Printer Friendly

Advanced technology development for remote triage applications in bleeding combat casualties.

Accurate, early diagnosis of hemorrhage to enable timely application of life saving interventions is a high priority for the Army Medical Department, since hemorrhage remains a leading cause of death on the battlefield. (1,2) Survival rates increase when victims requiring immediate intervention are correctly and expeditiously identified, (3) but methods of assessing the severity of hemorrhage based on current triage algorithms are severely limited. Despite ongoing study, mental status and low blood pressure (systolic < 90 mm Hg) are still considered to be the best indicators of the need for life-saving interventions, (4-6) even though the unreliability of arterial blood pressure as an indicator of blood loss was recognized as early as World War II. (7,8) In trauma and combat casualty care medicine, a profound need exists for improved physiological algorithms that will provide a reliable early indication of hemodynamic instability, and provision of these algorithms has been the focus of our research efforts. (9) Indeed, delays in identification and control of hemorrhage in the prehospital phase of treatment accounted for a large percentage of potentially preventable deaths during Operation Iraqi Freedom. (2) In recognition of this need, the Combat Casualty Care Research Program of the US Army Medical Research and Materiel Command established a specific task area (Advanced Capabilities for Emergency Medical Monitoring) in 2002 to investigate new ways to meet capability gaps in medical monitoring, particularly in the prehospital phase.

Physiologic status assessment in casualties can be problematic in the military setting, where physical access to the injured individual may be complicated by terrain, weather and hostile action. Likewise, some civil sector settings may challenge first responders, particularly when victims are located remotely. The lack of a remote triage capability may therefore result in the medic attending to either a) a Soldier who is uninjured but caught in the vicinity of combat; or b) a Soldier under severe fire who has an injury that is deemed unsalvageable. (10) Indeed, a combat medic may place himself in harm's way to assist a Soldier who may not even be injured or may be unsalvageable. Data collected during the Vietnam War indicate that the fatality rate of US Army medics was double that seen in infantrymen. (11) Anecdotally, this risk continues in the current combat setting, as medics routinely place themselves in potentially vulnerable positions in order to physically assess and treat a wounded Soldier. It is therefore desirable to provide a remote triage capability that protects combat medics while accurately assessing the injury severity of a wounded Soldier.

WEAR-AND-FORGET MONITORING SYSTEMS

The concept of continuous, remote, physiological monitoring has gained traction for use by Warfighters, (12,13) astronauts, (14) and emergency first responders, (15) and implementation systems have been actively pursued by military developers. (12,13) In particular, the US Army has embarked on a program to develop a "wear-and-forget" monitoring system that will wirelessly provide continuous streams of physiological data from individual Soldiers to a medic-held personal data assistant (Figure 1). It should be noted that the initial impetus for development of a remote triage system evolved from the desire for continuous monitoring capabilities to assess the physiological status of Soldiers to determine their readiness for battle, thereby providing a greater degree of operational and situational information to tactical commanders. Hence, as originally envisioned, these monitoring systems include the capability to measure hydration status, body core temperature, and the amount of sleep obtained. (13) It was realized early, however, that physiological responses to combat injury might also be measured by these systems, and could provide the capability for remote triage.

[FIGURE 1 OMITTED]

The Army currently has received 2 prototypes of a physiological status monitor (PSM) that were developed under an Army Technology Objective and congressionally-funded programs. For the purposes of combat casualty care, the PSM is designed to provide continuous monitoring of the electrocardiogram (ECG) and respiration rate. We recently tested both of these prototype systems for their ability to accurately measure R-R intervals (RRI, the interval between 2 R waves, derived from the ECG) and respiration rate during central hypovolemia. Briefly, healthy human volunteers were exposed to lower body negative pressure (LBNP), which we and others have demonstrated to be a reliable and reproducible experimental model of hemorrhage that can be performed in conscious humans. (9,16) Measurements of RRI and respiratory rate from both of the prototype systems during hypovolemia were compared with those derived from a standard ECG and capnograph. Results from these experiments demonstrated that both prototype systems reliably measured RRI; while the Hidalgo belt also measured respiration rate with high fidelity, the Foster Miller shirt tended to underestimate the true respiration rate (Figure 2). In parallel with the laboratory experiments, both prototypes were also tested under field conditions during US Army Ranger training at Fort Benning, Georgia, in 2008. During a 2-day field test, the prototypes were evaluated for their ability to capture data as well as for their wearability and comfort. While data capture was acceptable from the Foster Miller shirt, there were some synchronization problems between the Hidalgo belts and the personal data assistant, resulting in a loss of data. Furthermore, there were complaints of chafing and discomfort from data capture devices that were placed on pressure points under the body armor with both prototypes. Clearly, further end-user testing under different environmental conditions will be required before either the current prototype or new systems are proposed for fielding.

