Department of Pharmacy, Mbarara University of Science and Technology, Mbarara, Uganda.
Department of Pharmacy, Ambo University, Ambo, Ethiopia.
Clin Interv Aging. 2022 Feb 25;17:195-210. doi: 10.2147/CIA.S350500. eCollection 2022.
Adverse drug reactions (ADR) detection and prediction methods in hospitalized older adults remain imprecise. The identification of the risk factors for ADRs in this group of patients is crucial to develop plausible prediction models.
This study aimed at developing and validating a "Prediction of ADR in Older Inpatients (PADROI)" risk assessment tool in hospitalized older adults.
We had previously conducted a derivational study that aimed to determine the risk factors of ADRs in hospitalized older adults. We developed the PADROI model as a potential ADR risk assessment tool incorporating 8 predictors each given a score by rounding off the respective adjusted odds ratios (AORs) to the nearest whole number. Subsequently, we conducted another prospective cohort among adults aged 60 years and older admitted to Gynecology and Obstetrics, Medical, Oncology, Surgery, and Psychiatry wards at Mbarara Regional Referral Hospital (MRRH) from July 5 to September 17, 2021.
A total of 124 participants, 70 females and 54 males aged 60-95 years, were included in this validation cohort; 62 of them experienced 90 ADRs. When applied to the derivational cohort, the area under receiver operating characteristic curve (AUROC) for the PADROI model was shown to be 0.896 (0.869-0.923; at 95% CI). In the validation study, AUROC of PADROI was 0.917 (0.864-0.971 at 95% CI; p < 0.001). Overall, PADROI correctly predicted 91.7% of those who experienced an ADR.
Using the adjusted odds ratios from our derivational cohort, we developed an ADR prediction tool (PADROI) that achieved an excellent AUROC (0.917), high sensitivity (87.1%) and specificity (90.3%). The current model demonstrated a high potential for clinical applicability which can be strengthened if similar results are reproduced in larger and multi-centered studies.
老年人住院期间不良反应(ADR)的检测和预测方法仍不够精确。确定该人群中 ADR 的危险因素对于建立合理的预测模型至关重要。
本研究旨在开发和验证一种用于住院老年患者的“预测老年住院患者 ADR(PADROI)”风险评估工具。
我们之前进行了一项衍生研究,旨在确定住院老年患者 ADR 的危险因素。我们开发了 PADROI 模型,作为一种潜在的 ADR 风险评估工具,纳入了 8 个预测因子,每个预测因子的分数通过将各自的调整后比值比(AOR)四舍五入到最接近的整数来确定。随后,我们于 2021 年 7 月 5 日至 9 月 17 日,在姆巴拉拉地区转诊医院(MRRH)的妇产科、内科、肿瘤、外科和精神病科,对年龄在 60 岁及以上的成年人进行了另一项前瞻性队列研究。
共有 124 名参与者,年龄 60-95 岁,其中 70 名女性和 54 名男性,纳入了验证队列;其中 62 名发生了 90 例 ADR。当应用于衍生队列时,PADROI 模型的接受者操作特征曲线(AUROC)面积为 0.896(0.869-0.923;95%CI)。在验证研究中,PADROI 的 AUROC 为 0.917(95%CI 为 0.864-0.971,p<0.001)。总体而言,PADROI 正确预测了 91.7%发生 ADR 的患者。
使用我们的衍生队列中的调整后比值比,我们开发了一种 ADR 预测工具(PADROI),其 AUROC(0.917)、高灵敏度(87.1%)和特异性(90.3%)均表现出色。如果在更大和多中心的研究中复制类似的结果,当前模型将具有很高的临床适用性潜力。