Method, system and device for personalized oxygen supply treatment of premature infant

Abstract

Embodiments of methods, systems, and / or devices facilitate dynamic optimization of oxygen saturation target ranges for preterm infants in a manner that personalizes the physiological state of the preterm infant. In an exemplary embodiment, an oxygen saturation target is dynamically set by monitoring a heart rate of a preterm infant and / or determining a pulmonary elasticity measurement (PRM) and adjusting an oxygen saturation target range of the preterm infant. In various embodiments, heart rate variability measurements and / or PRM are evaluated according to a preset threshold, and if the heart rate variability measurements and / or PRM reach or exceed the preset threshold, the oxygen saturation target range is adjusted. Embodiments of the present disclosure may also optionally readjust the oxygen saturation target range at fixed time intervals based on alerts communicating the oxygen saturation target range and / or based on heart rate variability measurements and / or PRM.

Description

Technical Field

[0001] This invention relates to personalized healthcare, and more particularly to a method, system, and apparatus for personalized control of one or more factors affecting the health outcomes of preterm infants. Background Technology

[0002] Bronchopulmonary dysplasia (BPD) is a chronic lung disease in infants with high morbidity and mortality. Extremely preterm newborns face a paradox at birth: oxygen is essential for extrauterine life support, but its toxicity is undeniable, especially for preterm infants whose lungs and other organs should develop in the hypoxic intrauterine environment. Attempts to minimize oxygen exposure by reducing oxygen saturation appear to reduce BPD, but increase mortality. Given the potential link between lower oxygen saturation and increased mortality, practice guidelines tend to target higher oxygen saturation. This consistently increases oxygen exposure, triggering a range of pathogenic mechanisms associated with BPD development.

[0003] Using these higher target saturations as standards of care, 22-45% of very low birth weight infants will be affected by BPD. The downstream effects of BPD are very serious: the cost of initial hospitalization is twice as high; the risk of late-onset sepsis, cerebral palsy, neurodevelopmental disorders, and pulmonary disease is increased, and the risk of readmission in the first year is doubled; the socioeconomic impact on the patient's entire life extends to the family.

[0004] Although the pathogenesis of BPD is multifactorial, oxidative stress (OS) is generally considered to be the cause of its characteristic pulmonary inflammation and vascular dysplasia. OS in preterm infants is a driver of morbidity and mortality and can be termed “neonatal oxygen free radical disease.” Evidence suggests that OS in preterm lungs is characteristic and highlights its mechanisms of influencing pulmonary inflammation and vascular changes. Reactive oxygen species (ROS) include free radical molecules that are highly toxic to cells. OS can occur in full-term infants, but preterm newborns are at greater risk because: (1) there is an increased supply of free iron available to generate additional free radicals; (2) the preterm environment challenge of transitioning from a hypoxic womb to air; (3) oxygen may be required to treat respiratory distress and inadequate respiratory function; and (4) the antioxidant defense system is impaired. Multiple organs in preterm infants are susceptible to damage caused by OS, and neonatal oxygen free radical disease can lead to manifestations of postpreterm diseases such as BPD, necrotizing enterocolitis (NEC), and retinopathy of prematurity (ROP; which itself increases the risk of blindness).

[0005] A prospective meta-analysis of neonatal oxygenation (NeOProM) found that for infants with a gestational age (GA) less than 28 weeks, a target oxygen saturation (SpO2) range of 85-89%, compared to 91-95%, reduced the incidence of recurrent oxygen saturation (ROP) but increased the risk of death. Currently, there are limited physiological parameters for optimizing oxygen delivery to reduce morbidity and mortality. For example, minimizing oxygen exposure can reduce morbidity but increase mortality. The amount of oxygen therapy is determined by the range of oxygen saturation measured by pulse oximetry, usually by setting alarm limits on the pulse oximeter, but the optimal target for balancing the best benefit with the least harm remains unknown. Therefore, the clinical challenge is that efforts to minimize oxygen exposure and reduce the incidence of oxygen free radical diseases can be offset by increased mortality. To date, the standard recommendations have specified uniform oxygen saturation targets that favor higher oxygen exposure for all preterm newborns in the neonatal intensive care unit (NICU) to minimize mortality, even if this results in overoxygenation in some or most infants.

[0006] In various embodiments, this disclosure addresses the aforementioned and more challenges by measuring lung resilience and autonomic nervous system (ANS) activity through heart rate signal analysis. Lung resilience is a homeostatic process driven by the ANS, acting as a regulator of physiological stress and, when functioning, can inform successful environmental adaptation after extreme preterm birth. Early ANS function can explain individual variability in the association between cumulative oxygen supply (CSO) exposure and short-term respiratory outcomes. Measurements of lung resilience (PRM) may include one or more of heart rate (HR), mean, median, and standard deviation of heart rate, measurements of heart rate deceleration and acceleration, heart rate variability (HRV), heart rate characteristics (HRC), HRC index (HRCi), heart rate entropy, vagal tone, and parasympathetic / sympathetic balance. PRM alters the association between early vital oxygen exposure and short-term respiratory outcomes.

