the influence of different generations of computer algorithms on diabetes control

Computer Methods and Programs in Biomedicine, 32 (1990) 225-232 225 Elsevier

COMMET 01103

The influence of different generations of computer algorithms on diabetes control

Jiirgen Beyer 1, Jiirgen Schrezenmeir 1, Gerhard Schulz 1, Thomas Strack 1, Ernst Kiistner 1 and GUnter Schulz 2

J Department of Internal Medicine and Endocrinology, III. Medical Clinic, University of Mainz, Mainz, F.R.G., and 2 WBK Fachhochschule Bergbau Bochum, Bochum, F.I~ G.

With all control schedules, the management of diabetes is possible using Skyler's algorithm. In general, those control algorithms which do not allow the individual adaptation to changing conditions lead to overinsulinisation. So-called meal-related algorithms do usually minimise the fluctuations in blood sugar. The introduction of self-adapting algorithms, detecting peripheral insulin resistance, may further improve metabolic diabetes control.

Insulin treatment; Insulin injection; Diabetes mellitus; Control algorithm; Self-adaptation; Blood glucose; Meal

1. Introduction

Microcomputers are widely employed in medicine in a continuously expanding range of applications. Up to now, this technology has been mainly applied in medical equipment to attain greater con- venience in system handling, data analysis, data presentation and documentation [1,2]. The objec- tive is to achieve better quality in the exchange of information between the physician and the techni- cal systems. This is, however, only of little help in the interpretation of medical aspects including decision making in diagnosis and therapy. As a first step, intelligent functions are entailed to de- velop expert systems [3,4]. Since medical thinking is quite analogous to control algorithms in a tech- nical environment, therapy appears well-suited for a computer-based optimisation. Both the physi-

Correspondence: Jiirgen Beyer, Department of Internal Medi- cine and Endocrinology, IlL Medical Clinic, University of Mainz, Malnz, F.R.G.

cian and the engineer start with a given situation and they envisage a final state of desired char- acteristics.

This methodological approach appears easily transferrable to the treatment of diabetics, be- cause in a simplified representation, there is only one input (insulin) and one output (blood glucose). However, other investigations have shown that the correlation between glucose and insulin is affected by a large number of variables and that, therefore, a simple function is not adequate for long-term adaptation of diabetic metabolism. Factors in- fluencing the correlation between the effect of insulin and blood sugar responses are, for exam- ple, the current blood sugar level, the amount and composition of ingested food, the metabolic alterations after physical work, and the individually differing sensitivity to insulin.

It is, nevertheless, possible to adjust the blood sugar level to the desired range, applying exoge- nous insulin according to empirical rules relating reproducibly the intake of food to insulin doses. The first models were empirically evaluated. Using

0169-2607/90/$03.50 © 1990 Elsevier Science Publishers B.V. (Biomedical Division)

226

the artificial pancreas, Beyer et al. [5] have de- termined the insulin requirement in the fasting state and after standardised food intake. In this way, the basal requirement could be quantified and then meal-dependent extra-doses were de- termined. Later, it was shown that the insulin requirement follows certain principles around the day which allow the rough calculation of insulin doses to be administered at defined times. Finally, reproducible differences in insulin requirement could be demonstrated at various times of the day. More detailed descriptions of these relationships were empirically derived by Skyler et al. [6,7].

2. Aim of the study

On the basis of our own experience and of the results of other investigators, we have been devel- oping various computer programs for the control of blood glucose concentration in diabetic patients. In a retrospective anmv~i~,'2-"- it v"~s found that the quality of model-based therapy does strongly depend on the permanent application of blood sugar self-control in the morning, before breakfast, before lunch, before dinner, before going to bed, and sometimes in addition at 03.00 h in the morning.

3. Prospective adaptation of insulin doses using tables according to empirical rules (1983 model)

In the context of a proven individual insulin therapy, the insulin doses were varied according to the blood sugar value, altering both the doses of regular and of basal insulin (Table 1). The control of the average blood sugar level and schematic (and it could only be achieved on the basis of strict observation of diet) was relatively rough.

