Greg Grudic

Running on empty? The compensatory reserve index.

BACKGROUND Hemorrhage is a leading cause of traumatic death. We hypothesized that state-of-the-art feature extraction and machine learning techniques could be used to discover, detect, and continuously trend beat-to-beat changes in arterial pulse waveforms associated with the progression to hemodynamic decompensation. METHODS We exposed 184 healthy humans to progressive central hypovolemia using lower-body negative pressure to the point of hemodynamic decompensation (systolic blood pressure > 80 mm Hg with or without bradycardia). Initial models were developed using continuous noninvasive blood pressure waveform data. The resulting algorithm calculates a compensatory reserve index (CRI), where 1 represents supine normovolemia and 0 represents the circulatory volume at which hemodynamic decompensation occurs (i.e., “running on empty”). Values between 1 and 0 indicate the proportion of reserve remaining before hemodynamic decompensation—much like the fuel gauge of a car indicates the amount of fuel remaining in the tank. A CRI estimate is produced after the first 30 heart beats, followed by a new CRI estimate after each subsequent beat. RESULTS The CRI model with a 30-beat window has an absolute difference between actual and expected time to decompensation of 0.1, with a SD of 0.09. The model distinguishes individuals with low tolerance to reduced central blood volume (i.e., those most likely to develop early shock) from those with high tolerance and are able to estimate how near or far an individual may be from hemodynamic decompensation. CONCLUSION Machine modeling can quickly and accurately detect and trend central blood volume reduction in real time during the compensatory phase of hemorrhage as well as estimate when an individual is “running on empty” and will decompensate (CRI, 0), well in advance of meaningful changes in traditional vital signs.

Detection of Low-volume Blood Loss: Compensatory Reserve Versus Traditional Vital Signs

BACKGROUND Humans are able to compensate for low-volume blood loss with minimal change in traditional vital signs. We hypothesized that a novel algorithm, which analyzes photoplethysmogram (PPG) wave forms to continuously estimate compensatory reserve would provide greater sensitivity and specificity to detect low-volume blood loss compared with traditional vital signs. The compensatory reserve index (CRI) is a measure of the reserve remaining to compensate for reduced central blood volume, where a CRI of 1 represents supine normovolemia and 0 represents the circulating blood volume at which hemodynamic decompensation occurs; values between 1 and 0 indicate the proportion of reserve remaining. METHODS Subjects underwent voluntary donation of 1 U (approximately 450 mL) of blood. Demographic and continuous noninvasive vital sign wave form data were collected, including PPG, heart rate, systolic blood pressure, cardiac output, and stroke volume. PPG wave forms were later processed by the algorithm to estimate CRI values. RESULTS Data were collected from 244 healthy subjects (79 males and 165 females), with a mean (SD) age of 40.1 (14.2) years and mean (SD) body mass index of 25.6 (4.7). After blood donation, CRI significantly decreased in 92% (&agr; = 0.05; 95% confidence interval [CI], 88–95%) of the subjects. With the use of a threshold decrease in CRI of 0.05 or greater for the detection of 1 U of blood loss, the receiver operating characteristic area under the curve was 0.90, with a sensitivity of 0.84 and specificity of 0.86. In comparison, systolic blood pressure (52%; 95% CI, 45–59%), heart rate (65%; 95% CI, 58–72%), cardiac output (47%; 95% CI, 40–54%), and stroke volume (74%; 95% CI, 67–80%) changed in fewer subjects, had significantly lower receiver operating characteristic area under the curve values, and significantly lower specificities for detecting the same volume of blood loss. CONCLUSION Consistent with our hypothesis, CRI detected low-volume blood loss with significantly greater specificity than other traditional physiologic measures. These findings warrant further evaluation of the CRI algorithm in actual trauma settings. LEVEL OF EVIDENCE Diagnostic study, level II.