[0007] The ANS operates at a subconscious level, routinely adjusting various physiological systems in response to body temperature-related needs and coordinating cardiovascular, respiratory, digestive, excretory, and reproductive functions. The sympathetic and parasympathetic branches of the ANS develop independently during fetal development. The sympathetic branches responsible for the fight-or-flight response and increased heart rate develop rapidly in the first trimester, then at a slower pace; the parasympathetic branches responsible for the rest-and-digest response and decreased heart rate develop significantly between 25 and 30 weeks of gestation (GA). Immature and underdeveloped ANSs can lead to irregular and rapid fluctuations in heart rate (HR), and HRV can be affected by sleep patterns and postnatal growth and development.

[0008] Preterm infants exhibit predominantly active sleep patterns in their electrical and neural activity. HRV measurements reveal increased sympathetic activity, decreased parasympathetic activity, and reduced overall ANS complexity and adaptability. HRV studies have shown that postnatal ANS development and maturation are associated with increased GA (growth age) and postnatal age. HRV characterization analysis indicates that preterm infants have the lowest sympathetic and parasympathetic tone, even compared to term infants. Furthermore, early life in preterm infants is characterized by predominantly sympathetic activity and reduced parasympathetic activity, an imbalance that can be further altered by postnatal complications and morbidity. Compared to healthy controls, preterm infants with intrauterine growth restriction (IUGR) and those who smoked in utero had more impaired HRV, both of which are risk factors for BPD (biological developmental delay) and other preterm complications. Therefore, ANS functional immaturity and potential dysregulation of interactions between its two branches are expected consequences of preterm birth. The extent of this dysfunction and how it affects the regulation of inflammatory neuroreflexes may influence both short-term and long-term outcomes in preterm infants, but this remains under-researched.

[0009] The clinical significance of ANS dysfunction has been described in critically ill adult patients and is associated with conditions such as multiple organ failure, sepsis, myocardial infarction, decompensated heart failure, and severe brain injury. The ANS maintains homeostasis by routinely regulating various physiological systems. The sympathetic and parasympathetic nervous systems of the ANS transmit peripheral events from all systems, including those from the pulmonary vascular bed and components of the immune system, to the brainstem regulatory centers responsible for cardiopulmonary changes. Heart rate variability (HRV) is a non-invasive measure of ANS function, defined as the variation in the length of time between consecutive heartbeats, as the ANS continuously adjusts heart rate and rhythm in response to bodily needs. ANS function measured by HRV has been studied and described during fetal and neonatal development, and a well-known clinical use of HRV is monitoring fetal HRV to detect fetal distress. Detecting unique characteristics of fetal heart rate variability, such as transient decelerations, may indicate fetal distress, and this monitoring has significantly reduced morbidity and mortality.

[0010] Early life oxygenation (ANS) activity levels are an indicator of lung resilience and modulate the association between oxygen exposure and respiratory outcomes, impacting overall outcomes such as mortality, lung disease progression (BPD), lung endocarditis (NEC), and respiratory failure (ROP). In embodiments of this disclosure, ANS function is measured to inform clinicians of the optimal oxygen delivery dose to facilitate post-preterm environmental adaptation while minimizing the toxicity of excessive oxygen delivery, which may occur under current strategies that aim for a uniform higher saturation range.

[0011] HRC is a specific subset of HRV, selected or developed to identify abnormalities in the HR pattern of preterm infants. Previous studies have shown that HRCi (also known as HeRO score) can predict various neonatal diseases, including sepsis, urinary tract infection, NEC, meningitis, respiratory decompensation, extubation preparation, and death; and is associated with cytokines. According to this disclosure, various aspects of HRCi and / or some intermediate calculations related to HRCi can be used to dynamically adjust the target range of oxygen saturation for preterm infants. For example, patients with lower HRCi have a lower or likely lower risk of death and can safely maintain oxygenation at 85-89%. As HRCi increases, the risk of death also increases, and these infants should be managed within a higher target range of oxygen saturation. Furthermore, various aspects of HRCi and / or some intermediate calculations related to HRCi can be used together with other factors to measure lung elasticity. This PRM can be used to dynamically adjust the target range of oxygen saturation for preterm infants. Therefore, only patients at risk of death will be at risk of BPD or ROP. Summary of the Invention

[0012] In various embodiments, the methods, systems, and / or apparatuses according to this disclosure facilitate personalized control of one or more factors, such as a target oxygen saturation range for preterm infants. In exemplary embodiments, the oxygen saturation target for a preterm infant is dynamically set by monitoring the preterm infant's HRV and / or measuring the preterm infant's PRM and adjusting the target oxygen saturation range. It is understood that the adjustment of the target oxygen saturation range is based on or may be based on HRV measurements and / or PRM. In various embodiments, HRV measurements and / or PRM are evaluated against preset thresholds, and the target oxygen saturation range is adjusted if the HRV measurements and / or PRM reach or exceed the preset thresholds. Embodiments of this disclosure may also selectively readjust the target oxygen saturation range, for example, based on an alarm conveying the target oxygen saturation range, and / or based on HRV measurements and / or PRM at regular time intervals.