4. Prospective / retrospective computer-assisted adaptation of insulin dose in accordance with empirical rules (IDAP, 1984/85 model)

This program, too, presupposes a strict diabetes diet. The storage of entered blood sugar values

TABLE 1

Changes in insulin dose following blood glucose self-control

Regular NPH insulin

I. Normal insulin dose Morning 12 U 24 U Evening, before dinner 12 U - Evening, late (10 p.m.) - 8 U

II. Adaptation before breakfast BG < 120 mg/dl 8 U BG 120-180 mg/di 10 U BG 180-240 mg/di 12 U BG 240-300 mg/dl 16 U

Ill. Adaptation before dinner BG < 120 mg/dl 8 U BG 120-180 mg/dl 10 U BG 180-240 mg/dl 12 U BG 240-300/400 mg/dl 16 U

IV. Adaptation before bedtime BG < 80 mg/dl

BG 80-120 mg/dl

BG 120-180 mg/dl BG 180-240 mg/dl BG 240-300/400 mg/dl

22 U 24U 24 U 24 U

Eat in addition 20 g CHO 5 U

Eat in addition 10 g CHO 5 U

- 7 U 2 U 8U 4 U 8U

BG = blood glucose.

and the output of calculated insulin doses are carried out over 100 days. The Sharp 1500 pocket computer with 16 kbyte RAM extension was used where a so-called regulation matrix is the basis of the computer program. This regulation matrix was established empirically in accordance with the general experience in diabetes therapy. The matrix takes into consideration the kinetics of insulin action on the blood sugar level, i.e. its onset, the maximum effect and the duration.

The fasting blood sugar values in the morning are subject to the effect of intermediate-acting insulin administered the evening before, but in turn they determine the amount of regular insulin to be administered in the morning. The blood sugar values before lunch result above all from the action of regular insulin administered in the morning, and the dose of intermediate-acting insulin adminstered in the morning affects the blood sugar level after lunch and in the afternoon. Analogous

rag/a1

200

150

100

r , 1

~ SE

Day

Fig, 1. Blood glucose graph during a 7-day phase of therapy.

profiles apply to the insulin adminstered in the evening.

In order to adapt insulin therapy to the daily fluctuations of blood sugar, the doses of intermediate-acting and the short-acting formulations are altered independently of each other (Table 2). In addition, the total daily insulin dose is entered into the regulation matrix. The pattern of insulin

227

Go 12

11

Do 14 dOy5

,o

9

se

7

6

before IDAP 40 doys o f t e r IDAP

Fig. 2. HbAlc values during IDAP treatment.

doses can essentially be established on the basis of four daily blood sugar measurements, i.e. the fasting blood sugar, the preprandial value at noon and before the evening meal, and the level at bedtime [8-10].

The computer program consists of routines for the doctor and one for the patient, respectively.

TABLE 2

Regulation matrix for IDAP

Time of BG control Fasting Before lunch

Insulin N B N B

Before dinner Before night

N B N B

Changes in insulin (Aim) as result of the measured BG

Blood glucose (mg/dl) 300 +4 280-300 + 3 260-280 + 3 240-260 + 2 220-240 + 2 200- 220 + 2 180-200 + 1 160-180 + 1 140-160 + 1 120-140 0 100-120 0

80-100 0 60- 80 - 1

- 60 - 2

+3 +2 +4 +4 +2 +3 +2 +3 +2 +4 +4 +3 +3 +2 +3 +3 +4 +3 +2 +2 +2 +2 +1 +3 +3 +2 +2 +2 +2 +1 +3 +2 +1 +2 +2 +2 +1 +2 +2 +1 +1 +1 +2 +1 +2 +2 +1 +1 +1 +1 +1 +1 +1 +1 +1 +1 +1 +1 +1 +1 +1 0 0

0 0 +1 0 +1 0 0 0 0 0 0 0 - 1 0 0 1 0 0 0 - 1 0

- 1 - 3 2 - 1 - 1 - 1 - 2 - 2 - 4 - 2 - 2 - 2 - 1 2

N = normal; B = basal; BG = blood glucose.

228

Iu {

70 ~ Gr

60 Du 14 days

Se 5C

4O D,

3O

I T before IDAP 40 cloys ofter IDAP Fig, 3. Insulin consumption during IDAP per 24 h.

