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Despite the frequent use of symptomatic therapies in cough, evidence of their benefits is lacking.We compared the effectiveness of 3 symptomatic therapies and usual care in acute bronchitis.Multicenter, pragmatic, multiarm parallel group, open randomized trial in primary care (ClinicalTrials.gov, Identifier: NCT03738917) was conducted in Catalonia. Patients ≥18 with uncomplicated acute bronchitis, with cough3 weeks as the main symptom, scoring ≥4 in either daytime or nocturnal cough (7-point Likert scale), were randomized to usual care, dextromethorphan 15 mg t.i.d., ipratropium bromide inhaler 20 µg 2 puffs t.i.d, or 30 mg of honey t.i.d., all taken for up to 14 days. The main outcome measure was the number of days with moderate-to-severe cough. A symptom diary was given. A second visit was scheduled at days 2-3 for assessing evolution, with 2 more visits at days 15 and 29 for clinical assessment, evaluation of adverse effects, re-attendance, and complications.We failed to achieve the sample size scheduled due to the COVID-19 pandemic. We finally recruited 194 patients. The median number of days with moderate-to-severe cough (score ≥ 3) in the usual care arm was 5 (interquartile range [IQR], 4, 8.75), 5 in the ipratropium bromide arm (IQR, 3, 8), 5 in the dextromethorphan arm (IQR, 4, 9.75), and 6 in the honey arm (IQR, 3.5, 7). The same results were obtained in the Kaplan-Meier survival analysis for the median survival time of each arm with the usual care as the reference group.The symptomatic treatment evaluated has shown to be ineffective against cough.Cough is the most frequent symptom reported by patients with lower respiratory tract infections. Despite being a defense mechanism, cough is unpleasant and negatively affects sleep and overall well-being. Accordingly, many patients with acute cough seek medical help to mitigate symptoms and reduce their duration despite the typically self-limiting nature of the condition. In this randomized clinical trial, we explored the benefit of 3 common symptomatic treatments recommended in some guidelines for relieving this symptom during the course of uncomplicated acute bronchitis, a cough suppressant, an inhaler, and honey intake. Although the total number of patients initially expected could not be achieved due to the disruption caused by the COVID-19 pandemic, the results of our study demonstrate a lack of efficacy of these products as the number of days of severe-to-moderate cough was similar in the 3 arms and comparable to the group of patients allocated to usual care.

Background Since March of 2020, the scientific community has been engaged a marathon to answer the different questions that COVID-19 pandemic has brought. During this time, Ethics Committees played an important role in reviewing the research protocols, COVID-19 or not, ensuring that the quality of scientific research is not relaxed by the hasty need for answers. Methods Descriptive study from January 2019 to December 2021, comparing COVID-19 protocols to those not COVID-19 related protocols and comparing the work overload. Variables related to the characteristics of the research protocols (i.e. study design, funding…), the principal investigators (gender, PhD degree, professional role…) and outcomes of the Ethics Committee process (requirements of modifications and time until approval) were analyze. Results The number of sessions increased during COVID-19 pandemics (12 in 2019, 25 in 2020 and 18 in 2021). In total 751 protocols were evaluated during the study period; 513 (68.3%) had an observational design and 434 (57.8%) had no funding. The principal investigator was a woman in 491 (65.4%) studies and a General Practitioner in 330 (43.9%). The mean of the days until the protocol approval was 42.09 days (SD 60.2) with a decrease of 20.1 days from 2019 to 2021. A total of 614 (81.7%) protocols were approved, 336 (54.7%) within the first month after their initial evaluation. Less than half of the protocols were COVID-19 related (208, 44.3%). The COVID-19 protocols main topics were impact on the population (71, 34.1%); and COVID-19 pharmacological treatments (including vaccines) showed a higher increase in 2021 (37, 30.3%). Conclusions Despite the work overload during the pandemic due to the increase in the number of meetings and protocols, the IDIAPJGol EC reviewed all of them (COVID-19 or not) adapting to the new situation but according to its criteria of good practices to provide a quick response in the EC opinion. In Primary Health Care the most study designs have been observational studies, many of them with no funding and led by GPs. In 2021 there was an increase in the number of protocols focused on drugs, most likely related to COVID-19 vaccines studies.

