WO2009063339A2 - Method for following pediatric development - Google Patents

Method for following pediatric development Download PDF

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WO2009063339A2
WO2009063339A2 PCT/IB2008/053562 IB2008053562W WO2009063339A2 WO 2009063339 A2 WO2009063339 A2 WO 2009063339A2 IB 2008053562 W IB2008053562 W IB 2008053562W WO 2009063339 A2 WO2009063339 A2 WO 2009063339A2
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height
weight
values
head circumference
value
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PCT/IB2008/053562
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French (fr)
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WO2009063339A3 (en
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Michael Inbar
Ziv Belsky
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Indicare
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Priority to IL205139A priority Critical patent/IL205139A0/en

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    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H10/00—ICT specially adapted for the handling or processing of patient-related medical or healthcare data
    • G16H10/60—ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
    • G16H50/20—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
    • G16H50/50—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for simulation or modelling of medical disorders

Definitions

  • This invention relates to pediatric development monitoring and in particular to methods of determining normal vs. abnormal development in infants.
  • Child development also referred to herein as “pediatric development” or
  • “pediatric growth”) in particular in the first 2 years after birth, is a key concern for parents, caregivers and the medical community.
  • pediatric growth is evaluated through growth charts. These are used to track measurements of a patient's height (length), weight and head circumference, to see how the patient measures in relation to other children his/her age or to other children with similar diagnoses.
  • a growth chart includes percentile curves of children's measurements and a patient's measurements are plotted in relation to the percentile curves.
  • Types of growth charts include the Center for Disease Control (CDC) growth charts, specialty growth charts such as Down's Syndrome, Turner Syndrome, Babson and Nallhaus growth charts and other growth charts specific to countries or regions.
  • the determination whether pediatric growth is "normal” depends therefore on the separate measurement of at least three parameters and the separate comparison of each parameter with a respective growth chart. Normally, the measurement of each parameter is performed separately, with a dedicated device (e.g. measurement tape for height/length and/or for head circumference) and weight balance for weight). The comparison to a growth chart is normally done manually, by a nurse or pediatrician. Sometimes, the three parameters are not in agreement as to a particular development status (i.e. each parameter may lie in a different percentile of its respective chart), making it difficult to determine if there is a problem that needs to be addressed. It would therefore be beneficial to have a simple method that allows quick and accurate determination of pediatric growth status based on a single parameter value.
  • the invention discloses a system and method for providing a single, combined growth parameter which indicates whether the pediatric growth of a patient is "normal” or "abnormal".
  • the combined growth parameter is obtained by applying an algorithm on measured values of three parameters: the patient's height (or length), the patient's weight and the patient's head circumference.
  • a method for indicating the pediatric growth status of a patient for which a data set of measured weight, height and head circumference values is obtained at each measurement time t, the method comprising the steps of: at each time t, obtaining a set of direct percentile values of weight, height and head circumference using the respective measured weight, height and head circumference values arid computing a single combined indication value from the direct percentile values of weight, height and head circumference, the single combined indication value indicative of a pediatric growth status.
  • Steps in the computation of the single combined indication value include, for each of the weight, height and head circumference: computing a set of slow average weighted percentile values; computing a set of fast average weighted percentile values; computing a set of difference values from differences between the fast average and the slow average weighted percentile values; computing a set of weight, height and head circumference augmented values from the difference values; and computing the single combined indication value from the set of weight, height and head circumference augmented values.
  • FIG. 1 shows a flow chart of an embodiment of the method of the invention.
  • a patient e.g. infant
  • age from date of birth
  • gender a data set of measured height (h), weight (w) and head circumference (c) values (all three being physiological parameters).
  • the physiological parameter set values may be in MKS units (e.g. "cm” for height and circumference and “kg” for weight, or in any other unit system used in growth charts (for example inches for height and circumference and pounds for weight).
  • MKS units e.g. "cm” for height and circumference and "kg” for weight, or in any other unit system used in growth charts (for example inches for height and circumference and pounds for weight).