WILL CURRENT PSM MEASUREMENTS AID REMOTE TRIAGE?

Making the assumption that wearability and data capture issues can be overcome with further development, the question becomes whether the information provided by the current PSM prototypes will provide sufficient clinical information to properly assess the status of a wounded Soldier beyond that of being alive or dead. Unfortunately, elevated heart and respiration rates resulting from hemorrhage in a wounded Soldier may not be distinguishable from elevated heart and respiration rates in a Soldier actively participating in a military maneuver or firefight. However, the investigation of naturally-occurring rhythmic fluctuations in RRIs obtained from the ECG (ie, heart period variability (HPV)) underscores a multitude of feedback control mechanisms that may lend insight into normal and abnormal physiology, such as reduced blood volume resulting from severe hemorrhage. Since the first suggestion in 1963 that HPV might be useful for clinical monitoring of patients, (17) this field has literally exploded, with indications that HPV monitoring might provide useful diagnostic information for such chronic disease states as cardiac diseases (eg, myocardial infarction, congestive heart failure), sleep apnea, diabetes, and renal failure. (18) In fact, a PubMed search performed in October 2010 on the term "heart rate variability" revealed more than 13,000 published papers. Despite this interest, these techniques have not yet been widely implemented into clinical practice or monitoring devices. (19,20)

[FIGURE 2 OMITTED]

In the laboratory environment, frequency-domain analyses of HPV have been used extensively to explore human autonomic cardiovascular rhythms, especially as they relate to maintenance of steady-state hemodynamics through activation and inhibition of the autonomic nervous system. Spontaneous fluctuations in intervals between ECG R waves (ie, R-R intervals) around the respiratory (high) frequency (HF) are known to be mediated by parasympathetic neural activity, (21) while oscillations occurring at frequencies lower than respiration (LF) are thought to be mediated by both parasympathetic elements and sympathetic modulation of vascular resistance. (22,23) Furthermore, HF spectral power decreases progressively (ie, parasympathetic withdrawal) during reductions in central blood volume and is inversely associated with sympathetic activation, demonstrating the expected shift in sympathovagal balance during central hypovolemia. (24,25)

Based on this understanding, we first investigated whether frequency domain metrics of HPV would provide predictive power to discriminate between trauma patients in the prehospital environment who subsequently lived or died. To test this hypothesis, we measured HPV from ECG data collected during prehospital transport of civilian trauma patients who sustained blunt or penetrating injuries leading to hemorrhage. (26) RRI data were collected between 45 and 90 minutes after injury, while the average time of death was 9.5 hours in those patients who were nonsurvivors. The results indicated that patients who died had statistically higher RRI HF/LF ratios than those patients who lived. In a subsequent analysis, these results were verified in a larger cohort of patients that included more head and blunt injuries. (27) These initial analyses indicated that alterations in RRI HF/LF might be early markers of patient survival and thus provide clues for development of PSM-based algorithms to assist the combat medic with important remote triage decisions, particularly in a mass casualty scenario. Subsequently, Batchinsky et al (28) extended these observations to demonstrate that loss of RRI complexity (using nonlinear analysis of RRI to produce entropy and fractality measurements) was associated with subsequent mortality. Finally, loss of RRI variability and complexity was shown to be associated with the administration of a life-saving intervention (LSI) in data taken from trauma patients during the prehospital phase of care. (29,30) Recently, RRI complexity metrics have been specifically advocated for use in remote triage applications. (31) It should be noted, however, that in the majority of these studies demonstrating an association between HPV and either the administration of a life-saving intervention29 or eventual mortality, (26-28) at least one easily obtainable standard vital sign (eg, Glasgow Coma Scale motor score) also distinguished the 2 groups of patients (eg, LSI vs no LSI, lived vs died). It was therefore unclear whether complicated calculation of a HPV metric would provide "added value" in enhancing triage capabilities over standard vital signs, particularly in situations in which the medic either had physical access to the patient or had radio communication that could be used to ascertain the patient's ability to respond (ie, Glasgow Coma Scale).

