Electrical Bioimpedance for Cardiac Output Monitoring and Other Selected Indications

Number: 0472

Table Of Contents

Policy
Applicable CPT / HCPCS / ICD-10 Codes
Background
References


Policy

Scope of Policy

This Clinical Policy Bulletin addresses electrical bioimpedance for cardiac output monitoring and other selected indications.

  1. Medical Necessity

    1. Aetna considers cardiac monitoring using electrical bioimpedance devices medically necessary for any of the following uses, when medical history, physical examination, and standard assessment tools provide insufficient information and the treating physician has determined that thoracic electrical bioimpedance hemodynamic data are necessary for appropriate management of the member:

      1. Differentiation of cardiogenic from pulmonary causes of acute dyspnea; or
      2. Evaluation for rejection in persons with a heart transplant as a pre-determined alternative to a myocardial biopsy.  Medical necessity would need to be documented should a biopsy be performed after thoracic electrical bioimpedance; or
      3. Monitoring of response to medication changes in treatment of drug-resistant hypertension; or
      4. Optimization of atrio-ventricular (AV) interval for member with AV sequential cardiac pacemakers; or
      5. Optimization of fluid management in persons with congestive heart failure (CHF); or
      6. Outpatient monitoring of continuous inotropic therapy for persons with terminal CHF.
  2. Experimental and Investigational

    The following procedures are considered experimental and investigational because the effectiveness of these approaches has not been established:

    1. Electrical bioimpedance devices for lung capacity screening, and for detection and/or prognosis of cancers, and palliative cancer care; and evaluation of sarcopenia.
    2. Electrical impedance myography for evaluation of neuromuscular diseases (e.g., back pain and Duchenne muscular dystrophy) 
    3. Cardiac monitoring using electrical bioimpedance devices for any other indications including the following:
      1. Monitoring in congenital heart disease surgery; or
      2. Monitoring of persons during orthotopic liver transplantation; or 
      3. Monitoring of persons on a cardiopulmonary bypass machine as these devices do not render accurate measurements in this situation; or
      4. Monitoring of persons who have ischemic heart disease, but without overt cardiac failure, edema or arrhythmias; or
      5. Monitoring of persons with minute ventilation sensor function pacemakers as the device may adversely affect the functioning of this type of pacemaker; or
      6. Monitoring of persons with proven or suspected disease involving severe regurgitation of the aorta as these devices have not been proven to provide reliable measurements in this situation.
  3. Related Policies


Table:

CPT Codes / HCPCS Codes / ICD-10 Codes

Code Code Description

Information in the [brackets] below has been added for clarification purposes.   Codes requiring a 7th character are represented by "+":

CPT codes covered if selection criteria are met:

93701 Bioimpedance, thoracic, electrical

CPT codes not covered if selection criteria are met:

0358T Bioelectrical impedance analysis whole body composition assessment, with interpretation and report

Other CPT codes related to the CPB:

47135 Liver allotransplantation, orthotopic, partial or whole, from cadaver or living donor, any age

ICD-10 codes covered if selection criteria are met:

I09.81 Rheumatic heart failure
I10 - I16.2 Hypertensive diseases
I50.1 - I50.9 Heart failure
R06.00- R06.09 Dyspnea [acute]
T86.20 - T86.39 Complications of heart transplant
Z45.010 Encounter for checking and testing of cardiac pacemaker pulse generator [battery]
Z45.018 Encounter for adjustment and management of other part of cardiac pacemaker
Z48.21 Encounter for aftercare following heart transplant
Z48.280 Encounter for aftercare following heart-lung transplant
Z94.1 Heart transplant status
Z94.3 Heart and lungs transplant status
Z95.0 Presence of cardiac pacemaker

ICD-10 codes not covered for indications listed in the CPB (not all-inclusive):

C00.0 - C96.9 Malignant Neoplasms
G71.01 Duchenne or Becker muscular dystrophy
I20.0 - I25.9 Ischemic heart disease [without overt cardiac failure, edema, or arrhythmias]
I35.0 - I35.9 Nonrheumatic aortic valve disorders
M54.40 - M54.9 Dorsalgia
M62.84 Sarcopenia
Q20.0 - Q26.9 Bulbus cordis anomalies and anomalies of cardiac septal closure, other congenital anomalies of heart, other congenital anomalies of circulatory system, and anomalies of great veins [monitoring congenital heart disease surgery]
Z13.83 Encounter for screening for respiratory disorder NEC [lung capacity screening]
Z51.5 Encounter for palliative care [palliative cancer care]

Background

This policy is consistent with the Centers for Medicare & Medicaid Services (CMS), coverage guidelines on measurement of cardiac output (CO) with electrical bioimpedance.

Hemodynamic measurements of CO using thoracic electrical bioimpedance (TEB) devices, a form of plethysmography, relate change in thoracic electrical conductivity to changes in thoracic aortic blood volume and blood flow.  This form of impedance cardiography has been proposed as a simple and readily reproducible non-invasive technique for the determination of CO, specifically, stroke volume, contractility, systemic vascular resistance and thoracic fluid content.  Proponents claim that TEB can measure CO with the same clinical accuracy as either the Fick or thermodilution (TD) technique and that it offers the potential for sequential measurements of CO in patients for whom invasive measurements are impractical or contraindicated.  In addition, TEB can determine CO on a beat-to-beat basis or a predetermined intermittent frequency, which may, if required, permit a more rapid intervention than techniques using time-averaged data.  Its modest gain in popularity as a clinical technique appears to be related to its suggested usefulness as a monitor to detect changes in CO within individual subjects as an alternative to invasive techniques, especially when serial measurements are required.

Currently, there are 2 Food and Drug Administration-approved electrical bioimpedance devices in the marketplace: Bio Z® (Cardiodynamics, Inc.), and TEBCO (Thoracic Electrical Bioimpedance Cardiac Output, Hemo Sapiens, Inc.).

Gujjar and colleagues (2010) compared CO measured by TEB with that measured by multi-gated radionuclide equilibrium cardiography (RNEC).  Studies on CO were carried out sequentially at a single sitting by TEB and RNEC methods among patients with cardiac symptoms referred for radionuclide study as part of their evaluation.  Thoracic electrical bioimpedance-CO was measured by placing 2 pairs of electrodes on either side of neck and 2 other pairs on either side of the lower chest.  Stroke volume was estimated from the sequential changes in TEB induced by rhythmic aortic blood flow, using Kubicek equation; RNEC-CO was measured by intravenous injection of radio-active technitium-tagged red blood cells followed by electrocardiography-gated blood pool imaging over the chest (multiple-gated acquisition study).  Bland-Altman analysis was used to compare the measurements.  A total of 32 subjects with proven or suspected ischemic heart disease, but without overt cardiac failure, edema or arrhythmias were studied (male:female ratio was 26:6; mean age of 48 +/- 12 years).  The mean TEB-CO was 3.54 +/- 1.052 L/min and mean RNEC-CO was 3.907 +/- 0.952 L/min.  Correlation coefficient (r) for these measurements was 0.67 (p < 0.01), with bias: -0.421 L/min; precision: 1.557 L/min; and percentage error of measurement: 42.35 %.  The authors concluded that this study found a moderate correlation between TEB and RNEC methods of CO measurement.  They stated that further studies are needed to examine the relative utility of TEB in comparison with RNEC as well as other methods of CO measurement before considering its use in patients with ischemic heart disease.