  • M(t) also referred to as a "mark”
  • mark M(t) is computed using an algorithm that includes a series of formulas and parameters defined below. The computation is now described in detail, with reference to FIG. 1.
  • a step 102 two sets of averaged parameters (defined below) are computed for each physiological parameter: a "slow average” weighted percentile parameter (referred to simply as “slow average” of the parameter), which reacts slowly to differences in new data compared to the average, and a “fast average” weighted percentile parameter (referred to simply as “fast average” of the parameter), which reacts more quickly to such changes.
  • the "slow average” parameters (for each physiological parameter, i.e. for height, weight and head circumference) are respectively "H P AV s (t)” [%], “W P AV s (t)” [%], “C P AV s (t)” [%].
  • the “fast average” parameters are respectively ⁇ P AV F (t)” [%], “W P AV F (t)” [%], “CpAV F (t)” [%].
  • These parameters represent respective percentiles or "weighted averages of percentile values”.
  • “t” refers to an integer measurement time t (e.g. O 1 1, 2 ... etc.) and "t-1 "refers to the integer measurement time (t minus 1 ).
  • the formulas are recursive and given next: Slow average weighted percentile of height:
  • HpAVs(I) [%] HpAVs(M )+H P (t)*AV s )/(l+AV s )
  • CpAV s (t) [%] (CpAV s (t-l)+Cp(t)*AV s )/(l+AV s ) Fast average weighted percentile of height:
  • WpAV F (t) [%] (W P AV F (t-l)+Wp(t)*AV F )/(l+AV F )
  • the recursive formulas of the "slow average” and “fast average' 1 parameters use preset constants, designated here as AVWs, AVW F for weight, AVHs, AVH F for height and AVCs, AVC F for head circumference. These constants conform to (where X represent W, H or C) the requirement.
  • AVs and AVp' 1 are constants in the algorithm which do not change per measurement or per child. They may be fixed for every race group or nationality, or may have different values for different race groups or nationalities.
  • HpAV s (-l) [%] sum [Hp(O), H P (1) ? H P (2),..., H P (N)]/(N+1)
  • WpAV s ( ⁇ l) [%] sum [W P CO), W P CI), W P (2) V .., W P (N)]/(N+1)
  • a way to test the adequacy of the chosen values of "AVg” and “AV F " is to generate a test group of full sets of historical data of both "normal” and “not normal” children (as determined by an expert physician examination of the historical growth data) and compare their classification as “normal” and “not normal” to that of the algorithm (as explained below).
  • the size of the test group and the amount of fit required to use specific constant values depend on the user-defined tolerable error margin (how many "wrongs" the potential algorithm user is willing to accept in his target population based on the amount of misclassifi cations observed in the test group, which is easily computed by statisticians).
  • a value of the difference "DIFF" [%] between the “fast” and “slow” average of each measurement (“D ⁇ FF H P AV" [%] for height, "DIFF WpAV” [%] for weight and "DIFF CpAV” [%] for head circumference) is computed as follows:
  • the value for each parameter is augmented to reflect the "importance" of this difference: the closer to 50% the "fast” average is, the less significance there is to the difference between it and the "slow” average.
  • the augmentation process includes first the determination of a measure of the "distance” (DIS) value of the "fast average” from the extreme percentiles (0% and 100%). Exemplarily, if the fast average weighted percentile value is smaller than or equal to 50%, DIS is set equal to the respective fast average weighted percentile value, and if the fast average weighted percentile value is larger than 50%, DIS is set equal to the result of a subtraction of the respective fast average weighted percentile value from 100%:
  • step 108 combined indication value M(t) is now computed based on all three augmented values MHp(t), MWp(t) and MCp(t).
  • An exemplary calculation of M(t) is based on setting M(t) to equal the highest absolute value of the three (MH ⁇ (t), MWp(t) or MCp(t)) (the furthest from 0, be it plus or minus).
  • Tables 1 and 2 provide exemplary values of each parameter (measured or computed) above, for, respectively two infants (infant A and infant B).
