Prevalence, Incidence, and Characteristics of Adverse Drug Reactions Among Older Adults Hospitalized at Mbarara Regional Referral Hospital, Uganda: A Prospective Cohort Study

Yadesa, Tadele Mekuriya; Kitutu, Freddy Eric; Tamukong, Robert; Alele, Paul E.

doi:10.2147/cia.s332251

Cited by 8 publications

(9 citation statements)

References 47 publications

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“…Consistent with previous studies, the proportion of hospital-acquired ADR was higher in patients aged 60–75 years compared with those older than 75; 41 , 42 , 48 , 49 among those who were hospitalized for 11 and more days, in patients with a history of an ADR in the previous one year, 17 , 50 in those with a renal disease, 18 , 22 , 30 in patients with heart failure 17 , 18 , 51 and those with a CCI ≥6, 17 , 18 , 48 in older patients that took at least one PIM 18 , 30 and those on polypharmacy 10 , 22 , 45 , 50 compared with their controls.…”

Section: Discussionsupporting

confidence: 87%

“…Details of the results were published elsewhere. 22 In the current validation study, we aimed at developing a potential ADR-risk assessment tool from the data set of the derivational study, and then to validate it in a separate follow-on prospective observational study. The data on the 19 independent variables were extracted and were assessed for assumptions of logistic regressionand subjected to multivariable logistic regression.…”

Section: Methodsmentioning

confidence: 99%

“…The sample size for this validation study was calculated using MedCalc ® Software Version 19.2 (©1993–2020), that employed the standard formula for sample size determination for ROC studies. 23 Taking a power of 90% and Type I error of 0.01, null hypothesis AUROC (the best available AUROC in older inpatients) of 0.74, 10 and a target AUROC of 0.896 obtained from derivational cohort of the current project, 22 48 positive cases (patients with ADR) and 48 negative cases (patients without ADR) are required for this ROC study. By adding 25% for potential drop-outs, 60 positive cases and 60 negative cases, totaling 120 patients, who are 60 years and older were required.…”

Section: Methodsmentioning

confidence: 99%

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Development and Validation of ‘Prediction of Adverse Drug Reactions in Older Inpatients (PADROI)’ Risk Assessment Tool

Yadesa¹,

Kitutu²,

Tamukong³

et al. 2022

CIA

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Background 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. Objective This study aimed at developing and validating a “Prediction of ADR in Older Inpatients (PADROI)” risk assessment tool in hospitalized older adults. Methods and Materials 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. Results 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. Conclusion 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.

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Section: Discussionsupporting

confidence: 87%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

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Development and Validation of ‘Prediction of Adverse Drug Reactions in Older Inpatients (PADROI)’ Risk Assessment Tool

Yadesa¹,

Kitutu²,

Tamukong³

et al. 2022

CIA

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“…Being an interventional study design also allowed the investigators to avoid medications with potential DDIs whenever possible. The current high proportion of moderate to major drug-drug interactions among cancer patients requires more emphasis to prevent ADEs due to drug interactions in addition to high ADR risk associated with the antineoplastic agents [ 12 , 33 , 34 ], in the bid to assure patient safety.…”

Section: Discussionmentioning

confidence: 99%

Frequency, severity, and factors associated with clinically significant drug-drug interactions among patients with cancer attending Mbarara Regional Referral Hospital Cancer Unit, Uganda

et al. 2022

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Background Cancer is a major public health problem with pharmacotherapy being the cornerstone of its management. Cancer patients receive multiple drugs concurrently risking Drug-Drug Interactions (DDIs). DDIs, though avoidable, can significantly contribute to morbidity, mortality, and increased healthcare costs in this population of patients. Currently, there is no published study from Uganda on clinically significant DDIs (cs-DDIs) among cancer patients. This study identifies frequency, severity, and factors associated with cs-DDIs at Mbarara Regional Referral Hospital Cancer Unit (MRRHCU). Method A cross-sectional study was conducted among 300 cancer patients receiving chemotherapy from a tertiary care hospital in western Uganda from January–February 2022. A questionnaire and data collection form were used to collect patient data. Lexicomp® Drug interaction software was used to screen the patient drug information for DDIs and assess their severity. Predictors of DDIs were identified using logistic regression using SPSS (Statistical Package for Social Sciences). Result Three hundred participants were enrolled with a mean age of 48 ± 23.3 years. One hundred eighty-one patients experienced 495 cs-DDIs; with a mean of 1.7 ± 2.2. The prevalence of cs-DDI was 60.3% (55.0-66.0% at 95% CI). Digestive organ neoplasms were the most commonly (80, 26.7%) diagnosed category, and ‘plant alkaloids and other natural products were the most frequently (143, 47.7%) used chemotherapeutic drug classes. About three-quarters of cs-DDIs were rated as category C risk (367, 74.1%) whereas over two-thirds (355, 71.7%) were moderate in severity.. Being female (aOR = 2.43 [1.23–4.48 at 95% CI]; P-value = 0.011) and use of ≥ 6 drugs concurrently (aOR = 18.82 [9.58–36.95 at 95% CI]; P-value < 0.001)) were significantly associated with cs-DDIs. Conclusion More than half of the participants experienced at-least one cs-DDI which is generally higher than what was reported in high-income settings. About three-quarters were category C and moderate in severity, and require enhanced monitoring for safety and treatment outcome. Being female and using ≥ 6 drugs were significantly associated with cs-DDIs.