The initial doses of insulin as a mixture of intermediate.acting and of short-acting insulin for injections in the morning and in the evening as well as the maximum insulin doses are recommended

by the physician [11-14]. The related results in ten insulin-dependent diabetic inpatients are shown in Fig. 1. These patients had no insulin resistance but they required some re-adaptation of their meta- boric regimens. The average blood sugar and HbAlc went down but no major fluctuations and no appreciable number of hypoglycaemic episodes occurred. Under this computer-assisted diabetes management, the total daily insulin doses were higher after 40 days (Figs. 2 and 3) which, however, did not reach statistical significance [12].

5. Prospective/retrospective computer-assisted insulin dose adaptation by means of mathematically defined algorithms in diabetics using conventional insulin therapy (CACIT 1985)

Following this line, an improved version of the program was created for conventional therapy with short-acting and intermediate-acting insulin (Fig. 4). This improvement comprises three aspects: - unification and elucidation of the control sys-

tem by means of non-linear functions for the prospective and retrospective correction of in-

-.[

~' I noon

blOOd glucose J :J 1st regulator I m°rning'n°°n I I injecti°n I'~

0,ooo ! .. r.o.o.o I . afternoon J injection ~.

blood glucose I 2 nd regulator I injection J ~ .

blood glucose l :~l 2 nd regulator J bedtime'm°rning I I injection I~

short - acting insulin

inter - mediate- actin 9 insulin

injection in the

mornin 9

short - acting insult n

inter - mediate - actin 9 insulin

injection in the

afternoon

insulin parameters, exercise, illness, hypoglycemia

Fig. 4. Flow diagram of CACIT.

- - 1

I { I I

I

A

E~G

22C

~ 15C

8C

rl:11

I 2 2 E

BE

i ~ 3 A 5 6 7 8 " c

m

BG°aY T

2 3 4 5 6 7 8 -

Fig. 5. in-patient treatment: daily mean blood glucose values of 11 patients.

sulin doses to replace the non-methodological matrices described above;

- improvement of insulin economy to avoid both overinsulinisation and down-regulation by means of combining the doses of short-acting and of intermediate-acting insulin;

- long-term storage of blood glucose values, insulin doses, hypoglycaemic episodes and physical exercise for purposes of documentation and evaluation. In an in-patient study, this computer-assisted

conventional insulin therapy (CACIT) decreased over 8 days the mean blood glucose level to 103 _+ 23 (SD) m g / d l (Fig. 5). If the mean daily blood glucose values are classified into four different ranges, reflecting the incidence of hypoglycaemia, euglycaemia, hyperglycaemia, and of values above 220 mg/dl , the latter disappeared after 5 days, and the majority of values were in the euglycaemic range. This effect was also seen in out-patients during follow-up periods of between 1 and 2 months. However, as a consequence of the

229

mathematical structure cf the controller used [15] we observed an increase in the doses of basal insulin (NPH insulin) and a decrease in the pro- portion of regular insulin.

6. Computer-assisted mea~-dependent insulin therapy (CAMIT 1985)

It has been well documented that the combination of self-control and self-adaptation by patients may result in optimal metabolic control. Meal-related insulin regimens such as multiple subcutaneous injections (MSI) and continuous subcutaneous insulin infusion (CSII) appear to provide the best results. To facilitate switching from conventional to intensified insulin therapy and to optimise the performance of both regimens, we have developed algorithms which are applicable in a more general sense [16-20].

They allow a really quantitative adaptation to the actual requirements and the variation in food intake from day to day. Also, it became feasible to calculate different basal infusion rates for different times of the day. These algorithms serve in the instruction of patients, and they are the basis of a program for hand-held computers.

Before designing an adaptation program for meal-related insulin therapy, the following fea- tures of the therapeutic regimens had to be taken into consideration [19]: - fasting insulin requirement to be covered by

long-acting insulin;

TABLE 3 Formula for management of intensified insulin therapy

T i m e

(0.45 DINCT) Breakfast

CHO/day Lunch ( ) Supper ( )

Short-acting insulin (U)

(DINCT) (x -120) 1.5 CHO+ 40 3O 1.0 CHO+ ( ) ( ) 1.2 CHO+ ( ) ( )

Long acting

0.23 DINCT

0.21 DINCT

Term a b c d e f ,.

