Use of methylphenidate and reporting of valvular heart disease: Global pharmacovigilance analysis in children and adults.

INTRODUCTION: Methylphenidate (MPH) is a common treatment of attention-deficit/hyperactivity disorder (ADHD). Concern has been raised regarding its cardiovascular safety, partly in relation with its micromolar affinity for the 5-HT2B receptor, whose activation may result in valvular heart disease (VHD). METHODS: To explore the association between the use of MPH and VHD reporting, we performed a disproportionality analysis within the WHO global safety database (VigiBase) using data, since inception until March 6th 2024, from: (i) the full database and (ii) different age groups (children/adolescents 6-17 years; adults 18-64 years). To avoid competition bias, safety reports with amphetamine-like appetite suppressants were excluded. Disproportionality was expressed using reporting odds-ratio (ROR) and its 95% confidence interval (CI). RESULTS: Of 29 129 spontaneous reports with MPH, 23 VHD cases (7.9 per 10 000 reports) were identified, including 13 adults and 10 children. Most cases concerned injury on the mitral valve. A disproportionate reporting was observed overall (ROR 1.6, 95% CI 1.1-2.4). Analysis according to age group found that disproportionality in VHD reporting was found in adults only (ROR 2.7, 95% CI 1.6-4.7) but not in children/adolescents (ROR 1.7, 95% CI 0.9-3.2). Furthermore, amongst MPH users only, VHD reporting was higher in adults compared to children (ROR 2.7, 95% CI 1.2-6.3). CONCLUSION: VHD reporting appears rare with MPH compared to other adverse events and is increased in adults only. Our findings support a potential safety signal of VHD in adults exposed to MPH. A risk in that population cannot be excluded and requires further assessment.

Multimorbidity prevalence and health outcome prediction: assessing the impact of lookback periods, disease count, and definition criteria in health administrative data at the population-based level.

BACKGROUND: Health administrative databases play a crucial role in population-level multimorbidity surveillance. Determining the appropriate retrospective or lookback period (LP) for observing prevalent and newly diagnosed diseases in administrative data presents challenge in estimating multimorbidity prevalence and predicting health outcome. The aim of this population-based study was to assess the impact of LP on multimorbidity prevalence and health outcomes prediction across three multimorbidity definitions, three lists of diseases used for multimorbidity assessment, and six health outcomes. METHODS: We conducted a population-based study including all individuals ages > 65 years on April 1st, 2019, in Québec, Canada. We considered three lists of diseases labeled according to the number of chronic conditions it considered: (1) L60 included 60 chronic conditions from the International Classification of Diseases (ICD); (2) L20 included a core of 20 chronic conditions; and (3) L31 included 31 chronic conditions from the Charlson and Elixhauser indices. For each list, we: (1) measured multimorbidity prevalence for three multimorbidity definitions (at least two [MM2+], three [MM3+] or four (MM4+) chronic conditions); and (2) evaluated capacity (c-statistic) to predict 1-year outcomes (mortality, hospitalisation, polypharmacy, and general practitioner, specialist, or emergency department visits) using LPs ranging from 1 to 20 years. RESULTS: Increase in multimorbidity prevalence decelerated after 5-10 years (e.g., MM2+, L31: LP = 1y: 14%, LP = 10y: 58%, LP = 20y: 69%). Within the 5-10 years LP range, predictive performance was better for L20 than L60 (e.g., LP = 7y, mortality, MM3+: L20 [0.798;95%CI:0.797-0.800] vs. L60 [0.779; 95%CI:0.777-0.781]) and typically better for MM3 + and MM4 + definitions (e.g., LP = 7y, mortality, L60: MM4+ [0.788;95%CI:0.786-0.790] vs. MM2+ [0.768;95%CI:0.766-0.770]). CONCLUSIONS: In our databases, ten years of data was required for stable estimation of multimorbidity prevalence. Within that range, the L20 and multimorbidity definitions MM3 + or MM4 + reached maximal predictive performance.

