Optimal values exploration for responsiveness rates in stable and unstable schizophrenic patients

Maher A J. Alasasleh, Raafat Hani Aburumman, Arafat Khalaf Alzoubi, Hala Abdel Hamid Al Najada, Mohammad Wa'el Hindeyeh
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Abstract

Background: Schizophrenia leads to multifunctional disability, characterized by cognitive and social impairments, everyday skill and self-assessment difficulties, and negative symptoms. Long-term clinical stability, often achieved with antipsychotics, improves everyday functioning. Aim: The goal is to determine to determine the efficacy of different antipsychotic classes (%Prob of APDs' Resp) and adherence rates, as measured by the Behavioural Adherence Rating Scale (BARS). Methods: The study focuses on schizophrenia-spectrum disorders in adults and elderly psychiatric patients, using established diagnostic systems. The observational and retrospective study will be conducted at the Princess Aisha Bint Al Hussein Medical Centre from January 2021 to January 2023. The study will use positive and negative symptom domains to measure initial severity and assess ideal values for antipsychotic drugs. A Chi Square test will be used to analyze distribution rates and odds ratios. The study will use SPSS version 25 with a 5% significance level. Results: The binary logistic regression model was created using patient adherence patterns evaluated using BARS. The model aimed to predict positive responsiveness (Δ PANSS≥20%) and negative responsiveness (Δ PANSS<20%) using patient data. The model accurately identified 94.4% of cases, with a chi-square value of 4.412 and a p-value of 0.818. BARS testing revealed a probable range of APDs' reaction from 64.4% to 88.2%, with individuals determining this range. The study suggests that the specific range may be different depending on the Cox & Snell R2 or Nagelkerke R2 procedures used, but all factors should be considered. The model's accuracy is significant, and the findings suggest that individuals are responsible for determining this range. Conclusion: The study reveals that psychotic individuals require 68.5% adherence for optimal responsiveness. Adding LAIAP to oral APDs enhances responsiveness.
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探索稳定型和不稳定型精神分裂症患者反应率的最佳值
背景:精神分裂症会导致多种功能障碍,主要表现为认知和社交障碍、日常技能和自我评估困难以及阴性症状。抗精神病药物通常可实现长期临床稳定,从而改善日常功能。目的:旨在确定不同类别抗精神病药物的疗效(APDs应答百分比)和依从率,依从率以行为依从性评定量表(BARS)来衡量。研究方法研究重点是成人和老年精神病患者中的精神分裂症谱系障碍,采用已建立的诊断系统。这项观察性和回顾性研究将于 2021 年 1 月至 2023 年 1 月在艾莎-宾特-侯赛因公主医疗中心进行。研究将使用阳性和阴性症状域来衡量初始严重程度,并评估抗精神病药物的理想值。将使用Chi Square检验分析分布率和几率比。研究将使用 SPSS 25 版本,显著性水平为 5%。研究结果二元逻辑回归模型是利用 BARS 评估的患者依从性模式建立的。该模型旨在利用患者数据预测阳性反应性(Δ PANSS≥20%)和阴性反应性(Δ PANSS<20%)。该模型准确识别了 94.4% 的病例,卡方值为 4.412,P 值为 0.818。BARS 测试显示,APDs 反应的可能范围为 64.4% 至 88.2%,这一范围由个体决定。研究表明,根据所使用的 Cox & Snell R2 或 Nagelkerke R2 程序,具体范围可能有所不同,但所有因素都应考虑在内。该模型的准确性很高,研究结果表明,个人对确定这一范围负有责任。结论研究显示,精神病患者需要 68.5% 的依从性才能获得最佳反应。在口服 APD 的基础上添加 LAIAP 可提高反应性。
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