DINCT ffi daily insulin need during conventional therapy; term a = individual insulin sensitivity; b ffi alterations of insulin sensitivity during the day; c = carbohydrate content (CHO) of the meal; d + e = correction term for prospective self-adaptation; f = fasting insulin need.

H bA 1 "1.

100

- amount of short-acting insulin to cover meals at different times of the day;

- response to the actual difference and to previously observed differences between the blood glucose target and the measured level (prospective and retrospective adaptation);

-a lgor i thm describing the individual insulin sensitivity and adapting continuously the calculated insulin doses to the endogenous conditions. These considerations resulted in an adaptation

formula (Table 3) with the six terms a, b, c, d, e, and f which contains two individual variables: (1) the insulin-blood glucose equivalent describes

the relation between 1 IU insulin and the related decrease in blood glucose concentration [19]:

40 1 IU = ~ • 30 mg/dl

(DIN = daily insulin need),

(2) the insulin-carbohydrate equivalent describes the relation between ingested carbohydrates and the related insulin requirement [19]:

1 g CHO 1 I U =

a - b

where a ffi individual insulin sensitivity and b = alteration of insulin sensitivity around the day.

These two equivalents allow the conversion from desired blood glucose to alterations in inputs of insulin and carbohydrate and vice versa. Their use makes possible (1) the exchange of insulin and carbohydrate inputs thereby promising a more liberal life style, and (2) the quantification com- prising all interacting parts of diabetes therapy: glucose level, insulin and carbohydrate intake, etc.

On this basis, the equivalent ratios may serve the further adaptation during follow-up [19]. Thus, the initial adaptation formula is not only indi- vidualised, but also continuously updated. The results of various controlled long-term studies have shown that the computer-assisted, meal-dependent insulin .therapy improves blood glucose control [18,21]. During a randomised multicentre study,

p<O05

9C

BO

230

MS1 Camit

Fig. 6. Decrease of HbAlc after 3 months treatment with multiple meal-dependent insulin injections (MSI) without computer in comparison with computer-assisted meal-dependent insulin therapy (CAMIT) (n =12). Dashed columns: before treatment ( = 1005[); open columns: after 3 months of treat-

meat.

we were able to compare the usual intensified insulin therapy with a computer-assisted regimen. In the latter group, a significant reduction was found in HBA1 and in the incidence of hypoglycaemic episodes (Fig. 6) but the daily insulin doses could be reduced or they remained un- changed [17,18,22,23].

T

Vl v2 v4 v6

I w,t=,,tO, r ,t I Iw, hcom,tJ tw ho Com, ]

Fig. 7. Frequency of hypoglycaemic episodes per week: V1 = intensified meal-dependent insulin therapy before re-education; V2 = 6 - 8 weeks after intensive re-education and improved blood glucose regulation; V 4 - 6-8 weeks after the beginning of computer-assisted insulin therapy (CAMIT); V6 = 8-10 weeks following interruption of computer-assisted in-

sulin lherapy.

In another extremely well-controlled group of 22 patients who had previously been using an intensified insulin therapy, we found after re- peated teaching and training in computer algorithms a more stable metabolic control with a lower incidence of hypoglycaemie episodes as compared with control observations which were made both before and after the computer trial (Fig. 7). The average insulin need was practically identical during all three intervals, but the relation changed in favour of the portion of regular insulin [231.

7. Discussion and conclusion

The introduction of blood sugar self-control has brought about an enormous advance in diabetes therapy. This enabled a generally better control of diabetes. At the same time, the empirical algorithms as introduced by Skyler [6] have shown the way to further improve conventional insulin therapy. The initial computer algorithms were based in part on these approaches. The purely mathematically defined algorithms had similar ob- jectives. The feedback regulation between blood sugar and applied insulin led not only to an improvement of diabetes management but they re- suited also in an alteration of the glucose/insulin ratio in certain non-typical situations. In these cases, an overinsulinisation may result which in turn may re-inforce insulin resistance which is possibly present.

Only the self-adaptation to individual variables can give rise to further therapeutic effectiveness. In this way, hyperinsulinaemia might be abolished and the insulin level could also be adapted to the low blood sugar values. A valuable instrument could thus be created for the practical management of diabetic patients.

References

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231

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the influence of different generations of computer algorithms on diabetes control

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