Tizanidine's potent muscle relaxant properties and short onset of action makes it desirable for pain management. However, concomitant use of tizanidine with ciprofloxacin, a strong inhibitor of the P450-CYP1A2 cytochrome metabolic pathway of tizanidine, can result in increased tizanidine plasma levels and associated adverse outcomes, particularly hypotension. The aim of this study was to assess the risk of hypotension with coadministration of tizanidine and ciprofloxacin.An observational nested cohort study of patients 18 years or older on tizanidine was conducted using data from electronic health records from 2000 to 2018 in the US. We estimated the prevalence and risk of hypotension associated with the DDI between tizanidine and ciprofloxacin using multivariable logistic regression models.Our analysis included 70,110 encounters of patients on tizanidine across 221 hospitals. Most encounters included females (65.7%), whites (82.4%), with an average age of 56 years (SD 14.9) and an Elixhauser comorbidity index mean of 1.6 (SD 2.3). Ciprofloxacin was co-administered with tizanidine in 2487 encounters (3.6%). Compared to patients who did not receive ciprofloxacin, co-administration of tizanidine and ciprofloxacin was associated with an increased likelihood of hypotension (adjusted odds ratio: 1.43, 95% Confidence Intervals:1.25-1.63, p-value0.001).Our findings suggest that the concomitant use of tizanidine and ciprofloxacin is associated with an elevated risk of hypotension. The prevalence of co-administration of drugs with a documented interaction highlights the need for continuous education across providers to avoid the incidence of DDI related adverse events and further complications and to improve patient outcomes.

BACKGROUND Since the use of electronic health records (EHRs) in an automatized way, pharmacovigilance or pharmacoepidemiology studies have been trying to characterize the therapy using different algorithms. Although progress has been made in this area for monotherapy, in exposure to combinations of two or more drugs the challenge to characterize the treatment increases significantly and more research is needed. OBJECTIVE To develop and describe a novel algorithm that automatically returns the most likely therapy of one drug or combinations of two or more drugs over time. METHODS We used the Information System for Research in Primary Care (SIDIAP) as our reference EHRs platform for the smooth algorithm development. The algorithm is inspired by statistical methods based on moving averages and depends on a parameter Wt, a flexible window that determines the level of smoothing. The effect of Wt was evaluated in a simulation study with different window lengths on the same dataset. To understand the algorithm performance in a clinical or pharmacological perspective, we conducted a validation study. We designed four different pharmacological scenarios and asked to four independent professionals to compare a standard algorithm with the smooth algorithm. Then, the data from the simulation and the validation studies was analysed. RESULTS The Wt parameter has an impact over the raw data. As we increased the window length, the number of smoothed patients augmented, although we hardly see changes bigger than five percent of the total data. In the validation study, significant differences were obtained in the performance of the smooth algorithm against the standard method. These differences were consistent across pharmacological scenarios. CONCLUSIONS The smooth algorithm is an automatic approach that standardizes, simplifies, and improves the data processing in drug exposition studies using EHRs. This algorithm can be generalized to almost any pharmacological medication and facilitates the detection of treatment switches, discontinuations and/or terminations throughout the study period.

Background Since the use of electronic health records (EHRs) in an automated way, pharmacovigilance or pharmacoepidemiology studies have been used to characterize the therapy using different algorithms. Although progress has been made in this area for monotherapy, with combinations of 2 or more drugs the challenge to characterize the treatment increases significantly, and more research is needed. Objective The goal of the research was to develop and describe a novel algorithm that automatically returns the most likely therapy of one drug or combinations of 2 or more drugs over time. Methods We used the Information System for Research in Primary Care as our reference EHR platform for the smooth algorithm development. The algorithm was inspired by statistical methods based on moving averages and depends on a parameter Wt, a flexible window that determines the level of smoothing. The effect of Wt was evaluated in a simulation study on the same data set with different window lengths. To understand the algorithm performance in a clinical or pharmacological perspective, we conducted a validation study. We designed 4 pharmacological scenarios and asked 4 independent professionals to compare a traditional method against the smooth algorithm. Data from the simulation and validation studies were then analyzed. Results The Wt parameter had an impact over the raw data. As we increased the window length, more patient were modified and the number of smoothed patients augmented, although we rarely observed changes of more than 5% of the total data. In the validation study, significant differences were obtained in the performance of the smooth algorithm over the traditional method. These differences were consistent across pharmacological scenarios. Conclusions The smooth algorithm is an automated approach that standardizes, simplifies, and improves data processing in drug exposition studies using EHRs. This algorithm can be generalized to almost any pharmacological medication and model the drug exposure to facilitate the detection of treatment switches, discontinuations, and terminations throughout the study period.