The application of HPV for combat medic decision support has several attractive features, including: a) it can provide remote and continuous monitoring from a sensor system that can be worn by every Soldier; and, b) it can utilize a simple ECG signal provided by the current prototypes of PSM. While we (26,27) and others (28-31) had initially used group mean analysis for determination of HPV utility, several important questions remained before realistically proposing the use of HPV metrics of any kind for remote triage of individual Warfighters or, for that matter, clinical monitoring of individual patients. For example, what are "normal" values for HPV metrics and are these reproducible in the same subject? What are technical requirements for valid calculation of HPV metrics? Are alterations in HPV metrics specific only to loss of central blood volume? Do HPV metrics track central hypovolemia in any given individual? In our further work, we systematically sought to answer these questions by determining whether HPV metrics are of use in tracking hemorrhage in individual patients, and whether responses of HPV metrics are specific to hemorrhage rather than to other combat stressors such as physical activity.

To answer the question of whether HPV metrics would track blood loss in individuals, we first determined intersubject and intrasubject variability in resting human subjects during the same experimental session to determine normal values and their reproducibility. (32) While some of the complexity metrics (but not the time and frequency domain metrics) displayed reasonably low (coefficient of variation (CV) [less than or equal to ] 8.5%) intersubject variability and high (CV [less than or equal to ] 8.9%) reproducibility in our study, recent work from Tan et al (33) demonstrated that these metrics a) are not reproducible within individuals during different experimental sessions; and b) do not reliably reflect autonomic mechanisms responsible for HPV. The authors therefore concluded that caution is warranted in using these metrics as diagnostic tools. (33) In agreement with the conclusions of this study, we found that, while group means of HPV metrics are highly correlated ([absolute value of r] [greater than or equal to] 0.87) * with stroke volume (an index of central blood volume) during progressive reductions in central blood volume, analysis of the individual trajectories for HPV metrics demonstrated poor and inconsistent correlations ([absolute value of r] [less than or equal to ] 0.49) with changes in stroke volume at the individual subject level (Figure 3). (34) From these data, we concluded that the HPV metrics do not reliably track individual reductions in central volume in the controlled laboratory setting and therefore may not be useful, even in trending analysis, in monitoring hemorrhagic injuries in individual patients. (34)

[FIGURE 3 OMITTED]

In further analyses using real world data, we determined that 36% to 52% of trauma patients undergoing helicopter transport to the hospital demonstrate the presence of at least one ectopic beat within their ECG record, (35) valid determination of HPV metrics requires ECG waveforms that are free of noise and ectopic beats. (36) When the percentage of ECG waveforms rendered unusable by the presence of electromagnetic noise from patient movement or electrical interference is added, these limitations potentially exclude between 48% and 74% of prehospital trauma patients. On an individual basis, HPV measurements could therefore only be applied to approximately 26% to 52% of trauma patients. (35) For remote triage applications, it might be anticipated that electromagnetic noise due to movement might produce an even larger problem. Finally, we determined whether HPV metrics provided added value to the ability to determine whether an individual patient would subsequently require a LSI. We analyzed ECG recordings collected on prehospital trauma patients with normal standard vital signs, testing the hypothesis that, if HPV metrics provided additional information above that of standard vital signs, these metrics would distinguish between those receiving a LSI and those that did not. (37) While group means of some of these HPV metrics statistically differed between the groups, there was inordinately high (81% to 94%) overlap of individual patient HPV values between groups, suggesting that patients would have been incorrectly classified if HPV alone was used as a triage tool (Figure 4). This finding assumes even greater importance when considered in the context of remote triage, as ECG-derived metrics would be the only available resource in the absence of physical access to the patient using currently proposed PSM systems.

