BONE FIXATION METHOD

Abstract

A method of monitoring a bone fracture in an individual. The method comprises the steps of: measuring a first parameter indicative of the load on said bone fracture; measuring a second parameter indicative of the activity level of said individual; obtaining a plurality of values for said first and second parameters; correlating said values to determine a measure of bone fracture condition; monitoring a change in said correlation over time; and determining a measure of the change in bone fracture condition over time. A bone fixation system implements this method of monitoring a bone fracture in an individual. The method and system provide a more accurate and reliable measure of bone fracture condition and of the progression of healing of the bone fracture.

Claims

1. A method of monitoring a bone fracture in an individual, the method comprising the steps of: measuring a first parameter indicative of a load on said bone fracture; measuring a second parameter indicative of an activity level of said individual; obtaining a plurality of values for said first and second parameters; correlating said values to determine a measure of a bone fracture condition; monitoring a change in said correlation over time; and determining a measure of the change in bone fracture condition over time.

2. The method as recited in claim 1 wherein said first parameter is any one of: interfragmentary movement; deformation; acceleration; pressure; strain; and any combination(s) thereof.

3. The method as recited in claim 1 wherein said second parameter is any one of: hip movement; acceleration; orientation; and any combination(s) thereof.

4. The method as recited in claim 1 wherein the method further comprises the steps of: measuring a third parameter associated with said bone fracture; obtaining a plurality of values for said third parameter; correlating said values for said third parameter with said values for said first and second parameters to determine a measure of bone fracture condition; monitoring a change in said correlation over time; and determining a measure of the change in the bone fracture condition over time.

5. The method as recited in claim 4 wherein said third parameter is any one of: temperature; lactic acid level; hip movement; acceleration; orientation; strain; pressure; oxygen level; tension; and any combination(s) thereof.

6. The method as recited in claim 1 wherein on measuring at least one of said parameters to obtain a value, the method further comprises the step of: comparing said at least one measured parameter value to at least one threshold value; and activating an indicating means when said at least one threshold value is exceeded.

7. The method as recited in claim 1 wherein determining a measure of the change in bone fracture condition over time further comprises the step of: comparing said correlated data with pre-determined data typical of healing bone fractures.

8. The method as recited in claim 7 wherein said pre-determined data comprises at least one of average, upper and lower boundaries for values of said correlated data typical of healing bone fractures.

9. The method as recited in claim 1 wherein the method further comprises the step of: providing an output based on at least one of said determinations.

10. The method as recited in claim 9 wherein providing an output involves providing feedback on at least one of: whether the bone fracture is healing; the progression of healing of the bone fracture; predicting the endpoint of the healing process; whether a problem has developed with the bone fracture; whether the patient is not active enough or is too active.

11. The method as recited in claim 10 wherein predicting the endpoint of the healing process comprises the steps of: extrapolating said correlated data to a point representing a healed bone fracture based on said pre-determined data; and calculating a time period over which the fracture can be expected to reach said point.

12. The method as recited in claim 1 wherein the method further comprises the steps of: detecting whether there is a problem associated with a bone fixator applied to the bone fracture based on at least one of said determinations; and, if a problem is detected, identifying said problem and sending feedback commands to an actuation means for manipulating said bone fixator based on the identified problem.

13. The method as recited in claim 12 wherein the steps of identifying said problem, sending feedback commands and manipulating said bone fixator, are automatically controlled.

14. The method as recited in claim 1 wherein each of the steps are implemented with a bone fixation system comprising a bone fixator, a first sensor, a second sensor and a processing means.