Background: Colchicine has a narrow therapeutic index. Its toxicity can be increased due to concomitant exposure to drugs inhibiting its metabolic pathway; these are cytochrome P450 3A4 (CYP3A4) and P-glycoprotein (P-gp). Objective: To examine clinical outcomes associated with colchicine drug interactions using the spontaneous reports of the US Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS). Methods: We conducted a disproportionality analysis using FAERS data from January 2004 through June 2020. The reporting odds ratio (ROR) and observed-to-expected ratio (O/E) with shrinkage for adverse events related to colchicine’s toxicity (ie, rhabdomyolysis/myopathy, agranulocytosis, hemorrhage, acute renal failure, hepatic failure, arrhythmias, torsade de pointes/QT prolongation, and cardiac failure) were compared between FAERS reports. Results: A total of 787 reports included the combined mention of colchicine, an inhibitor of both CYP3A4 and P-gp drug, and an adverse event of interest. Among reports that indicated the severity, 61% mentioned hospitalization and 24% death. A total of 37 ROR and 34 O/E safety signals involving colchicine and a CYP3A4/P-gp inhibitor were identified. The strongest ROR signal was for colchicine + atazanavir and rhabdomyolysis/myopathy (ROR = 35.4, 95% CI: 12.8-97.6), and the strongest O/E signal was for colchicine + atazanavir and agranulocytosis (O/E = 3.79, 95% credibility interval: 3.44-4.03). Conclusion and Relevance: This study identifies numerous safety signals for colchicine and CYP3A4/P-gp inhibitor drugs. Avoiding the interaction or monitoring for toxicity in patients when co-prescribing colchicine and these agents is highly recommended.

Economic evaluations using Real World Data (RWD) has been increasing in the very recent years, however, this source of information has several advantages and limitations. The aim of this review was to assess the quality of full economic evaluations (EE) developed using RWD. A systematic review was carried out through articles from the following databases: PubMed, Embase, Web of Science and Centre for Reviews and Dissemination. Included were studies that employed RWD for both costs and effectiveness. Methodological quality of the studies was assessed using the Consolidated Health Economic Evaluation Reporting Standards (CHEERS) checklist. Of the 14,011 studies identified, 93 were included. Roughly half of the studies were carried out in a hospital setting. The most frequently assessed illnesses were neoplasms while the most evaluated interventions were pharmacological. The main source of costs and effects of RWD were information systems. The most frequent clinical outcome was survival. Some 47% of studies met at least 80% of CHEERS criteria. Studies were conducted with samples of 100-1000 patients or more, were randomized, and those that reported bias controls were those that fulfilled most CHEERS criteria. In conclusion, fewer than half the studies met 80% of the CHEERS checklist criteria.

Background The use of direct oral anticoagulants (DOAC) for stroke prevention in non-valvular atrial fibrillation (NVAF) has not been previously assessed in our setting. We aimed to describe sociodemographic, comorbidities, co-medication and risk of thromboembolic events and bleeding in patients with NVAF initiating oral anticoagulants (OAC) for stroke prevention, and to estimate adherence and persistence to OAC.Methods Population-based cohort study including all NVAF adult patients initiating OAC for stroke prevention in August 2013-December 2015. Persistence was measured in patients initiating OAC in August 2013-December 2014. Data source is SIDIAP, which captures electronic health records from Primary Health Care in the Catalan Health Institute, covering approximately 5.8 million people.Results 51,690 NVAF patients initiated OAC; 47,197 (91.3%) were naive to OAC and 32,404 initiated acenocoumarol (62.7%). Mean age was 72.8 years (SD 12.3) and 49.4% were women. Platelet-aggregation inhibitors were taken by 9,105 (17.6%) of the patients. For 22,075 patients, persistence was higher among the non-naive patients [n=258 (61.7%)] than among the naive [n=11,502 (53.1%)]. Adherence was estimated for patients initiating DOAC and was similar in naive and non-naive patients. Among the naive to DOAC treatment, those starting rivaroxaban showed a highest proportion [(n=360 (80.1%)] of good adherence at implementation (MPR>80%) while patients starting dabigatran were less adherent [n= 203 47.8%)].Conclusions Acenocoumarol was the most frequently prescribed OAC as first therapy in NVAF patients. Non-naive to DOAC showed better persistence than naive. Rivaroxaban showed higher proportion of adherent patients during the implementation phase than apixaban and dabigatran the lowest.

Economic evaluations using Real World Data (RWD) has been increasing in the very recent years, however, this source of information has several advantages and limitations. The aim of this review was to assess the quality of full economic evaluations (EE) developed using RWD. A systematic review was carried out through articles from the following databases: PubMed, Embase, Web of Science and Centre for Reviews and Dissemination. Included were studies that employed RWD for both costs and effectiveness. Methodological quality of the studies was assessed using the Consolidated Health Economic Evaluation Reporting Standards (CHEERS) checklist. Of the 14,011 studies identified, 93 were included. Roughly half of the studies were carried out in a hospital setting. The most frequently assessed illnesses were neoplasms while the most evaluated interventions were pharmacological. The main source of costs and effects of RWD were information systems. The most frequent clinical outcome was survival. Some 47% of studies met at least 80% of CHEERS criteria. Studies were conducted with samples of 100–1000 patients or more, were randomized, and those that reported bias controls were those that fulfilled most CHEERS criteria. In conclusion, fewer than half the studies met 80% of the CHEERS checklist criteria.