In Patients With Sepsis, Initial Lactate Clearance Is Confounded Highly by Comorbidities and Poorly Predicts Subsequent Lactate Trajectory

McCallister, Reid; Nuppnau, Mark; Sjoding, Michael W.; Dickson, Robert P.; Chanderraj, Rishi

doi:10.1016/j.chest.2023.04.023

Cited by 2 publications

(2 citation statements)

References 6 publications

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“…On the other hand, there are also studies showing that the initial lactate level measured at the time of hospitalization is a poor predictor of mortality. Mortality studies with a single lactate value at the time of hospitalization as well as studies with serial lactate measurements are still controversial (10,22,27).…”

Section: Discussionmentioning

confidence: 99%

A Retrospective Study on the Availability of Arterial Lactate Levels as a Biomarker of Mortality in Critically Ill Children

GİRGİN,

CEYLAN,

SARAÇ SANDAL

et al. 2023

Türkiye Çocuk Hast Derg

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Objective: We aimed to determine the threshold value of lactate levels, and to analyze its avaliability as mortality biomarker by correlating it with scoring systems in pediatric intensive care unit (PICU). Material and Methods: Observational retrospective cohort study. Our study was conducted among patients admitted to the 24-bed tertiary PICU of our hospital in 2015. All children between the ages of 1 month and 18 years were evaluated. Among 433 patients whose arterial blood gases were obtained during hospitalization, a total of 382 were included in the study. Patients with congenital metabolic disease with lactic acidosis were excluded. The arterial blood lactate levels on admission, PIM-2, PRISM-III and PELOD scores and survival status of the patients were evaluated. Correlation between lactate levels and mortality scores, threshold values of lactate levels and the factors affecting mortality risk were the main variable of interest. Results: There was a significant correlation between lactate levels and scores in patients who died (p<0.001). Receiver operating characteristic (ROC) curve analysis showed that blood lactate level was an effective parameter on mortality (area under the curve=AUC: 0.861; p<0.001) with a cut-off value of 2.55 mmol/L. The mortality risk was 1.38 fold higher in patients with higher levels of lactate. Conclusion: In our series, the levels of lactate were higher in critically ill children who died. Again, lactate levels and mortality scores of these children were correlated. In our series, the levels of lactate were higher in critically ill children who died. Again, lactate levels and mortality scores of these children were correlated. We were able to establish a cut-off point with high specificity for predicting evolution. These findings should be validated in prospective and multicenter studies for their incorporation into scoring systems.

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Section: Discussionmentioning

confidence: 99%

A Retrospective Study on the Availability of Arterial Lactate Levels as a Biomarker of Mortality in Critically Ill Children

GİRGİN,

CEYLAN,

SARAÇ SANDAL

et al. 2023

Türkiye Çocuk Hast Derg

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“…Sepsis-associated acute kidney injury (SA-AKI) is a severe and frequent complication among critically ill septic patients, with reported incidences between 35% and 61% [1][2][3][4][5][6]. Furthermore, SA-AKI significantly increases the mortality risk, with some studies demonstrating mortality rates of up to 70% in patients with SA-AKI [7][8][9]. The clinical course of SA-AKI patients tends to deteriorate, with ex-tended intensive care unit (ICU) stays and increased risks of chronic kidney disease, cardiovascular events, and death [9].…”

Section: Introductionmentioning

confidence: 99%

Artificial intelligence and machine learning’s role in sepsis-associated acute kidney injury

Cheungpasitporn,

Thongprayoon,

Kashani

2024

Kidney Res Clin Pract

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Sepsis-associated acute kidney injury (SA-AKI) is a serious complication in critically ill patients, resulting in higher mortality, morbidity, and cost. The intricate pathophysiology of SA-AKI requires vigilant clinical monitoring and appropriate, prompt intervention. While traditional statistical analyses have identified severe risk factors for SA-AKI, the results have been inconsistent across studies. This has led to growing interest in leveraging artificial intelligence (AI) and machine learning (ML) to predict SA-AKI better. ML can uncover complex patterns beyond human discernment by analyzing vast datasets. Supervised learning models like XGBoost and RNN-LSTM have proven remarkably accurate at predicting SA-AKI onset and subsequent mortality, often surpassing traditional risk scores. Meanwhile, unsupervised learning reveals clinically relevant sub-phenotypes among diverse SA-AKI patients, enabling more tailored care. In addition, it potentially optimizes sepsis treatment to prevent SA-AKI through continual refinement based on patient outcomes. However, utilizing AI/ML presents ethical and practical challenges regarding data privacy, algorithmic biases, and regulatory compliance. AI/ML allows early risk detection, personalized management, optimal treatment strategies, and collaborative learning for SA-AKI management. Future directions include real-time patient monitoring, simulated data generation, and predictive algorithms for timely interventions. However, a smooth transition to clinical practice demands continuous model enhancements and rigorous regulatory oversight. In this article, we outlined the conventional methods used to address SA-AKI and explore how AI and ML can be applied to diagnose and manage SA-AKI, highlighting their potential to revolutionize SA-AKI care.

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In Patients With Sepsis, Initial Lactate Clearance Is Confounded Highly by Comorbidities and Poorly Predicts Subsequent Lactate Trajectory

Cited by 2 publications

References 6 publications

A Retrospective Study on the Availability of Arterial Lactate Levels as a Biomarker of Mortality in Critically Ill Children

A Retrospective Study on the Availability of Arterial Lactate Levels as a Biomarker of Mortality in Critically Ill Children

Artificial intelligence and machine learning’s role in sepsis-associated acute kidney injury

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