Description

BRIEF DESCRIPTION OF THE DRAWINGS

[0061] Embodiments of the present invention will now be described, by way of example only, with reference to the accompanying drawings, of which:

[0062] FIG. 1 shows an embodiment of a bone fixation system operable to implement the method of the present invention;

[0063] FIG. 2 shows an embodiment of a bone fixation system for intramedullary nails;

[0064] FIG. 3 shows an embodiment of a bone fixation system for intramedullary plates;

[0065] FIG. 4 shows an embodiment of a bone fixation system for a plaster-of-paris cast;

[0066] FIG. 5 shows an embodiment of a bone fixation system for ring fixation systems (frames) used for manipulation of the frame configuration;

[0067] FIG. 6 shows the embodiment of FIG. 1 in communication with a local server;

[0068] FIG. 7 shows an example registration of a data-logging system;

[0069] FIGS. 8(a)-8(c) show a typical profile for analysis, and various plots;

[0070] FIG. 9 shows pull mode of data inspection for patient and healthcare provider;

[0071] FIG. 10 shows how the system may be used to provide early indication of a potential complication;

[0072] FIG. 11 shows how the system may be used to provide automatic medicinal intervention;

[0073] FIG. 12 shows an example of a standard profile for a graph of fracture movement versus time;

[0074] FIG. 13 shows an example of three potential complications that could be detected using the graph in FIG. 12;

[0075] FIG. 14 shows another data set indicating potential complications using normal, and upper and lower quartile data curves;

[0076] FIG. 15 shows the detection of a catastrophic event;

[0077] FIG. 16 shows the use of the upper lower quartile data curves detecting further potential complications;

[0078] FIG. 17 shows another data set where a patient has been motivated by the data; and

[0079] FIGS. 18(a)-18(b) show the use of data-fit equations to predict a healing end point.

DETAILED DESCRIPTION

[0080] FIG. 1 is a typical embodiment of the bone fixation system. The bone fixation system is operable to implement the method of the present invention. A bone fixator (1) (for the sake of clarity this is illustrated as an external fixator but could be any fixation system such as an intramedullary nail, a plate or any other applicable fixation method) is used to fix a fracture. Attached to the fixation is a data-logging system (2). This has the ability to log data in a variety of forms, store this data and transmit this data. The data logging system could be integral to the fixation, or it could be a stand alone item. In addition to item (2) a variety of one or more sensors will be required to measure parameters of the patient, which are of importance (3). These parameters may be, but are not limited to, interfragmentary movement, pedometer data, fracture site temperature, lactic acid levels, measured strain, compartmental pressure, elevation and/or orientation and/or attitude of the fracture and/or of the patient, e.g. a limb of the patient. The sensors themselves could be wired directly to the data-logging unit (2) or could be connected wirelessly. The data-logging unit (2) would be required to collect the data from the sensors (3), and this could be in any form for example time-domain, frequency domain or tabular, and then store this locally until it is required. One method of data analysis would be to upload the data to a main server (4), or host computer (not shown). The uploading could be conducted using wired technology, wireless technology (such as Zigbee or Bluetooth), or using internet (or cloud) technology (for example 3G, 4G or WiFi). It is anticipated, however, that the greatest strength of the invention will be the use of internet based communication to a main server (4). The uploading could be synchronous or asynchronous.

[0081] In another embodiment, a processing means (not shown) connected to the bone fixator (1) and data-logging unit (2) could perform data-analysis. The raw logged data and/or processed data could then be sent to the main server (4), or host computer (not shown), for storage and/or to provide a back-up analysis of the logged data.

[0082] Another embodiment is a complete, stand alone data-logging system with all diagnostics pre-programmed on-board.

[0083] The main server (4) has a number of main tasks. The first task will be to collect the data from patients on a regular basis. This could be in either push or pull modes. For example, the data-logging system could detect an open Wi-Fi zone and then use this internet service to upload data to the server (push); alternatively the server could dial the data-logging unit and then enforce uploading of data (pull). The server's 2.sup.nd task will be to analyse and store the data that has been uploaded. This data could be numerical, or it could be graphical (some examples are given later); equally it could be a diagnostic result. However all data may need to be stored anonymously. To this end the third task of the server will be registration of the data-logging system such that only the patient and their healthcare practitioner have access to the data (described later). The fourth task of the server will be to communicate the data to the patient (5), the healthcare provider (6) and the healthcare community (7); the preferred methodology is described more fully later. It is suggested that this communication is once again push and pull. In the context of data interrogation 5,6 and 7 would interrogate their data at will in a pull mode; however if the system detected the onset of a complication then the system would contact the healthcare provider in push mode.