Promoting early diagnosis of hemodynamic instability during simulated hemorrhage with the use of a real-time decision-assist algorithm

BACKGROUND This study aimed to test the hypothesis that the addition of a real-time decision-assist machine learning algorithm by emergency medical system personnel could shorten the time needed to identify an unstable patient during a hemorrhage profile as compared with vital sign information alone. METHODS Fifty emergency medical team-paramedics from a large, urban fire department participated as subjects. Subjects viewed a monitor screen on two occasions as follows: (1) display of standard vital signs alone and (2) with the addition of an index (Compensatory Reserve Index) associated with estimated central blood volume status. The subjects were asked to push a computer key at any point in the sequence they believed the patient had become unstable based on information provided by the monitor screen. The average difference in time to identify hemodynamic instability between experimental and control groups was assessed by paired, two-tailed t test and reported with 95% confidence intervals (95% CI). RESULTS The mean (SD) amount of time required to identify an unstable patient was 18.3 (4.1) minutes (95% CI, 17.2–19.4 minutes) without the algorithm and 10.7 (4.2) minutes (95% CI, 9.5–11.9 minutes) with the algorithm (p < 0.001). CONCLUSION In a simulated patient encounter involving uncontrolled hemorrhage, the use of a monitor that estimates central blood volume loss was associated with early identification of impending hemodynamic instability. Physiologic monitors capable of early identification and estimation of the physiologic capacity to compensate for blood loss during hemorrhage may enable optimal guidance for hypotensive resuscitation. They may also help identify casualties benefitting from forward administration of plasma, antifibrinolytics and procoagulants in a remote damage-control resuscitation model.

The Compensatory Reserve Index Following Injury: Results of a Prospective Clinical Trial.

Introduction: Humans are able to compensate for significant blood loss with little change in traditional vital signs. We hypothesized that an algorithm, which recognizes compensatory changes in photoplethysmogram (PPG) waveforms, could detect active bleeding and ongoing volume loss in injured patients. Methods: Injured adults were prospectively enrolled at a level I trauma center. PPG data collection was conducted using a custom-made pulse oximeter. Waveform data were post-processed by an algorithm to calculate the compensatory reserve index (CRI), measured on a scale of 1 to 0, with 1 indicating fully compensated and 0 indicating no reserve, or decompensation. CRI was compared to clinical findings. Results: Fifty patients were enrolled in the study; 3 had incomplete data, 3 had indeterminate bleeding, 12 were actively bleeding, and 32 were not bleeding. The mean initial CRI of bleeding patients was significantly lower compared with the non-bleeding patients (CRI 0.17, 95% CI = 0.13–0.22 vs. CRI 0.56, 95% CI = 0.49–0.62, P < 0.001). Using a cut-off of 0.21 had a sensitivity of 0.97 and specificity of 0.83 for identifying bleeding patients. CRI had a higher sensitivity than heart rate (75%), systolic blood pressure (63%), shock index (27%), base deficit (29%), lactate (80%), hemoglobin (50%), and hematocrit (50%). During ongoing bleeding, CRI decreased following fluid resuscitation, and conversely increased for patients who were not bleeding. Conclusions: A novel computational algorithm that recognizes subtle changes in PPG waveforms can quickly and noninvasively discern which patients are actively bleeding and continuing to bleed with high sensitivity and specificity in acutely injured patients.

Comparison of compensatory reserve during lower-body negative pressure and hemorrhage in nonhuman primates.

