Global Trigger Tool: Proficient Adverse Drug Reaction Autodetection Method in Critical Care Patient Units

Pandya, Amee; Patel, Kalan; Rana, Devang; Gupta, Sapna; Malhotra, Supriya D.; Patel, Pankaj

doi:10.5005/jp-journals-10071-23367

Cited by 14 publications

(5 citation statements)

References 16 publications

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“…The use of sedation has a PPV of 0.67 this may be due to the administration of sedation used as a response to the occurrence of insomnia side effects after antimicrobial administration. Another study conducted by previous researchers also showed that the increase in BUN (Blood Urea Nitrogen), the use of antiemetics (Naessens, et al, 2010) and antihistamines (Pandya et al, 2020) were also sensitive enough to detect ADR.…”

Section: Kusumawardani Maria and Amartamentioning

confidence: 86%

Adverse drug reactions evaluation of antimicrobials in COVID-19 inpatients using Modified Trigger Tool and Naranjo Algorithm

Kusumawardani,

Maria,

Amarta

2023

Pharm Educ

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Background: The use of antimicrobials in COVID-19 treatment might increase the risk of adverse drug reactions (ADR). Therefore, the adverse effect further identification was needed to understand the safety profile of using these medicines. Objective: The research aims to evaluate the adverse effects of the use of COVID-19 antimicrobial agents, causality analysis, and factors related to this ADR. Method: Cross-sectional study using random sampling was conducted to obtain the data. The study used samples from COVID-19 adult inpatients in a hospital located in Java from July-December 2020. Adverse events (AE) were detected by a modified trigger tool using medication and laboratory result module triggers with 21 total triggers. Causality analysis of ADR was conducted using Naranjo Scale. Result: Of the 107 patients examined in this study, 92 patients had triggers. A total of 274 adverse events were found, where 265 adverse events were detected using the trigger tool, and 9 adverse events were detected without the trigger tool. The results of the ADR analysis using the Naranjo algorithm were obtained from as many as 126 ADRs in 60 patients with possible (94.4%) and probable (5.6%) scoring. The most common antimicrobials that cause ADR were azithromycin and oseltamivir. The most effective trigger in detecting ADR was the use of sedation with a positive predictive value of 0.67. The statistical analysis results showed no relationship between gender, age, comorbidities, severity, and body mass index on the incidence of ADR (p>0.05). Conclusion: Adverse drug reactions were commonly found in the use of azithromycin and oseltamivir for COVID-19 patients, so it is necessary to consider the choice of this therapy. The trigger tool and Naranjo algorithm were adequate to help the ADR monitoring process.

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Section: Kusumawardani Maria and Amartamentioning

confidence: 86%

Adverse drug reactions evaluation of antimicrobials in COVID-19 inpatients using Modified Trigger Tool and Naranjo Algorithm

Kusumawardani,

Maria,

Amarta

2023

Pharm Educ

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“…In the present study, we found a low performance of triggers such as "antiemetic administration" and "increased blood urea nitrogen or serum creatinine" to cause harm. Silva et al (2018) and Patel et al (2020) identified antiemetic administration as the most frequent trigger in human patients that are hospitalized. However, antiemetic administration presented the lowest performance compared with the other triggers due to the large number of false-positive cases, corroborated by our findings (Silva et al, 2018;Patel et al, 2020).…”

Section: Discussionmentioning

confidence: 99%

“…Silva et al (2018) and Patel et al (2020) identified antiemetic administration as the most frequent trigger in human patients that are hospitalized. However, antiemetic administration presented the lowest performance compared with the other triggers due to the large number of false-positive cases, corroborated by our findings (Silva et al, 2018;Patel et al, 2020). Furthermore, in another study conducted in humans, Brenner et al (2012) evaluated abnormal laboratory parameters as triggers for the detection of ADEs in outpatients.…”

Section: Discussionmentioning

confidence: 99%

Use of trigger tool to identify Adverse Drugs Events in dogs.

Fonseca

Forgerini

Zorzin³

et al. 2020

Braz. J. Vet. Med.

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“…Pandya and Patel et al [8] have taken the advantage of Electronic Health Records (EHR) where numerous clinical narratives and notes are written by physicians, nurses, and even by the patients themselves to generate new TTs. Using statistical correlation approaches, the authors have identified new TTs.…”

Section: Related Workmentioning

confidence: 99%

“…The literature on ADR extraction showed a high dependency on the trigger terms utilization within the ADR detection task [7,8]. The utilization of trigger terms represents different challenging issues.…”

Section: Introductionmentioning

confidence: 99%

Utilizing Word Index Approach with LSTM Architecture for Extracting Adverse Drug Reaction from Medical Reviews

Alshaikhdeeb,

Cheah

2023

JAIT

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Adverse Drug Reaction (ADR) detection from social reviews refers to the task of exploring medical online stores and social reviews for extracting any mention of abnormal reactions that occur after consuming a particular medical product by the consumers themselves. A variety of approaches have been used for extracting ADR from social/medical reviews. These approaches include machine learning, dictionary-based and statistical approaches. Yet, these approaches showed either a high dependency on using an external knowledge source for ADR detection or relying on domain-dependent mechanisms that might lose contextual information. This study aims to propose word sequencing with Long Short-Term Memory (LSTM) architecture. A benchmark dataset of MedSyn has been used in the experiments. Then, a word indexing, mapping, and padding method have been used to represent the words within the reviews as fixed sequences. Such sequences have been fed into the LSTM consequentially. Experimental results showed that the proposed LSTM could achieve an F1 score of up to 92%. Comparing such a finding to the baseline studies reveals the superiority of LSTM. The demonstration of the efficacy of the proposed method has taken different forms including the examination of word indexing with different classifiers, the examination of different features with LSTM, and through the comparison against the baseline studies.

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Global Trigger Tool: Proficient Adverse Drug Reaction Autodetection Method in Critical Care Patient Units

Cited by 14 publications

References 16 publications

Adverse drug reactions evaluation of antimicrobials in COVID-19 inpatients using Modified Trigger Tool and Naranjo Algorithm

Adverse drug reactions evaluation of antimicrobials in COVID-19 inpatients using Modified Trigger Tool and Naranjo Algorithm

Use of trigger tool to identify Adverse Drugs Events in dogs.

Utilizing Word Index Approach with LSTM Architecture for Extracting Adverse Drug Reaction from Medical Reviews

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