Article

Blood refill time: Clinical bedside monitoring of peripheral blood perfusion using pulse oximetry sensor and mechanical compression

2310 Correspondence / American Journal of Emergency Medicine 36 (2018) 23072335

performance category level 3 to level 5, CPC3-5). The mean age of the population was 67 years old; 69% of the participants were male; 68% were residents; 15% had a shockable rhythm; the witness rate was 58%; the bystander CPR rate was 45%; the mean response time was

7.7 min; scene time interval was 12.3 min; and transport time was 6.5 min. We found that defibrillation by EMS, hyperkalemia (K N 5.0 mEq/L), and acidosis (pH b 7.35) were related to our primary and secondary outcomes in our parameters. The cut-off points were set for K and pH, close to the Upper limit of normal and lower limit of normal, respectively. We used Odds ratios calculated via adjusted po- tential confounding factor and positive predictive values (PPVs) and Negative predictive values to predict survival outcome. Obvious correlation was found in adjusted OR between death prior to discharge and K N 5 mEq/L (OR = 2.9, 95% CI: 1.97-5.23) and trend to unfavorable neurological outcome (OR = 3.1, 95% CI: 0.47-32.37). The acidosis (pH b 7.35) was related to death prior to discharge and poor CPC (OR = 6.3, 95% CI: 2.14-23.4; OR = 65.4, 95% CI: 6.87-395.5, respectively). Death

prior to discharge and unfavorable CPC, were strongly related with no

EMTs defibrillation at scene (OR = 5.3, 95% CI: 1.47-13.49; OR = 23.4, 95% CI: 3.46-234.3, respectively). OHCA patients with acidosis (pH b 7.35) even persistent high performance CPR were at a higher risk of death prior to discharge, and a unfavorable neurological outcome (PPVs of 77.2%, 95.8%, and 98.9%, respectively). Moreover, non- Shockable rhythms of AED at scene are also strongly related with sur- vival outcomes. Such patients were more likely to die before discharge and to have poor neurological outcomes (PPVs of 93.2% and 97.4%, respectively).

In past studies, Sauter found that a lower pH and a higher lactate level are associated with higher mortality rates in the emergency de- partment, predict in-hospital mortality and have a cardiac failure– related death probability of N0.5 [5-7]. Martinell showed that a non- shockable rhythm could be one predictor of poor outcomes in OHCA (other predictors were age of patients, location of cardiac arrest, time to basic life support to return of spontaneous circulation, corneal reflex, epinephrine treatment, acidosis, and PaCO2) and is associated with poor neurological outcomes [3]. Consistent with previous studies, we noticed that patients with initial Non-shockable rhythm at scene were at a higher risk to mortality and had an unfavorable neurological status. Our data suggests that acidosis and non-shockable rhythm at scene are important predictors of poor outcomes in OHCA patients. These findings were associated with a poor prognosis for cardiac arrest. If, after persis- tent high-quality CPR, OHCA patients have acidosis and no AED shock, they have higher probability to die prior to discharge and unfavorable CPC outcomes.

Chien-Hsiung Huang, MD

Li-Heng Tsai, MD Chan-Wei Kuo, MD

Department of Emergency Medicine, Chang Gung Memorial Hospital, and Chang Gung University College of Medicine, Linkou, Taiwan

Cheng-Yu Chien, MD Department of Emergency Medicine, Chang Gung Memorial Hospital, and Chang Gung University College of Medicine, Linkou, Taiwan Department of Emergency Medicine, Ton-Yen General Hospital,

Zhubei, Taiwan Corresponding author at: Department of Emergency Medicine, Chang Gung Memorial Hospital, No. 5 Fushing St., Gueishan Shiang,

Taoyuan, Taiwan.

E-mail address: [email protected]

28 March 2017

https://doi.org/10.1016/j.ajem.2018.04.002

References

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  2. Matos RI, Watson RS, Nadkarni VM, Huang HH, Berg RA, Meaney PA, et al. Duration of cardiopulmonary resuscitation and illness category impact survival and neurologic outcomes for in-hospital Pediatric cardiac arrests. Circulation 2013;127(4):442-51.
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  4. Yanagawa Y, Sakamoto T, Sato H. Relationship between laboratory findings and the outcome of cardiopulmonary arrest. Am J Emerg Med 2009;27(3):308-12.
  5. Sauter TC, Iten N, Schwab PR, Haulz WE, Ricklin ME, Exadaktylos AK. Out-of-hospital cardiac arrests in Switzerland: predictors for emergency department mortality in pa- tients with ROSC or on-going CPR on admission to the emergency department. PLoS One 2017;12(11):e0188180.
  6. Voicu S, Baud FJ, Malissin I, Deye N, Bihry N, Vivien B, et al. Can mortality due to cir- culatory failure in comatose out-of-hospital cardiac arrest patients be predicted on admission? A study in a retrospective derivation cohort validated in a prospective co- hort. J Crit Care 2016;32:56-62.
  7. Von Auenmueller KI, Christ M, Sasko BM, Trappe HJ. The value of arterial blood gas

    parameters for prediction of mortality in survivors of out-of-hospital cardiac arrest. J Emerg Trauma Shock 2017;10(3):134-9.

