Critically ill patients in emergency department may be characterized by low amplitude and high variability of amplitude of pulse photoplethysmography

Can Peripheral Perfusion Index (PPI) Predict Disease Severity in COVID-19 Patients in the Emergency Department?

Background Coronavirus disease 2019 (COVID-19) causes significant mortality and morbidity in severe patients.

Objective In this study, we aimed to examine the relationship between COVID-19 disease severity and peripheral perfusion index (PPI).

Patients and Methods This prospective observational study included COVID-19 patients admitted to the tertiary hospital emergency department. Basal clinical and demographic data of the patients and PPI values at the time of admission were recorded. The patients were categorized to severe and nonsevere groups according to clinical severity. The relationship between COVID-19 severity and PPI was examined in comparison with the control group.

Results A total of 324 patients who met the inclusion criteria were analyzed. COVID-19 (+) was detected in 180 of these patients. Ninety-two of the COVID-19 (+) patients were in the severe group, and 88 of them were in the non severe group. Note that 164 COVID-19 (–) patients were in the control group. PPI average was found to be 1.44 ± 1.12 in the severe group, and 3.69 ± 2.51 in the nonsevere group. PPI average was found to be significantly lower in the severe group than the nonsevere group (p< 0.01) As for the nonsevere group and control group, PPI averages were found to be 3.69 ± 2.51 and3.54 ± 2.32, respectively, and a significant difference was determined between the two groups (p< 0.05). PPI COVID-19 severity predicting activity was calculated as area under the curve: 0.833, sensitivity:70.4%, andspecificity:71%(p = 0.025) at 2.2 cutoff value.

Conclusion The results of our study showed that PPI is an easy-to-apply and useful parameter in the emergency department in determining the severity of COVID-19 patients.

Prognostic performance of peripheral perfusion index and shock index combined with ESI to predict hospital outcome

INTRODUCTION

Peripheral perfusion index (PPI) and shock index (SI) are considered valuable predictors of hospital outcome and mortality in various operative and intensive care settings. In the present study, we evaluated the prognostic capabilities of these parameters for performing emergency department (ED) triage, as represented by the emergency severity index (ESI).

METHODS

This prospective cross-sectional study included 367 patients aged older than 18 years who visited the ED of a tertiary referral hospital. The ESI triage levels with PPI, SI, and other basic vital sign parameters were recorded for each patient. The hospital outcome of the patients at the end of the ED period, such as discharge, admission to the hospital and death were recorded.

RESULTS

A total of 367 patients (M/F: 178/189) admitted to the ED were categorized according to ESI and included in the study. A decrease in diastolic BP, SpO2 and PPI increased the likelihood of hospitalization and 30-day mortality. Based on univariate analysis, a significant improvement in performance was found by using age, diastolic BP, mean arterial pressure, SpO2, SI and PPI in terms of predicting high acuity level patients (ESI < 3). In the multivariable analysis only SpO2 and PPI were found to predict ESI < 3 patients.

CONCLUSION

Peripheral perfusion index and SI as novel triage instruments might provide useful information for predicting hospital admission and mortality in ED patients. The addition of these parameters to existing triage instruments such as ESI could enhance the triage specificity in unselected patients admitted to ED.

The role of peripheral perfusion index in differential diagnosis of cardiac and pulmonary-origin dyspnea in emergency service

Introduction:

Pulmonary and cardiac disorders are diagnosed in most patients presenting to the emergency department with dyspnea. Discrimination of pulmonary and cardiac pathologies from each other and early intervention have vital importance. Various methods have been used for assessment of peripheral perfusion, and the peripheral perfusion index) has gained popularity in recent years. This study aimed to investigate the contribution of peripheral perfusion index to the evaluation process in patients presenting with the complaint of dyspnea and diagnosed with either a pulmonary or cardiac pathology.

Materials and Methods:

We retrospectively reviewed the charts of patients who presented to emergency department with dyspnea between 1 July 2018 and 1 July 2019. Patients in whom the cause of dsypnea was determined to be a cardiac or pulmonary pathology were included in the study. The age, gender, peripheral perfusion index value at admission, the diagnosis, and the hospitalization status were recorded.

Results:

One hundred and ninety patients consisting of 106 (55.8%) males and 84 (44.2%) females were included in our study. While a pulmonary pathology was determined in 141 (74.2%) patients and a cardiac pathology in 49 (25.8%) patients, 72 (37.9%) patients were decided to be hospitalized. No difference was determined between patients with pulmonary and cardiac pathologies regarding peripheral perfusion index. When the patients were compared regarding hospitalization status and discharge from the emergency department, no significant difference was found to be present between the groups.

