Abstract
Background
Acute pulmonary embolism (APE) is a common pulmonary vascular disease with its incidence rising year by year. Accurate diagnosis and early risk stratification of patients with APE are crucial for treatment follow-up, especially for patients with intermediate-to-high and high-risk. The aim of this study is to explore the value of blood gas parameters, especially arterial partial pressure of oxygen/fraction of inspired oxygen (PaO2/FiO2) ratio (P/F ratio), in evaluating the risk stratification of APE.
Methods
A retrospective analysis of demographic data, complications, clinical symptoms, and laboratory data of 227 adult patients with APE treated at Ruijin Hospital, Shanghai Jiao Tong University School of Medicine Ruijin Hospital, from January 2016 to December 2021 was conducted. According to risk stratification, patients were divided into the intermediate-low risk and below group (low-risk group and intermediate-low-risk group), intermediate-high-risk and above group (intermediate-high-risk group and high-risk group), and the correlation between various indicators and risk stratification of APE was analyzed. Multivariate binary logistic regression was used to identify independent influencing factors for intermediate-high-risk and high-risk APE; receiver operating characteristic (ROC) curve analysis was used to evaluate the efficacy of P/F ratio in assessing intermediate-high-risk and high-risk APE.
Results
There were significant differences in dyspnea, syncope, and fever among the two groups (P<0.05). There were significant differences in P/F ratio, partial pressure of carbon dioxide (PaCO2), pulse oxygen saturation/fraction of inspired oxygen (SpO2/FiO2) among the two groups (P<0.05). Correlation analysis showed that dyspnea, syncope, fever, P/F ratio, PaCO2, and SpO2/FiO2 were correlated with the risk stratification (P<0.05). Multivariate binary logistic regression analysis showed that P/F ratio was an independent risk factor for intermediate-high-risk and high-risk APE (P=0.01). The area under the curve (AUC) of P/F ratio for predicting APE in the intermediate-high-risk group and the high-risk group was 0.850, the cut-off value was 256.41, the sensitivity was 74.2%, and the specificity was 81.6%.
Conclusions
The P/F ratio has certain evaluative value in risk stratification of APE and can serve as a rapid and convenient method for predicting intermediate-high-risk and high-risk APE.
Keywords: Pulmonary embolism (PE), blood gas analysis, oxygen saturation, retrospective studies, risk assessment
Highlight box.
Key findings
• The arterial partial pressure of oxygen/fraction of inspired oxygen (P/F) ratio has certain evaluative value in risk stratification of acute pulmonary embolism (APE) and can serve as a rapid and convenient method for predicting intermediate-high-risk and high-risk APE.
What is known and what is new?
• Blood gas analysis is an easily accessible, simple, and reliable indicator; however, there is still a lack of adequate and extensive research on how to apply the blood gas analysis to grading the severity of patients with pulmonary embolism.
• This study aims to provide preliminary evidence suggesting that the P/F ratio can serve as a rapid and convenient method for predicting intermediate-high-risk and high-risk APE.
What is the implication, and what should change now?
• We advocate for the inclusion of blood gas analysis indexes in the initial diagnostic workup, as they offer a simple and effective means for early prediction and monitoring of disease progression.
Introduction
Acute pulmonary embolism (APE) is a common, potentially life-threatening disease, with a high incidence and mortality in the world (1-3). With the continuous optimization of treatment methods, although the overall mortality rate of APE has decreased significantly, the course of the disease for intermediate-high-risk and high-risk patients remains unpredictable. Therefore, early determination of risk stratification for APE is crucial for subsequent treatment (4).
The risk stratification of APE in current guidelines is mainly based on hemodynamics, right ventricular function, cardiac markers, pulmonary embolism severity index (PESI) (5), or simplified PESI (sPESI) (6). PESI requires many indicators, and the calculation is complicated, making it unsuitable for rapid clinical assessment (7). Even sPESI requires the assessment of six parameters, resulting in longer wait times, all of which hinder the rapid assessment of risk stratification for APE.
Therefore, it is necessary to explore a new tool that can rapidly and effectively assess the risk stratification of APE. Increasing evidence suggests that the risk stratification and adverse outcomes of APE are not only related to cardiac function but also closely related to respiratory function (8,9). Respiratory function parameters can be objectively assessed through arterial blood gas analysis. Blood gas analysis is an easily accessible, simple, and reliable indicator; however, there is still a lack of adequate and extensive research on how to apply the blood gas analysis to grading the severity of patients with pulmonary embolism (PE).