Compensatory reserve was measured in baboons (n = 13) during hemorrhage (Hem) and lower-body negative pressure (LBNP) using a machine-learning algorithm developed to estimate compensatory reserve by detecting reductions in central blood volume during LBNP. The algorithm calculates compensatory reserve index (CRI) from normovolemia (CRI = 1) to cardiovascular decompensation (CRI = 0). The hypothesis was that Hem and LBNP will elicit similar CRI values and that CRI would have higher specificity than stroke volume (SV) in predicting decompensation. Blood was removed in four steps: 6.25%, 12.5%, 18.75%, and 25% of total blood volume. Four weeks after Hem, the same animals were subjected to four levels of LBNP that was matched on the basis of their central venous pressure. Data (mean ± 95% confidence interval) indicate that CRI decreased (P < 0.001) from baseline during Hem (0.69 ± 0.10, 0.57 ± 0.09, 0.36 ± 0.10, 0.16 ± 0.08, and 0.08 ± 0.03) and LBNP (0.76 ± 0.05, 0.66 ± 0.08, 0.36 ± 0.13, 0.23 ± 0.11, and 0.14 ± 0.09). CRI was not different between Hem and LBNP (P = 0.20). Linear regression analysis between Hem CRI and LBNP CRI revealed a slope of 1.03 and a correlation coefficient of 0.96. CRI exhibited greater specificity than SV in both Hem (92.3 vs. 82.1) and LBNP (94.8 vs. 83.1) and greater ROC AUC in Hem (0.94 vs. 0.84) and LBNP (0.94 vs. 0.92). These data support the hypothesis that Hem and LBNP elicited the same CRI response, suggesting that measurement of compensatory reserve is superior to SV as a predictor of cardiovascular decompensation.

State-of-the-art monitoring in treatment of dengue shock syndrome: a case series

BackgroundEarly recognition and treatment of circulatory volume loss is essential in the clinical management of dengue viral infection. We hypothesized that a novel computational algorithm, originally developed for noninvasive monitoring of blood loss in combat casualties, could: (1) indicate the central volume status of children with dengue during the early stages of “shock”; and (2) track fluid resuscitation status.MethodsContinuous noninvasive photoplethysmographic waveforms were collected over a 5-month period from three children of Thai ethnicity with clinical suspicion of dengue. Waveform data were processed by the algorithm to calculate each child’s Compensatory Reserve Index, where 1 represents supine normovolemia and 0 represents the circulatory volume at which hemodynamic decompensation occurs. Values between 1 and 0 indicate the proportion of reserve remaining before hemodynamic decompensation.ResultsThis case report describes a 7-year-old Thai boy, another 7-year-old Thai boy, and a 9-year-old Thai boy who exhibited signs and symptoms of dengue shock syndrome; all the children had secondary dengue virus infections, documented by serology and reverse transcriptase polymerase chain reaction. The three boys experienced substantial plasma leakage demonstrated by pleural effusion index >25, ascites, and >20 % hemoconcentration. They received fluid administered intravenously; one received a blood transfusion. All three boys showed a significantly low initial Compensatory Reserve Index (≥0.20), indicating a clinical diagnosis of “near shock”. Following 5 days with fluid resuscitation treatment, their Compensatory Reserve Index increased towards “normovolemia” (that is, Compensatory Reserve Index >0.75).ConclusionsThe results from these cases demonstrate a new variation in the diagnostic capability to manage patients with dengue shock syndrome. The findings shed new light on a method that can avoid possible adverse effects of shock by noninvasive measurement of a patient’s compensatory reserve rather than standard vital signs or invasive diagnostic methods.

A noninvasive computational method for fluid resuscitation monitoring in pediatric burns: a preliminary report.

The fluid resuscitation needs of children with small area burns are difficult to predict. The authors hypothesized that a novel computational algorithm called the compensatory reserve index (CRI), calculated from the photoplethysmogram waveform, would correlate with percent total body surface area (%TBSA) and fluid administration in children presenting with ⩽20% TBSA burns. The authors recorded photoplethysmogram waveforms from burn-injured children that were later processed by the CRI algorithm. A CRI of 1 represents supine normovolemia; a CRI of 0 represents the point at which a subject is predicted to experience hemodynamic decompensation. CRI values from the first 10 minutes of monitoring were compared to clinical data. Waveform data were available for 27 children with small to moderate sized burns (4–20 %TBSA). The average age was 6.3 ± 1.1 years, the average %TBSA was 10.4 ± 0.8%, and the average CRI was 0.36 ± 0.03. CRI inversely correlated with the %TBSA (P < .001). Twenty children were transferred with an average reported %TBSA of 16.5 ± 1.4%, which was significantly higher than the actual %TBSA (P < .001). CRI correlated better with actual %TBSA compared to reported %TBSA (P = .02). CRI correlated with the amount of fluid resuscitation given at the time of CRI measurement (P = .02) and was inversely related to total fluids given per 24 hours for children with adequate urine output (>0.5 ml/kg/hr) (P < .001). The CRI is decreased in children with small to moderate size burns, and correlates with %TBSA and fluid administration. This suggests that the CRI may be useful for fluid resuscitation guidance, warranting further study.