    Blood refill time: Clinical bedside monitoring of peripheral blood perfusion using pulse oximetry sensor and mechanical compression

    Prior presentations

    No

    Funding sources/Disclosures

    No

    Chi-Chun Lin, MD1

    Letter to the editor:

    Shock states can be detected rapidly by measuring the Capillary refill time or other measures of blood refill time (BRT) at the peripheral body parts of patients [1,2]. CRT is defined as the time required for a dis- tal capillary bed (e.g., fingertip) to regain its color after receiving enough compression to cause blanching [1,3]. CRT measured at the bedside is promulgated as an acceptable method to identify circulatory shock in critically ill patients [1,2]. However, since the measurement of CRT in- volves visual inspection of fingertip color, it is subject to inter-

    Department of Emergency Medicine, Chang Gung Memorial Hospital, and Chang Gung University College of Medicine, Linkou, Taiwan Department of Emergency Medicine, Ton-Yen General Hospital,

    Zhubei, Taiwan

    Cheng-Yu Lin, MD1

    Department of Emergency Medicine, Ton-Yen General Hospital,

    Zhubei, Taiwan

    1 Chi-Chun Lin and Cheng-Yu Lin are the first authors. The first two authors contributed equally to this paper.

    observer variability [4,5] and may be unreliable [1].

    The optical technology of infrared spectroscopy has been used to noninvasively measure the concentration of hemoglobin and oxygen sat- uration [6]. This technology is used in pulse oximetry and it can trace blood in tissues and be used to monitor BRT at the fingertips [2,7]. Since blood is a major component affecting Skin color (oxyhemoglobin is visually perceived as red and deoxyhemoglobin as blue), this technol- ogy can provide an alternative measure of skin color change that does not rely on visual inspection. Driven by the motivation to develop objec- tive and reliable measures of peripheral blood perfusion, we applied a new method of analysis that uses the pulse oximetry waveform. In

    Correspondence / American Journal of Emergency Medicine 36 (2018) 23072335 2311

    [side view]

    addition, we created a mechanical compression device that applies firm pressure to the fingertip. The combination of these two components al- lows for a precise, consistent, and objective measure of BRT.

    The purpose of this report is to show how the technology works in vivo. The Peripheral perfusion of a healthy volunteer subject was al- tered by cooling down the fingertip temperature, which was observed by our device. We measured BRT and fingertip temperature before and after changing the conditions wherein the subject’s hand was at Room temperature and then immersed in cold water. This report pro- vides clinicians a fine perspective of how blood flows when they per- form CRT measurements in clinical settings.

    The study was approved by University of Pennsylvania. All proce- dures were performed in a climate controlled environment at an ambi- ent temperature of 20-22 ?C. We measured BRT under two different conditions: hands at room temperature (ROOM TEMPERATURE) and immersed in cold water (COLD, 15 +- 2 ?C). The hand was immersed in a cold water bath for 5 min and then BRT was measured inside a tem- perature controlled box. A thermocouple sensor was attached to the fin- gertip as an adjunction to the BRT sensor.

    We defined BRT as the time required for a fingertip to recover its blood volume after release from compression. The device consists of two components (Fig. 1): a measuring device and a fingertip compres- sion device. A Pulse oximeter (OLV-3100, Nihon Kohden Corporation, Tokyo, Japan) was used as the measuring device to capture pulse oxim-

    [bladder inflation]

    [bladder deflation]

    etry waveforms. We used one wavelength (infrared light: 940 nm) to trace the change in hemoglobin concentration that reflects the recovery of blood flow to the fingertip.

    The fingertip compression device is composed of an air pump and a finger-cap with a polyurethane soft bladder. The air pump supplies air to the bladder when measuring BRT. The device controls the pressure of the inflated bladder at approximately 400 mm Hg. The duration of the bladder inflation is 5 s. The device deflates the bladder pressure 5 s after inflation. The thermocouple sensor was attached to the side of the fingertip in order to avoid interference with either the transmis- sion light from the pulse oximetry sensor or the fingernail compression with the polyurethane bladder (Fig. 2).

    Light intensity was recorded by the measuring device and the data were analyzed thereafter. The light intensity transmitted through the fingertip increases during compression as blood, which is the major ab- sorber of the light, is squeezed out of the fingertip. The compression phase is followed by the release phase during which the light intensity returns to the original level (Fig. 3). The measuring device captures the changes in the transmitted light intensity and records the wave- forms. The curve describing the recovery phase of the intensity

    Compression device (air pump)

    Measuring device

    (pulse oximeter)

    Finger-cap

    Pulse oximetry sensor

    Fig. 1. The investigation device is composed of two devices, which are modified pulse oximeter (measuring device) and compression device. A pulse oximetry sensor is attached to the measuring device and the compression device controls a bladder cuff inside a finger-cap.

    Fig. 2. The inflation and deflation of a polyurethane soft bladder cuff are controlled by the compression device.

    waveform (intensity returning to its original levels) is modeled as an ex- ponential decay using the least squares method. The time to achieve 90% return of the intensity was reported as BRT.

