Comparison of point-of-care peripheral perfusion assessment using pulse oximetry sensor with manual capillary refill time: clinical pilot study in the emergency department

Abstract

Background: Traditional capillary refill time (CRT) is a manual measurement that is commonly used by clinicians to identify deterioration in peripheral perfusion status. Our study compared a novel method of measuring peripheral perfusion using an investigational device with standardized visual CRT and tested the clinical usefulness of this investigational device, using an existing pulse oximetry sensor, in an emergency department (ED) setting.

Material and methods: An ED attending physician quantitatively measured CRT using a chronometer (standardized visual CRT). The pulse oximetry sensor was attached to the same hand. Values obtained using the device are referred to as blood refill time (BRT). These techniques were compared in its numbers with the Bland-Altman plot and the predictability of patients' admissions.

Results: Thirty ED patients were recruited. Mean CRT of ED patients was 1.9 ± 0.8 s, and there was a strong correlation with BRT (r = 0.723, p < 0.001). The Bland-Altman plot showed a proportional bias pattern. The ED physician identified 3 patients with abnormal CRT (> 3 s). Area under the receiver operator characteristic curve (AUC) of BRT to predict whether or not CRT was greater than 3 s was 0.82 (95% CI, 0.58-1.00). Intra-rater reliability of BRT was 0.88 (95% CI, 0.79-0.94) and that of CRT was 0.92 (0.85-0.96). Twelve patients were admitted to the hospital. AUC to predict patients' admissions was 0.67 (95% CI, 0.46-0.87) by BRT and 0.76 (0.58-0.94) by CRT.

Conclusions: BRT by a pulse oximetry sensor was an objective measurement as useful as the standardized CRT measured by the trained examiner with a chronometer at the bedside.

Keywords: Capillary refill time; Outcome prediction; Peripheral perfusion status; Visual assessment.

Conflict of interest statement

Competing interestsLSJ, JMF, TL, and JK have no known conflicts of interest associated with this study, and there has been no significant financial support for this work that could have influenced its outcome. Kota S., HH, NK, and SW are employees of Nihon Kohden Corporation and Nihon Kohden Innovation Center, Inc. There are no products in the market to declare. This does not alter the authors’ adherence to all the journal’s policies on sharing data and materials. Koichiro S. and LBB have a patent right of metabolic measurements in critically ill patients. Koichiro S. has grant/research support from Nihon Kohden Corp. LBB has a grant/research support from Philips Healthcare, the NIH, Nihon Kohden Corp., Zoll Medical Corp, PCORI, BrainCool, and United Therapeutics and owes patents including 7 issued patents and several pending patents involving the use of medical slurries as human coolant devices to create slurries, reperfusion cocktails, and measurement of respiratory quotient.

© The Author(s). 2019.

Figures

Fig. 1

Schema of the device BRT and the standardized visual CRT measurements. CRT was measured using a chronometer. The examiner compressed the fingertip for 5 s, signaled by “start compression” and “release compression” beep sounds. When the fingertip was released from compression, the examiner began the standardized visual CRT measurement. A pulse oximetry sensor was applied, and the fingertip was compressed and released 5 s after starting compression. There is a SD card slot on the back panel of the device. The waveforms of the light intensity were stored in the SD card. The data was calculated by a pre-fixed algorithm

Fig. 2

Scatter plot of device BRT as a function of standardized visual CRT. There was a strong correlation between CRT and BRT (Pearson correlation coefficient: 0.72, p <0.001). Black dots represent patients who were required admission, and white circular dots are patients who were discharged. BRT, blood refill time; CRT, capillary refill time

Fig. 3

The Bland-Altman Plot. The differences between the two techniques were plotted against the averages of the two techniques since there were no gold standard techniques. A proportional bias pattern was found between BRT and CRT

Fig. 4

Receiver operating curve of device BRT to predict abnormal standardized visual CRT. ROC analysis of BRT was performed to predict whether or not standardized visual CRT by the attending physician was greater than or less than 3.0 s. The area under the ROC curve was 0.82 (95% CI, 0.58–1.00). ROC, receiver operating curve; BRT, blood refill time; CRT, capillary refill time

Fig. 5

Receiver operating curve of device BRT and standardized visual CRT to predict ED patients’ admissions. The area under the ROC curve of standardized visual CRT was 0.76 (95% CI, 0.58–0.94) and that of device BRT was 0.67 (95% CI, 0.46–87). ROC, receiver operating curve; ED, emergency department; BRT, blood refill time; CRT, capillary refill time