This study collected basic clinical data of patients with APE, blood gas analysis parameters, especially the ratio of partial oxygen pressure (PaO2) to the fraction of inspired oxygen (FiO2) (PaO2/FiO2, P/F), to explore its value in risk stratification assessment of APE and to find simpler methods to predict the severity of APE. We present this article in accordance with the STROBE reporting checklist (available at https://jtd.amegroups.com/article/view/10.21037/jtd-24-1821/rc).
Methods
Study design and participants
We enrolled patients aged ≥18 years who were hospitalized with APE at Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, between January 2016 and December 2021. Inclusion criteria were: (I) diagnosis of APE meeting the relevant criteria of the “2019 European Society of Cardiology Guidelines for the Diagnosis and Management of Acute Pulmonary Embolism” (2); (II) complete clinical data with clear risk stratification results; (III) no anticoagulant or thrombolytic therapy before admission. Exclusion criteria were: age <18 years and incomplete data. This study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. This study was approved by the Ethics Committee of Ruijin Hospital, Shanghai Jiao Tong University School of Medicine (No. 2024-EC-023). The data are anonymous, and the requirement for informed consent for this retrospective analysis was therefore waived. All methods were performed in accordance with the relevant guidelines and regulations.
Data collection
General information about the participants was collected, including demographics (age, gender), comorbidities (such as hypertension, diabetes, cancer, rheumatic immune system diseases, chronic pulmonary diseases, chronic heart failure, atrial fibrillation), recent surgery, deep vein thrombosis, all blood gas analysis and cardiac biomarker test results within 1 hour of the patient’s arrival at the emergency department or admission. Diagnosis was primarily based on computed tomography pulmonary angiography (CTPA) or ventilation/perfusion (V/Q) lung scan. All patients underwent echocardiography. This study required patients to undergo transthoracic echocardiography within 24 hours of being diagnosed with acute pulmonary embolism. We collected clinical symptoms (such as cough, sputum production, hemoptysis, dyspnea, chest pain, etc.), and laboratory parameters, including arterial blood gas analysis, serum cardiac biomarkers troponin I (TnI), and N-terminal pro-brain natriuretic peptide (NT-proBNP).
Risk stratification
Based on the relevant criteria of the 2019 European Society of Cardiology (ESC) Guidelines for the Diagnosis and Management of APE, patients are assessed for risk stratification and categorized into high-risk group, intermediate-high-risk group, intermediate-low-risk group, and low-risk group. In this study, the number of patients in the high-risk group was small and compared with the low-risk group and the intermediate-low-risk group, the intermediate-high-risk group and the high-risk group of APE are two groups that need special clinical attention, once improperly treated, it may cause serious adverse consequences, so we combined the two groups into one group for statistical analysis.
Statistical analysis
All statistical analyses were performed with the use of the SPSS 23.0 software. Non-normal distribution data were described by median and compared by Kruskal-Wallis test. Count data were expressed as examples (rates), and χ2 test was used to compare the differences between groups. Spearman’s correlation coefficient was used to measure the correlation between the variables. Multivariate binary logistic regression was used to calculate the odds ratio (OR) and 95% confidence interval (95% CI). Receiver operating characteristic (ROC) curves were constructed to evaluate the sensitivity and specificity of P/F ratio in predicting intermediate-high risk and high-risk APE, and Youden index method was used to determine the cut-off value. P<0.05 was considered statistically significant.
Results
A total of 227 patients were included in the analysis. According to ESC guidelines, we divided the patients into two groups: the intermediate-low-risk and below group (low-risk group + intermediate-low-risk group, n=196) and the intermediate-high-risk and above group (intermediate-high-risk group + high-risk group, n=31). Comparison of general patient information, clinical symptoms, and blood gas analysis parameters can be found in Table 1.