Taylor et al (2011) evaluated the measurement of CO using continuous electrical bioimpedance cardiography (Physioflow; Neumedx, Philadelphia, PA) (CO(PF)) with a simultaneous direct Fick measurement (CO(FICK)) in children with congenital heart disease.  The Physioflow measured continuous real time CO in 15-second epochs and simultaneous measurement of CO by direct Fick (with mass spectrometry to assess VO(2)) were acquired.  A total fo 65 patients were recruited, and data from 56 (25 males) were adequate for analysis.  The median age at study was 3.5 years (range of 0.4 to 16.6 years), and the median body surface area was 0.62 m(2) (range of 0.31 to 1.71).  There were 25 of 56 (45 %) with uni-ventricular physiology.  A total of 19,228 Physioflow data points were available for the analysis of which 14,569 (76 %) were valid; 96 % of the invalid measurements were identified as artifacts by the device.  The average cardiac index of valid measurements was 3.09 +/- 0.72 L/min/m(2).  Compared with the Fick CO, the mean bias was -0.09 L/min, but the 95 % limits of agreement were -3.20 to +3.01 L/min/m(2).  Consequently, only 20 of 56 (36 %) of measurements were within 20 %, and 31 of 56 (55 %) of measurements were within 30 % of each other.  The authors concluded that compared with measurements made by direct Fick, CO measured using the Physioflow device was unreliable in anesthetized children with congenital heart disease.

Cardiac Monitoring Using Electrical Bioimpedance Devices During Orthotopic Liver Transplantation

Magliocca and colleagues (2018) noted that orthotopic liver transplantation (OLT) is characterized by significant intra-operative hemodynamic variability.  Accurate and real-time CO monitoring aids clinical decision-making during OLT.  These researchers compared accuracy, precision, and trending ability of CO estimation obtained non-invasively using pulse wave transit time (estimated continuous CO [esCCO; Nihon Kohden, Tokyo, Japan]) or thoracic bioimpedance (ICON; Osypka Medical GmbH, Berlin, Germany) to thermodilution CO (TDCO) measured with a pulmonary artery catheter.  A total of 19 patients undergoing OLT were enrolled; CO measurements were collected with esCCO, ICON, and thermodilution at 5 time points: (T1) pulmonary artery catheter insertion; (T2) surgical incision; (T3) portal reperfusion; (T4) hepatic arterial reperfusion; and (T5) abdominal closure.  The results were analyzed with Bland-Altman plot, percentage error (the percentage of the difference between the CO estimated with the non-invasive monitoring device and CO measured with the thermodilution technique), 4-quadrant plot with concordance rate (the percentage of the total number of points in the I and III quadrant of the 4-quadrant plot), and concordance correlation coefficient (a measure of how well the pairs of observations deviate from the 45-degree line of perfect agreement).  Although TDCO increased at T3 to T5, both esCCO and ICON failed to track the changes of CO with sufficient accuracy and precision.  The mean bias of esCCO and ICON compared to TDCO were -2.0 L/min (SD, ± 2.7 L/min) and -3.3 L/min (SD, ± 2.8 L/min), respectively.  The percentage error was 69 % for esCCO and 77 % for ICON.  The concordance correlation coefficient was 0.653 (95 % confidence interval [CI]: 0.283 to 0.853) for esCCO and 0.310 (95 % CI: -0.167 to 0.669) for ICON.  Nonetheless, esCCO and ICON exhibited reasonable trending ability of TDCO (concordance rate: 95 % [95 % CI: 88 to 100] and 100 % [95 % CI: 93 to 100]), respectively.  The mean bias was correlated with systemic vascular resistance (SVR) and arterial elastance (Ea) for esCCO (SVR, r = 0.610, 95 % CI: 0.216 to 0.833, p < 0.0001; Ea, r = 0.692, 95 % CI: 0.347 to 0.872; p < 0.0001) and ICON (SVR, r = 0.573, 95 % CI: 0.161 to 0.815, p < 0.0001; Ea, r = 0.612, 95 % CI: 0.219 to 0.834, p < 0.0001).  The authors concluded that non-invasive CO estimation with esCCO and ICON exhibited limited accuracy and precision, despite with reasonable trending ability, when compared to TDCO, during OLT.  These investigators stated that inaccuracy of esCCO and ICON is especially large when SVR and Ea were decreased during the neo-hepatic phase.  They stated that further refinement of the technology is desirable before non-invasive techniques could replace TDCO during OLT.

Electrical Bioimpedance Devices for Lung Capacity Screening

Pino and colleagues (2019) described the development and implementation at a prototype level of a wireless, low-cost system for the measurement of the electrical bioimpedance of the chest with 2 channels using the AD5933 in a bi-polar electrode configuration to measure lung volume variation.  A total of 15 volunteers were measured with the prototype, and the acquired signal presented the phases of the respiratory cycle, useful for the breathing rate calculation and for possible screening applications (e.g., lung capacity).

Segmental Bioelectrical Impedance Spectroscopy Devices for Body Composition Measurement

Cannon and Choi (2019) stated that whole-body bioelectrical impedance analysis for measuring body composition has been examined; however, its use may not be sensitive enough to changes in the trunk compared to changes in the limbs.  Measuring individual body segments could address this issue.  These researchers designed a segmental bioelectrical impedance spectroscopy device (SBISD) for body composition measurement and a prototype was implemented.  Compensation was performed to adjust the measured values to correct for a phase difference at high frequencies and to counteract the hook effect when measuring the human body.  The SBISD was used to measure 5 subjects and was compared against 3 existing analyzers.  For most segmental measurements, the SBISD was within 10 % of the R0 and R∞ values determined with a Bodystat Multiscan 5000 and an Impedimed SFB7.  The impedance values from the 3rd reference device, a Seca 514, differed significantly due to its 8-electrode measuring technique, meaning impedance measurements could not be compared directly.  These researchers stated that it is suggested that future work be performed to address the issues in measuring the trunk.  This might be addressed by increasing the number of current injection sites to increase the number of current paths so that the different areas with different makeups could be addressed.  With the current measuring part of the SBISD validated, further components could be focused on, like signal generation and data acquisition, to create a stand-alone device.

Detection / Prognosis of Cancers and Palliative Cancer Care

Gupta et al (2004) noted that bioelectrical impedance analysis (BIA) is an easy-to-use, non-invasive and reproducible technique to examine changes in body composition and nutritional status.  These investigators examined the prognostic role of phase angle in advanced pancreatic cancer.  They examined a case series of 58 stage-IV pancreatic cancer patients treated at Cancer Treatment Centers of America at Midwestern Regional Medical Center (Zion, IL) between January 2000 and July 2003.  BIA was carried out on all patients using a bioelectrical impedance analyzer that operated at 50-kHz.  The phase angle was calculated as capacitance (Xc)/resistance (R) and expressed in degrees.  The Kaplan-Meier method was used to calculate survival.  Cox proportional hazard models were constructed to examine the prognostic effect of phase angle independent of other clinical and nutritional variables.  The correlations between phase angle and traditional nutritional measures were assessed using Pearson and Spearman coefficients.  Patients with phase angle of less than 5.0 degrees had a median survival time of 6.3  months (95 % CI: 3.5 to 9.2; n = 29), while those with phase angle of greater than 5.0 degrees had a median survival time of 10.2 months (95 % CI: 9.6 to 10.8; n = 29); this difference was statistically significant (p = 0.02).  The authors concluded that the findings of this study showed that phase angle was a strong prognostic indicator in advanced pancreatic cancer.  Moreover, these researchers stated that similar studies in other cancer settings with larger sample sizes are needed to further validate the prognostic significance of the phase angle.

