Interações medicamentosas potenciais em prescrições de pacientes da unidade de infectologia de um hospital universitário / Potential drug interactions in patients’ prescriptions in the infectious disease unit of a university hospital

Benetti, Jorge Luiz; Benetti, Camila; Rodrigues, Alexia Ferreira; Aguiar, João Eduardo Andrade Tavares de; Carvalho, Marcos Antônio Lima; Sousa, Mariana Cunha de; Silva, Wellington Barros da; Silva, Ângela Maria da

doi:10.34119/bjhrv4n3-118

Cited by 1 publication

(2 citation statements)

References 8 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Many patients with infectious diseases use polypharmacy, including complex antibiotic, antiretroviral and antifungal regimens. In addition, they may have comorbidities, making treatment even more difficult 19 . Factors such as polypharmacy can increase the risk of harm to these patients 20…”

Section: Introductionmentioning

confidence: 99%

“…In addition, they may have comorbidities, making treatment even more difficult. 19 Factors such as polypharmacy can increase the risk of harm to these patients. 20 An instrument to assess drug-related outcome was developed in a Brazilian tertiary-level, high-complexity general hospital, with the objective of prioritizing hospitalized patients for clinical pharmacy intervention, classifying them as high, moderate and low risk.…”

mentioning

confidence: 99%

See 1 more Smart Citation

Fully independent validation and updating of a clinical pharmacy prioritizing risk score in an infectious disease hospital ward

Barreto

Rezende

Santos

et al. 2022

Brit J Clinical Pharma

View full text Add to dashboard Cite

The aim of this study was to validate and update the risk score originally developed at Hospital de Clínicas de Porto Alegre, verifying its performance in an infectious disease population.Methods: This is an observational study with consecutive selection of admission in a ward of participants with infectious diseases. Predictors were age, number of medications, intravenous drugs, potentially dangerous drugs, renal dysfunction, liver dysfunction, use of nasoenteral tube, nasogastric tube, gastrostomy feeding, jejunostomy feeding, oral enteral tube, total parenteral nutrition, cardiac or pulmonary dysfunction and immunosuppression. Outcome was defined as preventable prescription incidents by a clinical pharmacist. A GEE model was fit to make predictions each week. Results: A total of 219 patients participated in the study, 79.25% of whom had prescription incidents in the first week of admission. Predictors of the updated model were number of drugs prescribed, number of intravenous drugs, use of tubes, truncated age at 36 years and week of hospitalization. The performance of the original model was poor. The updated model's discrimination and calibration were moderate (overall AUC 0.74). A calculator to apply the model is available at https://pedrobrasil. shinyapps.io/INDWELL/. Conclusion: The updated risk score enabled the user to make predictions at admission and throughout the weeks, allowing for a prioritized weekly update for clinical pharmacy intervention. The updated model has a moderate and satisfactory performance for infectious disease patients. K E Y W O R D S clinical pharmacy service, drug-related side effects and adverse reactions, forecasting, medication errors, risk assessment, risk score 1 | INTRODUCTION Medication errors can be defined as any preventable event that can cause or lead to medication misuse or harm to the patient while theThe authors confirm that the Principal Investigator for this paper is Pedro Emmanuel Alvarenga Americano do Brasil and that he has direct clinical responsibility for patients.

show abstract

Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%