Calculating daily dose in the Observational Medical Outcomes Partnership Common Data Model.

PURPOSE: We aimed to develop a standardized method to calculate daily dose (i.e., the amount of drug a patient was exposed to per day) of any drug on a global scale using only drug information of typical observational data in the Observational Medical Outcomes Partnership Common Data Model (OMOP CDM) and a single reference table from Observational Health Data Sciences And Informatics (OHDSI). MATERIALS AND METHODS: The OMOP DRUG_STRENGTH reference table contains information on the strength or concentration of drugs, whereas the OMOP DRUG_EXPOSURE table contains information on patients' drug prescriptions or dispensations/claims. Based on DRUG_EXPOSURE data from the primary care databases Clinical Practice Research Datalink GOLD (United Kingdom) and Integrated Primary Care Information (IPCI, The Netherlands) and healthcare claims from PharMetrics® Plus for Academics (USA), we developed four formulas to calculate daily dose given different DRUG_STRENGTH reference table information. We tested the dose formulas by comparing the calculated median daily dose to the World Health Organization (WHO) Defined Daily Dose (DDD) for six different ingredients in those three databases and additional four international databases representing a variety of healthcare settings: MAITT (Estonia, healthcare claims and discharge summaries), IQVIA Disease Analyzer Germany (outpatient data), IQVIA Longitudinal Patient Database Belgium (outpatient data), and IMASIS Parc Salut (Spain, hospital data). Finally, in each database, we assessed the proportion of drug records for which daily dose calculations were possible using the suggested formulas. RESULTS: Applying the dose formulas, we obtained median daily doses that generally matched the WHO DDD definitions. Our dose formulas were applicable to >85% of drug records in all but one of the assessed databases. CONCLUSION: We have established and implemented a standardized daily dose calculation in OMOP CDM providing reliable and reproducible results.

Ascertaining the Francophone population in Ontario: validating the language variable in health data.

BACKGROUND: Language barriers can impact health care and outcomes. Valid and reliable language data is central to studying health inequalities in linguistic minorities. In Canada, language variables are available in administrative health databases; however, the validity of these variables has not been studied. This study assessed concordance between language variables from administrative health databases and language variables from the Canadian Community Health Survey (CCHS) to identify Francophones in Ontario. METHODS: An Ontario combined sample of CCHS cycles from 2000 to 2012 (from participants who consented to link their data) was individually linked to three administrative databases (home care, long-term care [LTC], and mental health admissions). In total, 27,111 respondents had at least one encounter in one of the three databases. Language spoken at home (LOSH) and first official language spoken (FOLS) from CCHS were used as reference standards to assess their concordance with the language variables in administrative health databases, using the Cohen kappa, sensitivity, specificity, positive predictive value (PPV), and negative predictive values (NPV). RESULTS: Language variables from home care and LTC databases had the highest agreement with LOSH (kappa = 0.76 [95%CI, 0.735-0.793] and 0.75 [95%CI, 0.70-0.80], respectively) and FOLS (kappa = 0.66 for both). Sensitivity was higher with LOSH as the reference standard (75.5% [95%CI, 71.6-79.0] and 74.2% [95%CI, 67.3-80.1] for home care and LTC, respectively). With FOLS as the reference standard, the language variables in both data sources had modest sensitivity (53.1% [95%CI, 49.8-56.4] and 54.1% [95%CI, 48.3-59.7] in home care and LTC, respectively) but very high specificity (99.8% [95%CI, 99.7-99.9] and 99.6% [95%CI, 99.4-99.8]) and predictive values. The language variable from mental health admissions had poor agreement with all language variables in the CCHS. CONCLUSIONS: Language variables in home care and LTC health databases were most consistent with the language often spoken at home. Studies using language variables from administrative data can use the sensitivity and specificity reported from this study to gauge the level of mis-ascertainment error and the resulting bias.