[0013] In various embodiments, one or more thresholds may be established for monitoring conditions. An alarm is generated when a measured threshold is reached or exceeded. For example, the alarm may provide suggested action plans. In various embodiments, the alarm may provide instructions to autonomous devices or human-monitored electronic devices to take indicated actions. For example, when an HRV measurement reaches or exceeds a threshold, an alarm may be issued to the oxygen supply device (e.g., a standard ventilator, a high-frequency oscillatory ventilator, a continuous positive airway pressure device, a nasal cannula, or other oxygen supply device) or human-machine monitoring electronic device to adjust the patient's oxygenation according to a defined target range for oxygen saturation.

[0014] The exemplary system according to this disclosure employs a monitoring device and means adapted to receive an alarm based on operation according to this disclosure, the alarm being triggered based on a measurement result received from the monitoring device disclosed herein.

[0015] The embodiments disclosed herein help to dynamically optimize the target range of oxygen saturation for preterm infants in a personalized manner based on the infant's physiological state. Attached Figure Description

[0016] Figure 1 and Figure 2 This is a flowchart illustrating an exemplary method according to an embodiment of the present disclosure.

[0017] Figure 3 This is a schematic diagram of an exemplary system according to an embodiment of the present disclosure.

[0018] Figure 4 This is a schematic diagram of an exemplary apparatus or machine that may implement or operate one or more aspects of the embodiments of this disclosure.

[0019] Figure 5 and Figure 6 This is a flowchart illustrating an exemplary method according to an embodiment of the present disclosure. Detailed Implementation

[0020] The foregoing and other aspects of this disclosure will now be described in more detail with respect to the descriptions and methods provided herein. It should be understood that this disclosure may be embodied in different forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of this disclosure to those skilled in the art.

[0021] The terminology used in the description disclosed herein is for the purpose of describing particular embodiments only and is not intended to limit the scope of this disclosure. As used in the description of embodiments of this disclosure and in the appended claims, the singular forms “a,” “an,” and “the” are intended to include the plural forms as well, unless the context clearly indicates otherwise. For example, a measurement may include one or more measurements, a processor may include one or more processors, and so on. Furthermore, as used herein, “and / or” refers to and covers any and all possible combinations of one or more of the associated listed items. As used herein, the terms “comprising,” “including,” specify the presence of the stated features, integers, steps, operations, elements, and / or components, but do not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and / or groups thereof.

[0022] In various embodiments, the method according to this disclosure relates to dynamic targets for oxygen saturation in preterm infants. For example... Figure 1 As shown, the method includes: at 50, monitoring the preterm infant's heart rate via a monitoring device to obtain an HRV measurement; and at 52, adjusting the preterm infant's target oxygen saturation range. It should be understood that adjusting the target oxygen saturation range is based on, or may be based on, the HRV measurement. In various embodiments, the method may optionally determine whether the HRV measurement has reached or exceeded a preset threshold, as shown at 54 and indicated by a dashed line. If the HRV measurement result does not reach or exceed the preset threshold, the method returns to 50. If the HRV measurement result reaches or exceeds the preset threshold, the method continues to 52. In various embodiments, the method may also optionally readjust the oxygen saturation range, for example, based on an alarm conveying the target oxygen saturation range, and / or based on the HRV measurement value at fixed time intervals, as shown by a dashed line at 56.

[0023] For example, a predetermined threshold of 2.0 for the HRCi score can be set, and if the measured HRV produces an HRCi score higher than this threshold, no changes are made to the established default oxygen saturation target range (e.g., this range can remain at 91-95%). Alternatively, if the measured HRV produces an HRCi score lower than this threshold, the oxygen saturation target range is adjusted to a new range (e.g., 85-89%). As another example, the method of this disclosure adds the HRCi score determined by the measured HRV to a baseline or default oxygen saturation target range. In various embodiments, this range adjustment is performed sequentially starting from a lower default range. For example, if the default range is 85-89% and the HRCi score is below 1, the target oxygen saturation range will remain at 85-89%. However, if the HRCi score is 1, the target oxygen saturation range is increased by 1% at the low and high ends to 86-90%. If the HRCi score is 2, the target oxygen saturation range is increased by 2% at the low and high ends to 87-91%, and so on. It should be understood that the HRCi score can be determined based on the measured HRV according to, for example, the method described in U.S. Patent No. 6,216,032 to Griffin et al., the disclosure of which is incorporated herein by reference in its entirety.

[0024] refer to Figure 2 A predetermined threshold can be determined at point 60 by determining the probability of one or more outcomes based on HRV measurements. In various embodiments, this can be determined within a low oxygen saturation target range and a high oxygen saturation target range. In other embodiments, this can be determined at a continuum of oxygen saturation target ranges. At point 62, embodiments of the method can add a product of cost or utility associated with each of the one or more outcomes, where each cost or utility is weighted by the predicted probability. As shown at point 64, embodiments of the method can then select an oxygen saturation target range with lower or lowest cost, or higher or highest utility.