  • step HO 5 the M(t) value is compared to two extreme values of -1 and +1. If the M(t) value exceeds any of the two extreme values, this may be considered an indication of abnormal growth.
  • the Mp(t) values at each measurement time were chosen to be equal to the maximum value in each three parameter MWp(t), MHp(t), MCp(t) set.
  • the Mp(t) values may be plotted as a function of time (calibrated for "months since birth"), where values of 1 and -1 mark “normal” values. Any value above 1 or below -1 constitutes a transgression from “normal” to “caution” meaning the algorithm indicates a possible developmental problem. One can see that infant A is "normal, as the M(t) value never extends beyond the two bounds.
  • Mp(I) values at each measurement time were chosen to be equal to the maximum value in each three parameter MWp(I), MHp(t), MCp(t) set.
  • M P (t) MW P (t) - -4.43.
  • the Mp(t) values may be plotted as a tunction of time (calibrated for "months since birth"), where values of 1 and -1 mark "normal” values.
  • infant B shows "abnormal" growth starting on day 279, when the value of Mp(t) falls below the -1 value.
  • the physiological parameters of height, weight and head circumference may be measured using standard equipment known in the art, or a dedicated system that measures all three parameters.
  • the algorithm described above may be implemented as a computer program storing program code for performing the method.

Abstract

Method for indicating the pediatric growth status of a patient based on a single combined indication value. The single combined indication value is obtained by performing weight, height and head circumference measurements, using these measurements to compute a set of slow average weighted percentile values and a set of fast average weighted percentile values, computing a set of difference values from differences between the fast average and the slow average weighted percentile values, computing a set of weight, height and head circumference augmented values from the difference values and computing the single combined indication value from the set of weight, height and head circumference augmented values.

Description

METHOD FOR FOLLOWING PEDIATRIC DEVELOPMENT
FIELD OF THE INVENTION
This invention relates to pediatric development monitoring and in particular to methods of determining normal vs. abnormal development in infants.
BACKGROUND OF THE INVENTION
Child development (also referred to herein as "pediatric development" or
"pediatric growth"), in particular in the first 2 years after birth, is a key concern for parents, caregivers and the medical community. In existing art, pediatric growth is evaluated through growth charts. These are used to track measurements of a patient's height (length), weight and head circumference, to see how the patient measures in relation to other children his/her age or to other children with similar diagnoses. A growth chart includes percentile curves of children's measurements and a patient's measurements are plotted in relation to the percentile curves. Types of growth charts include the Center for Disease Control (CDC) growth charts, specialty growth charts such as Down's Syndrome, Turner Syndrome, Babson and Nallhaus growth charts and other growth charts specific to countries or regions.
The determination whether pediatric growth is "normal" depends therefore on the separate measurement of at least three parameters and the separate comparison of each parameter with a respective growth chart. Normally, the measurement of each parameter is performed separately, with a dedicated device (e.g. measurement tape for height/length and/or for head circumference) and weight balance for weight). The comparison to a growth chart is normally done manually, by a nurse or pediatrician. Sometimes, the three parameters are not in agreement as to a particular development status (i.e. each parameter may lie in a different percentile of its respective chart), making it difficult to determine if there is a problem that needs to be addressed. It would therefore be beneficial to have a simple method that allows quick and accurate determination of pediatric growth status based on a single parameter value. SUMMARY OF THE INVENTION
The invention discloses a system and method for providing a single, combined growth parameter which indicates whether the pediatric growth of a patient is "normal" or "abnormal". The combined growth parameter is obtained by applying an algorithm on measured values of three parameters: the patient's height (or length), the patient's weight and the patient's head circumference. The algorithm uses these measured values to provide a single growth parameter value, which can then be used in comparison with "normal" values to determine the development status of the patient In an embodiment, there is provided a method for indicating the pediatric growth status of a patient for which a data set of measured weight, height and head circumference values is obtained at each measurement time t, the method comprising the steps of: at each time t, obtaining a set of direct percentile values of weight, height and head circumference using the respective measured weight, height and head circumference values arid computing a single combined indication value from the direct percentile values of weight, height and head circumference, the single combined indication value indicative of a pediatric growth status. Steps in the computation of the single combined indication value include, for each of the weight, height and head circumference: computing a set of slow average weighted percentile values; computing a set of fast average weighted percentile values; computing a set of difference values from differences between the fast average and the slow average weighted percentile values; computing a set of weight, height and head circumference augmented values from the difference values; and computing the single combined indication value from the set of weight, height and head circumference augmented values.