Table 1. Comparison of demographic data, comorbidities, clinical symptoms, and blood gas analysis parameters among different risk stratifications.
| Characteristics | Low-risk and intermediate-low-risk (n=196) | Intermediate-high-risk and high-risk (n=31) | P |
|---|---|---|---|
| Demographic characteristics | |||
| Gender | 0.16 | ||
| Male | 96 (49.0) | 11 (35.5) | |
| Female | 100 (51.0) | 20 (64.5) | |
| Age, years | 68 (61, 76) | 72 (64, 76) | 0.28 |
| Comorbidities | |||
| Hypertension | 88 (44.9) | 12 (38.7) | 0.52 |
| Diabetes | 38 (19.4) | 5 (16.1) | 0.67 |
| Cancer | 39 (19.9) | 4 (12.9) | 0.36 |
| Rheumatic immune system diseases | 14 (7.1) | 3 (9.7) | 0.62 |
| Chronic pulmonary diseases | 29 (14.8) | 2 (6.5) | 0.21 |
| Chronic heart failure/atrial fibrillation | 12 (6.1) | 2 (6.5) | 0.94 |
| Recent surgery | 26 (13.3) | 5 (16.1) | 0.67 |
| Thrombophilia | 12 (6.1) | 3 (9.7) | 0.46 |
| Deep vein thrombosis | 156 (79.6) | 23 (74.2) | 0.47 |
| Symptoms | |||
| Cough | 66 (33.7) | 7 (22.6) | 0.22 |
| Expectoration | 52 (26.5) | 6 (19.4) | 0.40 |
| Chest pain | 52 (26.5) | 9 (29.0) | 0.77 |
| Dyspnea | 115 (58.7) | 27 (87.1) | 0.002 |
| Hemoptysis | 21 (10.7) | 2 (6.5) | 0.47 |
| Syncope | 15 (7.7) | 7 (22.6) | 0.009 |
| Palpitations | 21 (10.7) | 4 (12.9) | 0.72 |
| Fever | 29 (14.8) | 0 (0.0) | 0.03 |
| Blood gas analysis indicators | |||
| P/F ratio | 311.6 (267.7, 375.4) | 227 (185.5, 270) | <0.001 |
| PaCO2 | 37.5 (34.9, 41.7) | 37.4 (32.5, 39.0) | <0.001 |
| SpO2/FiO2 | 404 (295.2, 457) | 278.0 (232, 352) | 0.002 |
Data are presented as n (%) or median (interquartile range). P/F, partial oxygen pressure/fraction of inspired oxygen; PaCO2, partial pressure of carbon dioxide; SpO2/FiO2, pulse oxygen saturation/fraction of inspired oxygen.
There were no differences between the two groups in terms of gender, age, hypertension, diabetes, recent surgery, rheumatologic autoimmune diseases, chronic lung disease, chronic heart failure or atrial fibrillation; and there were no differences in the incidence of thrombophilia or deep vein thrombosis.
In terms of clinical symptoms, there were significant differences in dyspnea, syncope and fever among the two groups. Dyspnea and syncope in the intermediate-high-risk and high-risk group were significantly higher than that of the low-risk and intermediate-low-risk group. The fever of the low-risk and intermediate-low-risk group was significantly higher than that of the intermediate-high-risk and high-risk group. There were no significant differences in cough, expectoration, chest pain, hemoptysis, and palpitation among the two groups.
There were significant differences between the two groups in terms of blood gas analysis parameters, including P/F ratio, partial pressure of carbon dioxide (PaCO2), and SpO2/FiO2. The P/F ratio of the intermediate-high-risk and high-risk group was significantly lower than that of the intermediate-low-risk and the low-risk group (P<0.001). Pulse oxygen saturation (SpO2) was recorded in 57 patients, and the SpO2/FiO2 of the intermediate-high-risk and high-risk group was significantly lower than that of the intermediate-low-risk and the low-risk group (P=0.002).
Correlation analysis showed that the risk stratification of APE was positively correlated with dyspnea and syncope, but negatively correlated with fever, P/F ratio, PaCO2, and SpO2/FiO2; among which P/F ratio was the strongest correlation (Table 2).
Table 2. Correlation analysis between risk stratification and various parameters.
| Variables | Risk stratification of APE | P |
|---|---|---|
| Dyspnea | 0.202 | 0.002 |
| Syncope | 0.173 | 0.03 |
| Fever | −0.149 | 0.009 |
| P/F ratio | −0.417 | <0.001 |
| PaCO2 | −0.260 | <0.001 |
| SpO2/FiO2 | −0.404 | 0.002 |
APE, acute pulmonary embolism; P/F, partial oxygen pressure/fraction of inspired oxygen; PaCO2, partial pressure of carbon dioxide; SpO2/FiO2, pulse oxygen saturation/fraction of inspired oxygen.