[0084] FIGS. 2, 3 and 4 illustrate further embodiments for the system illustrated in FIG. 1. FIG. 2 is an intramedullary nail (8); FIG. 3 is a plate (9); and FIG. 4 a plaster-of-paris (or other appropriate material) cast (10).

[0085] FIG. 5 illustrates how the system could be used to provide feedback to a bone fixation system, in this case a ring-fixation system (11), in order to provide manipulation commands. Ring fixators are commonly used to provide an aid to reconstruction. If the relative positions of a number of rings are data-logged via one or more suitable sensors (12) and the structure of the ring-system (or frame) is known then the server (4) is able to provide commands for the manipulation of the frame in order to provide the planned alignment of the rings. This could be instructions to the patient who can manipulate the components manually; equally it could be commands to active components that would manipulate the components automatically. The active components could automatically manipulate the components at pre-determined time intervals dependent on how long the bone fixator has been applied for and/or in response to data collected by the bone fixation system. Manipulations to aid healing include stiffening and adjusting the alignment for example. Further to this, the bone fixation system could be used in reconstruction devices to control fixation parameters, to lengthen, align or perform bone transport for example.

[0086] FIG. 6 illustrates an embodiment of a system using local servers (13). In this embodiment the data-logging system would communicate with a local server (for example the healthcare provider's or the patient's desktop computer), this local server would store and analyse the data but would receive regular updates from the main server (14). Operating much like a standard virus-detection system, local detection and analysis is conducted on the standalone system using a database of information (12). The database of information is updated, regularly, from a main server (14). In turn that main server is updated from the information stored on the stand-alone system and thus analyses the data on a global scale.

[0087] FIG. 7 illustrates the registration of a new data logging system. To ensure patient confidentiality it is envisaged that each data logging unit should have a unique serial number (15); and it is this serial number that is used for all communication and storage of data (16). The only people to know this serial number would be the patient and the healthcare provider. However, as data security increases it could be envisaged that the patient ID could well include pertinent personal details. Registration of the data-logger should incorporate pertinent patient data (17), for example: age, sex, body weight, fracture classification, smoker/non-smoker, alcohol consumption. This data is important for the data analysis that is to follow.

[0088] FIGS. 8(a)-8(c) illustrate how a typical profile may be established. In this instance movement of the fracture is analysed. Whilst the data could come in time domain form (FIG. 8(a)) in this case the data has been analysed to count the number of events per day (frequency domain) by counting how many times a trigger level (17) was exceeded. This data in itself may be useful, but a further plot of events/day versus time (FIG. 8(b)) could be drawn. Once again this data may be useful in itself, but having the ability to compare it against norms is of greater value. Upper and lower quartile graphs (18) would be derived from the analysis of global data discussed previously and could be presented as data-sets based on age, sex smoker etc. The benefits of the global approach of data analysis is that these normal curves could be updatable on a regular basis; this is far more powerful than having a single algorithm fixed in time. Hence FIG. 8(c) illustrates how the data could be presented. An individual patient's curve (19) could then be compared with these norms. Any variance from the norm could be an indicator of a non-compliance, a complication, or a failure (described more fully later). It is easy to envisage that this is not restricted to fracture movement, nor is it restricted to frequency domain data. This power of the data lies in the ability to compare any of the variety of measured parameters for individuals, or groups of individuals, against constantly updated norms.

[0089] FIG. 9 illustrates how the patient and the healthcare provider would see this data. In this situation the data would be in pull mode. The patient (20), for example, would log onto the system using their unique serial number described earlier. They could then examine their own profile versus norms. They would not be able to see any other individual profile, and no one but their healthcare provider could see theirs. The healthcare (21) provider would also log onto the system but could examine any of the patients' data in their care, either individually or as a group. In this way they could see the progress of an individual patient but also how their own patients, as a whole, compare with the norms.

