3.2 Novel real-time algorithm for C B C detection
3.2.3 Comparison of computational costs
A total of 209 cases and 209 first degree relatives (serving as controls) took part in the study. In both cases and controls, 46.4% were females, while 53.6% were males. No significant statistical difference was noted (x2=0.000, df=1, P=1.00 (Table 1).
The age of the cases ranged from 13 to 42 years with a mean of 28.2 years (SD= 6.8), while the controls had a age range of 15 to 65 years with a mean of 33.7 years (SD=11.2) there was a statistical significant difference between the ages of the cases and controls (t= -6.125, df=416, p<0.001) (Table 2).
Thirty (14.3%) of the cases were married, 179 (85.7%) were single, while 111(53.1%) of the controls were married, and 98(46.9%) were single. This distribution is statistically significant (x2=70.22, df=1, p<0.001) (Table 3).
Amongst the cases, 92 (44%) were unemployed, while majority of the controls, 136(65%) were employed. This distribution is also statistically significant (x2=90.23, df=3, p<0.001) (Table 4).
Sixteen (7.7%) cases and 29(13.9%) of controls were graduates. A higher proportion of both cases and controls, 123(58.9%) and 119(56.9%) respectively, had secondary school education, whereas 9(4.3%) of the cases and none of the controls had no formal education (x2=12.95, df=4, p=0.012) (Table 5).
54 Table 1: Distribution of gender for cases and controls
N=418
Variable
Cases controls
X2 df p-value
n=209 frequency (%)
n=209 frequency (%)
Gender Female Male
97 (46.4) 112(53.6)
97 (46.4) 112(53.6)
0.000 1 1.00
55 Table 2: Age for cases and controls
N=418
Variable
Cases
Controls
t-test df p-value n=209
frequency (%)
n=209 frequency (%)
Age (years) Groups
13-17 18-22 23-27 28-32 33-37 38-42 43-47 48-52 53-57 58-62 63-67 Mean(SD)
11(5.3)
35(16.7) 59(28.2) 43(20.6) 34(16.3) 27(12.9) 0(0) 0(0) 0(0) 0(0) 0(0) 28.2(6.8)
8 (3.8) 34(16.3) 24(11.5) 36(17.2) 21(10.0) 41(19.6) 12(5.7) 25(12.0) 3(1.4) 4(1.9) 1(0.6) 33.7(11.2)
-6.125 416 <0.001
56 Table 3: Marital status of cases and controls
N=418
Cases Controls
X2 df P-value
n=209 frequency (%)
n=209 frequency (%)
Marital status Married Single
30 (14.3) 179(85.7)
111(53.1) 98 (46.9)
70.22 1 <0.001
57 Table 4: Employment status of cases and controls
N=418
Variable
Cases Controls
X2 df p-value
n=209 frequency (%)
n=209 frequency (%)
Employment status
Employed
Retired Student
Unemployed
52(24.9) 0 (0) 65 (31.1)
92(44.0)
136(65.0) 3 (1.4) 51 (24.4)
19 (9.2)
90.23 3 <0.001
58 Table 5: Educational attainments of cases and controls
N=418
Variable
Cases Controls
X2 df p-value
n=209 frequency (%)
n=209 frequency (%)
Educational level
Graduate
No formal education Primary Secondary Undergraduate
16 (7.7)
9 (4.3)
30 (14.3) 123(58.9) 31 (14.8)
29 (13.9)
0 (0)
32 (15.3) 119 (56.9) 29 (13.9)
12.953 4 0.012
59 5.2 Association between the use of antipsychotic agents and
hyperglycaemia
The mean initial fasting blood sugar for cases was 4.24mMol/L (SD=0.37) with a range of 3.4 to 5.4mMol/L, and a mean final fasting blood sugar of 5.27mMol/L(SD=0.67) with a range of 3.9 to 7.9mMol/L. There was a statistically significant difference between the initial and the final fasting blood sugar level (t= -22.13, df=208, p<0.001) (Table 6).