[FIGURE 4 OMITTED]

In order to effectively interpret an alteration in HPV metrics as suggestive of a casualty rather than a fighting Soldier in a remote situation, it is also necessary to distinguish the difference(s) in physiological responses under these conditions. To answer the question of specificity to hemorrhage, we tested the hypothesis that HPV metrics would be able to differentiate between subjects exposed to LBNP (simulating blood loss) or the same subjects undergoing moderate exercise. (10) Figure 5 demonstrates that HPV metrics respond in a similar fashion during controlled laboratory experiments using LBNP vs exercise. Therefore, HPV metrics are unable to differentiate an active Soldier from a bleeding Soldier when the individual is not visible to the combat medic. While we used exercise as an experimental model to produce sympathetic activation and increase heart rate, it is important to note that other physiological stimuli occurring in combat Soldiers that increase heart rate (eg, anxiety, pain, heat or cold stress) might also be confused with blood loss if HPV metrics were used in a remote triage system. Indeed, Sacha and Pluta recently demonstrated that increases in heart rate of any etiology produce profound decreases in HPV metrics, purely for mathematical reasons because of the curvilinear relationship between heart rate and RRI. (38)

To summarize, current remote triage wear-and-forget monitoring systems (ie, PSM prototypes) measure ECG and respiration rate. Certainly, this information could be useful in assessing whether a soldier is alive or dead following injury and the current prototypes therefore meet the objective criterion of life sign detection. An optimal remote triage system, however, would additionally provide valuable information a) that any elevation in heart rate, respiration, or other physiological indicator is a result of injury (specificity); and b) that could aid in determination of severity of injury (sensitivity). Such information could assist combat medic decisions such as the initiation of treatment and prioritization of evacuation. The data discussed above raise profound concerns that the implementation of HPV metrics into a remote triage system could provide this information. Therefore, we have redirected our focus to the development of a novel remote triage system that does not rely solely on ECG-derived metrics.

NOVEL MEASUREMENTS FOR REMOTE TRIAGE

If not HPV metrics, what should be measured to determine the presence and severity of hemorrhage in a remote triage system? From our laboratory studies, it is clear that stroke volume and pulse pressure (systolic minus diastolic blood pressure) decrease consistently with central hypovolemia, at least on a group mean basis. (39) As previously described, we performed a study in which the ability of HPV metrics to differentiate between a state of central hypovolemia simulating blood loss (via LBNP) and physical activity was ascertained (10) While HPV metrics could not reliably distinguish between these physiological conditions (Figure 5), we were able to identify that pulse pressure could differentiate the conditions of physical activity from LBNP (Figure 6). This was not an unexpected finding as pulse pressure (ie, systolic blood pressure minus diastolic blood pressure) tracks stroke volume, which increases with exercise (40) and decreases with LBNP. (34,39) Hence, both stroke volume and pulse pressure could be reasonable candidates for determination of central hypovolemia during hemorrhage.

Currently, however, the only portable methods of measuring ambulatory blood pressure (and thereby deriving pulse pressure) or stroke volume are cumbersome and restrict movement and dexterity. Ambulatory blood pressure monitors, for example, use inflatable, restrictive cuffs around the upper arm or fingers in order to make blood pressure measurements. Additionally, for technical and comfort reasons, the majority of these monitors cannot take measurements continuously, with most providing output once every 3 to 5 minutes. Clearly, current noninvasive blood pressure systems are not practicable for use in remote triage systems.

Recently, the emergence of artificial intelligence technology has offered a potential solution to this issue. By definition, this scientific discipline designs algorithms that allow computers to evolve behaviors based on empirical data (eg, from sensors). In essence, the algorithms can "learn" to solve problems, and therefore show promise as being able to predict in time the point of cardiovascular decompensation in individuals subjected to central hypovolemia. (41) Using this technology, machine-learning algorithms can be developed that learn to recognize patterns of responses in low-level physiological signals that are associated with changes in parameters that reflect volume status (eg, stroke volume or pulse pressure). As an example, a wearable, noninvasive monitor for the indirect measurement of energy expenditure has recently been developed (SenseWear Pro2 armband (BodyMedia Inc, Pittsburgh, PA); Figure 7, left panel). When placed in the designated location on the upper arm, this sensor system armband is able to detect the galvanic skin response, heat flux, and skin temperature. Using these 3 inputs, a proprietary machine-learning algorithm has been developed to track the response of pulse pressure to physiological stimuli. In our laboratory, preliminary data indicate the ability of the armband algorithm to track the progressive decrease in pulse pressure with application of LBNP (Figure 7, right panel). As a result, there was a very strong linear relationship between conventionally measured pulse pressure via finger photoplethysmography (Finometer (Finapres Medical Systems B.V., Amsterdam, The Netherlands)) and the pulse pressure predicted by the algorithm ([R.sup.2]=0.9). Furthermore, recent results indicate that the algorithm could predict actual pulse pressure or stroke volume values during either LBNP or exercise and that this algorithm was able to distinguish between LBNP and exercise with high ([greater than or equal to] 92%) accuracy, sensitivity, and specificity. (42) While preliminary, these results suggest that machine-learning technology may be a promising component of future re mote triage systems, as algorithms could be developed for distinguishing Soldiers who are active during combat from those who are hypovolemic due to traumatic hemorrhage. To date, all of these preliminary results have been acquired in a controlled laboratory setting with subjects who are not moving their arms appreciably. As development proceeds, it will be imperative to determine whether movement and other stressors (eg, dehydration, heat stress) produce measurement artifacts and, if so, whether these can be overcome. As always, field testing will be necessary to determine wearability and usefulness for the Warfighter.