[0025] For example, embodiments of this disclosure use HRV measurements to provide dynamic, personalized probabilities of patient outcomes, such as death.

[0026] For example, using a Bayesian classifier framework, a binary decision can be made to select a high or low oxygen saturation target range for a specific patient at a given time. For the patient at that time, the most recent HRV measurement can be used to estimate the dynamic probability of outcomes such as death and various diseases. If the patient is in either the low or high oxygen saturation target range group, the probability of multiple outcomes can be further estimated. The probability of each outcome can be multiplied by the cost associated with that outcome, and this can be summed separately for the number of low and high oxygen saturation target range groups. Finally, the oxygen saturation target range that minimizes the total cost associated with the predicted outcome can be selected. For example, the U.S. Department of Health and Human Services (HHS) reported lifetime costs associated with intellectual disability, cerebral palsy, hearing loss, and visual impairment in 2003 dollars: $1,014,000, $921,000, $417,000, and $566,000, respectively. The U.S. Department of Health and Human Services (HHS) published a value of life of $9.3 million in 2014 dollars (compared to $7.2 million in 2003 dollars). If the estimated probabilities of a patient's death, intellectual disability, cerebral palsy, hearing loss, and visual impairment at a specific time are 20%, 20%, 10%, 5%, and 5%, respectively, and these probabilities are 15%, 25%, 15%, 10%, and 10% when the patient is within the target range for hypoxia saturation, then the expected cost of choosing the target range for hypoxia saturation is $1,784,050 ($0% x $7.2M + 20% x $1,014,000 + 10% x $921,000 + 5% x $417,000 + 5% x $566,000), while the expected cost of choosing the target range for hyperxia saturation is $1,569,950 ($15% x $7.2M + 25% x $1,014,000 + 15% x $921,000 + 10% x $417,000 + 10% x For example, at $566,000, people would choose a high oxygen saturation target range. In various embodiments, the patient's outcome probability can be multiplied by the benefit or utility associated with the outcome, and the quantities can be summed separately for the low oxygen saturation target range group and the high oxygen saturation target range group. In this case, an oxygen saturation target range can be selected to maximize the total utility or benefit associated with the predicted outcome. A common example of a benefit associated with certain healthcare-related outcomes is Quality Adjusted Life Year (QALY), which is calculated similarly to the cost calculation methods described above, ultimately selecting an oxygen saturation target range that maximizes the expected QALY.

[0027] In various embodiments, linear interpolation can be used to estimate the probability of some or all of the morbidity associated with a target range of oxygen saturation on a continuum. Similarly, the weighted cost of each range within the continuum can be calculated by adding the product of cost and / or utility to the corresponding probability. Finally, the target range of oxygen saturation can be selected to minimize total cost and / or maximize total utility. Extending the binary cost example above, one might estimate that a target range of moderate oxygen saturation (88-92%) has a 16% HRV-based probability of death, while other outcomes estimated using linear interpolation are 22.5% for intellectual disability, 12.5% ​​for cerebral palsy, 7.5% for blindness, and 7.5% for deafness. This would lead people to choose the middle range of oxygen saturation targets, as it minimizes the expected cost of $1,569,000 ($16% x $7.2M + 22.5% x $1,014,000 + 12.5% ​​x $921,000 + 7.5% x $417,000 + 7.5% x $566,000).

[0028] In various embodiments, one or more thresholds can be established for monitoring conditions. An alarm is generated when a measured threshold is reached or exceeded. In various embodiments, alarms are detection event communications based on detected events. In various cases, the "event" appears in the form of reaching or exceeding a threshold. For example, an alarm can provide suggested course of action. In various embodiments, alarms can provide instructions to autonomous devices to take indicated actions. For example, an alarm regarding an adjusted oxygen saturation range can be issued when an HRV measurement reaches or exceeds a threshold.

[0029] As a concrete example, see reference Figure 3System 10, in which a monitoring device 12 for a preterm infant (i.e., the patient) monitors the preterm infant's heart rate characteristics, such as HRV. The monitoring device may include electrocardiogram (ECG) leads, pulse oximeter sensors, chest straps, watches, armbands, or other suitable devices or equipment for monitoring HRV. If the HRV measurement reaches or exceeds a preset threshold, an alarm may be issued to a servo-controlled oxygen supply device 14, operable to adjust the oxygen flow rate to maintain the preterm infant within the oxygen saturation range. As another example, an alarm may be issued to a device 18 used by a caregiver, instructing a recommended oxygen saturation range setting or adjustment for the ventilation device 16 of the monitored preterm infant. Upon receipt, the caregiver may physically or electronically interact with the pulse oximeter or oxygen supply device 14 to adjust one or more settings on the respective device according to the received recommended oxygen saturation range. It should be understood that the threshold measurements and determinations described herein can be performed by a suitable computing device including a processor and memory storing instructions operable to perform the functions described herein. For example, monitoring device 12 may have an internal processor and programs to establish thresholds, make determinations, and issue one or more alarms based on the determinations, in accordance with this disclosure. Such alarms can be communicated via network 20 to other systems and / or devices communicating with network 20. In other examples, monitoring device 12 may transmit raw measurement results via network 20 to an external computing system or device 22, which employs a processor and programs to establish thresholds, make determinations, and issue one or more alarms based on the determinations, in accordance with this disclosure. For example, device 22 may be an electronic health record or electronic medical record system, which may be programmed to generate commands that should be sent by a doctor to a nurse to modify the target range. In other examples, monitoring device 12 may transmit raw measurement results via network 20 to a personal computing device 18, which employs a processor and programs to establish thresholds, make determinations, and issue one or more alarms based on the determinations, in accordance with this disclosure. In various other embodiments, according to this disclosure, the oxygen supply device 14 employs a processor and programs to establish thresholds, perform measurements, issue alarms, and mechanically or electronically operate and adjust the oxygen supply and / or oxygen saturation range on the ventilation device 16.