BRIEF DESCRIPTION OF THE DRAWINGS
The invention is herein described, by way of example only, with reference to the accompanying drawing, wherein: FIG. 1 shows a flow chart of an embodiment of the method of the invention. DETAILED DESCRIPTION OF THE INVENTION
In one embodiment (see details in Tables 1 and 2), a patient (e.g. infant) is checked at measurement times t and the following data is obtained in each such measurement: age (from date of birth), gender and a data set of measured height (h), weight (w) and head circumference (c) values (all three being physiological parameters). The physiological parameter set values may be in MKS units (e.g. "cm" for height and circumference and "kg" for weight, or in any other unit system used in growth charts (for example inches for height and circumference and pounds for weight). The data set is processed to provide a single combined growth parameter M(t) (also referred to as a "mark") at time t. An exemplary computation is given below.
Figure imgf000005_0001
Table 1 - Patient A
Figure imgf000005_0002
Table 2 - Patient B Exemplary Computation
• For every physiological parameter data set (h - height, w - weight, c - circumference) obtained at a specific date (time (t)), a percentile datum (percentile representation of the measured value) is computed based on age and gender from an appropriate curve (growth chart) set: o Hp(t) [%]= the direct percentile of height, taken directly from height vs. age curves (e.g. from CDC growth charts) as appropriate for the age and gender of the child. o Wp(t) [%] = the direct percentile of weight, taken directly from weight vs. age curves (e.g. from CDC growth charts) as appropriate for the age and gender of the child. o Cp(t) [%]= the direct percentile of head circumference, taken directly from head circumference vs. age curves (e.g. from CDC growth charts) as appropriate for the age and gender of the child.
For each new data set taken at time t (for example, in Table 1, at 1.2, 1.5, 1.9, etc. months from birth), mark M(t) is computed using an algorithm that includes a series of formulas and parameters defined below. The computation is now described in detail, with reference to FIG. 1. In a step 102, two sets of averaged parameters (defined below) are computed for each physiological parameter: a "slow average" weighted percentile parameter (referred to simply as "slow average" of the parameter), which reacts slowly to differences in new data compared to the average, and a "fast average" weighted percentile parameter (referred to simply as "fast average" of the parameter), which reacts more quickly to such changes. In an embodiment of the method, the "slow average" parameters (for each physiological parameter, i.e. for height, weight and head circumference) are respectively "HPAVs(t)" [%], "WPAVs(t)" [%], "CPAVs(t)" [%]. The "fast average" parameters are respectively ΗPAVF(t)" [%], "WPAVF(t)" [%], "CpAVF(t)" [%]. These parameters represent respective percentiles or "weighted averages of percentile values". In the formulas below, "t" refers to an integer measurement time t (e.g. O1 1, 2 ... etc.) and "t-1 "refers to the integer measurement time (t minus 1 ). The formulas are recursive and given next: Slow average weighted percentile of height:
HpAVs(I) [%] = HpAVs(M )+HP(t)*AVs)/(l+AVs) Slow average weighted percentile of weight: WpAVs(t) [%] - (WpAVs(l-l)+Wp(t)*AVs)/(l+AVs)
Slow average weighted percentile of head circumference:
CpAVs(t) [%] = (CpAVs(t-l)+Cp(t)*AVs)/(l+AVs) Fast average weighted percentile of height:
HpAVp(t) [%] - (HPAVF(t-l)+Hp(t)*AVF)/(l+AVF) Fast average weighted percentile of weight
WpAVF(t) [%] = (WPAVF(t-l)+Wp(t)*AVF)/(l+AVF) Fast average weighted percentile of head circumference:
CpAVF(t) [%] = (CPAVF(t-l)+Cp(t)*AVF)/(l+AVp)
The recursive formulas of the "slow average" and "fast average'1 parameters use preset constants, designated here as AVWs, AVWF for weight, AVHs, AVHF for height and AVCs, AVCF for head circumference. These constants conform to (where X represent W, H or C) the requirement.