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“…The rating of the causal relationship of an ADR and the suspected medication was done using the Naranjo ADR assessment scale [ 39 ], and all possible, probable and definite ADRs were considered. The definition of specific ADRs as well as their severity and clinical outcomes were published elsewhere [ 40 ].…”

Section: Methodsmentioning

confidence: 99%

Predictors of hospital-acquired adverse drug reactions: a cohort of Ugandan older adults

et al. 2022

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Background Globally, it is estimated that the number of older adults will become 2 billion by 2050. The identification of the predictors of adverse drug reaction (ADR) in hospitalized older patients is crucial to the development of prediction tools and preventive strategies to mitigate the burden of ADRs. This study aimed to determine the predictors of hospital-acquired ADR occurrence among hospitalized older adults in a low-income country. Methods We conducted a prospective cohort of older adults admitted to medical, oncology, and surgery wards at Mbarara Regional Referral Hospital (MRRH) for a consecutive 6 months where each patient was followed up daily from admission to discharge. We used Edwards and Aronson’s definition of ADR and the Naranjo ADR Causality Scale. We employed Beer’s criteria and Lexicomp to determine potentially inappropriate medications, and drug interactions, respectively. We conducted univariate and multivariable logistic regression using Statistical Package for the Social Science (SPSS) Version 23.0. Results Out of 523 participants with median (Inter Quartile Range) age of 67 (62–76) years, 256 (48.9%) experienced at least one ADR. Independent predictors of occurrence of hospital acquired ADRs included age of 60–75 (Adjusted odds ratio (AOR) = 1.97, 95% C.I: 1.14–3.41; p value = 0.015) compared to > 75 years, previous ADR in 1 year (AOR = 2.43, 95% C.I: 1.42–4.17; p value = 0.001), potentially inappropriate medication (AOR = 4.56, 95% C.I: 2.70–7.70; p value< 0.001), polypharmacy (AOR = 3.29, 95% C.I: 1.98–5.46; p value< 0.001)), having a Charlison Comorbidity Index (CCI) ≥ 6 (AOR = 8.47, 95% C.I: 4.85–14.99; p value< 0.001), having heart failure (AOR = 2.83, 95% C.I: 1.34–6.02; p value = 0.007) or kidney disease (AOR = 1.95, 95% C.I: 1.05–3.61; p value = 0.034) and a hospital stay > 10 days (AOR = 3.53, 95% C.I: 1.89–6.61; p value< 0.001) compared to < 5 days. Conclusion The current prevalence of ADR is higher than previously reported in high-income countries. Disease-related factors followed by medication-related factors were shown to be the most important predictors of hospital-acquired ADRs. CCI and PIM showed the strongest association with ADR. The predictors of ADRs identified in our study were generally comparable with those reported by previous studies. Plain language title Conditions that predispose older patients to experience harmful effects from their medications while in hospital. Plain language summary Identifying the conditions that predispose older adults to incur harmful effects of their medications helps to plan on how best to predict, take precautions and closely follow up on them and thus, to prevent these undesirable outcomes. This study aimed to identify these conditions which determine which older adults are higher risk to incur these harmful undesirable effects of medicines. Everydayduring their hospital stay, we closely followed older patients who were 60 years and above from their entry to the hospital wards until they left the hospital. We interviewed the participants, reviewed their medication files and we also examined them physically to identify any unwanted and harmful outcome from their current medications. Out of 523 participants, almost half of them experienced at least one harmful or undesired effect related to their medicine. Conditions which predisposed them to experience a harmful effect from their medicines included being in age bracket of 60–75 years, having a history of experiencing harmful outcomes from medicines in the previous 1 year, taking a medication which was listed as potentially inappropriate for older adults, taking 5 or more medications concurrently, having a lower 10 years survival chance, having heart or kidney disease and a hospital stay > 10 days.

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Prevalence, Incidence, and Characteristics of Adverse Drug Reactions Among Older Adults Hospitalized at Mbarara Regional Referral Hospital, Uganda: A Prospective Cohort Study

Cited by 8 publications

References 47 publications

Development and Validation of ‘Prediction of Adverse Drug Reactions in Older Inpatients (PADROI)’ Risk Assessment Tool

Development and Validation of ‘Prediction of Adverse Drug Reactions in Older Inpatients (PADROI)’ Risk Assessment Tool

Frequency, severity, and factors associated with clinically significant drug-drug interactions among patients with cancer attending Mbarara Regional Referral Hospital Cancer Unit, Uganda

Predictors of hospital-acquired adverse drug reactions: a cohort of Ugandan older adults

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