[0030] In various embodiments, oxygen supply device 14 and / or ventilation device 16 may provide a bedside display of real-time PRM to inform the user of a dynamic prescription for oxygenation saturation targets during oxygen supply, in accordance with the present disclosure. It is understood that the exact manner of acquiring vital signs, measuring lung elasticity, and subsequent analysis can be achieved through a variety of techniques. For example, it can be achieved by collecting vital signs and analyzing vital sign samples locally, or by transmitting information via a data communication network (e.g., network 20) ​​to another location or computing device (e.g., 14, 18, 22), where further analysis or other processing can be performed. Furthermore, data and results can be displayed in a variety of ways at any point in the process. For example, readings and data can be conveyed to the user via visual media or auditory signals (e.g., speech or tone) or a combination thereof.

[0031] It should be understood that network 20 can be a local area network (LAN), a wide area network (WAN), a public network such as the Internet, or a private network. Devices 12, 14, 18 and / or system / device 22 are configured to connect to network 20 or a remote communication link in any suitable manner. In various embodiments, such connection is achieved through: traditional telephone lines or other data transmission lines, digital subscriber lines (DSL), T-1 lines, coaxial cables, fiber optic cables, wireless or wired routing equipment, mobile communication network connections (e.g., cellular networks or mobile internet networks), or any other suitable medium. In various embodiments, system / device 22 is an online-accessible cloud portal or server.

[0032] Therefore, embodiments of system 10 may include a monitoring device 12 adapted to monitor the HRV of a preterm infant, and a computing device (e.g., 14, 18, or 22) adapted to determine the PRM of the preterm infant based on the HRV measurement, determine whether the PRM has reached or exceeded a preset threshold, and issue an alarm, such as communicating a target range for the preterm infant's oxygen saturation. This target range may be adjustable by manually or electronically setting limits on the pulse oximeter device, as described elsewhere herein.

[0033] Figure 4This is a block diagram illustrating an example of a machine or apparatus 100 on which one or more aspects of embodiments of the present disclosure may be implemented (or operated). Apparatus 100 is one example; others may include logic, a machine, circuit, module, or mechanism having one or more components. In one example, one or more computer systems or one or more hardware processors (processors) may be configured by software to perform certain operations as described herein. Apparatus 100 may be a classic von Neumann computer architecture, wherein instructions 124 are stored in non-volatile memory 106 and then loaded into microprocessor 102. Volatile memory 104 may be used as temporary storage (i.e., cache) to improve performance. Communication between the various subsystems in apparatus 100 is achieved via a shared communication bus 108. In this example embodiment, instructions 124 cause microprocessor 102 to implement one or more aspects of the present invention. Examples of apparatus 100 include Figure 3 Devices 12, 14, 16, 18 and 22.

[0034] Specific data for one or more patients can be acquired via network interface 120 from network 20 or from sensor 122 connected to analog-to-digital converter or A / D converter 121. Users or operators can interact with device 100 using keyboard 112 or mouse 114; however, those skilled in the art will understand that many other examples of devices for interacting with a computer exist, including touchscreen displays, touchpads, trackballs, speech recognition software, etc. The output of this invention can be conveyed to the user or operator on display 110, or by causing audio card 116 to emit certain tones or sounds, or by causing digital-to-analog converter (D / A) converter 118 to issue alarm signals, or by transmitting these results to other computers or devices on network 20 via network interface 120. Those skilled in the art will understand that computers can also convey results to users or operators in other ways, including printers, non-volatile memory devices, synthesized speech audio, etc.

[0035] refer to Figure 5It should be understood that the embodiments described herein can establish a default level for the range of oxygen saturation provided to preterm infants, as shown at 70. This default level differs from the adjusted oxygen saturation range determined according to the procedures described elsewhere in this document. It should also be understood that the oxygen saturation range can be adjusted by reducing the oxygen saturation range based on a coefficient multiplied by the HRV measurement, as shown at 72. For example, the target oxygen saturation range could be equal to the default target range minus M multiplied by the PRM, where M is the coefficient. For example, the PRM could be calculated as 7 minus the highest HRCi over the previous 72 hours, the coefficient M could be chosen to be 0.5, and the default range could be 91-95%. Therefore, the target range for dynamic oxygen saturation for a particular patient could be 91% to 95%, minus 0.5 x (7 minus the highest HRCi over the previous 72 hours).