Sarode and associates (2015) stated that molecular alterations at the membrane, cytosol and nuclear level in cancer cells/tissues demonstrated variations in bioimpedance measure.  These researchers examined bioimpedance measurements between oral squamous cell carcinoma (OSCC) and normal tissue.  Study further involved clinicopathological correlation of bioimpedance values in OSCC.  The present study was comprised of 50 OSCC cases and 50 healthy control (HC) subjects.  A total of 4 electrical properties of OSCC were measured: Impedance (Z); Phase angle (9); Real part of impedance (R); and Imaginary part of impedance (X) at 6 frequencies: 20 Hz; 50 kHz; 1.3 MHz; 2.5 MHz; 3.7 MHz; and 5 MHz with the amplitude of the applied voltage limited to 200 mV.  The bioimpedance of OSCC as well as control group decreased as the measurement frequency increased from 20 Hz to 5 MHz.  The bioimpedance of OSCC was generally smaller than that of control group.  The mean bioimpedance of OSCC was found to be 4,493 ± 216.9 Ω and 370.0 ± 26.45 Ω and that of control group was 15,490 ± 287.2 Ω and 817.1 ± 7.227 Ω at frequencies of 20 Hz and 50 MHz, respectively which was statistically significant (p < 0.0001).  The values of phase angle, real and imaginary part of impedance of OSCC group were found to be significantly larger than that of control group (p < 0.0001) at 20 Hz and 50 MHz frequency.  Impedance values of OSCC decreased from stages I to IV.  Statistically significant differences in values of impedance were observed between stage I (4,881 ± 262.5 Ω) and IV (4,500 ± 181.6 Ω) (p = 0.0060) and also between stage I (4,881 ± 262.5 Ω) and III (4,376 ± 121.3 Ω) at frequency of 20 Hz (p-value 0.0005).  Statistically significant differences in values of impedance were also observed between well-differentiated (4,557 ± 260.8) and poorly-differentiated OSCC (4,347 ± 76.12) (p = 0.0004) but only at 20-Hz frequency.  The authors concluded that bioimpedance at a particular frequency showed significant alteration in OSCC tissue as compared to control; thus, it could be a potentially promising technique for detection of OSCC.

Hui et al (2017) examined the association of phase angle obtained from multi-frequency BIA (MF-BIA) with overall survival (OS) in patients with advanced cancer.  These investigators included consecutive patients with advanced cancer who had an outpatient palliative care consultation; MF-BIA was carried out to evaluate phase angle at 3 different frequencies (5-, 50-, and 250-kHz) on each hemi-body (right/left).  Survival analysis was carried out by means of the Kaplan-Meier method, log-rank test, and multi-variate Cox regression analysis.  Among 366 patients, the median OS was 250 days (95 % CI: 191 to 303 days).  The mean phase angle for 5-, 50-, and 250-kHz were 2.2°, 4.4°, and 4.2° on the right and 2.0°, 4.2° and 4.1° on the left, respectively.  For all 6 phase angles, a lower value was significantly associated with a poorer OS (p < 0.001).  After adjusting for cancer type, performance status, weight loss, and inflammatory markers, phase angle remained independently associated with OS (hazard ratio [HR] 0.85 per degree increase, 95 % CI: 0.72 to 0.99; p = 0.048).  The authors concluded that phase angle represented a novel objective prognostic factor in outpatient palliative cancer care setting, regardless of frequency and body sides.  Moreover, these researchers stated that future studies are needed to examine how phase angle values could be used to inform both patients with advanced cancer and clinicians in decision-making on the many complex issues in the last months of life, such as palliative procedures, chemotherapy and nutrition.

The authors stated that this study had several drawbacks.  First, the retrospective nature of data gathering meant that they were unable to include several key prognostic variables such as the Palliative Prognostic Score and C-reactive protein (CRP).  Second, patients needed to be able to stand on the scale for a few minutes to use the Inbody 720 device; and a few individuals seen at the outpatient clinic were excluded due to muscle weakness.  Therefore, the Inbody 720 device may not be feasible in the inpatient setting, although other MF-BIAs are available that could be used with patient in a supine position.

Pathiraja and colleagues (2020) noted that recent research has begun to emerge into the potential uses of electrical impedance technology in the detection and diagnosis of pre-malignant and malignant conditions.  In a systematic review, these investigators examined the clinical application of electrical impedance technology in the detection of malignant neoplasms.  They searched Embase Classic, Embase and Medline databases from 1980 to February 22, 2018 to identify studies reporting on the use of bioimpedance technology in the detection of pre-malignant and malignant conditions.  The ability to distinguish between tissue types was defined as the primary endpoint, and other points of interest were also reported.  A total of 731 articles were identified, of which 51 reported sufficient data for analysis.  These studies covered 16 different cancer subtypes in a total of 7,035 patients.  As the studies took various formats, a qualitative analysis of each cancer subtype's data was undertaken.  All the studies were able to show differences in electrical impedance and/or related metrics between malignant and normal tissue.  The authors concluded that electrical impedance technology provided a novel method for the detection of malignant tissue, with large studies of cervical, prostate, skin and breast cancers showing encouraging results.  Moreover, these researchers stated that while these studies provided promising insights into the potential of this technology as an adjunct in screening, diagnosis and intra-operative margin assessment, customized development as well as multi-center clinical trials are needed before it can be used reliably in the clinical detection of malignant tissue.

The authors stated that 1 major drawback of this review was that several of the studies (25/51) included in this systematic review used ex-vivo specimens; only the cervical, cutaneous and oral lesion studies exclusively looked at electrical impedance in pre-malignant and normal tissue.  One of the breast studies included a comparison between in-vivo and ex-vivo measurements of specimens and showed that various electrical impedance spectroscopy (EIS) metrics (conductivity and permittivity) clearly decreased as measurements were taken ex-vivo.  It is known that as soon as tissue is resected and loses its blood supply, the fluid status of the tissue changes, which in turn would affect the electrical conductivity and impedance properties of the tissue.  However, it is understandable that in these initial proof-of-concept studies where novel technology and techniques are being used for the first time, ex-vivo studies precede more realistic in-vivo studies.  Thus, further research examining the electrical impedance of these tissue types in-vivo would be needed before an assessment of the effectiveness of this technology could be made.  Another drawback was that many of the studies included had a small sample size, and had each reported on different outcomes, which therefore could not be statistically analyzed as a whole.  This heterogeneity was increased by the studies having multiple variables, such as frequency ranges applied by the studies’ tools, the specific impedance tool used as well as unreported ischemic times.  For the cancer types that have many studies reporting findings, the studies had often been conducted at the same institution using the same methodology but had not reported quantitative statistics that could be pooled for analysis.  Consequently, more meaningful statistical analysis of the results could not be reported at this early stage.  Nevertheless, qualitative analysis of the results was still possible, from which significant conclusions and further work can be planned.

Mansouri and co-workers (2020) noted that early detection of breast cancer saves lives; however, existing detecting techniques are invasive.  Electrical bioimpedance is a non-invasive approach and has a high diagnostic potential; and an impedance value different from the normal can predict a physiological abnormality.  These researchers employed a designed bioimpedance device for early detection of breast cancer.  A low-frequency current (1 kHz, 0.9 mA) was injected to each breast to measure the extracellular resistances.  The resistances of the 2 breasts were then measured, and if there was a significant difference, warning was displayed.  The performance was tested on a set of reference resistors, and the validation was carried out in-vitro on (NaCl) solutions and in-vivo on a group of 40 volunteer women.  The results confirmed that the electrical conductivity of an ionic solution was proportional to its concentration.  The concentration and the resistance were strongly correlated (correlation coefficient of 0.97).  The accuracy and the repeatability of the measures were satisfactory.  Early detection meant that clinicians could detect small extracellular concentration variations into the breast (from 0.6 g/L).  In-vivo measurements made it possible to set the threshold at 50 Ohm.  If the difference between the 2 measured breast resistances was greater than this threshold, the patient would be advised to consult a doctor promptly.  The authors concluded that the difference between measured resistances of the right and left breast was a pertinent parameter for early detection of cancer.  The lowest resistance value (RR or RL) could provide information on the breast affected by the cancer (right or left).  These investigators noted that various improvements in the system are possible; but the results are encouraging.  In the future, this system could be integrated into a bra.

