The results of this prospective study show that obesity, a modifiable risk factor, is an independent predictor of procedural failure after catheter ablation of AF. Whether treating obesity may improve the results of catheter ablation of AF warrants further investigation.

Objective: The ratio of the partial pressure of arterial oxygen to fraction of inspired oxygen is a key component of the sequential organ failure assessment score that operationally defines sepsis. But, it is calculated infrequently due to the need for the acquisition of an arterial blood gas. So, we sought to find an optimal imputation strategy for the estimation of sepsis-defining hypoxemic respiratory failure using oximetry instead of an arterial blood gas. Approach: We retrospectively studied a sample of non-intubated acute-care patients with oxygen saturation recorded  ⩽10 min before arterial blood sampling (N  =  492 from 2013–2017). We imputed ratios of the partial pressure of arterial oxygen to the fraction of inspired oxygen and sepsis criteria from existing imputation equations (Hill, Severinghaus–Ellis, Rice, and Pandharipande) and compared them with the ratios and sepsis criteria measured from arterial blood gases. We devised a modified model-based equation to eliminate the bias of the results. Main results: Hypoxemia severity estimates from the Severinghaus–Ellis equation were more accurate than those from other existing equations, but showed significant proportional bias towards under-estimation of hypoxemia severity, especially at oxygen saturations  >96%. Our modified equation eliminated bias and surpassed others on all imputation quality metrics. Significance: Our modified imputation equation, is the first one that is free of bias at all oxygen saturations. It resulted in ratios of partial pressure of arterial oxygen to fraction of inspired oxygen and sepsis respiratory criteria closest to those obtained by arterial blood gas testing and is the optimal imputation strategy for non-intubated acute-care patients.

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Background Early reports of increased thrombosis risk with SARS-CoV-2 infection led to changes in venous thromboembolism (VTE) management. Real-world data on the prevalence, efficacy and harms of these changes informs best practices. Objective Define practice patterns and clinical outcomes related to VTE diagnosis, prevention, and management in hospitalized patients with coronavirus disease-19 (COVID-19) using a multi-hospital US sample. Methods In this retrospective cross-sectional study of 1121 patients admitted to 33 hospitals, exposure was dose of anticoagulant prescribed for VTE prophylaxis (standard, intensified, therapeutic), and primary outcome was VTE (pulmonary embolism [PE] and deep vein thrombosis [DVT]); secondary outcomes were PE, DVT, arterial thromboembolism (ATE), and bleeding events. Multivariable logistic regression models accounting for clustering by site and adjusted for risk factors were used to estimate odds ratios (ORs). Inverse probability weighting was used to account for confounding by indication. Results 1121 patients (mean age 60 ± 18, 47% female) admitted with COVID-19 between February 2, 2020 and December 31, 2020 to 33 US hospitals were included. Pharmacologic VTE prophylaxis was prescribed in 86%. Forty-seven patients (4.2%) had PE, 51 (4.6%) had DVT, and 23 (2.1%) had ATE. Forty-six patients (4.1%) had major bleeding and 46 (4.1%) had clinically relevant non-major bleeding. Compared to standard prophylaxis, adjusted odds of VTE were 0.67 (95% CI 0.21–2.1) with no prophylaxis, 1.0 (95% CI 0.06–17) with intensified, and 3.0 (95% CI 0.89–10) with therapeutic. Adjusted odds of bleeding with no prophylaxis were 5.6 (95% CI 3.0–11) and 5.3 (95% CI 3.0–10) with therapeutic (no events on intensified dosing). Conclusions Therapeutic anticoagulation was associated with a 3-fold increased odds of VTE and 5-fold increased odds of bleeding. While higher bleeding rates with high-intensity prophylaxis were likely due to full-dose anticoagulation, we conclude that high thrombosis rates were due to clinical concern for thrombosis before formal diagnosis.

Background: Progressive hypoxemia is the predominant mode of deterioration in COVID-19. Among hypoxemia measures, the ratio of the partial pressure of arterial oxygen to the fraction of inspired oxygen (P/F ratio) has optimal construct validity but poor availability because it requires arterial blood sampling. Pulse oximetry reports oxygenation continuously, but occult hypoxemia can occur in Black patients because the technique is affected by skin color. Oxygen dissociation curves allow non-invasive estimation of P/F ratios (ePFR) but this approach remains unproven. Research Question: Can ePFRs measure overt and occult hypoxemia? Study Design and methods: We retrospectively studied COVID-19 hospital encounters (n=5319) at two academic centers (University of Virginia [UVA] and Emory University). We measured primary outcomes (death or ICU transfer within 24 hours), ePFR, conventional hypoxemia measures, baseline predictors (age, sex, race, comorbidity), and acute predictors (National Early Warning Score (NEWS) and Sepsis-3). We updated predictors every 15 minutes. We assessed predictive validity using adjusted odds ratios (AOR) and area under receiver operating characteristics curves (AUROC). We quantified disparities (Black vs non-Black) in empirical cumulative distributions using the Kolmogorov-Smirnov (K-S) two-sample test. Results: Overt hypoxemia (low ePFR) predicted bad outcomes (AOR for a 100-point ePFR drop: 2.7 [UVA]; 1.7 [Emory]; p<0.01) with better discrimination (AUROC: 0.76 [UVA]; 0.71 [Emory]) than NEWS (AUROC: 0.70 [UVA]; 0.70 [Emory]) or Sepsis-3 (AUROC: 0.68 [UVA]; 0.65 [Emory]). We found racial differences consistent with occult hypoxemia. Black patients had better apparent oxygenation (K-S distance: 0.17 [both sites]; p<0.01) but, for comparable ePFRs, worse outcomes than other patients (AOR: 2.2 [UVA]; 1.2 [Emory], p<0.01). Interpretation: The ePFR was a valid measure of overt hypoxemia. In COVID-19, it may outperform multi-organ dysfunction models like NEWS and Sepsis-3. By accounting for biased oximetry as well as clinicians' real-time responses to it (supplemental oxygen adjustment), ePFRs may enable statistical modelling of racial disparities in outcomes attributable to occult hypoxemia.