[FIGURE 5 OMITTED]

[FIGURE 6 OMITTED]

[FIGURE 7 OMITTED]

It should be noted that, with the current configuration, implementation of an armband device in a remote triage system requires that the combat casualty have at least one upper extremity that is not severely injured. We therefore queried the Joint Theater Trauma Registry as to the likelihood that Soldiers in the current conflict would not meet this criterion. In Operations Iraqi Freedom and Enduring Freedom, only 6.47% of wounded Soldiers have presented with severe injury between the elbow and shoulder on one arm that would preclude effective use of an armband device. Therefore, a remote triage system based on an armband device could be used after injury in at least 93.5% of Soldiers. Given the equal probability that injury would occur to any one side (ie, 50% chance of an injury to the right arm), a remote triage system based on a single armband device worn on one arm alone should be able to capture approximately 96% of Soldier monitoring.

STANDOFF REMOTE TRIAGE

In addition to wearable systems that would yield continuous physiological monitoring, it is also desirable to have a system for standoff triage of a wounded Soldier who can be visualized. Such a capability would allow a combat medic to ascertain the status of a wounded Soldier under fire before putting himself at risk, and would therefore decrease the probability of harm to the medic. In fact, a Navy corpsman presented a battle vignette from Operation Enduring Freedom at the US Army Institute of Surgical Research in 2009, in which he discussed how he cared for 17 wounded-in-action comrades while under fire. At the end of his presentation, he was asked for a "wish list" of capabilities that would help him care for wounded Soldiers. His highest priority was "a ray gun to check out patients" (HM1 J. Torrisi, oral communication, 2009). Indeed, the authors have heard a number of high-ranking individuals within the medical departments of the various military branches express their wish for a "Star Trek tricorder."

At this point, the capability for standoff triage has not been realized. Both the US Department of Homeland Security and the Defense Advanced Research Projects Agency are currently funding, or have funded, initiatives aimed at developing this capability, using such technologies as laser Doppler vibrometry (43) and ultrawide-band radiofrequency radiation. It is quite conceivable that standoff technology could be developed to determine alive/dead status. If additional information concerning patient status is desired, the most promising signals to be measured will be those somehow associated with compensatory physiological responses to central hypovolemia. Measurement of such signals without contacting the body surface may be more challenging.

POTENTIAL ISSUES FOR REMOTE TRIAGE

It is clear that both combat medics and injured Soldiers would benefit from development of a capability for remote triage, whether in a wearable system or a standoff device. The above discussion focuses on our efforts to determine the best physiological responses to be measured by such a system during hemorrhage. Once developed, a number of other important issues must be resolved before fielding a capability in a battlefield situation. Clearly, any wearable remote triage system will have to be small, lightweight, rugged, and comfortable, and must not impede movement. In every war in recorded history, Soldiers have littered battlefields with gear that they felt was either not essential or diminished their mission performance. From this standpoint, solicitation of input from end-users is essential during the early developmental stages of these systems. Furthermore, remote triage systems will have to include algorithms that recognize when the physiological signals being collected have been corrupted by artifactual noise and are therefore not valid for accurate decision support. Additionally, any wireless radiofrequency communication produced by such a device will have to be integrated into the wireless communication network used on the battlefield. As part of this process, data transmission will have to be encrypted so that the location and status of an injured Soldier is not made evident to enemy combatants. It will also be important to have any remote triage systems hardened to withstand common battlefield occurrences such as vibration, blast, and electromagnetic pulses, which can disable all electrical devices on the battlefield. Power supply issues should also be considered, with the ability to use commercially available small batteries (eg, AAA) for operation in remote areas without electricity. None of these issues are insoluble, with the key being integration of engineering and communication expertise early in the process of development of a system. Development of remote triage devices for battlefield use will also benefit from the recent profound commercial interest in development of similar devices for home healthcare applications. This is a very active area of research and development which will use similar technologies that could be adapted for applicability to combat casualty care use, and which could serve as predicate devices for FDA approval. Once a legitimate candidate for a wearable system is prototyped, it will also be essential to field-test the system to gather input on wearability and useability from both combat medics and Soldiers, the ultimate customers for the system.

