Isabel Vitória Figueiredo’s research while affiliated with University of Coimbra and other places

Objective To identify new articles that describe services provided by pharmacists during the first year of the COVID-19 pandemic. Methods An update scoping review was conducted in MEDLINE, Embase, Scopus, LILACS, and Google Scholar between 21 May 2020 and 31 May 2021. Study selection and data extraction were performed by two independent authors. DEPICT v. 2 was used to characterize the components of pharmacists’ interventions. It was also verified whether the articles evaluated outcomes of care. Key findings A total of 8983 records were identified, of which 120 met the inclusion criteria. The hospital was the workplace of the pharmacist most often described (55%). The majority of articles (73.3%) described the main domains of DEPICT v.2. Pharmacists provided interventions for patients (27.5%), healthcare professionals (25.8%), both (34.2%), individually (84.2%), through face-to-face contact (44.2%), and followed by telephone (41.7%). The main actions included patient counseling (56.7%), drug supply management (42.5%), and drug information for healthcare professionals (40.8%). Less than half of the articles (36.6%) evaluated the dimension “outcomes of care” of the study population. Conclusion Although most of the articles reported the pharmacists’ interventions, the description is still not satisfactory. In addition, the majority of articles focused solely on the dimension “process of care”. Future research should provide more detailed descriptions of the pharmacists’ interventions and assess the effectiveness of their interventions.

Introdução: As doenças cardiovasculares (DCV) são um problema de saúde pública importante a nível mundial, sendo responsáveis por uma elevada taxa de morbilidade e mortalidade. Através da implementação de programas de rastreio e da utilização de algoritmos de previsão de risco de DCV, os farmacêuticos comunitários podem detetar precocemente utentes com risco de DCV. Com o presente estudo pretendeu-se comparar a previsão do risco de DCV através dos algoritmos SCORE e SCORE2 em utentes de uma farmácia comunitária que não se encontravam sob terapêutica cardiovascular. Métodos: Estudo observacional transversal realizado numa farmácia comunitária portuguesa. Procedeu-se ao registo de todos os utentes que entraram na farmácia no período de uma semana, os quais foram posteriormente contactados tendo em vista a participação no estudo. Posteriormente, durante uma entrevista, o farmacêutico registou os dados sociodemográficos, avaliou parâmetros fisiológicos, bioquímicos e determinou o risco cardiovascular dos utentes. Para análise deste estudo foram apenas considerados os utentes que não estavam sob terapêutica cardiovascular. Para a avaliação do SCORE aplicaram-se os fatores de risco idade, sexo, tabagismo, pressão arterial sistólica e colesterol total. Para a avaliação do SCORE2 aplicaram-se os mesmos fatores de risco, mas utilizou-se o colesterol não HDL em vez do colesterol total. Resultados: Dos utentes contactados, 56,4% (n=621) aceitaram o convite para participar no estudo e 53,4% (n=588) efetivamente voltaram à farmácia para a avaliação do seu risco cardiovascular. Dos 588 participantes, 56,6% já estavam sob terapêutica cardiovascular, tendo sido excluídos do estudo. Dos 43,4% (n=255) que não se encontravam sob terapêutica cardiovascular, 94,9% (n=242) apresentavam pelo menos um fator de risco cardiovascular modificável: 18,4% (n=47) tabagismo, 60,4% (n=154) dislipidemia, 53,7% (n=137) excesso de peso, 41,6% (n=106) hipertensão, 21,6% (n=55) glicemia em jejum alterada e 57,7% (n=147) sedentarismo. Aplicaram-se os algoritmos SCORE e SCORE2 aos 150 participantes elegíveis. Da aplicação da escala SCORE, que estima o risco de DCV fatal a 10 anos, 96,0% foram estratificados com risco cardiovascular baixo a moderado, 2,7% risco cardiovascular elevado e 1,3% risco cardiovascular muito elevado. Com a escala SCORE2, que estima o risco de DCV fatal e não fatal a 10 anos, 64,7% apresentavam risco cardiovascular baixo a moderado, 32,0% risco cardiovascular elevado e 3,3% risco cardiovascular muito elevado. Conclusão: O algoritmo SCORE2 proporcionou uma maior discriminação na classificação do risco nas faixas etárias mais baixas, fator importante em rastreios de DCV, permitindo assim assinalar um maior número de utentes que poderão beneficiar de intervenção precoce. Demonstrou-se ainda a viabilidade do rastreio de risco de DCV nas farmácias comunitárias, quer pela elevada percentagem de utentes que aceitaram avaliar o seu risco cardiovascular pelo farmacêutico comunitário, quer pela elevada prevalência de doentes em risco de DCV rastreados.

Purpose To evaluate the impact of the pandemic on the consumption of antidepressive agents in Central Portugal. Methods To estimate the causal effect of the pandemic an interrupted time series analysis was conducted. Data of antidepressant drugs monthly dispensed in community pharmacies between Jan-2010 and Dec-2021 were provided by the regional Health Administration. Anti-Parkinson dopaminergic agents and statins, theoretically not influenced by COVID-19 pandemics, were used as comparator series. The number of packages was converted into defined daily doses and presented as defined daily doses/1000 inhabitants/day. A Bayesian structural time-series model with CausalImpact on R/RStudio was used to predict the counterfactual. Analyses with different geographical granularity (9 sub-regions and 78 municipalities) were performed. Results When compared to counterfactual, regional consumption non-significantly increased after the pandemic declaration, with a relative effect of + 1.30% [95%CI -1.6%:4.2%]. When increasing the granularity, differences appeared between sub-region with significant increases in Baixo Mondego + 6.5% [1.4%:11.0%], Guarda + 4.4% [1.1%:7.7%] or Cova da Beira + 4.1% [0.17%:8.3%], but non-significant variation in the remaining 6 sub-regions. Differences are more obvious at municipality level, ranging from increases of + 37.00% [32.00%:42.00%] to decreases of -11.00% [-17.00%:-4.20%]. Relative impact positively correlated with percentage of elderly in the municipality (r = 0.301; p = 0.007), and negatively with population density (r=-0.243; p = 0.032). No other predicting variables were found. Conclusion Antidepressant consumption suffered very slight variations at regional level after the COVID-19 pandemic declaration. Analysis with higher granularity allowed identifying municipalities with higher impact (increase or decrease). The absence of clear association patterns suggests other causal hypotheses of the differences.