These researchers stated that in order to improve their work, they will first perform a measurement campaign on patients with breast cancer as well as on healthy subjects.  This measurement campaign will improve their system and choose the best threshold.  Then, these investigators will increase the number of electrodes to accurately locate the tumor in the affected breast and to create an image that will be displayed on the smartphone.  This will allow having a smart mammograph by the electrical bioimpedance method.

Aleixo and colleagues (2020) stated that the loss of muscle mass, known as sarcopenia, is a natural process of aging that is associated with adverse health outcomes regardless of age.  Because cancer is a disease of aging, interest in sarcopenia and its potential impact in multiple cancer populations has increased significantly.  Bioelectrical impedance analysis is a guideline-accepted method for sarcopenia detection.  In a systematic review, these investigators examined the literature pertaining to BIA use in the detection of sarcopenia in adults with cancer.  They carried out a search of the literature for randomized controlled trials (RCTs) and observational studies using Medline, Cochrane CENTRAL, and Embase, through July 15, 2019.  For study inclusion, patients had to be aged 18 years or older and diagnosed with solid or hematological neoplasia, and BIA had to be used to detect sarcopenia.  A total of 5,045 articles were identified, of which 24 studies were selected for inclusion in the review (total number of 3,607 patients).  In 5 studies, BIA was rated comparable to axial computed tomography (CT) scan, calf circumference, or grip strength for sarcopenia screening.  In 14 studies, BIA-identified sarcopenia was associated with adverse clinical outcomes.  The authors concluded that the findings of this review suggested that BIA‐assessed sarcopenia could be of prognostic value for multiple types of cancer.  BIA is an affordable, portable, easy‐to‐use, effective method for detecting sarcopenia in adults with cancer before treatment and a viable alternative to CT, dual‐energy x‐ray absorptiometry (DXA) scans, and magnetic resonance imaging (MRI) in clinical practice.  These researchers stated that imaging studies have higher accuracy compared with BIA and remain the gold standard; however, their implementation complexity and cost reduce their applicability in oncologic clinical practice.  They stated that further research is needed to improve the understanding of how routine assessment of sarcopenia can lead to interventions that improve outcomes in patients with cancer.

The authors stated that the drawbacks of this study reflected the limitations of using BIA to identify sarcopenia.  Different scales, different BIA equipment, different equations and cut‐points for determining sarcopenia, and different types of cancers precluded meta‐analysis of our data.  Furthermore, a majority of patients included in this review were older, which may have influenced their hydration status and body mass index (BMI) at the time of BIA measurement.  This is a common concern for the use of BIA and is especially relevant in cancers that cause severe weight loss and hydration changes, such as gastro-intestinal (GI) and head and neck (H&N) cancers.  Interestingly, GI cancers were the most common type of cancer in this review, which confirmed that even in these patient populations, BIA can be effective when appropriate protocols are followed . It would also be informative to conduct BIA measures in a younger patient population to examine if outcomes remain similar to the older patients included in this review.  Another concern was that some studies had shown that BIA should be used with caution in morbidly obese patients (BMI greater than 35 kg/m2), as it may under-estimate body fat and over-estimate fat free mass.  These researchers also noted that not all societies accept BIA as a valuable method for lean mass estimation.  Recently, the Society of Sarcopenia Cachexia and Wasting Disorders (SCWD) recommended that physicians should make a formal diagnosis of sarcopenia using grip strength or chair stand and, if possible, a measurement of fat‐free mass.  SCWD recommends appendicular skeletal muscle per height squared estimated by DXA, but they also recognize that CT, BIA, ultrasound (US), or creatine dilution techniques may become as good or more accurate for estimating muscle mass in the future.  Furthermore, BIA was not strongly endorsed in the latest EWGSOP report for measuring muscle mass; however, it was recognized that BIA's portability, affordability, and availability made this measure a feasible tool for estimating muscle mass in many care settings.  These investigators also noted that Newcastle Ottawa Scale analysis rated 38 % of the studies as only fair quality, which indicated higher risk for bias.  Despite the wide spectrum of cancers included in this review, some types of cancer such as breast, melanoma, and pancreatic did not have BIA studies for sarcopenia.  Finally, there was a high degree of heterogeneity among the included studies.  BIA‐based estimates of sarcopenia can be influenced by the patient's ethnicity (note the differences in European and Asian guidelines pertaining to the use of BIA for sarcopenia detection), medical condition and co-morbidities, hydration, exercise history, and food intake.  These factors could influence the accuracy of BIA‐determined sarcopenia among patients, even within the same patient at different time points of the day.  It had been shown that multi-frequency BIA (using a combination of low and high frequencies to calculate intercellular water, extracellular water, and total body water) had a greater accuracy than single‐frequency BIA (which generally uses a 50‐kHz current that passes through extracellular and intracellular fluids for the estimation of total body water), especially in obese and under-weight patients.  These variables need to be considered in establishing optimal pretest preparation, selecting the equation to be used by the BIA software, and determining sarcopenia cutpoints for a specific patient population in order to reduce potential inaccuracies in BIA measurements.  It is suggested that in clinical practice, patients should receive instructions pertaining to hydration, food consumption, and exercise prior to the BIA, such as not drinking excessive amounts of water or performing vigorous physical activity 2 to 3 hours prior to the evaluation.  This is not unlike instructions provided to patients before tests such as a routine blood pressure measurement.  These investigators stated that the value of BIA would also be greatly enhanced by an international consensus on cut-points for BIA‐assessed sarcopenia in different cancer populations.  Furthermore, additional research is needed to examine if BIA is useful or accurate for detecting low lean muscle mass for the diagnosis of sarcopenia in patients with cancers that were under‐represented in this review, such as breast cancer and melanoma, and in younger patients.  In addition, further research is needed to examine the potential benefits of BIA‐generated data for treatment decisions and overall cancer care.

Lee et al (2021) stated that BIA provides information on body composition and nutritional status; however, it is unclear if the pre-operative edema index or phase angle predicts post-operative complication or mortality in patients with hepato-cellular carcinoma (HCC).  These investigators examined if pre-operative BIA could predict post-operative complications and survival in patients with HCC.  A total of 79 patients who underwent hepatectomy for HCC were prospectively enrolled and BIA was carried out before surgery.  Post-operative ascites or acute kidney injury (AKI) and patients' survival were monitored following surgery.  Among 79 patients, 35 (44.3 %) developed ascites or AKI following hepatectomy.  In multi-variate analysis, a high pre-operative edema index (extracellular water/total body water) (greater than 0.384) (odds ratio [OR] 3.96; 95 % CI: 1.03 to 15.17; p = 0.045) and higher fluid infusion during surgery (OR 1.36; 95 % CI: 1.04 to 1.79; p = 0.026) were identified as significant risk factors for ascites or AKI following hepatectomy.  Subgroup analyses showed that the edema index was a significant predictor of ascites or AKI in patients with cirrhosis.  Tumor size was the only significant predictive factor for short-term survival after hepatectomy.  The authors concluded that the pre-operative edema index using BIA could be used as a predictor of post-hepatectomy complication, especially in patients with liver cirrhosis.