O<AVXF<1
Figure imgf000007_0001
In a particular case, used exemplarily henceforth, we can take AVWs-A VHs~A VCs ~ AVs and
Figure imgf000007_0002
Thus, the requirement above translates to:
O<AVF<1
Figure imgf000007_0003
"AVs" and "AVp'1 are constants in the algorithm which do not change per measurement or per child. They may be fixed for every race group or nationality, or may have different values for different race groups or nationalities.
The recursive formulas above also require a starting value from which to calculate the values at other times (larger values of t). If the first measurement is taken at time t=0, values for these parameters at a time I=- 1 need to be known in order to allow calculation at time t=0. In order to generate the value at time t=-l, and only at that time, a different set of formulas is used:
HpAVs(-l) [%] = sum [Hp(O), HP(1)? HP(2),..., HP(N)]/(N+1) WpAVs(~l) [%] = sum [WPCO), WPCI), WP(2)V .., WP(N)]/(N+1)
CpAVsC-I) [%] = sum [Cp(O), CP(1), CP(2),..., CP(N)]/(N+1)
(where N is an integer >=0). A similar computation is run for the fast average weighted percentiles HPAVF(-1), WPAVF(-1) and CpAVp(-l). During the time it takes to gather samples 0...N, the algorithm is unable to produce M(t) in the table, but upon gathering the data of time point N, the algorithm outputs for all times 0..N can be reconstructed. The values at time t = -1 should represent the "born averaged percentile" of each physiological property, meaning the infants' inherent height, weight and head circumference percentile relative to the larger population before the infant exhibits any developmental problems. Physicians normally use the 2-3 measurements taken in the first 2-3 weeks of life to determine the infant's inherent ("from birth") percentile by means of a non-mathematical "by observation" averaging of these measurements: in the example below we expect a once-a-week use (measurement set), which translates to N=2. We note that data samples are gathered at different times. Therefore, the full set of data does not exist for times 0... N and one cannot do the calculation for the (-1) parameters (HpAVs (-1), WpAVs(-l ) and CpAVS (-1)) and therefore cannot get M(O) or M(I) or ... M(N) at such times. Only at the time of measurement (N+ 1) will there be enough data to actually perform the calculations. Therefore, in normal use, the marks M(O) and M(I) which are related to the first two measured data sets are not computed directly after the measurement of these data sets, because M(-l) cannot be computed yet. When the third measurement is taken, M(O) and M(I), as well as M(2) can be computed retroactively. Tables 1 and 2 above are therefore given as "historical" tables, implying that the starting conditions have been computed from existing data. The (-1) values are computed as unweighted averages., which are neither slow averages nor fast averages.
In the example Tables 1 and 2, "AVs" and "AVp" are given parametric values of respectively 0.2 and 0.9. These values were chosen so that a theoretical "step function change" in the data would have the fast average differ by about less than 10% from a new value in about 4 steps (i.e. not to enable a single, possibly erroneous measurement, to affect it too much), and the slow average differ by <10% from a new value in about 12 steps. The 3 times more measurements (12 vs. 4) correspond to 3 times more "growth time" when measurements are about equally spaced. It is noted that other values of "AVS" and "AVF" may be chosen, as long as they fulfill the condition
O<AVF<1 0<AVS<AVF
A way to test the adequacy of the chosen values of "AVg" and "AVF" is to generate a test group of full sets of historical data of both "normal" and "not normal" children (as determined by an expert physician examination of the historical growth data) and compare their classification as "normal" and "not normal" to that of the algorithm (as explained below). The size of the test group and the amount of fit required to use specific constant values depend on the user-defined tolerable error margin (how many "wrongs" the potential algorithm user is willing to accept in his target population based on the amount of misclassifi cations observed in the test group, which is easily computed by statisticians).
