Correlation Between the Spo2/Fio2 Ratio and Pao2/Fio2 Ratio in Ards

Wongsrichanalai, Virissorn

doi:10.1016/j.chest.2019.02.097

Cited by 12 publications

(9 citation statements)

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“…The partial pressure of oxygen in arterial blood (PaO 2 ) is one of the main determinants of arterial oxygen content, a parameter that we aim to estimate continuously. The ratio of fraction of oxygen in the inspiratory gas (FiO 2 ) and PaO 2 (P/F ratio, PaO 2 /FiO 2 in mmHg) is commonly used to determine the severity of RF 19 . To measure PaO 2 , an arterial blood sample is necessary.…”

Section: Resultsmentioning

confidence: 99%

A comprehensive ML-based Respiratory Monitoring System for Physiological Monitoring & Resource Planning in the ICU

Hüser,

Lyu,

Faltys

et al. 2024

Preprint

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Respiratory failure (RF) is a frequent occurrence in critically ill patients and is associated with significant morbidity and mortality as well as resource use. To improve the monitoring and management of RF in intensive care unit (ICU) patients, we used machine learning to develop a monitoring system covering the entire management cycle of RF, from early detection and monitoring, to assessment of readiness for extubation and prediction of extubation failure risk. For patients in the ICU in the study cohort, the system predicts 80% of RF events at a precision of 45% with 65% identified 10h before the onset of an RF event. This significantly improves upon a standard clinical baseline based on the SpO2/FiO2 ratio. After a careful analysis of ICU differences, the RF alarm system was externally validated showing similar performance for patients in the external validation cohort. Our system also provides a risk score for extubation failure for patients who are clinically ready to extubate, and we illustrate how such a risk score could be used to extubate patients earlier in certain scenarios. Moreover, we demonstrate that our system, which closely monitors respiratory failure, ventilation need, and extubation readiness for individual patients can also be used for ICU-level ventilator resource planning. In particular, we predict ventilator use 8-16h into the future, corresponding to the next ICU shift, with a mean absolute error of 0.4 ventilators per 10 patients effective ICU capacity.

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Section: Resultsmentioning

confidence: 99%

A comprehensive ML-based Respiratory Monitoring System for Physiological Monitoring & Resource Planning in the ICU

Hüser,

Lyu,

Faltys

et al. 2024

Preprint

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“…26 PaO 2 , or perhaps more reliably PaO 2 /FiO 2 has been used to assess the degree of hypoxemia in both outpatient and inpatient setting as well as in the setting of acute lung injury and acute respiratory distress syndrome. SpO 2 /FiO 2 ratios correlate with PaO 2 /FiO 2 ratios in a study by Rice et al 27 In their study, using a large derivation dataset the investigators described the relationship between SpO 2 /FiO 2 to PaO 2 /FiO 2 by the following equation: SpO 2 /FiO 2 = 64+0.84 × (PaO 2 /FiO 2 ) (P < 0.0001; r = 0.89). In an equally large validation database the investigator displayed a similar linear relationship and showed that SpO 2 /FiO 2 ratios of 235 and 315 correlate with PaO 2 /FiO 2 ratios of 200 and 300.…”

Section: Discussionmentioning

confidence: 98%

The Impact of Thoracentesis On Postprocedure Pulse Oximetry

Taylor

Radchenko

Sánchez

et al. 2021

Journal of Bronchology &Amp; Interventional Pulmonology

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“…The historical use of PaO 2 /FiO 2 ve SpO 2 /FiO 2 ratios as indicators for assessing oxygenation and predicting outcomes in ARDS patients has been well established. 10,33 However, several studies have demonstrated the limitations of the PaO 2 /FiO 2 ratio in both diagnosing ARDS and predicting patient outcomes. 4,8,12 These limitations have spurred investigations into more effective methods for evaluating oxygenation in individuals with ARDS.…”

Section: Discussionmentioning

confidence: 99%

Novel Oxygenation and Saturation Indices for Mortality Prediction in COVID-19 ARDS Patients: The Impact of Driving Pressure and Mechanical Power

Aşar,

Rahim,

Rahimi

et al. 2024

J Intensive Care Med

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Background: The oxygenation index (OI) and oxygen saturation index (OSI) are proven mortality predictors in pediatric and adult patients, traditionally using mean airway pressure (Pmean). We introduce novel indices, replacing Pmean with DP (ΔPinsp), MPdyn, and MPtot, assessing their potential for predicting COVID-19 acute respiratory distress syndrome (ARDS) mortality, comparing them to traditional indices. Methods: We studied 361 adult COVID-19 ARDS patients for 7 days, collecting ΔPinsp, MPdyn, and MPtot, OI-ΔPinsp, OI-MPdyn, OI-MPtot, OSI-ΔPinsp, OSI-MPdyn, and OSI-MPtot. We compared these in surviving and non-surviving patients over the first 7 intensive care unit (ICU) days using Mann–Whitney U test. Logistic regression receiver operating characteristic (ROC) analysis assessed AUC and CI values for ICU mortality on day three. We determined cut-off values using Youden's method and conducted multivariate Cox regression on parameter limits. Results: All indices showed significant differences between surviving and non-surviving patients on the third day of ICU care. The AUC values of OI-ΔPinsp were significantly higher than those of P/F and OI-Pmean ( P values .0002 and <.0001, respectively). Similarly, AUC and CI values of OSI-ΔPinsp and OSI-MPdyn were significantly higher than those of SpO2/FiO2 and OSI-Pmean values (OSI-ΔPinsp: P < .0001, OSI-MPdyn: P values .047 and .028, respectively). OI-ΔPinsp, OSI-ΔPinsp, OI-MPdyn, OSI-MPdyn, OI-MPtot, and OSI-MPtot had AUC values of 0.72, 0.71, 0.69, 0.68, 0.66, and 0.64, respectively, with cut-off values associated with hazard ratios and P values of 7.06 (HR = 1.84, P = .002), 8.04 (HR = 2.00, P ≤ .0001), 7.12 (HR = 1.68, P = .001), 5.76 (HR = 1.70, P ≤ .0001), 10.43 (HR = 1.52, P = .006), and 10.68 (HR = 1.66, P = .001), respectively. Conclusions: Critical values of all indices were associated to higher ICU mortality rates and extended mechanical ventilation durations. The OI-ΔPinsp, OSI-ΔPinsp, and OSI-MPdyn indices displayed the strongest predictive capabilities for ICU mortality. These novel indices offer valuable insights for intensivists in the clinical management and decision-making process for ARDS patients.

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Correlation Between the Spo2/Fio2 Ratio and Pao2/Fio2 Ratio in Ards

Cited by 12 publications

References 0 publications

A comprehensive ML-based Respiratory Monitoring System for Physiological Monitoring & Resource Planning in the ICU

A comprehensive ML-based Respiratory Monitoring System for Physiological Monitoring & Resource Planning in the ICU

The Impact of Thoracentesis On Postprocedure Pulse Oximetry

Novel Oxygenation and Saturation Indices for Mortality Prediction in COVID-19 ARDS Patients: The Impact of Driving Pressure and Mechanical Power

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