[0090] FIG. 9 also illustrates how the data presented in FIGS. 8(a)-8(c) could be used as a motivational tool for the patient. For example, the data presented (22) could be number of pedometer events per day versus number of fracture movement events per day. A sedentary patient would not have many pedometer events hence the levels will remain low whereas the upper and lower quartile norms should increase with time to a constant plateau. A patient seeing this data could be motivated to be less sedentary. Equally the same data could be viewed by the clinician as a potential issue related to pain and may wish to discuss this with the patient; but not on an ad hoc basis. There is potential to include an alarm in the data-logger to alert the patient to inactivity that only stops once acceptable activity levels have been achieved. The data-logger may be programmable with pre-determined thresholds such that the alarm is activated when such a threshold is exceeded or not reached. The alarm may be an audio alarm, a visual alarm or both.

[0091] Analysis of the data and comparison with norms will enable the system to predict when a fracture is healed; it will also detect the point when the fracture is healed. The system could then warn the healthcare provider to contact the patient, equally it could inform the patient to contact the healthcare provider. With greater confidence in the system it is possible for the system to inform the patient and who would then use the equivalent of a district nurse to remove their fixation.

[0092] One of the hidden benefits is the early detection of complications. FIG. 10, for example, early detection of compartment syndrome could be accommodated using lactic acid and compartment pressure sensors. Detection could lead to a direct alarm to the healthcare provider. Other examples are the early detection of hypertrophic non-union, atrophic non-union, infection, and fixation failure. In this case the server would communicate an alarm (23) to the healthcare provider. Although this could be an immediate alarm time-zones makes this impractical and unnecessary. It is more practical for the healthcare provider to receive an email, text-message (or other electronic data form) from the server (24) at the start of the working dayin their time zone. If the alarm is urgent this could be in the form of a text message to the clinician directly.

[0093] FIG. 11 illustrates a system that incorporates a medical intervention. In this example an ambulatory infusion pump (25) is activated when an infection is detected and suitable medication is administered. A similar system could also inject stimulants in the case of a non-union. It could also start stimulation using electrical, electromagnetic, mechanical, thermal or any other appropriate system.

[0094] In an embodiment of the present invention, the bone fixator is a hollow, or cannulated, fixator pin. In this embodiment, a pin may contain one or more transducers, in the form of sensors or otherwise, and these could detect physical, physiological or biological parameters within the bone or limb. Sensors that measure temperature, pressure, oxygen level or tension may be used for example. The cannulated pin may contain means for dispensing or injecting medication, and/or antibiotics, locally to the fracture site. Injection/dispense of the medication and/or antibiotics may be automated. Commands may be sent to active components in the means for dispensing/injecting, providing automated release of the medication/antibiotics.

[0095] FIG. 12 illustrates an example of a standard graph to be used to assess fracture healing. In this case it is a graph of fracture movement events versus time. The number of events per day have been plotted as individual points (26). The standard curve (27) illustrates 4 phases. In phase 1 (28) the fracture is painful hence fracture movement is minimal. As pain subsides and confidence grows the number of events increase until a plateau of normal activity is achieved (29). As the fracture begins to heal events decrease (30) whilst ambulation is maintained. Eventually all fracture movement ceases and the fracture may be considered healed (30); in the case of the tibia this should be no later than 24 weeks or a delayed union may be indicated.

[0096] FIG. 13 is the graph as illustrated by FIG. 12 but in this case three different scenarios are presented. If the data reaches the plateau but does the movement does not subside (31) then the fracture could be progressing to a non-union, early intervention is essential. Another scenario is that at the start of the pain phase the slope of the graph is abnormally low (32), this could be indicating a delayed union. An extension of 32 is a slope close to zero (33); in this case it could be a sedentary patient or a fixation that is too stiff. In both cases early intervention is highly beneficial.

[0097] FIG. 14 is an extension of FIG. 12; in this case the standard graph is illustrated using normal, and upper and lower quartiles (34) as presented in FIGS. 8(a)-8(c), and 9. This individual patient's (35) data is falling below the lower quartile and may be indicating a delayed union (36).

