Pulse oximetry waveform: A non-invasive physiological predictor for the return of spontaneous circulation in cardiac arrest patients ---- A multicenter, prospective observational study

Xu, Jun; Li, Chen; Tang, Hanqi; Tan, Dingyu; Fu, Yangyang; Zong, Liang; Jing, Daoyuan; Ding, Banghan; Cao, Yu; Lu, Zhongqiu; Tian, Ye; Chai, Yifeng; Meng, Yanli; Wang, Zhen; Zheng, Yaan; Zhao, Xiaodong; Zhang, Xinyan; Lu, Liang; Zeng, Zhongyi; Li, Yan; Walline, Joseph Harold; Song, Priscilla; Zheng, Lulin; Sun, Feng; Shao, Shihuan; Sun, Minmin; Huang, Mingwei; Zeng, Ruifeng; Zhang, Shu; Yang, Xin‐She; Yao, Dongqi; Yu, Muming; Liao, Hua; Xiong, Yingxia; Kang, Zheng; Qin, Yan; An, Yingbo; Liu, Yuxiang; Chen, Kun; Zhu, Huadong; Yu, Xuezhong; Du, Bin

doi:10.1016/j.resuscitation.2021.09.032

Cited by 5 publications

(5 citation statements)

References 34 publications

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“…In our previous study, we found that POP parameters, such as AUCp and Amp, could be used to identify ROSC in patients with cardiac arrest. [17] The present study further suggests that AUCp and Amp can be used to identify the sustainability of ROSC. P OP parameters have been shown to be associated with peripheral perfusion in critically ill patients in many previous studies.…”

Section: Discussionsupporting

confidence: 59%

“…E TCO 2 has been investigated in many previous studies and is regarded as an indicator of ROSC in patients with cardiac arrest. [16,17] Its level reflects tissue metabolism, lung perfusion, and alveolar ventilation, and it is closely related to the quality of CPR and a patient's prognosis. In this study, the ETCO 2 of both groups exceeded 25 mmHg (1 mmHg=0.133 kPa) during CPR, indicating a generally high quality of resuscitation and a good possibility of ROSC.…”

Section: Discussionmentioning

confidence: 99%

“…We acquired the area under the curve (AUCp) and amplitude (Amp) of the POP waveform from the near-infrared signals of POP. [17] All patient data were collected for at least 20 min after ROSC to determine whether the patient rearrested. The mean Amp, AUCp, and ETCO 2 during the last 2 min of CPR and the fi rst 10 min after ROSC were calculated as described in a previous study.…”

Section: Data Collectionmentioning

confidence: 99%

“…The mean Amp, AUCp, and ETCO 2 during the last 2 min of CPR and the fi rst 10 min after ROSC were calculated as described in a previous study. [17] ROSC was defined as the restoration of a palpable pulse and autonomous cardiac rhythm after the completion or cessation of CPR. Unsustained ROSC was defined as rearrest within 20 min after a previous ROSC.…”

Section: Data Collectionmentioning

confidence: 99%

“…[12][13][14][15] Our research group has shown that pulse oximetry photoplethysmogram (POP) and its waveform components are also important physiological parameters during resuscitation and are also closely related to ROSC during CPR in patients with cardiac arrest. [13,16,17] We hypothesized that the combination of ETCO 2 and POP might be discriminative for the early recognition of patients at risk of unsustained ROSC before rearrest. Therefore, we conducted this multicenter, prospective, observational study to investigate whether ETCO 2 and POP either separately or in combination can predict unsustained ROSC.…”

Section: Introductionmentioning

confidence: 99%

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A novel predictor of unsustained return of spontaneous circulation in cardiac arrest patients through a combination of capnography and pulse oximetry: a multicenter observational study