CONCLUSION

When making a remote triage decision without access to the patient, the military medic must know if a Soldier is wounded or simply engaged in combat. To assist with such decisions, it has been suggested that the future Warfighter will be equipped with physiological monitoring devices that will have the capability to measure ECG and respiration signals. However, since our research demonstrates that the raw and derived measurements from these signals (eg, heart rate, HPV, respiration rate) will not differentiate an active Soldier from a bleeding Soldier, new technologies that provide measurements that specifically reflect bleeding trauma will be required for the situation in which the Soldier is not visible. Our research provides new evidence that technologies exist with the capability to obtain surrogate information about the continuous status of pulse pressure or stroke volume, and that such technologies could provide essential information to the combat medic on the blood volume status of the Soldier and the need for prompt medical attention. Providing accurate and reliable indicators of patient status from a remote location will potentially protect combat medics from unnecessary exposure to enemy fire, and assist in the timely triage and evacuation of combat casualties. By producing new triage capabilities for use by the combat medic, the Advanced Capabilities for Emergency Medical Monitoring Task Area will also improve recognition of the need for early (prehospital) hemorrhage control and thereby reduce mortality on the battlefield. (2)

[ILLUSTRATION OMITTED]

ACKNOWLEDGEMENTS

Funding support was provided by the US Army Medical Research and Materiel Command Combat Casualty Care Research Program, Ft. Detrick, Maryland.

We thank Mr Gary Muniz for his superb technical assistance, and the research subjects for their cheerful cooperation.

REFERENCES

(1.) Holcomb JB. The 2004 Fitts Lecture: current perspective on combat casualty care. J Trauma. 2005;59(4):990-1002.

(2.) Martin M, Oh J, Currier H, et al. An analysis of in-hospital deaths at a modern combat support hospital. J Trauma. 2009;66(suppl 4):S51-S61.

(3.) Pinsky MR. Hemodynamic evaluation and monitoring in the ICU. Chest. 2007;132(6):2020-2029.

(4.) Asensio JA, McDuffie L, Petrone P, et al. Reliable variables in the exsanguinated patient which indicate damage control and predict outcome. Am J Surg. 2001;182(6):743-751.

(5.) Franklin GA, Boaz PW, Spain DA, Lukan JK, Carrillo EH, Richardson JD. Prehospital hypotension as a valid indicator of trauma team activation. J Trauma. 2000;48(6):1034-1039.

(6.) Shoemaker WC, Wo CC, Chan L, et al. Outcome prediction of emergency patients by noninvasive hemodynamic monitoring. Chest. 2001;120(2):528-537.

(7.) Grant RT, Reeve EB. Clinical observations on air-raid casualties. Br Med J. 1941;2:293-297.

(8.) Shenkin HA, Cheney RH, Govons SR, Hardy JD, Fletcher AG Jr, Starr I. On the diagnosis of hemorrhage in man: a study of volunteers bled large amounts. Am J Med Sci. 1944;209:421-436.

(9.) Convertino VA, Ryan KL, Rickards CA, et al. Physiological and medical monitoring for en route care of combat casualties. J Trauma. 2008;64 (suppl4):S342-S353.

(10.) Rickards CA, Ryan KL, Cooke WH, Romero SA, Convertino VA. Combat stress or hemorrhage? Evidence for a decision-assist algorithm for remote triage. Aviat Space Environ Med. 2008;79(7):670-676.

(11.) Department of Defense. [Southeast Asia] Combat Area Casualties Current File. Washington, DC: National Archives; 1993.

(12.) Hoyt RW, Reifman J, Coster TS, Buller MJ. Combat medical informatics: present and future. Proc AMIA Symp. 2002:335-339.