Conclusion:

Since peripheral perfusion index is a noninvasive, easy-to-perform, rapid, and reproducible test, it has been promising as a prognostic and diagnostic parameter. However, it has been realized that PPI was unsuccessful in the evaluation of patients with dyspnea, in the differential diagnosis of cardiac and pulmonary pathologies and prediction of hospitalization status in the emergency department.

Use of photoplethysmography to predict mortality in intensive care units

PURPOSE

The aim of this study was to evaluate and compare the capacity to predict hemodynamic variables obtained with photoplethysmography (PPG) and Acute Physiology and Chronic Health Evaluation (APACHE II) in patients hospitalized in the intensive care unit (ICU).

MATERIALS AND METHODS

A prospective cohort study was conducted in the adult ICU of Hospital Nossa Senhora da Conceição, located in Tubarão, Santa Catarina, Brazil. The data collected included the diagnosis for hospitalization, age, gender, clinical or surgical profile, PPG pulse curve signal, and APACHE II score in the first 24 hours. A bivariate and a multivariate logistic regressions were performed, with death as an outcome. A mortality model using artificial neural networks (ANNs) was proposed.

RESULTS

A total of 190 individuals were evaluated. Most of them were males (6:5), with a median age of 67 (54-75) years, and the main reasons for hospitalization were cardiovascular and neurological causes; half of them were surgical cases. APACHE II median score was 14 (8-19), with a median length of stay of 6 (3-15) days, and 28.4% of the patients died. The following factors were associated with mortality: age (OR=1.023; 95% CI 1.001-1.044; P=0.039), clinical profile (OR=5.481; 95% CI 2.646-11.354; P<0.001), APACHE II (OR=1.168; 95% CI 1.106-1.234; P<0.001), heart rate in the first 24 hours (OR=1.020; 95% CI 1.001-1.039; P=0.036), and time between the systolic and diastolic peak (∆T) intervals obtained with PPG (OR=0.989; 95% CI 0.979-0.998; P=0.015). Compared with the accuracy (area under the receiver-operating characteristic curve) 0.780 of APACHE II (95% CI 0.711-0.849; P<0.001), the multivariate logistic model showed a larger area of 0.858 (95% CI 0.803-0.914; P<0.001). In the model using ANNs, the accuracy was 0.895 (95% CI 0.851-0.940; P<0.001).

CONCLUSION

The mortality models using variables obtained with PPG, with the inclusion of epidemiological parameters, are very accurate and, if associated to APACHE II, improve prognostic accuracy. The use of ANN was even more accurate, indicating that this tool is important to help in the clinical judgment of the intensivist.

Can the descending aortic stroke volume be estimated by transesophageal descending aortic photoplethysmography?

PURPOSE

The aim of this study was to investigate the ability of transesophageal photoplethysmography detected from the descending aorta (dPPG) for predicting low descending aortic stroke volume (dSV) level in cardiac surgical patients.

METHODS

Fifteen patients scheduled for elective cardiac surgery were enrolled in our study. A transesophageal echocardiography (TEE) probe with an attached oximetry sensor was placed into the esophagus for paired dPPG signal and descending aortic Doppler blood flow signal acquisition. Metrics, including alternating current (AC), direct current (DC), area under the curve (AUC) and width (W), were extracted from the dPPG signals. The TEE-measured dSV, which was defined as the blood flow through the descending aorta during a cardiac cycle, was chosen as the standard reference. A receiver operating characteristic (ROC) curve was built to evaluate the performance of dPPG metrics in predicting low dSV level, and dSV measuring agreement between TEE and dPPG was analyzed by the Bland-Altman method.

RESULTS

A total of 644 paired dPPG and Doppler signals of the descending aorta were acquired. Significant correlations were found between the dPPG metrics and TEE-measured dSV, and the correlation coefficients between TEE-measured dSV and AUC or AC were 0.64 and 0.66, respectively. AUC and AC values obviously decreased with the reduction of dSV level among the three groups (<20 mL, from 20-40 mL, and >40 mL). The areas under the ROC curve for AUC and AC in predicting low dSV level (<20 mL) were 0.85 and 0.88, respectively. Bland-Altman plot showed a small bias (0.02 mL) but a wide limit of agreement (-18.62 to 18.66 mL) in dSV measurement between dPPG and Doppler technology.

CONCLUSIONS

The AC and AUC extracted from the dPPG signal provided a sensitive and qualitative prediction for dSV level. The dSV value could not be accurately measured by dPPG metrics.

TRIAL REGISTRATION

Chinese Clinical Trials Register Identifier: ChiCTR-OCS-12002789.