Next, in a step 104, a value of the difference "DIFF" [%] between the "fast" and "slow" average of each measurement ("DΪFF HPAV" [%] for height, "DIFF WpAV" [%] for weight and "DIFF CpAV" [%] for head circumference) is computed as follows:
DIFF HpAV [%] - HpAVKt) - HPAVs(t) DIFF WpAV [%] - WPA VF(t) - WP AVs(t)
DIFF CpAV [%] = CPAVF(t) - CPAVs(t)
In a step 106, the value for each parameter is augmented to reflect the "importance" of this difference: the closer to 50% the "fast" average is, the less significance there is to the difference between it and the "slow" average. The augmentation process includes first the determination of a measure of the "distance" (DIS) value of the "fast average" from the extreme percentiles (0% and 100%). Exemplarily, if the fast average weighted percentile value is smaller than or equal to 50%, DIS is set equal to the respective fast average weighted percentile value, and if the fast average weighted percentile value is larger than 50%, DIS is set equal to the result of a subtraction of the respective fast average weighted percentile value from 100%:
DISHpAV [%] - min (HPAVF(t); 100-HPAVF(t)) DISWpAV [%]= min (WPAVF(t); 100-WPAVF(t))
DISCpAV [%]= min (CPAVF(t); 100-CP VF(t))
The augmentation of the DIFF values to receive augmented values MHp(t), MWP(t) and MCp(t) is then exemplarily achieved by division of the DIFF values with their respective DIS values:
MHp(t) = DIFF HpAV /DISHPAVF(t) MWp(t) = DIFF WpAV /DISWpA VF(t) MCp(I) = DIFF CpAV /DISCPAVF(t)
In a step 108, combined indication value M(t) is now computed based on all three augmented values MHp(t), MWp(t) and MCp(t). There are various possibilities to perform this computation. An exemplary calculation of M(t) is based on setting M(t) to equal the highest absolute value of the three (MHρ(t), MWp(t) or MCp(t)) (the furthest from 0, be it plus or minus). Tables 1 and 2 provide exemplary values of each parameter (measured or computed) above, for, respectively two infants (infant A and infant B). In a step HO5 the M(t) value is compared to two extreme values of -1 and +1. If the M(t) value exceeds any of the two extreme values, this may be considered an indication of abnormal growth.
Examples
Two examples are given with reference to the data in Tables 1 and 2. In a first example (Table 1), the algorithm described above was run using the following parametric values: AV8 = 0.2, AVF = 0.9 and N = 2. Infant A was a female for whom it was determined that HPAVS(-1) = 2%, WPAVS(-1) = 11% and CPAVS(~1) = 16%. All parameters measured or computed above have values under respective headings at each measurement time between 0.9 months after birth and 20.6 months after birth. The last column shows the indication value M(t) at each measurement time. The M(t) values from Table 1 are listed again in. Table 3 together with the MWp(t), MHp(t), MCP(t):
Table 3
Figure imgf000011_0001
In this example, the Mp(t) values at each measurement time were chosen to be equal to the maximum value in each three parameter MWp(t), MHp(t), MCp(t) set. Thus, at 0.9 months, MP(t) - MWP(t) = -0.24, at 1.2 months, MP(t) - MWP(t) - -0.14, at 13.8 months, MP(t) = MHP(t) = 0.31 and at 20.6 months, MP(t) = MHP(t) = MCP(t) = 0.18. Note that there may be other choices and ways to obtain a single Mp(t) value from a three parameter MWP(t), MHp(t). MCP(t) set. The Mp(t) values may be plotted as a function of time (calibrated for "months since birth"), where values of 1 and -1 mark "normal" values. Any value above 1 or below -1 constitutes a transgression from "normal" to "caution" meaning the algorithm indicates a possible developmental problem. One can see that infant A is "normal, as the M(t) value never extends beyond the two bounds.