[0036] refer to Figure 6 According to another exemplary method of this disclosure, a dynamic target for oxygen saturation in preterm infants is determined. Figure 6 As shown, the method includes, at 80, monitoring via a device (e.g., Figure 3 The device 12) monitors the heart rate of the preterm infant. At 82, the PRM of the preterm infant is determined. At 86, the target range for oxygen saturation of the preterm infant is adjusted. It should be understood that the measurement of lung elasticity is based on or may be based on HRV measurement. It should also be understood that the adjustment of the target range for oxygen saturation is based on or may be based on PRM. In various embodiments, the method may optionally determine whether the PRM has reached or exceeded a preset threshold, such as at 84 and indicated by a dashed line. If the PRM has not reached or exceeded the preset threshold, the method returns to 80. If the PRM has reached or exceeded the preset threshold, the method continues to 86.

[0037] In various embodiments, additional variables such as gestational age, birth weight, sex, maternal factors (e.g., race / ethnicity, prenatal steroid use, etc.), concomitant medications and interventions, and comorbidities may be used in conjunction with PRM measurements to assess the target range for oxygen saturation.

[0038] This disclosure envisions a variety of different systems, each having one or more of a variety of different features, attributes, or characteristics. As used herein, "system" can refer to various configurations such as: (a) one or more monitoring or measuring devices; (b) one or more monitoring or measuring devices and one or more external computing devices; (c) one or more monitoring or measuring devices communicating via one or more networks; (d) one or more monitoring or measuring devices communicating via one or more networks and one or more external computing devices; and (e) one or more computing devices, such as desktop computers, laptops, tablets, personal digital assistants, mobile phones, and other mobile computing devices. It is understood that monitoring devices can be programmed to determine what to monitor or measure, how to report measurement results, based on which parameters or thresholds to measure, and which triggers to use to issue alarms. In various embodiments, monitoring device 12 can measure heart rate, the mean, median, and standard deviation of heart rate, measurements of heart rate deceleration and acceleration, and heart rate entropy. This programming can be performed prior to installation of the monitoring device or can be performed remotely by a computing device (e.g., 18) accessing the monitoring device (e.g., 12) via network 20. In various embodiments, monitoring device 12 may access external systems or device 22 to obtain settings and / or settings updates for establishing and / or determining thresholds in accordance with this disclosure. External systems / devices 22 may be employed to facilitate centralized management of data, algorithms, and thresholds, as these items can be updated at any time based on practical and statistical determinations.

[0039] In various embodiments, one or more thresholds can be established for monitoring conditions. An alarm is generated when a measured threshold is reached or exceeded. In various embodiments, the alarm takes the form of detected event communication indicating that the threshold has been reached or exceeded. For example, the alarm can provide suggested course of action. In various embodiments, the alarm can provide instructions to autonomous devices to take the indicated action.

[0040] As an example above, the device can be configured to issue an alarm in the form of a detected event communication when the received monitoring data exceeds a pre-set threshold. For example, the device can issue a detected event communication when the threshold is exceeded at a specific time or within a set time period.

[0041] In various embodiments, the currently disclosed devices and systems can connect to a cloud-based application where alarms such as detected event communications are generated and propagated. Various devices according to this disclosure can be displayed on a map or building location (e.g., a NICU) to provide relative location on a building floor plan. It should be understood that monitoring device 12 can be securely configured and monitored via a cloud-based portal (e.g., system 22), which may be hosted by a third party. For example, a connection to the portal can be established via HTTPS. For example, an administrator can edit device settings, define sensor thresholds, and create and edit event rules to trigger other applications and devices. Account settings control groups, individual users, and permissions to define who has access to the portal account. For example, multiple login entries can be added to a single account. The account can contain maps of multiple buildings or locations, thus allowing management of all devices through a single login.

[0042] In embodiments combining cloud-based operations and other embodiments, as described elsewhere herein, it should be understood that the processor does not need to be placed or fixed within the monitoring device. For example, raw data collected by the monitoring device and / or system described herein can be transmitted to a cloud-based portal (e.g., 22), thereby enabling remote processing and subsequent operations.

[0043] Therefore, regardless of where the computational operation is located, the system can operate to receive data from one or more monitors or measuring devices, process that data (e.g., by performing the determinations, calculations, and other analyses described herein), assess whether application thresholds are met, and, if the thresholds are met, trigger appropriate actions, such as alarms, communications, and other actions described herein. According to various embodiments, the system can also learn and improve its operation through learning networks and / or neural networks.

[0044] In various embodiments, if one or more defined thresholds are triggered, a display associated with a computing device (e.g., 12, 14, 18, 22) may display an event indicator.