A regression model was constructed through multivariate binary logistic regression, revealing that P/F ratio was an independent risk factor for APE in the intermediate-high-risk and above group (see Table 3).
Table 3. Analysis of influencing factors for risk stratification of acute pulmonary embolism.
| Parameter | B | S.E. | Wald | OR | 95% CI | P |
|---|---|---|---|---|---|---|
| Age | 0.002 | 0.048 | 0.002 | 1.002 | 0.912–1.102 | 0.96 |
| Cancer | −1.153 | 1.595 | 0.523 | 0.316 | 0.014–7.185 | 0.47 |
| Dyspnea | −0.285 | 1.460 | 0.038 | 0.752 | 0.043–13.147 | 0.85 |
| Syncope | 1.235 | 1.155 | 1.143 | 3.440 | 0.357–33.102 | 0.29 |
| P/F ratio | −0.034 | 0.014 | 6.120 | 0.967 | 0.941–0.993 | 0.01 |
| PaCO2 | 0.008 | 0.063 | 0.018 | 1.009 | 0.892–1.140 | 0.89 |
| SpO2/FiO2 | −0.014 | 0.009 | 2.733 | 0.986 | 0.969–1.003 | 0.10 |
CI, confidence interval; OR, odds ratio; P/F, partial oxygen pressure/fraction of inspired oxygen; PaCO2, partial pressure of carbon dioxide; SpO2/FiO2, pulse oxygen saturation/fraction of inspired oxygen.
The area under curve (AUC) of P/F ratio for predicting APE in the intermediate-high-risk group and the high-risk group was 0.850, the cut-off value was 256.41, the sensitivity was 74.2%, and the specificity was 81.6% (Table 4, Figure 1).
Table 4. Evaluation of the efficacy of the P/F ratio in assessing intermediate-high and high-risk acute pulmonary embolism.
| Variable | AUC (95% CI) | Cut-off | Sensitivity | Specificity |
|---|---|---|---|---|
| P/F ratio | 0.850 (0.778–0.923) | 256.41 | 0.742 | 0.816 |
AUC, area under the curve; CI, confidence interval; P/F, partial oxygen pressure/fraction of inspired oxygen.
Figure 1.
ROC curve of P/F ratio in predicting intermediate-high and high-risk groups of APE. APE, acute pulmonary embolism; P/F, arterial partial pressure of oxygen/fraction of inspired oxygen; ROC, receiver operating characteristic.
Discussion
APE is a severe respiratory condition, and in recent years, we have witnessed a gradual decrease in mortality rates associated with this condition in European and North American populations (10-13). The downward trend in PE mortality has also been observed in Asian populations, including in China (14-16). This positive trend has been linked to the successful implementation of guideline-recommended diagnostic and treatment protocols tailored to individual patient risks. Early identification of risk factors is crucial in managing APE. The current method for assessing risk factors is complex, prompting the need for a more streamlined approach. APE disrupts circulation and gas exchange, leading to hypoxemia, which is closely tied to disease severity (17). Despite this, current guidelines focus less on the respiratory aspect of PE risk assessment (2,18,19). Therefore, we aimed to explore the possibility of using blood gas analysis parameters for a quicker risk assessment. In this study, we gathered demographic information, comorbidities, clinical symptoms, and blood gas analysis results from PE patients, including P/F ratio, PaCO2, and SpO2/FiO2, to identify simpler parameters for risk assessment.
The clinical manifestations of APE commonly include dyspnea, chest pain, and cough. However, there is limited research on the variations in symptoms among patients in different risk categories. Our study found a significant relationship between dyspnea, syncope, fever and the severity of APE, aligning with previous research findings (20). It is worth noting that dyspnea is a subjective symptom influenced by the patient’s personal experience, while syncope occurs less frequently, underscoring the importance of objective indicators for assessing risk stratification in APE.