    Fig. 3A shows the light intensity curve from the fingertip at room temperature, where Fig. 3B shows the altered intensity curve at lowered fingertip temperature. BRT was 1.6 s with a fingertip temperature of

    29.3 ?C at room temperature. Our device successfully detected prolonged BRT after the fingertip temperature was cooled down to

    22.8 ?C and BRT at this condition was 5.8 s.

    Prolonged BRT induced by low fingertip temperature was observed well by our device. This technology provides clinicians a fine perspective of how blood flows through the fingertip following release from firm compression. Clinical implications of the technology include both contin- uous monitoring and spot check measurement. For example in ICU or op- eration room, the device can be used to measure BRT repeatedly. The trend in repeated measurements may provide patient’s information about the alteration of peripheral blood perfusion over time. For spot check measurements, the device can be used for detecting the alteration of peripheral blood perfusion in both acute and chronic conditions. It can be used in pre-hospital or emergency department for triaging patients. It can be also used for diagnosing peripheral artery disease. This technology provides an objective measure of peripheral perfusion and may provide more reliable results than a subjective visual assessment.

    Conflict of interest and sources of funding

    Research reported in this publication was supported by the research grant of Nihon Kohden Corporation.

    JK and MJC 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, KH, NK, and SW are employees of Nihon Kohden Corporation and Nihon Kohden Innova- tion Center, INC. There are no products in market to declare. This does not alter the authors’ adherence to all the journal’s policies on sharing data and materials. Koichiro S., JWL, and LBB have a patent right of met- abolic measurements in critically ill patients. Koichiro S. has a grant/re- search support from Nihon Kohden Corp. JWL has a grant/research support from Zoll Medical Corp., Philips Healthcare, Nihon Kohden

    2312 Correspondence / American Journal of Emergency Medicine 36 (2018) 23072335

    Inflation Deflation

    Compression

    (A) ROOM TEMPERATURE

    Skin temperature:

    29.3 ?C

    90% return

    Fitting curve (exponential decay)

    BRT : 1.6 s

    (B) COLD

    Skin temperature:

    22.8 ?C

    90% return

    BRT : 5.8 s

    Log10( infrared intensity )

    Time (sec)

    Log10( infrared intensity )

    Fig. 3. The measuring device captures the changes in the transmitted light intensity and records the waveforms. The time to achieve 90% return of the intensity was reported as BRT. BRT was measured at two different temperature conditions of a healthy subject.

    Corp., and the NIH, and owns intellectual property in resuscitation devices. LBB has a grant/research support from Philips Healthcare, the NIH, Nihon Kohden Corp., BeneChill Inc., Zoll Medical Corp, and Medtronic Foundation, patents in the areas of hypothermia induction and perfusion therapies, and inventor’s equity within Helar Tech LLC.

    Koichiro Shinozaki, MD, PhD

    The Feinstein Institute for Medical Research, Northwell Health System,

    Manhasset, NY, United States Corresponding author at: The Feinstein Institute for Medical Research, Northwell Health System, 350 Community Dr., Manhasset, NY 11030,

    United States.

    E-mail address: [email protected].

    Michael J. Capilupi, MS Department of Emergency Medicine, Northshore University Hospital, Northwell Health System, Manhasset, NY, United States

    Kota Saeki

    Nihon Kohden Innovation Center, Cambridge, MA, United States

    Hideaki Hirahara Katsuyuki Horie Naoki Kobayashi, PhD

    Nihon Kohden Corporation, Tokyo, Japan

    Steve Weisner

    Nihon Kohden Innovation Center, Cambridge, MA, United States

    Junhwan Kim, PhD Joshua W. Lampe, PhD

    The Feinstein Institute for Medical Research, Northwell Health System,

    Manhasset, NY, United States

    Lance B. Becker, MD, FAHA

    The Feinstein Institute for Medical Research, Northwell Health System,

    Manhasset, NY, United States Department of Emergency Medicine, Northshore University Hospital,

    Northwell Health System, Manhasset, NY, United States

    https://doi.org/10.1016/j.ajem.2018.04.006

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  8. Lima A, Bakker J. noninvasive monitoring of peripheral perfusion. Intensive Care Med 2005;31:1316-26.
  9. Schriger DL, Baraff L. Defining normal capillary refill: variation with age, sex, and tem- perature. Ann Emerg Med 1988;17:932-5.
  10. Alsma J, van Saase JLCM, Nanayakkara PWB, et al. The power of flash mob research: conducting a nationwide observational clinical study on capillary refill time in a single day. Chest 2017;151:1106-13.
  11. Espinoza ED, Welsh S, Dubin A. Lack of agreement between different observers and methods in the measurement of capillary refill time in healthy volunteers: an obser- vational study. Rev Bras Ter Intensiva 2014;26:269-76.
  12. Severinghaus JW, Honda Y. History of blood gas analysis. VII. Pulse oximetry. J Clin Monit 1987;3:135-8.
  13. Morimura N, Takahashi K, Doi T, et al. A pilot study of quantitative capillary refill time to identify high Blood lactate levels in critically ill patients. Emerg Med J 2015;32:444-8.

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