The authors stated that this study had several drawbacks.  Although the study was carried out on patients with early-stage operable HCC, they did not control for HCC stage in the study.  Similarly, although the study included only patients with preserved liver function who underwent surgery, the study population had various etiologies.  These factors could also have affected post-operative morbidity.  Furthermore, this study could not consider all other factors that could affect the edema index.

Cardiac Output Measurement in Neonates and Children

In a systematical review and meta-analyze, Mansfield and colleagues (2022) examined the validity of electrical bioimpedance-based non-invasive CO monitoring in pediatrics compared with standard methods such as thermodilution and echocardiography.  These investigators carried out systematic searches in Medline and Embase (2000 to 2019).  Method-comparison studies of trans-thoracic electrical velocimetry or whole body electrical bioimpedance versus standard CO monitoring methods in children (0 to 18 years of age) were included.  Two reviewers independently carried out study selection, data extraction, and risk of bias assessment.  Mean differences of CO, stroke volume (SV), or cardiac index measurements were pooled using a random-effects model (R Core Team, R Foundation for Statistical Computing, Vienna, Austria, 2019).  Bland-Altman statistics assessing agreement between devices and author conclusions regarding inferiority/non-inferiority were extracted.  A total of 29 of 649 identified studies were included in the qualitative analysis, and 25 studies in the meta-analyses.  No significant difference was observed between means of CO, SV, and cardiac index measurements, except in exclusively neonatal/infant studies reporting SV (mean difference [MD], 1.00 ml; 95 % CI: 0.23 to 1.77).  Median percentage error in child/adolescent studies approached acceptability (percentage error less than or equal to 30 %) for CO in L/min (31 %; range of 13 % to 158 %) and SV in ml (26 %; range of 14 % to 27 %), but not in neonatal/infant studies (45 %; range of 29 % to 53 % and 45 %; range of 28 % to 70 %, respectively); 20 of 29 studies concluded that trans-thoracic electrical velocimetry/whole body electrical bioimpedance was non-inferior.  Trans-thoracic electrical velocimetry was considered inferior in 6 of 9 studies with heterogeneous congenital heart disease populations.  The authors concluded that these meta-analyses demonstrated no significant difference between means of compared devices (except in neonatal SV studies).  The wide range of percentage error reported may be due to heterogeneity of study designs, devices, and populations included.  Trans-thoracic electrical velocimetry/whole body electrical bioimpedance may be acceptable for use in child/adolescent populations, but validity in neonates and congenital heart disease patients remains uncertain.  These researchers stated that larger studies in specific clinical contexts with standardized methodologies are needed.

Van Wyk et al (2022) stated that electrical biosensing technology (EBT) is an umbrella term for non-invasive technology using the body's fluctuating resistance to electrical current flow to CO.  Monitoring CO in neonates may allow for timely recognition of hemodynamic compromise and allow for prompt therapy; thus, mitigating adverse outcomes.  For a new technology to be safely used in the clinical environment for therapeutic decisions, it must be proven to be accurate, precise and be able to track temporal changes.  In a systematic review, these investigators examined studies that described the accuracy, precision, and trending ability of EBT to non-invasively monitor Left ventricular CO and/or SV in neonates.  Studies were identified from PubMed NCBI, SCOPUS, and EBSCOHost up to November 2021, where EBT technologies were analyzed in neonates, in comparison to a reference technology.  Outcome measures were bias, limits of agreement, percentage error for agreement studies and data from 4-quadrant and polar plots for trending studies.  Effect direction plots were used to present results.  A total of 15 neonatal studies were identified, 14 for agreement and 1 for trending analysis.  Only thoracic electrical biosensing technology (TEBT), with trans-thoracic echocardiography (TTE) as the comparator, studies were available for analyzes.  High heterogeneity existed between studies.  An equal number of studies showed over- and under-estimation of left ventricular output parameters.  All studies showed small bias, wide limits of agreement, with most studies having a percentage error of greater than 30 %.  Sub-analyses for respiratory support mode, cardiac anomalies and type of technology showed similar results.  The single trending study showed poor concordance, high angular bias, and poor angular concordance.  The authors concluded that overall, TEBT showed reasonable accuracy, poor precision, and non-interchangeability with TTE.  However, high heterogeneity hampered proper analysis.  These researchers stated that TEBT should be used with caution in the neonatal population for monitoring and determining therapeutic interventions.  The use of TEBT trend monitoring has not been adequately studied and requires further investigation in future trials.

Electrical Bioimpedance for Evaluation of Sarcopenia

Di Vincenzo and colleagues (2021) bioelectrical impedance analysis-derived phase angle (PhA) has been gaining attention in the clinical evaluation of nutritional status because it is thought to be a proxy of water distribution and body cell mass; it is also associated to muscle strength and is an effective predictor of different clinical outcomes.  Since an association may be expected between PhA and sarcopenia (defined by low skeletal muscle mass and impaired muscle function), the aim of this systematic review was to evaluate changes in PhA due to sarcopenia; prevalence of sarcopenia according to PhA values; derivation of PhA cut-offs for detecting sarcopenia; and  sarcopenia and PhA as predictors of clinical outcomes.  These investigators carried out a systematic research on electronic databases (PubMed, Embase, Scopus and Web of Science) from inception to January 31, 2020 according to PRISMA checklist.  Using PICOS strategy, "P" corresponded to participants of any age, gender or ethnicity, "I" designated diagnosis of sarcopenia, "C" indicated subjects without sarcopenia, "O" corresponded to PhA, and "S" selected all study types.  Methodological quality was assessed using the National Institute of Health (NIH) quality assessment tool.  Through the initial literature search and after removing duplicates and excluding papers by screening titles and abstracts, a total of 79 potentially relevant studies were examined; 13 studies (7,668 subjects) met the inclusion criteria.  The overall risk of bias was low.  Sarcopenia was associated with a significant lower PhA in 7 of 8 studies, while 5 of 6 studies reported a high prevalence of sarcopenia was in patients with low PhA.  Different cut-off point values from 4.05° to 5.05° have been derived for the identification of sarcopenia.  PhA and sarcopenia were independent predictors of survival in cancer patients and geriatric hospitalized patients.  The authors concluded that data from the selected papers demonstrated that PhA was decreased in sarcopenic subjects and the prevalence of sarcopenia was higher in subjects with low PhA.  Moreover, these researchers stated that further studies are needed to examine if PhA may or should be used as an additional parameter for detecting low muscle quality and identifying sarcopenia.

The authors stated that this study had several drawbacks.  According to inclusion criteria, a relatively small number of studies was selected (only 1 multi-center study), which in some cases had a small sample size.  Furthermore, there are no definite data for certain types of patients who are expected to suffer from sarcopenia, i.e., those with heart failure, diabetes, etc.  A single study was available for cancer, chronic obstructive pulmonary disease (COPD) and cirrhosis, making difficult to draw any specific conclusion.  In addition, the evaluation of sarcopenia was a secondary objective in many of the studies.  Also, comparisons between studies may be hampered by discrepancies in the characteristics of study groups and by using different definitions of sarcopenia; only 1 study used the recent EWGSOP 2019 criteria.  Moreover, there was a certain degree of uncertainty due to considering overall sarcopenia or severe versus non-severe sarcopenia.  Muscle mass was determined using a criterion method (DXA) just in 2 studies.  In addition, the definition of cut-off values has been based on relatively small samples, and no validation studies have been performed in other independent groups of patients.  Finally, there were only few data available on PhA and sarcopenia as possible concurrent predictors of hard clinical outcomes.