[0045] In some embodiments, the system includes a computing device combined with a measurement or monitoring device, which is any suitable computing device (e.g., a server) including at least one processor and at least one memory device or data storage device. As further described herein, the computing device includes at least one processor configured to transmit and receive data or signals representing events, messages, commands, or any other suitable information between the computing device and the monitoring device. The processor of the computing device is configured to execute the events, messages, or commands represented by these data or signals in conjunction with the operation of the computing device. Furthermore, the processor of the monitoring device is configured to transmit and receive data or signals representing events, messages, commands, or any other suitable information between the monitoring device and the computing device. The processor of the monitoring device is configured to execute the events, messages, or commands represented by these data or signals in conjunction with the operation of the monitoring device.

[0046] It should be understood that any combination of one or more computer-readable media can be used. A computer-readable medium can be a computer-readable signal medium or a computer-readable storage medium. A computer-readable storage medium can be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, or semiconductor system, apparatus, or device, or any suitable combination thereof, including portable computer floppy disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), suitable optical fiber with repeaters, portable optical disc read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing. In the context of this document, a computer-readable storage medium can be any tangible medium that can contain or store programs used by or associated with an instruction execution system, apparatus, or device.

[0047] Computer-readable signal media may include propagated data signals containing computer-readable program code, such as in baseband or as part of a carrier wave. Such propagated signals may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. Computer-readable signal media may be any computer-readable medium that is not a computer-readable storage medium and may communicate, propagate, or transmit programs for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer-readable signal medium may be transmitted using any suitable medium, including but not limited to wireless, wired, fiber optic cable, RF, etc., or any suitable combination thereof.

[0048] Those skilled in the art will understand that aspects of this disclosure can be described and illustrated herein in any of a variety of patentable classes or contexts, including any new and useful process, machine, article of manufacture, or composition of matter, or any new and useful improvement thereof. Therefore, aspects of this disclosure can be implemented entirely in hardware, entirely in software (including firmware, resident software, microcode, etc.), or in a combination of software and hardware, implementations of which are generally referred to herein as “circuit,” “module,” “component,” or “system.” Furthermore, aspects of this disclosure can take the form of a computer program product embodied in one or more computer-readable media, on which computer-readable program code is embodied.

[0049] It should be understood that all methods and procedures disclosed herein can be implemented using one or more computer programs or components. These components may be provided as a set of computer instructions on any conventional computer-readable medium, including RAM, SATA DOM, or other storage media. These instructions may be configured to be executed by one or more processors, and when executed, to perform or facilitate the performance of all or part of the disclosed methods and procedures.

[0050] Unless otherwise stated, the devices or components communicating with each other in this disclosure do not need to communicate continuously with each other. Furthermore, devices or components communicating with other devices or components may communicate directly or indirectly through one or more intermediate devices, components, or other intermediaries. Additionally, the description of several devices and / or components communicating with each other in the description of embodiments of this disclosure herein does not imply that all of these components are required, or that each disclosed component must communicate with every other component. Furthermore, while algorithms, process steps, and / or method steps may be described sequentially, these methods may be configured to operate in a different order. In other words, the order of any steps described herein does not presuppose that these steps must be performed in that order. Steps related to the methods and / or processes described herein may be performed in any practicable order. Furthermore, although described or implied as not occurring simultaneously, some steps may be performed simultaneously or substantially simultaneously.

[0051] It should be understood that the algorithms, method steps, and process steps described herein can be implemented, for example, by a suitably programmed computer and computing device. In this regard, a processor (e.g., a microprocessor or controller device) receives instructions from a memory or similar storage device containing and / or storing instructions, and the processor executes these instructions to perform the process defined by those instructions. Furthermore, aspects of this disclosure can take the form of a computer program product embodied in one or more computer-readable media, on which computer-readable program code is embodied.

[0052] Computer program code used to perform the operations of various aspects of this disclosure may be written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Java, Scala, Smalltalk, Eiffel, JADE, Emerald, C++, C#, VB.NET, Python, etc.; traditional procedural programming languages ​​such as the "C" programming language, Visual Basic, Fortran 2003, Perl, COBOL 2002, PHP, ABAP; dynamic programming languages ​​such as Python, Ruby, and Groovy; or other programming languages. The program code may execute entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer, partially on a remote computer, or entirely on a remote computer or server.

[0053] When databases are described in this disclosure, it should be understood that alternative database structures and other storage structures besides databases can be readily employed. The graphical representations and descriptions of any exemplary databases presented herein are illustrative and not restrictive arrangements of data storage representation. Furthermore, any exemplary entries for tables and parameter data represent example information only, and although databases are described as tables, other formats, including relational databases, object-based models, and / or distributed databases, can be used to store, process, and otherwise manipulate the data types described herein. Electronic storage can be local or remote, as will be understood by those skilled in the art. Those skilled in the art will understand that the systems of this disclosure can also employ appropriate encryption and other security methods.

[0054] Although this method has been shown and described herein with reference to preferred embodiments and specific examples, it will be apparent to those skilled in the art that other embodiments and examples can perform similar functions and / or achieve similar results. All such equivalent embodiments and examples are within the spirit and scope of this method.

