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Neutrophil/lymphocyte and platelet/lymphocyte ratios as potential markers of disease activity in patients with Ankylosing spondylitis: a case-control study
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Abstract<sec> <title>Background

The neutrophil/ lymphocyte ratio (NLR) and platelet/lymphocyte ratio (PLR) have the potential to be inflammatory markers that reflect the activity of many inflammatory diseases. The aim of this study was to evaluate the NLR and PLR as potential markers of disease activity in patients with ankylosing spondylitis.

Methods

The study involved 132 patients with ankylosing spondylitis and 81 healthy controls matched in terms of age and gender. Their sociodemographic data, disease activity scores using the Bath Ankylosing Spondylitis Disease Activity Index (BASDAI), erythrocyte sedimentation rate (ESR), and white blood cell, neutrophil, lymphocyte and platelet counts were recorded. The patients with ankylosing spondylitis were further divided according to their BASDAI scores into patients with inactive disease (BASDAI < 4) and patients with active disease (BASDAI ≥4). The correlations between the NLR, PLR and disease activity were analysed.

Results

There was a statistically significant difference in the NLR and PLR between the active and inactive ankylosing spondylitis patients (2.31 ± 1.23 vs. 1.77 ± 0.73, p = 0.002), (142.04 ± 70.98 vs. 119.24 ± 32.49, p <  0.001, respectively). However, there was no significant difference in both the NLR and PLR between the healthy control group and ankylosing spondylitis patients (p > 0.05). In addition, the PLR was significantly higher in both the active and inactive groups compared to those in the healthy control group (142.04 ± 70.98 vs. 99.32 ± 33.97, p = 0.014), (119.24 ± 32.49 vs. 99.32 ± 33.97, p = 0.019). The BASDAI scores were positively correlated with the PLR (r = 0.219, p = 0.012) and the NLR, but they were not statistically significant with the later (r = 0.170, p = 0.051). Based on the ROC curve, the best NLR cut-off value for predicting severe disease activity in ankylosing spondylitis patients was 1.66, with a sensitivity of 61.8% and a specificity of 50.6%, whereas the best PLR cut-off value was 95.9, with a sensitivity of 70.9% and a specificity of 55.5%.

Conclusion

The PLR may be used as a useful marker in the assessment and monitoring of disease activity in AS together with acute phase reactants such as the ESR.

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Diagnosis of Diabetes Using Artificial Intelligence Programs
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Scientific development has occupied a prominent place in the field of diagnosis, far from traditional procedures. Scientific progress and the development of cities have imposed diseases that have spread due to this development, perhaps the most prominent of which is diabetes for accurate diagnosis without examining blood samples and using image analysis by comparing two images of the affected person for no less than a period. Less than ten years ago they used artificial intelligence programs to analyze and prove the validity of this study by collecting samples of infected people and healthy people using one of the Python program libraries, which is (Open-CV) specialized in measuring changes to the human face, through which we can infer the

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