Rising cases of drug-induced pulmonary fibrosis: Analysis of the Food and Drug Administration Adverse Event Reporting System (FAERS) database, 2000-2022.

PURPOSE: Pulmonary fibrosis (PF) is a severe, progressive disease, which may be caused by exposure to certain medications. METHODS: We queried the U.S. FDA Adverse Event Reporting System (FAERS) from 2000 to 2022, using the search terms "pulmonary fibrosis" and "idiopathic pulmonary fibrosis" and excluded reports with patients under the age of 18 years, and patients with unknown sex or age. Reports were sorted by generic drug names, counted, and plotted over time using a best-fit trendline based on an exponential function. RESULTS: From 2000 to 2022, there were 24 095 935 adverse drug events reported in FAERS, of which 17 520 (0.07%) were reported as PF. After excluding reports containing patients with unknown age (5255, 30%), sex (122, 0.7%), and age below 18 years old (155, 0.9%), our study included 11 988 reports. The mean age of the study sample was 66.5 ± 13.1 years, and 6248 patients (52.1%) were male. Plotting the 11 988 reports by year revealed an exponential best fit line (R2 = 0.88) with a positive slope over time. The top five drug classes associated with PF were disease modifying antirheumatic drugs (DMARDs, 39.4%), antineoplastic agents (26.4%), cardiovascular agents (12.6%), corticosteroids (4.6%), and immunosuppressive agents (4.0%). CONCLUSION: A 23-year analysis of the FAERS database revealed exponentially increasing adverse event reports of PF. Significant annual increases in reporting of PF suspected with DMARDs and antineoplastic agents were identified. Our study highlights important trends, which should be used to guide PF research related to drugs of potential importance.

Appropriate Relevancy and Reliability of Real-World Data for the Utilization of Regulatory Submission.

The extraction of data that contribute to regulatory approval from real-world data (RWD) is difficult because of the lack of a standardized data format and extraction methodology. Additionally, when real-world evidence (RWE) is used as an external control group, the similarity between internal and external control data is not evaluated. To investigate the data extraction methodology for the external control data of rare molecular subtypes, we have initiated the "REALISE" study. In this study, we aim to elucidate the "relevance" and "reliability" of RWD/RWE necessary for regulatory approval. As most databases are not designed for regulatory use in the creation phase, we will investigate retrospective methodologies to ensure RWD/RWE reliability. This study will compare the "relevance" and "reliability" of the ARCAD global database, SCRUM-Japan Registry, SCRUM-Japan observational study, and Flatiron Health RWD, and statistically analyze the differences and similarities among the four databases. We will also examine the methodology for extracting sufficiently relevant data from the SCRUM-Japan observational study. Additionally, if the reliability of the RWD/RWE does not reach the required level for regulatory approval, we will examine the methodologies to ensure the "reliability" of the SCRUM-Japan observational study for regulatory approval. The obtained results will be submitted to the "Consultation for Development of Registry" in the Pharmaceuticals and Medical Devices Agency, and we will discuss the standard methodology. The procedures and findings identified in the REALISE study will be organized from the perspectives of "database construction," "data analysis," and "outcome evaluation" and will be issued as "the draft guidelines."

Extracorporeal Membrane Oxygenation-Associated Compartment Syndrome: Review of a National Database.