Claims

1. A system comprising: A computing device comprising a processor and a memory storing instructions which, when executed by the processor, cause the processor to: Determine heart rate variability measures in premature infants based on monitored heart rate; determining a target range of oxygen saturation for the premature infant; and An alarm is sounded to communicate the oxygen saturation target range for the premature infant.

2. The system according to claim 1 further comprises a monitoring device suitable for monitoring the heart rate of the premature infant.

3. A system according to claim 1, wherein the oxygen saturation target range for the premature infant is determined based on the heart rate variability measurement.

4. The system of claim 1 further comprising adjusting the oxygen saturation target range based on a factor by which the heart rate variability measurement is multiplied.

5. The system of claim 1, wherein the instructions further cause the processor to determine whether the heart rate variability measurement value reaches or exceeds a pre-set heart rate variability measurement value threshold.

6. The system of claim 5, wherein the instructions further cause the processor to determine the preset heart rate variability measurement value threshold by: determining a probability of one or more outcomes based on the heart rate variability measurements at the low oxygen saturation target range and the high oxygen saturation target range; summing the products of the costs or utilities associated with each of the one or more outcomes, wherein each cost or each utility is weighted by the determined probability; and Select the oxygen saturation target range with lower cost or higher utility.

7. The system of claim 1, wherein the instructions further cause the processor to: determining a probability of one or more outcomes based on the heart rate variability measurements at a continuum of oxygen saturation target ranges; summing the products of the costs or utilities associated with each of the one or more outcomes, wherein each cost or each utility is weighted by the determined probability; and The oxygen saturation target range is selected with the lowest cost or highest utility.

8. The system of claim 1, wherein the instructions further cause the processor to: establish a default level for an oxygen saturation range for oxygenating a premature infant.

9. The system of claim 8, wherein the oxygen saturation target range is determined to be different from the default level.

10. The system of claim 1 further comprising a servo-controlled oxygen supply communicatively coupled to the computing device and operable to adjust oxygen flow to maintain the premature infant within the oxygen saturation target range, wherein the alarm is issued to the servo-controlled oxygen supply.

11. The system of claim 10, wherein the servo-controlled oxygen delivery device is operable to readjust the oxygen saturation target range based on the alarm communicating the oxygen saturation target range.

12. The system of claim 10, wherein issuing the alarm to the servo-controlled oxygen supply device comprises issuing the alarm at fixed time intervals based on the heart rate variability measurement, and the servo-controlled oxygen supply device is then operable to readjust the oxygen saturation target range based on the alarm issued at fixed time intervals.

13. A system according to claim 1, wherein the instructions further cause the processor to determine a lung elasticity measurement of the premature infant based on the heart rate variability measurement.

14. The system of claim 13, further comprising a monitoring device adapted to monitor the heart rate of the premature infant.

15. A system according to claim 13, wherein the oxygen saturation target range for the premature infant is determined based on the lung elastance measurement.

16. The system of claim 13, further comprising adjusting the oxygen saturation target range based on a factor by which the lung elastance measurement is multiplied.

17. A system according to claim 13, wherein the instructions further cause the processor to determine whether the lung elasticity measurement value reaches or exceeds a preset lung elasticity measurement value threshold.

18. The system of claim 17, wherein the instructions further cause the processor to determine the predetermined lung elasticity measurement value threshold by: determining a probability of one or more outcomes based on the lung elastance measurements within a low oxygen saturation target range and a high oxygen saturation target range; summing the products of costs or utilities associated with each of the one or more outcomes, wherein each cost or each utility is weighted by the determined probability; and The oxygen saturation target range is selected with lower cost or higher utility.

19. The system of claim 13, wherein the instructions further cause the processor to: determining a probability of one or more outcomes based on the lung elastance measurements at a continuum of oxygen saturation target ranges; summing the products of the costs or utilities associated with each of the one or more outcomes, wherein each cost or each utility is weighted by the determined probability; and The oxygen saturation target range is selected with the lowest cost or highest utility.

20. The system of claim 13, wherein the instructions further cause the processor to: Default levels are established to establish the oxygen saturation range for oxygen delivery to premature infants.

21. The system of claim 20, wherein the oxygen saturation target range is determined to be different from the default level.

22. The system of claim 13, further comprising a servo-controlled oxygen supply communicatively coupled to the computing device and operable to adjust oxygen flow to maintain the premature infant within the oxygen saturation target range, wherein the alarm is issued to the servo-controlled oxygen supply.

23. The system of claim 22, wherein the servo-controlled oxygen delivery device is operable to readjust the oxygen saturation target range based on the alarm communicating the oxygen saturation target range.

24. The system of claim 22, wherein issuing the alarm to the servo-controlled oxygen supply device comprises issuing the alarm at fixed time intervals based on the lung elastance measurement, whereupon the servo-controlled oxygen supply device is operable to readjust the oxygen saturation target range based on the alarm issued at fixed time intervals.

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