(13.) Savell CT, Borsotto M, Reifman J, Hoyt RW. Life sign decision support algorithms. Medinfo. 2004;11 (Pt 2):1453-1457.

(14.) Hamilton D, Smart K, Melton S, Polk JD, Johnson-Throop K. Autonomous medical care for exploration class space missions. J Trauma. 2008;64(suppl 4):S354-S363.

(15.) Curone D, Dudnik G, Loriga G, et al. Smart garments for safety improvement of emergency/disaster operators. Conf Proc IEEE Eng Med Biol Soc 2007. 2007:3962-3965.

(16.) Cooke WH, Ryan KL, Convertino VA. Lower body negative pressure as a model to study progression to acute hemorrhagic shock in humans. J Appl Physiol. 2004;96(4):1249-1261.

(17.) Hon EH, Lee ST. Electronic evaluation of the fetal heart rate. VIII. Patterns preceding fetal death, further observations. Am J Obstet Gynecol. 1963;87:814 826.

(18.) Acharya UR, Joseph KP, Kannathal N, Lim CM, Suri JS. Heart rate variability: a review. Med Biol Eng Comput. 2006;44:1031-1051.

(19.) Goldstein B. How do we get from here to there? A pathway for trial design in complex systems analysis. Crit Care Med. 2007;35(2):656-658.

(20.) Huikuri HV, Perkiomaki JS, Maestri R, Pinna GD. Clinical impact of evaluation of cardiovascular control by novel methods of heart rate dynamics. Philos Transact A Math Phys Eng Sci. 2009;367 (1892):1223-1238.

(21.) Akselrod S. Components of heart rate variability: basic studies. In: Malik M, Camm AJ, eds. Heart Rate Variability. Armonk, NY: Futura Publishing Company, Inc; 1995:147-163.

(22.) Guyton AC, Harris JW. Pressoreceptor-autonomic oscillation: A probable cause of vasomotor waves. Am J Physiol. 1951;165:158-166.

(23.) Malliani A, Pagani M, Lombardi F, Cerutti S. Cardiovascular neural regulation explored in the frequency domain. Circulation. 1991;84(2):482-492.

(24.) Cooke WH, Convertino VA. Heart rate variability and spontaneous baroreflex sequences: implications for autonomic monitoring during hemorrhage. J Trauma. 2005;58(4):798-805.

(25.) Cooke WH, Rickards CA, Ryan KL, Convertino VA. Autonomic compensation to simulated hemorrhage monitored with heart period variability. Crit Care Med. 2008;36(6):1892-1899.

(26.) Cooke WH, Salinas J, Convertino VA, et al. Heart rate variability and its association with mortality in prehospital trauma patients. J Trauma. 2006;60 (2):363-370.

(27.) Cooke WH, Salinas J, McManus JG, et al. Heart period variability in trauma patients may predict mortality and allow remote triage. Aviat Space Environ Med. 2006;77(11):1107-1112.

(28.) Batchinsky AI, Cancio LC, Salinas J, et al. Prehospital loss of R-to-R interval complexity is associated with mortality in trauma patients. J Trauma. 2007;63(3):512-518.

(29.) Cancio LC, Batchinsky AI, Salinas J, et al. Heart-rate complexity for prediction of prehospital lifesaving interventions in trauma patients. J Trauma. 2008;65 (4):813-819.

(30.) King DR, Ogilvie MP, Pereira BM, et al. Heart rate variability as a triage tool in patients with trauma during prehospital helicopter transport. J Trauma. 2009;67(3):436-440.

(31.) Batchinsky AI, Salinas J, Kuusela T, Necsoiu C, Jones J, Cancio LC. Rapid prediction of trauma patient survival by analysis of heart rate complexity: impact of reducing data set size. Shock. 2009;32 (6):565-571.

(32.) Rickards CA, Ryan KL, Convertino VA. Characterization of common measures of heart period variability in healthy human subjects: implications for patient monitoring. J Clin Monit Comput. 2010;24(1):61-70.

(33.) Tan CO, Cohen MA, Eckberg DL, Taylor JA. Fractal properties of human heart period variability: physiological and methodological implications. J Physiol. 2009;587(15):3929-3941.

(34.) Ryan KL, Rickards CA, Ludwig DA, Convertino VA. Tracking central hypovolemia with ECG in humans: cautions for the use of heart period variability in patient monitoring. Shock. 2010;33 (6):583-589.

