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CPS1494 Senthilvel V. et al.
                The association and mean differences the between variables were found
            by using bi-variate analysis Chi-Square test and t-test.  Out of 123 normal total
            cholesterol patients, 87 (70.7%) patients were not having DR and 36 (29.3%)
            were having DR and in 27 abnormal total cholesterol patients, 24 (88.9%) were
            not having DR and 3 (11.1%) were having DR which was statistically merely
            significant with p=0.05.  except the variables like age, gender, Body Mass Index
            (BMI),  duration  of  Hypertension,  educational  status,  family  history  of  DM,
            smoking  habit,  alcohol  consumption,  duration of  hypertension  which  were
            statistically not significant with p-value > 0.05.  The mean duration of DM and
            mean HbA1C were statistically highly significant with p<0.01. 35 DR patients
            mean FBS was 160.25 ± 55.79 and the mean FBS of 100 non-DR group was
            136.84 ± 44.30 which was statistically significant with p<0.05 and age wasn’t
            statistically significant with p>0.05 as shown in Table – 1. The duration since
            diagnosis of DM was < 10 years in 42.7%, ≥ 10 years in 34.9% and ≥ 15 years
            in 39.3%.  The association between groups (with and no DR) and duration of
            DM were very highly significant with p-value < 0.01 as shown in Figure - 2.

              Figure: 2 Association between groups (with and without DR) and duration of
                                                DM















                We  have  used  Binary  Logistic  Regression  equation  with  backward
            conditional analysis to predict the influencing factor to develop the diabetic
            retinopathy among Type II DM patients.  From binary logistic regression, the
            above  results  were  obtained  and  Hosmer-Lemeshow  test  was  showed  a
            goodness of fit with Chi-Square value was 2.891 and the corresponding p-
            value  was  0.941  which  wasn’t  statistically  significant  with P-value  >
            0.05.  Therefore from this, we have concluded that the Chi-Square value wasn’t
            significant and this was proved the model was a good fit.  ie., the selected
            variables were perfectly fit to that binary logistic regression equation model
            approach.  In  the  backward  elimination  step-3,  we  have  got  HbA1C,  FBS,
            smoking  habit,  intake  of  tablet/insulin,  duration  of  DM  and  duration  of
            hypertension  are  significant  with P-value  <0.05  except  age  and  total
            Cholesterol.  The included variables and their odds ratio, significance and 95%
            Confidence Interval (95% C.I) were as shown in Table – 2.

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