Background Patients often require adjustments to drug doses due to impaired renal function. Glomerular filtration rate (GFR) estimation using various equations can result in discrepancies, potentially leading to different dose adjustment recommendations. Aim To determine the clinical significance of discrepancies observed between different equations used to estimate GFR for drug dose adjustments in a real-world group of patients over 65 years in primary care. Method The Cockcroft–Gault (CG), Modification of Diet in Renal Disease (MDRD), Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI), and Berlin Initiative Study 1 equations were applied to estimate GFR in a group of patients over 65 years old attending a primary care center. Results were compared using Bland–Altman plots, and limits of agreement (LoA) and overall bias were calculated. Regression analyses were conducted to identify the null difference GFR and the slope of differences for each pairwise comparison. Results A total of 1886 patients were analyzed. Differences between patient-adjusted and body surface area (BSA)-normalized versions of the equations were not clinically relevant for dose adjustments, with LoAs below 20 mL/min. However, discrepancies among the original versions of several equations presented LoAs over 30 mL/min. Greater differences were found between CG and MDRD or CKD-EPI equations. Conclusion Clinically relevant differences in GFR estimation were observed among different equations, potentially impacting drug dose adjustments. However, discrepancies were not considered significant when comparing patient-adjusted and BSA-normalized versions of the equations, particularly for patients with BSA close to the average.

Background: Different questionnaires assess self-reported medication adherence and others quantify aspects of patients attitudes towards medication, but not together in a single instrument. Gathering these two aspects in a single instrument could reduce patients survey burden. Aim: The aim of this study was to develop the Medication Adherence Universal Questionnaire (MAUQ) using the Maastricht Utrecht Adherence in Hypertension short version (MUAH-16) factorial structure as the hypothesized model. Method: A multistep process started with the modification of the MUAH-16 to obtain the MAUQ. Patients using at least one antihypertensive medicine were recruited. The two questionnaires, the MUAH-16 and MAUQ, were applied. A confirmatory factor analysis (CFA) was performed using the initial MUAH-16 s-order 4-factor model. An additional bifactor model with four uncorrelated factors and an overall score was tested. The comparative fit index (CFI), root mean square error of approximation (RMSEA) with confidence intervals (CIs), and standardized root mean squared residual (SRMR) were used to assess both models. Results: A sample of 300 hypertensive patients completed the instruments. The CFA with the second-order 4-factor solution resulted in similar results for the MUAH-16 and MAUQ: CFIs of 0.934 and 0.930, RMSEAs of 0.043 [CI 0.030-0.056] and 0.045 [CI 0.031-0.057] and SRMRs of 0.060 and 0.061, respectively. The CFA with the bifactor model showed slightly better results for both the MUAH-16 and MAUQ: CFIs of 0.974 and 0.976, RMSEAs of 0.030 [CI 0.005-0.046] and 0.028 [CI 0.001-0.044], and SRMRs of 0.043 and 0.044, respectively. Conclusion: CFA demonstrated that the MAUQ presented a better fit to both models than the MUAH-16, obtaining a robust universal free instrument to assess medicine-taking behaviour and four medicine beliefs components.

Anticholinergic burden tools have relevant pharmacological gaps that may explain their limited predictive ability for clinical outcomes. The aim of this study was to provide a universal pharmacological-based list of drugs with their documented affinity for muscarinic receptors. A comprehensive literature review was performed to identify the anticholinergic burden tools. Drugs included in these instruments were searched in four pharmacological databases, and the investigation was supplemented with PubMed. The evidence regarding the potential antagonism of the five muscarinic receptors of each drug was assessed. The proportion of drugs included in the tools with an affinity for muscarinic receptors was evaluated. A universal list of drugs with anticholinergic activity was developed based on their documented affinity for the different subtypes of muscarinic receptors and their ability to cross the blood-brain barrier. A total of 23 tools were identified, including 304 different drugs. Only 48.68%, 47.70%, 48.03%, 43.75%, and 42.76% of the drugs had an affinity to the M1, M2, M3, M4, and M5 receptor, respectively, reported in any pharmacological database. The proportion of drugs with confirmed antagonism varied among the tools (36.8% to 100%). A universal pharmacological-based list of 133 drugs is presented. It should be further validated in different clinical settings.

Nonadherence to prescribed medicines is a major public health issue intricately related to multimorbidity and polypharmacy. Increasing the number of medicines prescribed to a patient, regardless of whether polypharmacy can be classified as appropriate or inappropriate, increases the risk of medication nonadherence. Nonadherence is one of the factors more closely associated with poor control of chronic diseases, such as diabetes, hypertension and dyslipidemia but also with a rapid onset of complications and a subsequent decrease in the patient’s quality of life. From a systems perspective, the impact of nonadherence in healthcare systems must also be considered because it is responsible for over 20% of hospital admissions due to preventable adverse events, leading to unnecessary costs with a major economic impact.