(35.) Sethuraman G, Ryan KL, Rickards CA, Convertino VA. Ectopy in trauma patients: cautions for use of heart period variability in medical monitoring. Aviat Space Environ Med. 2010;81(2):125-129.

(36.) Task Force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology. Heart rate variability: standards of measurement, physiological interpretation and clinical use. Circulation. 1996;93(5):1043-1065.

(37.) Rickards CA, Ryan KL, Ludwig DA, Convertino VA. Is heart period variability associated with the administration of lifesaving interventions in individual prehospital trauma patients with normal standard vital signs? Crit Care Med. 2010;38(8):1666-1673.

(38.) Sacha J, Pluta W. Alterations of an average heart rate change heart rate variability due to mathematical reasons. Int J Cardiol. 2008;128(3):444-447.

(39.) Convertino VA, Cooke WH, Holcomb JB. Arterial pulse pressure and its association with reduced stroke volume during progressive central hypovolemia. J Trauma. 2006;61(3):629-634.

(40.) Janicki JS, Sheriff DD, Robotham JL, Wise RA. Cardiac output during exercise: contributions of the cardiac, circulatory, and respiratory systems. In: Rowell LB, Shepherd JT, eds. Handbook of Physiology. Exercise: Regulation and Integration of Multiple Systems. Bethesda, MD: American Physiological Society; 1996:649-704.

(41.) Convertino VA, Moulton SL, Grudic GZ, Rickards CA, Hinojosa-Laborde C, Ryan KL. Use of advanced machine-learning techniques for non-invasive monitoring of hemorrhage. In: Use of Advanced Technologies and New Procedures in Medical Field Operations. Brussels, Belgium: NATO Publication RTO-MP-HFM-182; 2010: Paper 23. Available at: http://www.rta.nato.int/Pubs/RDP.asp?RDP=RTOMP-HFM-182.

(42.) Convertino VA, Hurst GM, Ryan KL, Vyas N, Rickards CA. Bleeding or active? Validation of a machine-learning algorithm for remote determination of blood volume status. Med Sci Sports Exerc. 2010;42(suppl 5):S201.

(43.) Department of Homeland Security. Triage technology with a Star Trek twist: Tricorder-like device. ScienceDaily [serial online]. June 1, 2009. Available at: http://www.sciencedaily.com/releases/2009/05/09 0527174732.htm. Accessed July 21, 2010.

Kathy L. Ryan, PhD

Caroline A. Rickards, PhD

Carmen Hinojosa-Laborde, PhD

LTC(P) Robert T. Gerhardt, MC, USA

LTC (Ret) Jeffrey Cain, MC, USA

Victor A. Convertino, PhD

* [absolute value of r] indicates the absolute value of the correlation coefficient.

Dr Ryan is a Research Physiologist, US Army Institute of Surgical Research, Fort Sam Houston, Texas.

Dr Rickards is a Research Assistant Professor, Department of Health and Kinesiology, University of Texas at San Antonio, Texas.

Dr Hinojosa-Laborde is a Research Physiologist, US Army Institute of Surgical Research, Fort Sam Houston, Texas.

LTC(P) Gerhardt is Chief, Prehospital and Emergency Care Research Program, US Army Institute of Surgical Research, Fort Sam Houston, Texas.

LTC (Ret) Cain is a Staff Emergency Physician with QuestCare Partners, Dallas, Texas.

Dr Convertino is a Senior Research Physiologist and Task Area Manager, US Army Institute of Surgical Research, Fort Sam Houston, Texas.
COPYRIGHT 2011 U.S. Army Medical Department Center & School
No portion of this article can be reproduced without the express written permission from the copyright holder.
Copyright 2011 Gale, Cengage Learning. All rights reserved.

Article Details
Printer friendly Cite/link Email Feedback
Author:Ryan, Kathy L.; Rickards, Caroline A.; Hinojosa-Laborde, Carmen; Gerhardt, Robert T.; Cain, Jeffrey;
Publication:U.S. Army Medical Department Journal
Article Type:Report
Geographic Code:1USA
Date:Apr 1, 2011
Words:5856
Previous Article:Advances in prehospital burn resuscitation for the combat injured.
Next Article:Advanced monitoring and decision support for battlefield critical care environment.
Topics:

Terms of use | Copyright © 2017 Farlex, Inc. | Feedback | For webmasters