Introduction. The CGI-S score is an essential tool used in the evaluation of the severity of schizophrenia symptoms. It provides an objective and standardized measure of symptom severity that can be used to monitor treatment response and guide clinical decision-making. The CGI-S score alone may not provide sufficient information regarding the underlying factors contributing to the patient’s clinical presentation. Additionally, exploring the correlation between CGI-S score and other variables, such as sociodemographic and medical history factors, treatment history and other scales (PANNS, GAF, LUNSERS, SWN) can help clinicians better understand the factors that contribute to symptom severity and identify strategies to optimize treatment outcomes for patients with schizophrenia. Method. This study was conducted between 01.10.2009 – 01.10.2012, at the Clinical Hospital of Psychiatry Al. Obregia, Bucharest, Romania, on 110 patients, each of whom received a CGI-severity score at 7-day intervals. Excluding the small number of patients with a CGI-S score of 6 (6 out of 110), the study results are presented for 104 patients, divided into three categories based on the CGI-Severity score, respectively CGI-S 3,4, and 5. Descriptive analysis was performed on the subjects, and the ANOVA Tukey analysis was utilized to determine any significant correlation between the CGI-S score and other factors that could impact it. Results. We included 104 patients in our study, of whom 18.3% (n=19), 51.9% (n=54), and 29.8% (n=31) had a CGI-Severity score of 3, 4, and 5 points, respectively. Among them, 59.6% were female (n=62) and 40.4% were male (n=42), with a mean age of 40.19 (SD 10.35). We could not identify a statistically significant association between the CGI-S score and sociodemographic or medical history factors. However, we observed a significant negative association between the CGI-S score and the GAF and PANSS scales, with a p<0.006. We also found a significant association between CGI-S score and the level of medication procurement accessibility, with a p-value of 0.039 and a 95% CI (-1.65 to 0.04) between CGI-S scores of 3 and 4. Among other predictive factors for the CGI-S score, we identified the presence of adverse effects measured using the LUNSERS scale (in terms of extrapyramidal and psychic adverse effects) and a significant association between the CGI-S score and the Subjective Well-Being Under Neuroleptics scale (in terms of physical function, self-control, and social integration; SWN), with a p<0.05. Conclusion. It is important to correlate the CGI-S scale in schizophrenia with other scales such as PANSS, GAF, SWN, LUNSERS, illness history, and the patient’s treatment history because this provides a more comprehensive understanding of the patient’s symptoms, level of functioning, and response to treatment. By using multiple scales and considering various aspects of the patient’s illness, clinicians can make more informed decisions about the most appropriate treatment approach and monitor the patient’s progress over time. This can ultimately lead to better outcomes for patients with schizophrenia.
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