On the other hand, there was no significant change between the mean initial and the mean final fasting blood sugar levels among the controls. The mean initial fasting blood sugar for controls was 4.23(SD=0.42) while the mean final fasting blood sugar was 4.22(SD=0.41) (t=0.86, df=208, p=0.388) (Table 7).
Within the study period, 26 patients with schizophrenia being treated with antipsychotics (cases) developed hyperglycaemia whereas none among the comparison group (controls) had hyperglycaemia (x2=27.72, df =1, p<0.001).
Majority of the cases, 183(87.6%), and all the controls had a final fasting blood sugar level below 6.0mMol/L, while 26(12.4%) of the cases, and none of the controls had a final fasting blood sugar of 6.0mMol/L and above. This difference is of statistical significance(x2 =27.7, df =1, p<0.001) (Table 8).
Twenty (9.6%) cases had impaired fasting glucose, 6(2.8%) had diabetes mellitus, and 183(87.6%) had a normal final fasting blood sugar levels(x2=27.7, df=2, p<0.001) (Table 9). At the end of the study period, none of the controls developed hyperglycaemia, impaired fasting glucose or diabetes mellitus.
60 5.3 Association between the class or type of antipsychotic and hyperglycaemia
Thirty-two (15.3%) cases received atypical antipsychotic drugs, out of whom 5(15.6%) developed hyperglycaemia, whereas 177(84.7%) received typical antipsychotic drugs and 21(11.9%) of them developed hyperglycaemia. There was no significant association between the class of antipsychotic and hyperglycaemia (x2=0.352, df=1, p=0.364) (Table 14).
There was a significant correlation between dose of antipsychotics in chlorpromazine equivalent and change in fasting blood sugar levels(r=0.18, p=0.009). Therefore , the higher the dose of the medication, the greater the increase in the fasting blood sugar level.
Among cases that received typical antipsychotics, the combination of chlorpromazine and fluphenazine decanoate produced the highest change in mean fasting blood sugar level of 1.85mmol/L (SD=0.21). This is followed by the combination of trifluperazine and fluphenazine decanoate with a mean change of 1.75mmol/L (SD=1.20). Chlopromazine produced the largest single change in mean fasting blood sugar level of 1.34mmol/L (SD=0.78), whereas trifluperazine alone produced the least change in mean fasting blood sugar level of 0.78 mmol/L(SD=0.44) (Table 15).
Among the atypical antipsychotic agents, clozapine produced the greatest change in the mean fasting blood sugar level of 1.60(SD=0.90), followed by olanzapine and risperidone (F=2.76, df=197, p=0.002) (Table 15).
61 5.4 Relationship between the use of antipsychotic agents and weight
The mean initial weight for cases was 59.5kg, while that for the controls was 60.5kg. There was no statistically significant difference between them (t=-1.22, df=416, p=0.22) (Table 10). In other words, the matching for weight was successful.
The mean weight change for cases was 4.06kg (SD=3.05) while for the controls it was 0.06kg (SD=0.51). This difference was statistically significant (t=18.65, df=416, p=<0.001) (Table 11).
The mean weight gain among those on atypical antipsychotic agents was 7.4kg (SD=2.43), while among those on typical antipsychotics it was 3.4kg (SD=2.7).
This was statistically significant (t= 7.59, df =207, p<0.001) (Table 12).
At the end of the study period, 5.3% of cases were obese and 24.9% were overweight, while among the controls, 0.5% was Obese and 7.7% were overweight. This difference was statistically significant (x2=33.65, df=2, p<0.001). There was no association between gender and weight gain. (x2=11.51, df=12, p=0.486). There was a significant correlation between weight gain and a change in fasting blood sugar level(r=0.34, p<0.001).