APE can impact arterial gas exchange, with hypoxemia being a common manifestation (21), which has been overlooked for many years. The ESC guidelines currently only consider oxygen saturation <90% as one element in the PESI score, highlighting the need to further investigate the role of blood gas analysis parameters in risk stratification for APE. The P/F ratio, a commonly used indicator for assessing hypoxia (22), has been shown in a previous study (23) to be a reliable marker of V/Q mismatch in APE. Another study (24) has shown increased mortality in APE patients with low P/F ratio. Our study revealed that as the risk classification for APE increased, the P/F ratio, SpO2/FiO2, and PaCO2 decreased. This trend may be attributed to a V/Q mismatch caused by a combination of reduced blood flow in obstructed pulmonary arteries and an overflow zone in capillary beds supplied by nonobstructed vessels, leading to hypoxemia in APE (2). Hypoxemia triggers carotid chemoreceptors, stimulating the respiratory center and resulting in shortness of breath, often accompanied by hypocapnia (25). Correlation analysis demonstrated a negative correlation between APE risk classification and the P/F ratio (−0.417), SpO2/FiO2 (−0.404), and PaCO2 (−0.260), indicating a relationship between arterial blood gas parameters and APE risk classification, with the P/F ratio showing the strongest correlation.
Most deaths due to APE typically occur within the first few hours to days (26), highlighting the critical importance of timely risk stratification assessment. For low-risk patients, outpatient/emergency observation or home treatment may be suitable, while patients with intermediate-low-risk are advised to undergo admission for observation. It is noted that some patients with intermediate-high-risk APE may face clinical deterioration shortly after the event (27), leading to increased mortality rates (28,29). Therefore, early identification of intermediate-high-risk and high-risk patients, along with close monitoring, is essential. Our study utilized multivariate binary logistic regression analysis, revealing that the P/F ratio can serve as an independent risk factor for intermediate-high-risk and high-risk APE. The model achieved an AUC of 0.850 (95% CI: 0.778, 0.923) for predicting intermediate-high-risk and high-risk cases, with a sensitivity of 74.2% and specificity of 81.6% at a cut-off value of 256.41. These findings suggest that the P/F ratio is a valuable predictor for identifying intermediate-high-risk and high-risk APE, making it a useful tool for rapid screening. Therefore, we advocate for the inclusion of blood gas analysis indexes in the initial diagnostic workup, as they offer a simple and effective means for early prediction and monitoring of disease progression.
The P/F ratio is an independent predictor of intermediate-high-risk and high-risk APE. This study is the first to explore the correlation between the P/F ratio and risk stratification in APE, offering a straightforward and efficient laboratory test for evaluating intermediate-high-risk and high-risk APE.
There are several limitations in this study: (I) the sample size was small and it was a single-center retrospective study; (II) the enrollment was limited to hospitalized patients with APE, excluding those who died in the emergency department; (III) due to the small number of patients with a low P/F ratio at baseline, obtaining pre-disease P/F ratio data for patients with severe chronic lung diseases and hypoxemia could help in stratification. Assessing the change in P/F ratio before and after illness could minimize errors; (IV) additionally, the study did not evaluate the relationship between P/F ratio and prognosis, which will be addressed in future research.
Conclusions
Our study provides preliminary evidence suggesting that the P/F ratio can serve as a rapid and convenient method for predicting intermediate-high-risk and high-risk APE. While our findings indicate that the P/F ratio has certain evaluative value in risk stratification of APE, we acknowledge that further studies are necessary to confirm these results.
Supplementary
The article’s supplementary files as
Acknowledgments
None.
Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. This study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The study was approved by the Ethics Committee of Ruijin Hospital, Shanghai Jiao Tong University School of Medicine (No. 2024-EC-023). The data are anonymous, and the requirement for informed consent for this retrospective analysis was therefore waived. All methods were performed in accordance with the relevant guidelines and regulations.
Footnotes
Reporting Checklist: The authors have completed the STROBE reporting checklist. Available at https://jtd.amegroups.com/article/view/10.21037/jtd-24-1821/rc
Funding: This study was funded by the National Natural Science Funds of China (Nos. 8217010230, 82370025 and 82300023), Shanghai Sailing Program (No. 22YF1424800), and Shanghai Committee of Science and Technology, China (No. 21Y11901500).
Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://jtd.amegroups.com/article/view/10.21037/jtd-24-1821/coif). The authors have no conflicts of interest to declare.
