV-ECMO, low initial PEEP (<8 cm H2O) was associated with a lower likelihood of 30-day ECMO liberation versus moderate PEEP (8–10 cm H2O), while high PEEP (>10 cm H2O) did not differ significantly from moderate. Low PEEP was also linked to longer ECMO duration without differences in 60-day mortality.
Impact: The study informs a modifiable setting at ECMO initiation with potential to improve liberation outcomes and standardize practice across centers.
Clinical Implications: Avoiding insufficiently low PEEP at ECMO initiation may enhance liberation rates; centers may consider targeting moderate PEEP while awaiting prospective trials to define patient-specific strategies.
Key Findings
- 30-day ECMO liberation rates: low 57.8%, moderate 73.5%, high 72.5%.
- Adjusted hazard ratio for liberation low vs moderate PEEP: 0.56 (95% CI 0.39–0.81).
- No significant difference between high and moderate PEEP (HR 0.80, 95% CI 0.58–1.10).
- Low PEEP associated with longer ECMO duration; 60-day mortality similar across groups.
Methodological Strengths
- Large multicenter cohort across 24 institutions with contemporary practice (2012–2022).
- Multivariable Cox modeling to adjust for confounders.
Limitations
- Retrospective design with potential confounding by indication and center-level practices.
- PEEP assessed at initiation only; dynamic adjustments and individualized strategies were not captured.
Future Directions: Prospective studies or pragmatic trials to define optimal PEEP titration at ECMO initiation, including patient-specific phenotypes and lung recruitability.
IMPORTANCE: The optimal level of positive end-expiratory pressure (PEEP) during venovenous extracorporeal membrane oxygenation (ECMO) for acute respiratory distress syndrome (ARDS) remains uncertain. OBJECTIVES: This study aimed to evaluate the association between initial PEEP settings at ECMO initiation and the rate of successful ECMO liberation in patients with severe ARDS. DESIGN, SETTING, AND PARTICIPANTS: We conducted a post hoc analysis of the multicenter Japan Chest CT for ARDS Requiring Venovenous ECMO (J-CARVE) registry. Adult patients with severe ARDS treated with venovenous ECMO between 2012 and 2022 at 24 institutions were included. Participants were categorized into three groups according to PEEP at ECMO initiation: low (< 8 cm H2O), middle (8-10 cm H2O), and high (> 10 cm H2O). MAIN OUTCOMES AND MEASURES: The primary outcome was successful liberation from ECMO within 30 days. Multivariable Cox proportional hazards models were used to evaluate associations. Secondary outcomes included 60-day mortality, duration of ECMO support, and duration of mechanical ventilation. RESULTS: Among 683 patients analyzed, the overall ECMO liberation rate at 30 days was 69.2%. Liberation rates were 57.8% (103/178), 73.5% (259/352), and 72.5% (111/153) in the low, middle, and high PEEP groups, respectively. After adjustment, the low group had a significantly lower likelihood of successful ECMO liberation (hazard ratio [HR], 0.56; 95% CI, 0.39-0.81) compared with the middle group. No significant difference was observed between the high and middle groups (HR, 0.80; 95% CI, 0.58-1.10). The low group had longer ECMO duration; however, 60-day mortality and hospital length of stay did not differ significantly among groups. CONCLUSIONS AND RELEVANCE: Lower PEEP levels at ECMO initiation were associated with reduced likelihood of successful ECMO liberation compared with moderate PEEP, whereas estimates for high vs. moderate PEEP were not statistically significant. These findings support avoiding insufficiently low PEEP and underscore the need for prospective studies to refine optimal PEEP strategies in patients with severe ARDS.
3. Evaluation of oxygenation indices incorporating SpO₂ and PEEP for assessing ARDS severity: Evidence from the MIMIC-IV and eICU collaborative research database v2.0 databases.
Across MIMIC-IV and eICU databases, an oxygenation index that integrates SpO2/FiO2 with PEEP (S/FP) achieved higher discrimination for ARDS severity than S/F and comparable or better than P/FP, with consistent performance across multiple machine-learning models and cross-validations. For prognosis, S/F*P underperformed S/F, but its grading scheme aided prognostic assessment.
Impact: S/F*P offers a practical, minimally invasive severity measure that aligns oxygenation with ventilator settings and could standardize bedside assessment when arterial blood gases are unavailable.
Clinical Implications: In ventilated ARDS patients, incorporating PEEP into oxygenation assessment may reduce reliance on arterial blood gases and improve early triage; prospective validation and clinically actionable thresholds are needed.
Key Findings
- Discrimination AUCs: S/F 0.700 (95% CI 0.624–0.777), P/FP 0.720 (95% CI 0.668–0.772), S/FP 0.761 (95% CI 0.693–0.830).
- S/F*P maintained good diagnostic efficacy across 9 machine-learning approaches with 10-fold cross-validation.
- For prognosis, S/FP performed worse than S/F, yet S/FP-based grading aided prognostic evaluation.
- The study compared indices within ARDS patients, assessing relative performance rather than disease vs non-disease discrimination.
Methodological Strengths
- Use of two large, widely-used ICU databases (MIMIC-IV and eICU).
- Evaluation across multiple machine-learning models with cross-validation.
Limitations
- Retrospective design with potential measurement and selection biases.
- All participants had ARDS; analyses assessed relative severity discrimination rather than case vs control diagnosis.
Future Directions: Prospective validation of S/F*P, definition of clinical thresholds, and integration with dynamic ventilator parameters to guide bedside decision-making.
BACKGROUND: The in-hospital mortality of acute respiratory distress syndrome can reach 35-45%, with patients requiring a more convenient and accurate way to assess the disease condition, which can change even more rapidly in patients undergoing mechanical ventilation in intensive care units. METHODS: Eligible patients in MIMIC-IV v3.0and eICU Collaborative Research Database v2.0were screened by the Berlin definition to examine the comparison of the diagnostic abilities of SpO210/FiO2PEEP (S/FP), PaO210/FiO2PEEP (P/FP), and SpO2/ FiO2 (S/F), with nine types of machine learning performed on S/FP for 10 cross-validations, validating the diagnostic ability of the models for ARDS patients. RESULTS: ROC_AUC = 0.700(95 CI:0.624 ~ 0.777) for S/F, ROC_AUC = 0.720(95 CI:0.668 ~ 0.772) for P/FP, and ROC_AUC = 0.761(95 CI:0.693 ~ 0.830) for S/FP showed that S/F had a better fit in diagnosing ARDS with slightly inferior efficacy to P/FP, had superior diagnostic efficacy after incorporating peep into S/F, and S/FP showed good diagnostic efficacy in 9 machine learning and 10 cross-validations. In terms of predicting the prognosis of patients, the ability of S/FP is not as good as S/F, but the grading of S/FP has a more positive significance for the evaluation of the prognosis of patients. CONCLUSION: S/FP provides a more convenient judgment for mechanically ventilated patients, avoiding the phenomenon of clinical diagnosis of PEEP and oxygenation index separation as much as possible, minimizing invasive operation of patients and improving the selection of ARDS treatment modalities. Therefore, S/F*P provides a reference for the early treatment of ARDS in the clinic to improve the resource allocation in the ICU and reduce the mortality of patients, Given all patients had ARDS diagnosis, this study evaluated relative diagnostic performance among indices rather than disease vs. non-disease discrimination.