In a second example (Table 2), the algorithm described above was run using the same parametric values as in the first example: AVs = 0.2, AVF = 0.9 and N ~ 3 on Infant B. Infant B was a female for whom it was determined that HpAVs(-l) - 0.44, WpAVg(-l) - 0.52 and CpAVs(-l) = 0.23. All parameters measured or computed above have values under respective headings at each measurement time between day 0 (date of birth) and day 367 after birth. The M(t) values from Table 2 are listed again in Table 4 together with the MWP(t), MHP(t), MCP(t): Table 4
Figure imgf000012_0001
In this example too, the Mp(I) values at each measurement time were chosen to be equal to the maximum value in each three parameter MWp(I), MHp(t), MCp(t) set. Thus, at day 0, MP(t) = MWP(t) = 0.09, at day 13, MP(t) = MHP(t) = -0.13, at day 187, MP(t) = MCp(t) = 0.25 and at day 367, MP(t) = MWP(t) - -4.43. Similar to Example 1, the Mp(t) values may be plotted as a tunction of time (calibrated for "months since birth"), where values of 1 and -1 mark "normal" values. One can see that infant B shows "abnormal" growth starting on day 279, when the value of Mp(t) falls below the -1 value.
The physiological parameters of height, weight and head circumference may be measured using standard equipment known in the art, or a dedicated system that measures all three parameters. The algorithm described above may be implemented as a computer program storing program code for performing the method.
While the invention has been described with respect to a limited number of embodiments, it will be appreciated that many variations, modifications and other applications of the invention may be made.

Claims

1. A method for indicating the pediatric growth status of a patient for which a data set of measured weight, height and head circumference values is obtained at each measurement time t, the method comprising the steps of: a) at each time t, obtaining a set of direct percentile values of weight, height and head circumference using the respective measured weight, height and head circumference values; and, b) computing a single combined indication value from the direct percentile values of weight, height and head circumference, the single combined indication value indicative of a pediatric growth status.
2. The method of claim 1, wherein the step of computing a single combined indication value includes: at each time t: i. computing slow average weighted percentile values for each of the weight, height and head circumference from, respectively, the direct weight, height and head circumference percentile values, ii. computing fast average weighted percentile values for each of the weight, height and head circumference from, respectively, the direct weight, height and head circumference percentile values, iii. computing difference values from differences between the fast average and the slow average weighted percentile values of, respectively, each of the weight, height and head circumference, v. computing a set of weight, height and head circumference augmented values from, respectively, each of weight, height and head circumference difference values, and vi. computing the single combined indication value from the set of weight, height and head circumference augmented values.
3. The method of claim 1 , wherein the obtaining a set of direct percentile values is done by comparing the data set of measured weight, height and head circumference values to a growth chart.
4. The method of claim 3, wherein the growth chart is a CDC growth chart.
5. The method of claim 2, wherein the computing slow average weighted percentile values for each of the weight, height and head circumference includes, for each of the weight, height and head circumference, adding a slow average weighted percentile value at time t to a slow average weighted percentile value at time t-1 and dividing the resulting sum by (1+AVs), wherein AVs represents a predetermined constant, and wherein the computing fast average weighted percentile values for each of the weight, height and head circumference includes, for each of the weight, height and head circumference, adding a fast average weighted percentile value at time t to a slow average weighted value percentile value at time t-1, and dividing the resulting sum by (1+AVF), wherein AVp represents a predetermined constant.
6. The method of claim 5, wherein the computing a set of weight, height and head circumference augmented values includes, for each of the weight, height and head circumference, subtracting the slow average weighted percentile value from the fast average weighted value percentile and dividing the result by the fast average weighted percentile value.
7. The method of claim 6, wherein the computing a set of weight, height and head circumference augmented values further includes determining a distance value DIS of each fast average weighted percentile value from two extreme percentile values, 0% and 100%.