Data Sharing Statement
Available at https://jtd.amegroups.com/article/view/10.21037/jtd-24-1821/dss
References
- 1.Giri J, Sista AK, Weinberg I, et al. Interventional Therapies for Acute Pulmonary Embolism: Current Status and Principles for the Development of Novel Evidence: A Scientific Statement From the American Heart Association. Circulation 2019;140:e774-801. 10.1161/CIR.0000000000000707 [DOI] [PubMed] [Google Scholar]
- 2.Konstantinides SV, Meyer G, Becattini C, et al. 2019 ESC Guidelines for the diagnosis and management of acute pulmonary embolism developed in collaboration with the European Respiratory Society (ERS). Eur Heart J 2020;41:543-603. 10.1093/eurheartj/ehz405 [DOI] [PubMed] [Google Scholar]
- 3.Dahhan T, Siddiqui I, Tapson VF, et al. Clinical and echocardiographic predictors of mortality in acute pulmonary embolism. Cardiovasc Ultrasound 2016;14:44. 10.1186/s12947-016-0087-y [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Barbero E, Bikdeli B, Chiluiza D, et al. Performance of Early Prognostic Assessment Independently Predicts the Outcomes in Patients with Acute Pulmonary Embolism. Thromb Haemost 2018;118:798-800. 10.1055/s-0038-1637746 [DOI] [PubMed] [Google Scholar]
- 5.Aujesky D, Obrosky DS, Stone RA, et al. Derivation and validation of a prognostic model for pulmonary embolism. Am J Respir Crit Care Med 2005;172:1041-6. 10.1164/rccm.200506-862OC [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Jiménez D, Aujesky D, Moores L, et al. Simplification of the pulmonary embolism severity index for prognostication in patients with acute symptomatic pulmonary embolism. Arch Intern Med 2010;170:1383-9. 10.1001/archinternmed.2010.199 [DOI] [PubMed] [Google Scholar]
- 7.Jiménez D, Yusen RD. Prognostic models for selecting patients with acute pulmonary embolism for initial outpatient therapy. Curr Opin Pulm Med 2008;14:414-21. 10.1097/MCP.0b013e3283043e44 [DOI] [PubMed] [Google Scholar]
- 8.Ye W, Chen X, Li X, et al. Arterial partial pressure of oxygen and diffusion function as prognostic biomarkers for acute pulmonary embolism. Respir Med 2022. [Epub ahead of print]. doi: . 10.1016/j.rmed.2022.106794 [DOI] [PubMed] [Google Scholar]
- 9.Vedovati MC, Cimini LA, Pierpaoli L, et al. Prognostic value of respiratory index in haemodynamically stable patients with acute pulmonary embolism: The Respiratory Index model study. Eur Heart J Acute Cardiovasc Care 2020;9:286-92. 10.1177/2048872620913849 [DOI] [PubMed] [Google Scholar]
- 10.Dentali F, Ageno W, Pomero F, et al. Time trends and case fatality rate of in-hospital treated pulmonary embolism during 11 years of observation in Northwestern Italy. Thromb Haemost 2016;115:399-405. 10.1160/TH15-02-0172 [DOI] [PubMed] [Google Scholar]
- 11.Barco S, Mahmoudpour SH, Valerio L, et al. Trends in mortality related to pulmonary embolism in the European Region, 2000-15: analysis of vital registration data from the WHO Mortality Database. Lancet Respir Med 2020;8:277-87. 10.1016/S2213-2600(19)30354-6 [DOI] [PubMed] [Google Scholar]
- 12.Jiménez D, de Miguel-Díez J, Guijarro R, et al. Trends in the Management and Outcomes of Acute Pulmonary Embolism: Analysis From the RIETE Registry. J Am Coll Cardiol 2016;67:162-70. 10.1016/j.jacc.2015.10.060 [DOI] [PubMed] [Google Scholar]
- 13.Stein PD, Matta F, Hughes PG, et al. Nineteen-Year Trends in Mortality of Patients Hospitalized in the United States with High-Risk Pulmonary Embolism. Am J Med 2021;134:1260-4. 10.1016/j.amjmed.2021.01.026 [DOI] [PubMed] [Google Scholar]
- 14.Zhai Z, Wang D, Lei J, et al. Trends in risk stratification, in-hospital management and mortality of patients with acute pulmonary embolism: an analysis from the China pUlmonary thromboembolism REgistry Study (CURES). Eur Respir J 2021;58:2002963. 10.1183/13993003.02963-2020 [DOI] [PubMed] [Google Scholar]