Electrical Impedance Myography for Evaluation of Neuromuscular Diseases

Wang and associates (2019) examined the potential value of electrical impedance myography (EIM) for evaluating lumbosacral paraspinal muscle (LPM) condition in lower back pain (LBP) patients.  Standard methods for examining the condition of LPMs, such as MRI, are inconvenient and expensive.  One tool that could be useful for this purpose is EIM, a technique that can be carried out rapidly at the bedside.  After undergoing a screening history and examination, subjects were studied with the mView EIM device.  Bilateral LPMs were measured 3 times each and the 2 closest sets of measurements averaged on each side.  Data analysis included non-parametric 2-group comparisons between healthy subjects and back pain patients, receiver-operating curve (ROC) analyses, and correlation analyses to age and BMI.  A total of 86 healthy individuals (median age of (inter-quartile range) (IQR), 45.5 years (30.3 to 56.0), 42 men, 44 women) and 47 LBP (median age of 51.0 years (39.5 to 57.5), 21 men, 26 women) were enrolled.  Median EIM 100-kHz phase was lower in the LBP patients (9.3° (IQR 8.4° to 10.6°) versus 11.4° (IQR 9.4° to13.0°), p = 0.0007).  Significantly increased normalized side-to-side differences were present for all 3 EIM variables (e.g., median 100-kHz phase 0.15 (IQR 0.07 to 0.31 in LBP patients versus 0.09 (IQR 0.04 to 0.17) in healthy individuals).  A significant correlation between 100-kHz EIM phase and reactance was found with age (R spearman = -0.46, p = 0.0002 and R spearman = -0.440, p = 0.0003) but not for resistance.  The authors concluded that the findings of this study provided proof-of-principle that EIM measurements, on a population basis, detect changes in muscle in patients with LBP, and has potential to serve as a rapid and convenient approach for quantifying LPM health going forward.  These researchers stated that given the ongoing challenges in effectively managing and resolving LBP, as well as the severity of the opioid epidemic in the U.S., methods that can provide insight into back health, and that can potentially serve as indices of therapy response, may be of great value in the years to come.

The authors stated that this study had several drawbacks.  First, these researchers did not conduct a more extensive analysis of the underlying causes of LBP in this population.  Second, they provided no other quantification of severity of the LBP or its duration.  Their main focus was very much on examining differences between groups as a 1st step in this direction and not attempting to use their measures as a surrogate of individual pain or disability.  Third, these investigators did not provide imaging or other quantitative indices of paraspinal muscle condition.  This has been carried out previously using CT.  Fourth, the EIM system, the mView, remains a relatively early version of EIM technology, and suffered from a number of limitations including noise and fairly rudimentary electrode array design.  Newer versions of the technology, now in development, are likely to provide more robust and consistent data.  FFinally, these findings represented a single snap-shot in time and these researchers could not tell how these EIM values evolve over time or potentially may respond to therapy.  In addition to these limitations, the focus of this study has been in using a single frequency (100-kHz) in these measurements.  Multi-frequency data were obtained as well; therefore, future studies should incorporate these additional data as well as machine learning algorithms to fully employ the very rich impedance data set being obtained.

In a longitudinal, non-blinded, multi-center, cohort study, Leitner and co-workers (2020) examined the sensitivity of EIM to disease progression in both ambulatory and non-ambulatory boys with Duchenne muscular dystrophy (DMD).  This trial included 29 ambulatory and 15 non-ambulatory boys with DMD and age-similar healthy boys.  Participants were followed for up to 1 year and assessed using the Myolex mView EIM system.  In the ambulatory group, EIM 100-kHz resistance values showed significant change compared to the healthy boys.  For example, in lower extremity muscles, the average change in EIM 100-kHz resistance values over 12 months led to an estimated effect size of 1.58.  Based on these results, 26 DMD patients/arm would be needed for a 12-month clinical trial assuming a 50 % treatment effect.  In non-ambulatory boys, EIM changes were greater in upper limb muscles.  For example, biceps at 100-kHz resistance gave an estimated effect size of 1.92 at 12 months.  Based on these results, 18 non-ambulatory DMD patients/arm would be needed for a 12-month clinical trial assuming a 50 % treatment effect.  Longitudinal changes in the 100-kHz resistance values for the ambulatory boys correlated with the longitudinal changes in the timed supine-to-stand test.  EIM was well-tolerated throughout the study.  The authors concluded that the findings of this study supported that EIM 100-kHz resistance was sensitive to DMD progression in both ambulatory and non-ambulatory boys.  Moreover, these investigators stated that EIM remains a relatively new technique and its application in DMD even more recent.  Only through the incorporation of this technology into future clinical trials can researchers fully understand and refine EIM’s role in DMD in finding effective therapies for this disease.  Based on these promising findings, the authors encouraged academic researchers and the pharmaceutical industry alike to incorporate the use of EIM into their future DMD clinical trials.

The authors stated that there were several limitations to this study, with the most obvious of these being the limited amount of 12‐month data obtained.  This was entirely due to the unexpected funding limitations that required these researchers to close the study several months earlier than anticipated and not due to any technical or procedural concerns.  A 2nd major limitation was the absence of other dedicated upper extremity functional measures outside of the Brooke.  Specifically, these investigators did not include the PUL, which only became available after this study was designed.  Third, these researchers were unable to examine the impact of steroid initiation given the very few children who switched status during the study.  Fourth, many of the functional measures these investigators assessed changed minimally in both groups over the relatively short study time duration of 6 to 12 months; thus, seeking correlations between EIM changes and functional changes over time was a challenge.  However, this limitation also spoke to the limitations in the sensitivity and high variability of several of the current set of widely used functional measures and suggested the need to go beyond functional measures alone in assessing DMD progression.  Finally, these researchers have assumed linearity and the absence of ceiling or floor effects; clearly, the appropriateness of these assumptions can only be determined with additional studies.

Cebrian-Ponce and colleagues (2021) noted that EIM is a non-invasive method that provides information regarding muscle health and changes that occur within it.  EIM is based on the analysis of 3 impedance variables: resistance, reactance, and the phase angle.  In a systematic review, these investigators examined available literature to provide a deeper insight into the scope and range of applications of EIM in health and physical exercise.  They carried out systematic literature searches on PubMed, Scopus, SPORTDiscus and Web of Science up to September 2020 on any empirical investigations using localized bioimpedance devices to perform EIM within health and physical exercise contexts.  The search included healthy individuals, elite soccer players with skeletal muscle injury, and subjects with primary sarcopenia.  The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) checklist was employed to develop the systematic review protocol.  The quality and risk of bias of the studies included were assessed with the AQUA tool.  A total of 19 eligible original articles were included in this review, which were separated into 3 tables according to the nature of the study.  The 1st table included 6 studies on the bioelectrical characterization of muscle.  The 2nd table included 5 studies analyzing muscle changes in injured elite soccer players.  The 3rd table included studies on the short-, medium-, and long-term bioelectrical adaptations to physical exercise.  The authors concluded that EIM has been used for the evaluation of the muscle condition in the clinical field over the last few years, especially in different neuromuscular diseases.  Moreover, these researchers stated that EMI can also play an important role in other contexts as an alternative to complex and expensive methods such as MRI; however, further research is needed.  They stated that the main step in establishing EIM as a valid tool in the scientific field is to standardize the protocol for performing impedance assessments.

The authors stated that there were several drawbacks associated with the analysis of the literature on the use of EIM in health and physical exercise were.  First, the inconsistency between the EIM assessment techniques, with different protocols and devices used.  Second, the difficulty in controlling multiple sources of error that may influence the bioelectrical signal.  Third, the scarcity of scientific information regarding EIM not related to the study of neuromuscular diseases.  Fourth, the lack of analysis of some impedance parameters that could be of interest.  Fifth, the limited scientific evidence explaining the bioelectrical behavior of human tissues induced by exercise.