Among the cases, the mean initial body mass index was 22.03(SD=3.43), mean final body mass index was 23.63(SD=3.78). This change in the mean body mass index was statistically significant (t=14.203, df=208, p<0.001) (Table 13).
For the controls, the change in mean body mass index from 21.70(SD=2.21) to
62 21.72(SD=2.20) was not statistically significant (t=1.566, df=208, p=0.119) (Table 14).
63 Table 6: Fasting blood sugar of cases
N=209
Variable Mean SD t-test df P
Cases
FBS1(mmol/L) FBS2(mmol/L)
4.24 5.27
0.37 0.67
-22.03 208 <0.001
Key
FBS1=Initial fasting blood sugar FBS2=Final fasting blood sugar
64 Table .7: Fasting blood sugar for controls
N=209
Variable Mean SD t-test df P
Controls FBS1(mmol/L) FBS2(mmol/L)
4.23 4.22
0.423 0.414
0.623 208 0.534
65 Table 8: Final fasting blood sugar of cases and controls
N=418
Variable
Cases Controls
X2 df P-value
n=209 frequency (%)
n=209 frequency (%)
FBS2<6mmol/L
FBS2>6mmol/L
183(87.6)
26 (12.4)
209(100)
0(0)
27.7 1 <0.001
66 Table 9: Distribution of diabetes mellitus, and impaired fasting glucose among cases and controls
N=418
Variable
Cases Controls
X2 df P-value
n=209 frequency (%)
n=209 frequency (%)
Normal DM IFG
183(87.6) 6 (2.8) 20 (9.6)
209(100) 0 (0) 0 (0)
27.7 2 <0.001
key
DM=Diabetes mellitus IFG=Impaired fasting glucose.
67 Table 10: Initial weight of cases and controls
N=418
Variable Number
Mean wt1(SD)
Kg t-test Df P-value
Cases
Controls
209
209
59.45(9.7)
60.52(8.1)
-1.22 416 0.22
Key
Wt1=initial weight.
68 Table 11 : Weight change of cases and controls
N=418
Variable Number Mean weight
change(kg)(SD) t-test df P-value Cases
Controls
209
209
4.06(3.05)
0.06(0.51)
18.65 416 <0.001
key
SD=Standard deviation.
69 Table 12: Weight gain and class of antipsychotics
N=209
Variable Cases Mean wt
gain(SD) t-test df P-value
Atypical Typical
Total
32 177
209
7.4(2.43) 3.4(2.7)
7.59 207 <0.001
Key
Wt= Weight.
70 Table 13: Change in BMI for cases and controls
N=418
Variable mean SD t-test df P-value
Cases BMI 1
BMI 2
22.03 23.63
3.43 3.78
-14.2 208 <0.001
Controls BMI 1 BMI 2
21.70 21.72
2.21 2.20
-1.56 208 0.119
Key
BMI = Body mass index.
