巴基斯坦南部地区长期非传染性疾病对接受放射影像学检查的新型冠状病毒肺炎住院患者的影响

Impact of Long-Term Non-Communicable Diseases on SARS-COV-2 Hospitalized Patients Supported by Radiological Imaging in Southern Pakistan.

作者信息

Qureshi Ali, Syed Sulaiman Syed Azhar, Rajpoot Pushp Lata, Mohammed Sahli Maryam, Kumar Narendar, Bhurgri Shireen, Daud Nur Aizati Athirah

机构信息

Discipline of Clinical Pharmacy, School of Pharmaceutical Sciences, Universiti Sains Malaysia, Penang, MYS.

Department of Health Education and Promotion, College of Public Health Education and Tropical Medicine, Jazan University, Jazan, SAU.

出版信息

Cureus. 2024 Aug 18;16(8):e67110. doi: 10.7759/cureus.67110. eCollection 2024 Aug.

Abstract

COVID-19 patients with already existing chronic medical conditions are more likely to develop severe complications and, ultimately, a higher risk of mortality. This study analyzes the impacts of pre-existing chronic illnesses such as diabetes (DM), hypertension, and cardiovascular diseases (CVDs) on COVID-19 cases by using radiological chest imaging. The data of laboratory-confirmed COVID-19-infected hospitalized patients were analyzed from March 2020 to December 2020. Chest X-ray images were included to further identify the differences in X-ray patterns of patients with co-morbid conditions and without any co-morbidity. The Pearson chi-square test checks the significance of the association between co-morbidities and mortality. The magnitude and dimension of the association were calibrated by the odds ratio (OR) at a 95% confidence interval (95% CI) over the patients' status (mortality and discharged cases). A univariate binary logistic regression model was applied to examine the impact of co-morbidities on death cases independently. A multivariate binary logistic regression model was applied for the adjusted effects of possible confounders. For the sensitivity analysis of the model, receiver operating characteristic (ROC) was applied. Patients with different comorbidities, including diabetes (OR = 33.4, 95% CI: 20.31-54.78, p < 0.001), cardiovascular conditions (OR = 24.14, 95% CI: 10.18-57.73, p < 0.001), and hypertension (OR = 16.9, 95% CI: 10.20-27.33, p < 0.001), showed strong and significant associations. The opacities present in various zones of the lungs clearly show that COVID-19 patients with chronic illnesses such as diabetes, hypertension, cardiovascular disease, and obesity experience significantly worse outcomes, as evidenced by chest X-rays showing increased pneumonia and deterioration. Therefore, stringent precautions and a global public health campaign are crucial to reducing mortality in these high-risk groups.

摘要

已有慢性疾病的新冠病毒肺炎患者更有可能出现严重并发症,最终死亡风险更高。本研究通过胸部影像学分析糖尿病(DM)、高血压和心血管疾病(CVD)等既有慢性疾病对新冠病毒肺炎病例的影响。分析了2020年3月至2020年12月实验室确诊的新冠病毒肺炎住院患者的数据。纳入胸部X光图像以进一步识别合并症患者和无合并症患者的X光模式差异。Pearson卡方检验用于检验合并症与死亡率之间关联的显著性。关联的大小和维度通过患者状态(死亡率和出院病例)在95%置信区间(95%CI)的比值比(OR)进行校准。应用单变量二元逻辑回归模型独立检验合并症对死亡病例的影响。应用多变量二元逻辑回归模型分析可能混杂因素的调整效应。为进行模型的敏感性分析,应用了受试者工作特征(ROC)曲线。患有不同合并症的患者,包括糖尿病(OR = 33.4,95%CI:20.31 - 54.78,p < 0.001)、心血管疾病(OR = 24.14,95%CI:10.18 - 57.73,p < 0.001)和高血压(OR = 16.9,95%CI:10.20 - 27.33,p < 0.001),显示出强烈且显著的关联。肺部不同区域出现的opacity(此处未明确其准确中文术语,暂保留英文)清楚表明,患有糖尿病、高血压、心血管疾病和肥胖等慢性疾病的新冠病毒肺炎患者预后明显更差,胸部X光显示肺炎增加和病情恶化即为证据。因此,严格的预防措施和全球公共卫生运动对于降低这些高危人群的死亡率至关重要。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3029/11406398/e4498ae85908/cureus-0016-00000067110-i01.jpg

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