Elevated Plasma Nitric Oxide Consumption in Patients with Sepsis and in Sepsis Non-Survivors

Illipparambil, Lijo; Mroczek, S.; Maeda, Tetsuro; Robinson, C.; Dony, Carola; Malnoske, M.L.; Rovitelli, A.; Pietropaoli, Anthony P.

doi:10.1164/ajrccm-conference.2022.205.1_meetingabstracts.a5136

Cited by 3 publications

(1 citation statement)

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“…To test our hypothesis, we measured plasma NOC and CFH in a cohort of critically ill patients and a healthy control group. Preliminary analyses from this study were previously published in abstract form ( 14 ).…”

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confidence: 99%

Plasma Nitric Oxide Consumption Is Elevated and Associated With Adverse Outcomes in Critically Ill Patients

Dony,

Illipparambil,

Maeda

et al. 2023

Critical Care Medicine

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OBJECTIVES: Impaired nitric oxide (NO) bioavailability may contribute to microvascular dysfunction in sepsis. Excessive plasma NO consumption has been attributed to scavenging by circulating cell-free hemoglobin. This may be a mechanism for NO deficiency in sepsis and critical illness. We hypothesized that plasma NO consumption is high in critically ill patients, particularly those with sepsis, acute respiratory distress syndrome (ARDS), shock, and in hospital nonsurvivors. We further hypothesized that plasma NO consumption is correlated with plasma cell-free hemoglobin concentration. DESIGN: Retrospective cohort study. SETTING: Adult ICUs of an academic medical center. PATIENTS AND SUBJECTS: Three hundred sixty-two critically ill patients and 46 healthy control subjects. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Plasma NO consumption was measured using reductive chemiluminescence and cell-free hemoglobin was measured with a colorimetric assay. Mean (95% CI) plasma NO consumption (µM) was higher in critically ill patients versus healthy control subjects (3.9 [3.7–4.1] vs 2.1 [1.8–2.5]), septic versus nonseptic patients (4.1 [3.8–4.3] vs 3.6 [3.3–3.8]), ARDS versus non-ARDS patients (4.4 [4.0–4.9] vs 3.7 [3.6–3.9]), shock vs nonshock patients (4.4 [4.0–4.8] vs 3.6 [3.4–3.8]), and hospital nonsurvivors versus survivors (5.3 [4.4–6.4] vs 3.7 [3.6–3.9]). These relationships remained significant in multivariable analyses. Plasma cell-free hemoglobin was weakly correlated with plasma NO consumption. CONCLUSIONS: Plasma NO consumption is elevated in critically ill patients and independently associated with sepsis, ARDS, shock, and hospital death. These data suggest that excessive intravascular NO scavenging characterizes sepsis and adverse outcomes of critical illness.

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confidence: 99%

Plasma Nitric Oxide Consumption Is Elevated and Associated With Adverse Outcomes in Critically Ill Patients

Dony,

Illipparambil,

Maeda

et al. 2023

Critical Care Medicine

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Optimizing the Implementation of Clinical Predictive Models to Minimize National Costs: Sepsis Case Study

Rogers¹,

Boussina²,

Shashikumar³

et al. 2023

J Med Internet Res

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Background Sepsis costs and incidence vary dramatically across diagnostic categories, warranting a customized approach for implementing predictive models. Objective The aim of this study was to optimize the parameters of a sepsis prediction model within distinct patient groups to minimize the excess cost of sepsis care and analyze the potential effect of factors contributing to end-user response to sepsis alerts on overall model utility. Methods We calculated the excess costs of sepsis to the Centers for Medicare and Medicaid Services (CMS) by comparing patients with and without a secondary sepsis diagnosis but with the same primary diagnosis and baseline comorbidities. We optimized the parameters of a sepsis prediction algorithm across different diagnostic categories to minimize these excess costs. At the optima, we evaluated diagnostic odds ratios and analyzed the impact of compliance factors such as noncompliance, treatment efficacy, and tolerance for false alarms on the net benefit of triggering sepsis alerts. Results Compliance factors significantly contributed to the net benefit of triggering a sepsis alert. However, a customized deployment policy can achieve a significantly higher diagnostic odds ratio and reduced costs of sepsis care. Implementing our optimization routine with powerful predictive models could result in US $4.6 billion in excess cost savings for CMS. Conclusions We designed a framework for customizing sepsis alert protocols within different diagnostic categories to minimize excess costs and analyzed model performance as a function of false alarm tolerance and compliance with model recommendations. We provide a framework that CMS policymakers could use to recommend minimum adherence rates to the early recognition and appropriate care of sepsis that is sensitive to hospital department-level incidence rates and national excess costs. Customizing the implementation of clinical predictive models by accounting for various behavioral and economic factors may improve the practical benefit of predictive models.

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Optimizing the Implementation of Clinical Predictive Models to Minimize National Costs: A Sepsis Case Study (Preprint)

Rogers¹,

Boussina²,

Shashikumar³

et al. 2022

Preprint

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BACKGROUND Recent advancements in machine learning (ML) and the proliferation of healthcare data have led to widespread excitement about using these technologies to improve care. Predictive analytic models in domains such as sepsis, acute kidney injury, respiratory failure, and general deterioration have been proposed to improve the timely administration of life-saving treatments and mitigate expensive downstream complications. It has been argued that a more tailored approach that accounts for implementation constraints that may differ across care settings can further enhance the adoption of such systems. OBJECTIVE To optimize the parameters of a sepsis prediction model within distinct patient groups to minimize the excess cost of sepsis care and analyze the potential effect of factors contributing to end-user response to sepsis alerts on overall model utility. METHODS We calculated the excess costs of sepsis to the Center for Medicare and Medicaid Services (CMS) by comparing patients with and without a secondary sepsis diagnosis but with the same primary diagnosis and baseline comorbidities. We optimized the parameters of a sepsis prediction algorithm across different diagnostic categories to minimize these excess costs. At the optima, we evaluated diagnostic odds ratios and analyzed the impact of compliance factors—like non-compliance, treatment efficacy, and tolerance for false alarms—on the net benefit of triggering sepsis alerts. RESULTS Compliance factors significantly contributed to the net benefit of triggering a sepsis alert. However, a customized deployment policy can achieve a significantly higher diagnostic odds ratio and reduced costs of sepsis care. Implementing our optimization routine with powerful predictive models could result in $4.6 billion in excess cost savings for CMS. CONCLUSIONS We provide a framework that CMS policymakers could use to recommend minimum adherence rates to the early recognition and appropriate care of sepsis that is sensitive to hospital department-level incidence rates and national excess costs. Customizing the implementation of clinical predictive models by accounting for various behavioral and economic factors may improve the practical benefit of predictive models.

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Elevated Plasma Nitric Oxide Consumption in Patients with Sepsis and in Sepsis Non-Survivors

Cited by 3 publications

References 0 publications

Plasma Nitric Oxide Consumption Is Elevated and Associated With Adverse Outcomes in Critically Ill Patients

Plasma Nitric Oxide Consumption Is Elevated and Associated With Adverse Outcomes in Critically Ill Patients

Optimizing the Implementation of Clinical Predictive Models to Minimize National Costs: Sepsis Case Study

Optimizing the Implementation of Clinical Predictive Models to Minimize National Costs: A Sepsis Case Study (Preprint)

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