Development of a Non-invasive Cerebrovascular Status Algorithm to Estimate Cerebral Perfusion Pressure and Intracranial Pressure in a Porcine Model of Focal Brain Injury

Background New tools for diagnosis, monitoring, and treatment of elevated intracranial pressure (ICP) or compromised cerebral perfusion pressure (CPP) are urgently needed to improve outcomes after brain injury. Previous success in applying advanced data analytics to build precision monitors based on large, noisy sensor datasets suggested applying the same approach to monitor cerebrovascular status. In these experiments, a new algorithm was developed to estimate ICP and CPP using the arterial pressure waveform. Methods Sixty-five porcine subjects were subjected to a focal brain injury to simulate a mass lesion with elevated ICP. The arterial pressure waveform and the measured ICP from these subjects during injury and treatment were then utilized to develop and calibrate an ICP and CPP estimation algorithm. These estimation algorithms were then subsequently evaluated on 14 new subjects. Results The root mean square difference between actual ICP and estimated ICP was 2.0961 mmHg. The root mean square difference between the actual CPP and the estimated CPP was 2.6828 mmHg. Conclusion A novel ICP or CPP monitor based on the arterial pressure signal produced a very close approximation to actual measured ICP and CPP and warrants further evaluation.

Noninvasive monitoring of physiologic compromise in acute appendicitis: New insight into an old disease

INTRODUCTION Physiologic compromise in children with acute appendicitis has heretofore been difficult to measure. We hypothesized that the Compensatory Reserve Index (CRI), a novel adjunctive cardiovascular status indicator, would be low for children presenting with acute appendicitis in proportion to their physiological compromise, and that CRI would rise with fluid resuscitation and surgical management of their disease. METHODS Ninety-four children diagnosed with acute appendicitis were monitored with a CipherOx CRI™ M1 pulse oximeter (Flashback Technologies Inc., Boulder, CO). For clarity, CRI=1 indicates supine normovolemia, CRI=0 indicates hemodynamic decompensation (systolic blood pressure<80mmHg), and CRI values between 1 and 0 indicate the proportion of volume reserve remaining before collapse. Results are presented as counts with proportion (%), or mean with 95% confidence interval (CI). RESULTS Mean age was 11years old (95% CI: 10-12), and 49 (52%) of the children were male. Fifty-four (57%) had nonperforated appendicitis and 40 (43%) had perforated appendicitis. Mean initial CRI was significantly higher in those with nonperforated appendicitis compared to those with perforated appendicitis (0.57, 95% CI: 0.52-0.63 vs. 0.36, 95% CI: 0.29-0.43; P<0.001). The significant differences in mean CRI values between the two groups remained throughout the course of treatment, but lost its significance at 2h after surgery (0.63, 95% CI: 0.57-0.70 vs. 0.53, 95% CI: 0.46-0.61; P=0.05). CONCLUSION Low CRI values in children with perforated appendicitis are indicative of their lower reserve capacity owing to peritonitis and hypovolemia. CRI offers a real-time, noninvasive adjunctive tool to monitor tolerance to volume loss in children. LEVEL OF EVIDENCE Study of diagnostic test; Level of evidence: Level III.