BMI 1=Initial body mass index BMI 2=Final body mass index
71 Table 14: Class of antipsychotic and hyperglycaemia
N=209
Variable
Normoglycaemia Hyperglycaemia
total x2 df p n=183
frequency (%)
n=26 frequency
(%)
Class of
Antipsychotic Atypical
Typical
27 (84.4) 156(88.1)
5 (15.6) 21(11.9)
32 0.35 177
1 0.36
72 Table 15: Individual antipsychotics and blood sugar (mmol/L) N=209
Variabless Cases Mean
FBS1 (SD)
Mean Fbs2 (SD)
Mean Change (SD)
F df… P
Clozapine 14 3.90
(0.2) 5.57
(0.83) 1.60
(0.90) 2.76 197 0.002
Chlopromazine 28 4.27
(0.3) 5.61
(0.64) 1.34 (0.78) Chlopromazine,Fluphenaz 2 4.20
(0.2) 6.05
(0.07) 1.85 (0.21)
Haloperidol 80 4.24
(0.3)
5.25 (0.63)
1.00 (0.61) Haloperidol, Flupenthixol 2 4.15
(0.2) 5.25
(0.49) 1.10 (0.28) Haloperidol,Fluphenazine 9 4.06
(0.3) 4.97
(0.66) 0,91 (0.47)
Thioridazine 3 4.16
(0.3) 5.20
(0.36) 1.03 (0.70)
Fluphenazine 5 4.36
(0.2) 5.14
(0.34) 0.78 (0.22)
Olanzapine 10 4.45
(0.37) 5.63
(0.86) 1.18 (0.94)
Risperidone 8 4.21
(0.22) 5.36
(1.10) 1.15 (1.09) Trifluperazine,fluphenazi 2 4.15
(0.77) 5.90
(0.42) 1.75 (1.20)
Trifluperazine 46 4.22
(0.36)
4.99 (0.43)
0.78 (0.44)
TOTAL 209 4.22
(0.36) 5.28
(0.67) 1.06 (0.69)
73 Chapter six
Discussion
Studies done in the developed world showed a relationship between the use of antipsychotic medication, hyperglycaemia and weight gain. This study revealed that, the fasting blood sugar level among the cases was significantly elevated after four months of receiving antipsychotics in contrast with those of the controls. The prevalence of hyperglycaemia among the cases was 12.4%, prevalence of impaired fasting glucose was 9.6%, while the prevalence of diabetes mellitus was 2.8%. Within the study period, none of the controls developed hyperglyceamia.
In addition, this study showed no statistically significant association, between hyperglycaemia and the class of antipsychotic medication, but it showed a statistically significant correlation between the dose of antipsychotic in chlopromazine equivalent and change in fasting blood sugar levels. Also, atypical antipsychotics were significantly associated with weight gain compared with the typical antipsychotics.
Furthermore, there was a difference in the incidence of weight gain among patients with schizophrenia using antipsychotic medications and their controls, and a correlation between weight gain and change in fasting blood sugar level. There was however no association between gender and weight gain.
74 6.1 Socio-demographic characteristics of the sample.
The sample in this study had almost equal males (53.6%) and females (46.4%) This finding is at variance with previous studies (Mackin, Watkinson, and Young, 2005; Taylor, Young, Esop et al, 2004), which had more males than females in their sample.
The mean age (about 28years) for cases in this study was significantly different from that of the controls, and was lower than the mean age in two other studies ( Mackin, Watkinson and Young, 2005; Taylor, Young and Esop, 2004).
The studies did not use patients newly diagnosed with schizophrenia like in this study, but used patients with long standing schizophrenia. This may explain the higher mean age they reported. Furthermore, the finding in this study is a reflection of the usual age of onset of schizophrenia reported to be between 15-45 years (Postgraduate Psychiatry, 2001).
This study found that compared with the controls, the cases are significantly more likely to be unemployed. This is similar to the finding in previous studies (Hollingshead and Redlich, 1958; Goldberg and Morrison, 1963; Castle, Scott and Wessley, 1993; Makanjuola, Adeponle and Obembe, 2005). These studies report that schizophrenia is commoner in the lowest socioeconomic groups.
In this study, about 31 percent of the cases were students. This is slightly lower than what was reported (38 percent) in an Ilorin study which was measuring the quality of life of patients with schizophrenia (Makanjuola, Adeponle and Obembe, 2005). In addition only about 30 percent of the cases in
75 this study were married which was lower than the value (about 40 percent) reported in the Ilorin study mentioned above. These differences are probably due to the fact that the Ilorin study was on a cohort of patients with schizophrenia who had an illness duration of two or more years, most of whom were well and likely fully rehabilitated at the time of the study, have returned to their usual activities (including schooling) prior to the onset of the illness, and therefore are more likely to be married than the cases in this Enugu study, that at the time of study were ill, and thus less likely to be suitable for marriage.
6.2 Association between the use of antipsychotic agents and