[0098] FIG. 15 illustrates another scenario. In this case the patient activity suddenly stops (37). This is a catastrophic failure alarm and could be due to onset of severe pain, it could be the patient has had an accident or is severely ill, or the fixation has catastrophically failed or seized. Early intervention is required. FIG. 16 is the opposite and is indicating too much movement (38); this could be indicating that the fixation is too flexible (which in turn could lead to a mal-union) or it could be that the fracture is progressing to a non-union.

[0099] FIG. 17 illustrates how the data can provide motivation. In this case the patient has noticed that their activity levels are low (39) and decide to become more mobile. As a consequence their activity returns to within the normal boundaries and their healing pattern is normal.

[0100] FIGS. 18(a)-18(b) illustrate how data-fitting can be used to predict healing end-point. As normal data gets collected a known equation can be fitted to predict the overall profile. In FIG. 18(a) the data has only just started (40) and hence a first data-fit (41) obtains a rough estimate of healing end-point, T (42). As more data is collected (43), as in FIG. 18(b), the fitted data produces a curve (44) which will settle to a more consistent estimate for healing end-point, T (45). This information not only informs the healthcare team of the potential appointment for fixation removal but can also motivate patients.

[0101] The bone fixation system may comprise a plurality of sensors, which may measure a plurality of parameters. This may be useful in detecting the rate of healing and/or the onset of any particular problems which may be associated with the bone fixation system.

[0102] Sensors may include a strain gauge, which may enable the measurement of strain on the bone fixation to be used to assess fracture site excursions. In one embodiment, the fixator body comprises a composite material re-inforced with glass fibres and these fibres may be used as optical strain gauges. Sensors that measure a combination of linear and torsional strains may be used, which may enable measurement of motion in all degrees of freedom at the fracture site. This may be helpful in providing an accurate measure of patient activity level and/or movement at the fracture site.

[0103] Combinations of other measurements may be used to asses the rate of healing and/or any problems associated with the bone fixation system. A pedometer, associated with the bone fixation system, may be used to measure the activity of the patient. Activity of the wearer may be helpful in providing a more accurate and reliable measure of bone fracture condition and/or a measure of the progression of healing of the bone fracture. Any temperature monitoring means, associated with the bone fixation system, may be used to measure temperature at the fracture site. Parameters may have thresholds associated with them that enable a reading to be classed as high or low, which may depend on the length of time for which the bone fixation system has been applied and/or on how long it has been since the fracture occurred. A processing means may compare the measured data to these thresholds.

[0104] Measurement of patient activity, when combined with measurement of the fracture activity, may be beneficial as it may be used to asses the progression of the healing, onset of non-union and/or any subsequent failure of the fixation system. For example, if the patient activity is measured to be high, the fracture activity is measured to be low, and the number of weeks for which the bone fixation system has been applied is less than 7, this may suggest over-stiff fixation has been applied. Alternatively, if the patient activity is measured to be low, the fracture activity is measured to be high, and the number of weeks for which the bone fixation system has been applied is less than 7, this may suggest an unstable fixation or that the fixation is too flexible. Alternatively, if the patient activity is high, the fracture activity is high and the fracture activity is not decaying, this may indicate an atrophic non-union.

[0105] In another example, if the patient activity is low, the fracture activity is high and the fracture site temperature is high, this may suggest hypertrophic non-union.

[0106] Acceleration of the bone fixation system may also be measured, by way of a one-axis accelerometer connected to the bone fixation system, or otherwise. This may be used to assess whether the bone fixation system, and/or bone or part connected thereto is in a raised position. Measurement of acceleration may be used to asses fracture stiffness; this may be performed by multiplying the acceleration by a bodyweight factor, measuring the bend in the bone fixator and combining these results.

[0107] In an embodiment of the present invention, the fixator pin is electrically insulated. This may enable measurement of the potential difference across the fracture site, which may provide indications of the progression of healing.

[0108] In any embodiment of the invention, an indicating means, such as an alarm, may additionally be associated with the bone fixation system and may be used to indicate a problem to the user if the measured data is not as expected, if it exceeds or does not reach a threshold for example.

[0109] The above embodiments are described by way of example only. Many variations are possible without departing from the scope of the invention as defined in the appended claims.