Supplemental Digital Content is available in the text.

IMPORTANCE: Progressive hypoxemia is the predominant mode of deterioration in COVID-19. Among hypoxemia measures, the ratio of the Pao2 to the Fio2 (P/F ratio) has optimal construct validity but poor availability because it requires arterial blood sampling. Pulse oximetry reports oxygenation continuously (ratio of the Spo2 to the Fio2 [S/F ratio]), but it is affected by skin color and occult hypoxemia can occur in Black patients. Oxygen dissociation curves allow noninvasive estimation of P/F ratios (ePFRs) but remain unproven. OBJECTIVES: Measure overt and occult hypoxemia using ePFR. DESIGN, SETTING, AND PARTICIPANTS: We retrospectively studied COVID-19 hospital encounters (n = 5,319) at two academic centers (University of Virginia [UVA] and Emory University). MAIN OUTCOMES AND MEASURES: We measured primary outcomes (death or ICU transfer within 24 hr), ePFR, conventional hypoxemia measures, baseline predictors (age, sex, race, comorbidity), and acute predictors (National Early Warning Score [NEWS] and Sequential Organ Failure Assessment [SOFA]). We updated predictors every 15 minutes. We assessed predictive validity using adjusted odds ratios (AORs) and area under the receiver operating characteristic curves (AUROCs). We quantified disparities (Black vs non-Black) in empirical cumulative distributions using the Kolmogorov-Smirnov (K-S) two-sample test. RESULTS: Overt hypoxemia (low ePFR) predicted bad outcomes (AOR for a 100-point ePFR drop: 2.7 [UVA]; 1.7 [Emory]; p < 0.01) with better discrimination (AUROC: 0.76 [UVA]; 0.71 [Emory]) than NEWS (0.70 [both sites]) or SOFA (0.68 [UVA]; 0.65 [Emory]) and similar to S/F ratio (0.76 [UVA]; 0.70 [Emory]). We found racial differences consistent with occult hypoxemia. Black patients had better apparent oxygenation (K-S distance: 0.17 [both sites]; p < 0.01) but, for comparable ePFRs, worse outcomes than other patients (AOR: 2.2 [UVA]; 1.2 [Emory]; p < 0.01). CONCLUSIONS AND RELEVANCE: The ePFR was a valid measure of overt hypoxemia. In COVID-19, it may outperform multi-organ dysfunction models. By accounting for biased oximetry as well as clinicians’ real-time responses to it (supplemental oxygen adjustment), ePFRs may reveal racial disparities attributable to occult hypoxemia.

Breathing motion (respiratory kinematics) can be characterized by the interval and depth of each breath, and by magnitude-synchrony relationships between locations. Such characteristics and their breath-by-breath variability might be useful indicators of respiratory health. To enable breath-by-breath characterization of respiratory kinematics, we developed a method to detect breaths using motion sensors. In 34 volunteers who underwent maximal exercise testing, we used 8 motion sensors to record upper rib, lower rib and abdominal kinematics at 3 exercise stages (rest, lactate threshold and exhaustion). We recorded volumetric air flow signals using clinical exercise laboratory equipment and synchronized them with kinematic signals. Using instantaneous phase landmarks from the analytic representation of kinematic and flow signals, we identified individual breaths and derived respiratory rate (RR) signals at 1Hz. To evaluate the fidelity of kinematics-derived RR, we calculated bias, limits of agreement, and cross-correlation coefficients (CCC) relative to flow-derived RR. To identify coupling between kinematics and flow, we calculated the Shannon entropy of the relative frequency with which flow landmarks were distributed over the phase of the kinematic cycle. We found good agreement in the kinematics-derived and flow-derived RR signals [bias (95% limit of agreement) = 0.1 (± 7) breaths/minute; CCC median (IQR) = 0.80 (0.48 – 0.91)]. In individual signals, kinematics and flow were well-coupled (entropy 0.9-1.4 across sensors), but the relationship varied within (by exercise stage) and between individuals. The final result was that the flow landmarks did not consistently localize to any particular phase of the kinematic signals (entropy 2.2–3.0 across sensors). The Analysis of Respiratory Kinematics method can yield highly resolved respiratory rate signals by separating individual breaths. This method will facilitate characterization of clinically significant breathing motion patterns on a breath-by-breath basis. The relationship between respiratory kinematics and flow is much more complex than expected, varying between and within individuals.