INTRODUCTION: Extracorporeal membrane oxygenation (ECMO)-associated compartment syndrome (CS) is a rare complication seen in critically ill patients. The epidemiology and management of ECMO-associated CS in the upper extremity (UE) and lower extremity (LE) are poorly defined in the literature. We sought to determine the epidemiology and characterize treatment and outcomes of UE-CS compared to LE-CS in the setting of ECMO therapy. METHODS: Adult patients undergoing ECMO therapy were identified in the Nationwide Readmission Database (2015-2019) and followed up for 6 months. Patients were stratified based on UE-CS versus LE-CS. Primary outcomes were fasciotomy and amputation. All-cause mortality and length of stay were also collected. Risk-adjusted modeling was performed to determine patient- and hospital-level factors associated with differences in the management UE-CS versus LE-CS while controlling for confounders. RESULTS: A total of 24,047 cases of ECMO during hospitalization were identified of which 598 were complicated by CS. Of this population, 507 cases were in the LE (84.8%), while 91 (15.5%) were in the UE. After multivariate analysis, UE-CS patients were less likely to undergo fasciotomy (50.5 vs. 70.9; P = 0.013) and were less likely to undergo amputation of the extremity (3.3 vs. 23.7; P = 0.001) although there was no difference in mortality (58.4 vs. 65.4; P = 0.330). CONCLUSIONS: ECMO patients with CS experience high mortality and morbidity. UE-CS has lower rates of fasciotomy and amputations, compared to LE-CS, with similar mortality. Further studies are needed to elucidate the reasons for these differences.

Patterns in the Reporting of Aggressive Histologic Subtypes in Papillary Thyroid Cancer.

INTRODUCTION: The tall cell, columnar, and diffuse sclerosing subtypes are aggressive histologic subtypes of papillary thyroid cancer (PTC) with increasing incidence, yet there is a wide variation in reporting. We aimed to identify and compare factors associated with the reporting of these aggressive subtypes (aPTC) to classic PTC (cPTC) and secondarily identify differences in outcomes. METHODS: The National Cancer Database was utilized to identify cPTC and aPTC from 2004 to 2017. Patient and facility demographics and clinicopathologic variables were analyzed. Independent predictors of aPTC reporting were identified and a survival analysis was performed. RESULTS: The majority of aPTC (67%) were reported by academic facilities. Compared to academic facilities, all other facility types were 1.4-2.0 times less likely to report aPTC (P < 0.05). Regional variation in reporting was noted, with more cases reported in the Middle Atlantic, despite there being more total facilities in the South Atlantic and East North Central regions. Compared to the Middle Atlantic, all other regions were 1.4-5 times less likely to report aPTC (P < 0.001). Patient characteristics including race and income were not associated with aPTC reporting. Compared to cPTC, aPTC had higher rates of aggressive features and worse 5-y overall survival (90.5% versus 94.5%, log rank P < 0.001). CONCLUSIONS: Aggressive subtypes of PTC are associated with worse outcomes. Academic and other facilities in the Middle Atlantic were more likely to report aPTC. This suggests the need for further evaluation of environmental or geographic factors versus a need for increased awareness and more accurate diagnosis of these subtypes.

Epidemiology of myasthenia gravis in France: Incidence, prevalence, and comorbidities based on national healthcare insurance claims data.

BACKGROUND: The European literature has reported high variability in the incidence and prevalence rates of myasthenia gravis (MG), but no specific epidemiological data for France have been published. This study aimed to assess the incidence and prevalence rates of myasthenia gravis in France based on data extracted from the French National Health Insurance Claims Database (the SNIIRAM database). METHODS: We conducted a retrospective repeated cross-sectional population study from 2008 to 2018 using a representative sample of the French population (Échantillon généraliste des bénéficiaires) covered by health insurance. We calculated the incidence, prevalence, and sex ratio of MG and screened for comorbidities associated with MG (standardized to the general population). RESULTS: In total, 331 MG patients were identified between 2008 and 2018. The average incidence of MG in France was 50 per million person-years, while the mean prevalence was 465 per million people. The female-to-male ratio was 1.33. The Incidence of MG gradually increased from 40years of age for women and 60 for men. Thymoma was present for 5.1% of MG patients and a thymectomy was performed for 4.7%. Thyroid disease was the most prevalent autoimmune comorbidity, affecting approximately 8.5% of cases. MG patients had an increased cancer risk, with a standardized rate ratio of 2.38 (95% CI: 1.64-3.46). CONCLUSION: The incidence and prevalence rates of MG are significantly higher than those previously reported in the literature and the incidence increases with age. The excess risk of cancer raises concerns for MG patients, in particular, concerning the management of immunosuppressive drugs.