Yang,

Tang,

Shao

et al. 2024

World Journal of Emergency Medicine

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BACKGROUND: Unsustained return of spontaneous circulation (ROSC) is a critical barrier to survival in cardiac arrest patients. This study examined whether end-tidal carbon dioxide (ETCO 2 ) and pulse oximetry photoplethysmogram (POP) parameters can be used to identify unsustained ROSC. METHODS:We conducted a multicenter observational prospective cohort study of consecutive patients with cardiac arrest from 2013 to 2014. Patients' general information, ETCO 2 , and POP parameters were collected and statistically analyzed. RESULTS:The included 105 ROSC episodes (from 80 cardiac arrest patients) comprised 51 sustained ROSC episodes and 54 unsustained ROSC episodes. The 24-hour survival rate was significantly higher in the sustained ROSC group than in the unsustained ROSC group (29.2% vs. 9.4%, P<0.05). The logistic regression analysis showed that the difference between after and before ROSC in ETCO 2 (ΔETCO 2 ) and the difference between after and before ROCS in area under the curve of POP (ΔAUCp) were independently associated with sustained ROSC (odds ratio [OR]=0.931, 95% confi dence interval [95% CI] 0.881-0.984, P=0.011 and OR=0.998, 95% CI 0.997-0.999, P<0.001). The area under the receiver operating characteristic curve of ΔETCO 2 , ΔAUCp, and the combination of both to predict unsustained ROSC were 0.752 (95% CI 0.660-0.844), 0.883 (95% CI 0.818-0.948), and 0.902 (95% CI 0.842-0.962), respectively. CONCLUSION: Patients with unsustained ROSC have a poor prognosis. The combination of ΔETCO 2 and ΔAUCp showed signifi cant predictive value for unsustained ROSC.

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Section: Discussionsupporting

confidence: 59%

Section: Discussionmentioning

confidence: 99%

Section: Data Collectionmentioning

confidence: 99%

Section: Data Collectionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

A novel predictor of unsustained return of spontaneous circulation in cardiac arrest patients through a combination of capnography and pulse oximetry: a multicenter observational study

Yang,

Tang,

Shao

et al. 2024

World Journal of Emergency Medicine

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Development and external validation of a novel modality for rapid recognition of aortic dissection based on peripheral pulse oximetry waveforms

Luo,

Zhang,

Niu

et al. 2024

Medical Physics

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BackgroundAortic dissection (AD) is a life‐threatening cardiovascular emergency that is often misdiagnosed as other chest pain conditions. Physiologically, AD may cause abnormalities in peripheral blood flow, which can be detected using pulse oximetry waveforms.PurposeThis study aimed to assess the feasibility of identifying AD based on pulse oximetry waveforms and to highlight the key waveform features that play a crucial role in this diagnostic method.MethodsThis prospective study employed high‐risk chest pain cohorts from two emergency departments. The initial cohort was enriched with AD patients (n = 258, 47% AD) for model development, while the second cohort consisted of chest pain patients awaiting angiography (n = 71, 25% AD) and was used for external validation. Pulse oximetry waveforms from the four extremities were collected for each patient. After data preprocessing, a recognition model based on the random forest algorithm was trained using patients' gender, age, and waveform difference features extracted from the pulse oximetry waveforms. The performance of the model was evaluated using receiver operating characteristic (ROC) curve analysis and decision curve analysis (DCA). The importance of features was also assessed using Shapley Value and Gini importance.ResultsThe model demonstrated strong performance in identifying AD in both the training and external validation sets. In the training set, the model achieved an area under the ROC curve of 0.979 (95% CI: 0.961–0.990), sensitivity of 0.918 (95% CI: 0.873–0.955), specificity of 0.949 (95% CI: 0.912–0.985), and accuracy of 0.933 (95% CI: 0.904–0.959). In the external validation set, the model attained an area under the ROC curve of 0.855 (95% CI: 0.720–0.965), sensitivity of 0.889 (95% CI: 0.722–1.000), specificity of 0.698 (95% CI: 0.566–0.812), and accuracy of 0.794 (95% CI: 0.672–0.878). Decision curve analysis (DCA) further showed that the model provided a substantial net benefit for identifying AD. The median mean and median variance of the four limbs' signals were the most influential features in the recognition model.ConclusionsThis study demonstrated the feasibility and strong performance of identifying AD based on peripheral pulse oximetry waveforms in high‐risk chest pain populations in the emergency setting. The findings also provided valuable insights for future human fluid dynamics simulations to elucidate the impact of AD on blood flow in greater detail.

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Prognostic value of grey-white matter ratio obtained within two hours after return of spontaneous circulation in out-of-hospital cardiac arrest survivors: A multicenter, observational study

Murakami,

Hongo,

Yumoto

et al. 2024

Resuscitation Plus

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Pulse oximetry waveform: A non-invasive physiological predictor for the return of spontaneous circulation in cardiac arrest patients ---- A multicenter, prospective observational study

Cited by 5 publications

References 34 publications

A novel predictor of unsustained return of spontaneous circulation in cardiac arrest patients through a combination of capnography and pulse oximetry: a multicenter observational study

A novel predictor of unsustained return of spontaneous circulation in cardiac arrest patients through a combination of capnography and pulse oximetry: a multicenter observational study

Development and external validation of a novel modality for rapid recognition of aortic dissection based on peripheral pulse oximetry waveforms

Prognostic value of grey-white matter ratio obtained within two hours after return of spontaneous circulation in out-of-hospital cardiac arrest survivors: A multicenter, observational study

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