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- Maddali, Manoj V., et al.
(författare)
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Validation and utility of ARDS subphenotypes identified by machine-learning models using clinical data : an observational, multicohort, retrospective analysis
- 2022
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Ingår i: The Lancet Respiratory Medicine. - 2213-2600. ; 10:4, s. 367-377
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Tidskriftsartikel (refereegranskat)abstract
- Background: Two acute respiratory distress syndrome (ARDS) subphenotypes (hyperinflammatory and hypoinflammatory) with distinct clinical and biological features and differential treatment responses have been identified using latent class analysis (LCA) in seven individual cohorts. To facilitate bedside identification of subphenotypes, clinical classifier models using readily available clinical variables have been described in four randomised controlled trials. We aimed to assess the performance of these models in observational cohorts of ARDS. Methods: In this observational, multicohort, retrospective study, we validated two machine-learning clinical classifier models for assigning ARDS subphenotypes in two observational cohorts of patients with ARDS: Early Assessment of Renal and Lung Injury (EARLI; n=335) and Validating Acute Lung Injury Markers for Diagnosis (VALID; n=452), with LCA-derived subphenotypes as the gold standard. The primary model comprised only vital signs and laboratory variables, and the secondary model comprised all predictors in the primary model, with the addition of ventilatory variables and demographics. Model performance was assessed by calculating the area under the receiver operating characteristic curve (AUC) and calibration plots, and assigning subphenotypes using a probability cutoff value of 0·5 to determine sensitivity, specificity, and accuracy of the assignments. We also assessed the performance of the primary model in EARLI using data automatically extracted from an electronic health record (EHR; EHR-derived EARLI cohort). In Large Observational Study to Understand the Global Impact of Severe Acute Respiratory Failure (LUNG SAFE; n=2813), a multinational, observational ARDS cohort, we applied a custom classifier model (with fewer variables than the primary model) to determine the prognostic value of the subphenotypes and tested their interaction with the positive end-expiratory pressure (PEEP) strategy, with 90-day mortality as the dependent variable. Findings: The primary clinical classifier model had an area under receiver operating characteristic curve (AUC) of 0·92 (95% CI 0·90–0·95) in EARLI and 0·88 (0·84–0·91) in VALID. Performance of the primary model was similar when using exclusively EHR-derived predictors compared with manually curated predictors (AUC=0·88 [95% CI 0·81–0·94] vs 0·92 [0·88–0·97]). In LUNG SAFE, 90-day mortality was higher in patients assigned the hyperinflammatory subphenotype than in those with the hypoinflammatory phenotype (414 [57%] of 725 vs 694 [33%] of 2088; p<0·0001). There was a significant treatment interaction with PEEP strategy and ARDS subphenotype (p=0·041), with lower 90-day mortality in the high PEEP group of patients with the hyperinflammatory subphenotype (hyperinflammatory subphenotype: 169 [54%] of 313 patients in the high PEEP group vs 127 [62%] of 205 patients in the low PEEP group; hypoinflammatory subphenotype: 231 [34%] of 675 patients in the high PEEP group vs 233 [32%] of 734 patients in the low PEEP group). Interpretation: Classifier models using clinical variables alone can accurately assign ARDS subphenotypes in observational cohorts. Application of these models can provide valuable prognostic information and could inform management strategies for personalised treatment, including application of PEEP, once prospectively validated. Funding: US National Institutes of Health and European Society of Intensive Care Medicine.
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- Mojtahid, M., et al.
(författare)
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Assessing the impact of different carbonate system parameters on benthic foraminifera from controlled growth experiments
- 2023
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Ingår i: Chemical Geology. - : Elsevier BV. - 0009-2541. ; 623
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Tidskriftsartikel (refereegranskat)abstract
- Insights into past marine carbon cycling and water mass properties can be obtained by means of geochemical proxies calibrated through controlled laboratory experiments with accurate seawater carbonate system (C-system) manipulations. Here, we explored the use of strontium/calcium ratio (Sr/Ca) of the calcite shells of benthic foraminifera as a potential seawater C-system proxy through a controlled growth experiment with two deep-sea species (Bulimina marginata and Cassidulina laevigata) and one intertidal species (Ammonia T6). To this aim, we used two experimental set-ups to decouple as much as possible the individual components of the carbonate system, i.e., changing pH at constant dissolved inorganic carbon (DIC) and changing DIC at constant pH. Four climatic chambers were used with different controlled concentrations of atmospheric pCO2 (180 ppm, 410 ppm, 1000 ppm, 1500 ppm). Our results demonstrated that pH did not influence the survival and growth of the three species. However, low DIC conditions (879 μmol kg−1) negatively affected B. marginata and C. laevigata through reduced growth, whereas no effect was observed for Ammonia T6. Our results also showed that Sr/Ca was positively correlated with total Alkalinity (TA), DIC and bicarbonate ion concentration ([HCO3 −]) for Ammonia T6 and B. marginata; i.e., DIC and/or [HCO3 −] were the main controlling factors. For these two species, the regression models were coherent with published data (existing so far only for Ammonia T6) and showed overall similar slopes but different intercepts, implying species-specific effects. Furthermore, the Sr/Ca - C-system relationship was not impacted by ontogenetic trends between chamber stages, which is a considerable advantage for paleo-applications. This applied particularly to Ammonia T6 that calcified many chambers compared to the two other species. However, no correlation with any of the C-system parameters was observed for Sr/Ca in C. laevigata. This might imply either a strong species-specific effect and/or a low tolerance to laboratory conditions leading to a physiological stress, thereby impacting the Sr incorporation into the calcite lattice of C. laevigata.
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