Wang et al (2022) stated that LPM is important in spinal stabilization in patients with chronic LBP (CLBP); however, the electrical properties of LPM in patients with CLBP remain unclear.  EIM is a novel and non-invasive technique that provides a simple quantitative evaluation of electrical properties of the LPM.  These researchers employed EIM to evaluate the electrical properties of the LPM between patients with CLBP and healthy control (HC).  A total of 30 subjects (15 CLBP patients; 15 healthy controls) were enrolled in the study.  Subjects in the CLBP group were asked to complete the visual analog scale (VAS), Oswestry Disability Index (ODI), and Roland-Morris Disability Questionnaire (RDQ) to evaluate the pain intensity and disability in daily life.  Independent sample t-tests were adopted to analyze the basic characteristics between the 2 groups.  At 5-, 50-, 100-, and 200-kHz current frequencies, the electrical properties were measured on each side of the LPM.  The EIM parameters of resistance (R), reactance (X), PA, and Z value were analyzed by 1-way analysis of variance (ANOVA), with age as co-variate.  Spearman's rank correlation coefficient analysis was employed to examine the relationships between the questionnaires and the EIM parameters.  The R and Z values of bilateral LPM in the CLBP group were significantly larger than those in the HC group; the PA decreased; and the X did not change at these 4 tested current frequencies.  At 5-kHz, Z and R on the right side were non-significantly different between patients and HCs.  Correlation analysis showed that at 50-kHz, ODI and RDQ scores correlated negatively with the R of the bilateral LPM (r = 0.523, r = 0.581, respectively; p < 0.05).  RDQ scores correlated positively with the PA of the right LPM (r = 0.521, p < 0.05).  The authors concluded that the electrical properties of the bilateral LPMs differed between the patients with CLBP and HCs, regardless of the current frequency used.  The R and Z values were elevated, PA values were decreased, and no significant changes occurred in the X values in young adults with CLBP, as compared to HCs.  This may indicate that the LPM of the patients with CLBP has fewer muscle fibers with increased fatty infiltration or connective tissue, and that the cellular membranes are not damaged, but that their oscillation properties are altered.  The altered electrical properties of the LPM correlated with disability in daily life suggesting that examining the electrical properties of the LPM in patients with CLBP is meaningful and can contribute to discovering the pathological characteristics of the muscle composition.  These researchers stated that EIM, as a novel technique for evaluating CLBP, should have widely applications in future.

The authors stated that this study had several drawbacks.  First, the small sample size (n = 15 I the CLBP group) could have limited these findings and might present pathological characteristics of the LPM in only a part of this patient population.  Second, the age of the subjects included in the study was a limitation.  Measurements were taken only for the LPM in young adults; therefore, limiting the generalizability of the findings.  Difference in the age and sex of the patients with CLBP may consequently present different structural or functional status in their LPMs.  Third, the anatomical structure of the lumbar crest did not permit the measurement of the EIM parameters in the transverse direction; hence, the anisotropy ratios of each variable were not calculated.  Muscle anisotropy represents the degree of columnar order in the arrangement of the fibers; however, the arrangement of the LPM fibers in CLBP was not examined in this study.  Fourth, the location of the pain in the low back might result in different electrical impedance values.  Since some of the patients in the study could not state the location of their pain accurately, these researchers did not distinguish patients into unilateral and bilateral pain groups.  This should be examined in the future.


References

The above policy is based on the following references:

  1. Aleixo GFP, Shachar SS, Nyrop KA, et al. Bioelectrical impedance analysis for the assessment of sarcopenia in patients with cancer: A systematic review. Oncologist. 2020;25(2):170-182.
  2. Atkins CS. AANA Journal course: New technologies in anesthesia: Update for nurse anesthetists--noninvasive, continuous, cardiac output monitoring by thoracic electrical bioimpedance. 16. AANA J. 1991;59(5):445-452.
  3. Barney J. Thoracic electrical bioimpedance device. Crit Care Med. 1996;24(6):1090-1091.
  4. Becker K Jr. Resolved: A pulmonary artery catheter should be used in the management of the critically ill patient. Con. J Cardiothorac Vasc Anesth. 1998;12(2 Suppl 1):13-16.
  5. Cannon T, Choi J. Development of a segmental bioelectrical impedance spectroscopy device for body composition measurement. Sensors (Basel). 2019;19(22).
  6. Castor G, Klocke RK, Stoll M, et al. Simultaneous measurement of cardiac output by thermodilution, thoracic electrical bioimpedance and Doppler ultrasound. Br J Anaesth. 1994;72(1):133-138.
  7. Cebrian-Ponce A, Irurtia A, Carrasco-Marginet M, et al. Electrical impedance myography in health and physical exercise: A systematic review and future perspectives. Front Physiol. 2021;12:740877.
  8. Clancy TV, Norman K, Reynolds R, et al. Cardiac output measurement in critical care patients: Thoracic Electrical Bioimpedance versus thermodilution. J Trauma. 1991;31(8):1116-1121.
  9. Cote CJ, Sui J, Anderson TA, et al. Continuous noninvasive cardiac output in children: Is this the next generation of operating room monitors? Initial experience in 402 pediatric patients. Paediatr Anaesth. 2015;25(2):150-159.
  10. Di Vincenzo O, Marra M, Di Gregorio A, et al. Bioelectrical impedance analysis (BIA)-derived phase angle in sarcopenia: A systematic review. Clin Nutr. 2021;40(5):3052-3061.
  11. Doering L, Lum E, Dracup K, et al. Predictors of between-method differences in cardiac output measurement using thoracic electrical bioimpedance and thermodilution. Crit Care Med. 1995;23(10):1667-1673.
  12. Elwan MH, Hue J, Green SJ, et al. Thoracic electrical bioimpedance versus suprasternal Doppler in emergency care. Emerg Med Australas. 2017;29(4):391-393.
  13. Faini A, Omboni S, Tifrea M, et al. Cardiac index assessment: Validation of a new non-invasive very low current thoracic bioimpedance device by thermodilution. Blood Press. 2014;23(2):102-108.
  14. Ferraro S, D'Alto M, Maddalena G, et al. The usefulness of bioimpedance in patient monitoring in an intensive-therapy heart-surgery unit: A comparison with thermodilution. Cardiologia. 1993;38(9):577-583.
  15. Gujjar AR, Muralidhar K, Banakal S, et al. Non-invasive cardiac output by transthoracic electrical bioimpedence in post-cardiac surgery patients: Comparison with thermodilution method. J Clin Monit Comput. 2008;22(3):175-180.
  16. Gujjar AR, Muralidhar K, Bhandopadhyaya A, et al. Transthoracic electrical bioimpedence cardiac output: Comparison with multigated equillibrium radionuclide cardiography. J Clin Monit Comput. 2010;24(2):155-159.
  17. Gupta D, Lis CG, Dahlk SL, et al. Bioelectrical impedance phase angle as a prognostic indicator in advanced pancreatic cancer. Br J Nutr. 2004;92(6):957-962.
  18. Handelsman H. Measuring cardiac output by electrical bioimpedance. Agency for Health Care Policy and Research (AHCPR) Health Technology Assessment Report No. 6. AHCPR Pub. No. 92-0073. Bethesda, MD: AHCPR; September 1992.
  19. Hui D, Dev R, Pimental L, et al. Association between multi-frequency phase angle and survival in patients with advanced cancer. J Pain Symptom Manage. 2017;53(3):571-577.
  20. Joosten A, Desebbe O, Suehiro K, et al. Accuracy and precision of non-invasive cardiac output monitoring devices in perioperative medicine: A systematic review and meta-analysis. Br J Anaesth. 2017;118(3):298-310.
  21. Jordan HS, Ioannidis JPA, Goudas LC, et al. and the Tufts-New England Medical Center AHRQ Evidence-based Practice Center (EPC). Thoracic electrical bioimpedance. Evidence Report/Technology Assessment. EPC Technical Support of the CPTA Technology Assessment Program. Contract No. 290-97-0019, Task Order #10. Rockville, MD: Agency for Healthcare Research and Quality (AHRQ); revised November 27, 2002.
  22. Lee GH, Cho HJ, Lee G, et al. Bioelectrical impedance analysis for predicting postoperative complications and survival after liver resection for hepatocellular carcinoma. Ann Transl Med. 2021;9(3):190.
  23. Leitner ML, Kapur K, Darras BT, et al. Electrical impedance myography for reducing sample size in Duchenne muscular dystrophy trials. Ann Clin Transl Neurol. 2020;7(1):4-14.
  24. Littman L, Lasater M. Cost effectiveness of noninvasive hemodynamic monitoring as a screening tool prior to initiation of inotrope infusion. J Cardiovasc Manag. 1999;10(2):29-30.
  25. Magliocca A, Rezoagli E, Anderson TA, et al. Cardiac output measurements based on the pulse wave transit time and thoracic impedance exhibit limited agreement with thermodilution method during orthotopic liver transplantation. Anesth Analg. 2018;126(1):85-92. 
  26. Mansfield RC, Kaza N, Charalambous A, et al. Cardiac output measurement in neonates and children using noninvasive electrical bioimpedance compared with standard methods: A systematic review and meta-analysis. Crit Care Med. 2022;50(1):126-137.
  27. Mansouri S, Alhadidi T, Azouz MB. Breast cancer detection using low-frequency bioimpedance device. Breast Cancer (Dove Med Press). 2020;12:109-116.
  28. Moshkovitz Y, Kaluski E, Milo O, et al. Recent developments in cardiac output determination by bioimpedance: Comparison with invasive cardiac output and potential cardiovascular applications. Curr Opin Cardiol. 2004;19(3):229-237. 
  29. Nguyen LS, Squara P. Non-invasive monitoring of cardiac output in critical care medicine. Front Med (Lausanne). 2017;4:200.
  30. Pathiraja AA, Weerakkody RA, von Roon AC, et al. The clinical application of electrical impedance technology in the detection of malignant neoplasms: A systematic review. J Transl Med. 2020;18(1):227.
  31. Pino EJ, Gomez B, Monsalve E, Aqueveque P. Wireless low-cost bioimpedance measurement device for lung capacity screening. Conf Proc IEEE Eng Med Biol Soc. 2019;2019:1187-1190.
  32. Raval NY, Squara P, Cleman M, et al. Multicenter evaluation of noninvasive cardiac output measurement by bioreactance technique. J Clin Monit Comput. 2008;22(2):113-119.
  33. Sageman WS, Amundson DE. Thoracic electrical bioimpedance measurement of cardiac output in postaortocoronary bypass patients. Crit Care Med. 1993;21(8):1139-1142.
  34. Sageman WS, Riffenburgh RH, Spiess BD. Equivalence of bioimpedance and thermodilution in measuring cardiac index after cardiac surgery. J Cardiothorac Vasc Anesth. 2002;16(1):8-14.
  35. Sangkum L, Liu GL, Yu L, et al. Minimally invasive or noninvasive cardiac output measurement: An update. J Anesth. 2016;30(3):461-480.
  36. Sarode GS, Sarode SC, Kulkarni M, et al. Bioimpedance assessment of oral squamous cell carcinoma with clinicopathological correlation. J Contemp Dent Pract. 2015;16(9):715-722.
  37. Shoemaker WC, Wo CC, Bishop MH, et al. Multicenter trial of a new thoracic electrical bioimpedance device for cardiac output estimation. Crit Care Med. 1994;22(12):1907-1912.
  38. Smith MA. Noninvasive hemodynamic monitoring with thoracic electrical bioimpedance. Crit Care Nurse. 1994;14(5):56-59.
  39. Taylor K, La Rotta G, McCrindle BW, et al. A comparison of cardiac output by thoracic impedance and direct fick in children with congenital heart disease undergoing diagnostic cardiac catheterization. J Cardiothorac Vasc Anesth. 2011;25(5):776-779.
  40. Thangathurai D, Charbonnet C, Roessler P, et al. Continuous intraoperative noninvasive cardiac output monitoring using a new thoracic bioimpedance device. J Cardiothorac Vasc Anesth. 1997;11(4):440-444.
  41. U.S. Department of Health and Human Services, Center for Medicare & Medicaid Services (CMS). Decision Memo for Electrical Bioimpedance for Cardiac Output Monitoring (CAG-00001R). Medicare Coverage Database. Baltimore, MD: CMS; August 7, 2003.
  42. U.S. Department of Health and Human Services, Center for Medicare & Medicaid Services (CMS). Decision Memo for Electrical Bioimpedance for Cardiac Output Monitoring (CAG-00001R2). Medicare Coverage Database. Baltimore, MD: CMS; November 20, 2006.
  43. Van Wyk L, Gupta S, Lawrenson J, de Boode W-P. Accuracy and trending ability of electrical biosensing technology for non-invasive cardiac output monitoring in neonates: A systematic qualitative review. Front Pediatr. 2022;10:851850.
  44. Velmahos GC, Wo CC, Demetriades D, et al. Invasive and noninvasive hemodynamic monitoring of patients with cerebrovascular accidents. West J Med. 1998;169(1):17-22.
  45. Wang DJ, Gottlieb SS. Impedance cardiography: More questions than answers. Curr Heart Fail Rep. 2006;3(3):107-113.
  46. Wang H, Zheng J, Yu Q, et al. Electrical properties of lumbar paraspinal muscles in young adults with and without chronic low back pain based on electrical impedance myography: A cross-sectional study. Front Neurol. 2022;12:789589.
  47. Wang Y, Freedman L, Buck M, et al. Electrical impedance myography for assessing paraspinal muscles of patients with low back pain. J Electr Bioimpedance. 2019;10(1):103-109.
  48. Weiss S, Calloway E, Cairo J, et al. Comparison of cardiac output measurements by thermodilution and thoracic electrical bioimpedance in critically ill versus non-critically ill patients. Am J Emerg Med. 1995;13(6):626-631.
  49. Weiss SJ, Ernst AA, Godorov G, et al. Bioimpedance-derived differences in cardiac physiology during exercise stress testing in low-risk chest pain patients. South Med J. 2003;96(11):1121-1127.
  50. Weiss SJ, Kulik JP, Calloway E. Bioimpedance cardiac output measurements in patients with presumed congestive heart failure. Acad Emerg Med. 1997;4(6):568-573.
  51. Wong KL, Hou PC. The accuracy of bioimpedance cardiography in the measurement of cardiac output in comparison with thermodilution method. Acta Anaesthesiol Sin. 1996;34(2):55-59.
  52. World MJ. Methods of estimating cardiac output in the field. QJM. 1996;89(6):457-462.
  53. Young JD, McQuillan P. Comparison of thoracic electrical bioimpedance and thermodilution for the measurement of cardiac index in patients with severe sepsis. Br J Anaesth. 1993;70(1):58-62.
  54. Zacek P, Kunes P, Kobzova E, et al. Thoracic electrical bioimpedance versus thermodilution in patients post open-heart surgery. Acta Medica (Hradec Kralove). 1999;42(1):19-23.