- 15.Zhang Z, Lei J, Shao X, et al. Trends in Hospitalization and In-Hospital Mortality From VTE, 2007 to 2016, in China. Chest 2019;155:342-53. 10.1016/j.chest.2018.10.040 [DOI] [PubMed] [Google Scholar]
- 16.Lee LH, Gallus A, Jindal R, et al. Incidence of Venous Thromboembolism in Asian Populations: A Systematic Review. Thromb Haemost 2017;117:2243-60. 10.1160/TH17-02-0134 [DOI] [PubMed] [Google Scholar]
- 17.Becattini C, Vedovati MC, Pruszczyk P, et al. Oxygen saturation or respiratory rate to improve risk stratification in hemodynamically stable patients with acute pulmonary embolism. J Thromb Haemost 2018;16:2397-402. 10.1111/jth.14299 [DOI] [PubMed] [Google Scholar]
- 18.Pulmonary Embolism & Pulmonary Vascular Diseases Group of the Chinese Thoracic Society ; Pulmonary Embolism & Pulmonary Vascular Disease Working Group of Chinese Association of Chest Physicians; National Cooperation Group on Prevention & Treatment of Pulmonary Embolism & Pulmonary Vascular Disease. Guidelines for the diagnosis, treatment and prevention of pulmonary thromboembolism. Zhonghua Yi Xue Za Zhi 2018;98:1060-87. [Google Scholar]
- 19.Ortel TL, Neumann I, Ageno W, et al. American Society of Hematology 2020 guidelines for management of venous thromboembolism: treatment of deep vein thrombosis and pulmonary embolism. Blood Adv 2020;4:4693-738. 10.1182/bloodadvances.2020001830 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Ružičić DP, Dzudovic B, Matijasevic J, et al. Signs and symptoms of acute pulmonary embolism and their predictive value for all-cause hospital death in respect of severity of the disease, age, sex and body mass index: retrospective analysis of the Regional PE Registry (REPER). BMJ Open Respir Res 2023;10:e001559. 10.1136/bmjresp-2022-001559 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Howard L. Acute pulmonary embolism. Clin Med (Lond) 2019;19:243-247. Erratum in: Clin Med (Lond) 2019;19:359. 10.7861/clinmedicine.19-3-247 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Prediletto I, D'Antoni L, Carbonara P, et al. Standardizing PaO2 for PaCO2 in P/F ratio predicts in-hospital mortality in acute respiratory failure due to Covid-19: A pilot prospective study. Eur J Intern Med 2021;92:48-54. 10.1016/j.ejim.2021.06.002 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Ye W, Chen X, Li X, et al. Oxygenation index and NT-proBNP as predictors of pulmonary hypertension and ventilation/perfusion mismatch in acute pulmonary embolism. Front Cardiovasc Med 2023;10:1090805. 10.3389/fcvm.2023.1090805 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Pires M, Santos J, Neto V, et al. A new ratio with PaO2/FiO2 and pulmonary arterial systolic pressure in the prognosis of intermediate high risk pulmonary embolism. Eur Heart J 2021;42:ehab724.1929.
- 25.Fernandes CJ, Luppino Assad AP, Alves-Jr JL, et al. Pulmonary Embolism and Gas Exchange. Respiration 2019;98:253-62. 10.1159/000501342 [DOI] [PubMed] [Google Scholar]
- 26.Martinez Licha CR, McCurdy CM, Maldonado SM, et al. Current Management of Acute Pulmonary Embolism. Ann Thorac Cardiovasc Surg 2020;26:65-71. 10.5761/atcs.ra.19-00158 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27.Zuin M, Rigatelli G, Bongarzoni A, et al. Mean arterial pressure predicts 48 h clinical deterioration in intermediate-high risk patients with acute pulmonary embolism. Eur Heart J Acute Cardiovasc Care 2023;12:80-6. 10.1093/ehjacc/zuac169 [DOI] [PubMed] [Google Scholar]
- 28.Mirambeaux R, León F, Bikdeli B, et al. Intermediate-High Risk Pulmonary Embolism. TH Open 2019;3:e356-63. 10.1055/s-0039-3401003 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.Becattini C, Agnelli G, Maggioni AP, et al. Contemporary Management and Clinical Course of Acute Pulmonary Embolism: The COPE Study. Thromb Haemost 2023;123:613-26. 10.1055/a-2031-3859 [DOI] [PMC free article] [PubMed] [Google Scholar]