8. The method of claim 7, wherein, for each of the weight, height and head circumference, if the fast average weighted percentile value is smaller than or equal to 50%, DIS is set equal to the respective fast average weighted percentile value, and if the fast average weighted percentile value is larger than 50%, DIS is set equal to the result of a subtraction of the respective fast average weighted percentile value from 100%:
9. The method of claim 8, wherein the computing a set of weight, height and head circumference augmented values further includes, for each of the weight, height and head circumference, dividing the respective difference value by the respective distance value.
10. The method of claim 1, wherein the computing the single combined indication value from the set of weight, height and head circumference augmented values includes setting the single combined indication value to be equal to a maximum of the weight, height and head circumference augmented values.
11. The method of claim 1, wherein, when the single combined indication value indicative a pediatric growth status exceeds values of +1 or -1, the growth status is considered abnormal.
12. A method for indicating the pediatric growth status of a patient for which a data set of measured weight, height and head circumference values is obtained at each measurement time t, the method comprising the steps of: a) at each time t, obtaining a set of direct percentile values of weight, height and head circumference using the respective measured weight, height and head circumference values; b) processing each set of direct percentile values of weight, height and head circumference to obtain a corresponding set of augmented weight, height and head circumference values; and c) computing a single combined indication value from the set of weight, height and head circumference augmented values by setting the single combined indication value to be equal to a maximum of the weight, height and head circumference augmented values; whereby the single combined indication value is indicative of a pediatric growth status.
13. The method of claim 12, wherein the step of processing each set of direct percentile values of weight, height and head circumference to obtain a corresponding set of augmented weight, height and head circumference values includes: at each time t: i. computing slow average weighted percentile values for each of the weight, height and head circumference from, respectively, the direct weight, height and head circumference percentile values, ii. computing fast average weighted percentile values for each of the weight, height and head circumference from, respectively, the direct weight, height and head circumference percentile values, iii. computing difference values from differences between the fast average and the slow average weighted percentile values of, respectively, each of the weight, height and head circumference, and iv. computing a set of weight, height and head circumference augmented values from, respectively, each of weight, height and head circumference difference values
14. The method of claim 12, wherein the obtaining a set of direct percentile values is done by comparing the data set of measured weight, height and head circumference values to a growth chart.
15. The method of claim 13, wherein the computing slow average weighted percentile values for each of the weight, height and head circumference includes, for each of the weight, height and head circumference, adding a slow average weighted percentile value at time t to a slow average weighted percentile value at time t-1 and dividing the resulting sum by (1+AVs), wherein AVs represents a predetermined constant, and wherein the computing fast average weighted percentile values for each of the weight, height and head circumference includes, for each of the weight, height and head circumference, adding a fast average weighted percentile value at time t to a slow average weighted value percentile value at time t-1, and dividing the resulting sum by (1+AVF), wherein AVp represents a predetermined constant.
16. The method of claim 15, wherein the computing a set of weight, height and head circumference augmented values includes, for each of the weight, height and head circumference, subtracting the slow average weighted percentile value from the fast average weighted value percentile and dividing the result by the fast average weighted percentile value.
17. The method of claim 16, wherein the computing a set of weight, height and head circumference augmented values further includes determining a distance value DIS of each fast average weighted percentile value from two extreme percentile values, 0% and 100%.
18. The method of claim 17, wherein, for each of the weight, height and head circumference, if the fast average weighted percentile value is smaller than or equal to 50%, DIS is set equal to the respective fast average weighted percentile value, and if the fast average weighted percentile value is larger than 50%, DIS is set equal to the result of a subtraction of the respective fast average weighted percentile value from 100%:
19. The method of claim 18, wherein the computing a set of weight, height and head circumference augmented values further includes, for each of the weight, height and head circumference, dividing the respective difference value by the respective distance value.
20. The method of claim 1, wherein, when the single combined indication value indicative a pediatric growth status exceeds values of +1 or -1, the growth status is considered abnormal.
PCT/IB2008/053562 2007-11-13 2008-09-03 Method for following pediatric development WO2009063339A2 (en)

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CN113017311A (en) * 2021-03-03 2021-06-25 吕瑞 Intelligent learning table and growth monitoring method thereof

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