Thirst and drugs: A study in the World Health Organization's pharmacovigilance database.

Thirst is a complex physiological compensatory mechanism but could also be associated with drugs. This association was poorly investigated previously. Using the WHO global pharmacovigilance database, Vigibase®, disproportionality analyses potential associations between exposure to drugs and thirst reports were performed. All reports of thirst in adults between 01/01/2000 and 31/12/2023 were included. Results are expressed as reporting odds ratio (ROR). Analysis of the 3186 reports of thirst (978 'serious') allowed, first, to confirm the association between thirst and exposure to vasopressin antagonists (tolvaptan), lithium, gliflozins (dapagliflozin, empagliflozin), pregabalin and antimuscarinic drugs (glycopyronium, oxybutynin, tiotropium). Second, new safety signals were described with monoamine reuptake inhibitors (antidepressants: duloxetine, venlafaxine; anti-obesity agent: sibutramine), antipsychotic (olanzapine), glucocorticoid (prednisolone), diuretic (furosemide) drugs as well with ribavirin or sodium oxybate. This study is the first to offer a list of drugs associated with thirst in humans.

Readmissions After Traumatic Brain Injury in the Nationwide Readmissions Database.

INTRODUCTION: Readmissions after a traumatic brain injury (TBI) can have severe impacts on long-term health outcomes as well as rehabilitation. The aim of this descriptive study was to analyze the Nationwide Readmissions Database to determine possible risk factors associated with readmission for patients who previously sustained a TBI. METHODS: This retrospective study used data from the Nationwide Readmissions Database to explore gender, age, injury severity score, comorbidities, index admission hospital size, discharge disposition of the patient, and cause for readmission for adults admitted with a TBI. Multivariable logistic regression was used to assess likelihood of readmission. RESULTS: There was a readmission rate of 28.7% (n = 31,757) among the study population. The primary cause of readmission was either subsequent injury or sequelae of the original injury (n = 8825; 29%) followed by circulatory (n = 5894; 19%) and nervous system issues (n = 2904; 9%). There was a significantly higher risk of being readmitted in males (Female odds ratio: 0.87; confidence interval [0.851-0.922), older patients (65-79: 32.3%; > 80: 37.1%), patients with three or more comorbidities (≥ 3: 32.9%), or in patients discharged to a skilled nursing facility/intermediate care facility/rehab (SNF/ICF/Rehab odds ratio: 1.55; confidence interval [0.234-0.262]). CONCLUSIONS: This study demonstrates a large proportion of patients are readmitted after sustaining a TBI. A significant number of patients are readmitted for subsequent injuries, circulatory issues, nervous system problems, and infections. Although readmissions cannot be completely avoided, defining at-risk populations is the first step of understanding how to reduce readmissions.

Challenging Dogma by Skipping the Emergency Department Thoracotomy: A Propensity Score Matched Analysis of the Trauma Quality Improvement Database.

INTRODUCTION: Survival following emergency department thoracotomy (EDT) for patients in extremis is poor. Whether intervention in the operating room instead of EDT in select patients could lead to improved outcomes is unknown. We hypothesized that patients who underwent intervention in the operating room would have improved outcomes compared to those who underwent EDT. METHODS: We conducted a retrospective review of the Trauma Quality Improvement Program database from 2017 to 2021. All adult patients who underwent EDT, operating room thoracotomy (ORT), or sternotomy as the first form of surgical intervention within 1 h of arrival were included. Of patients without prehospital cardiac arrest, propensity score matching was utilized to create three comparable groups. The primary outcome was survival. Secondary outcomes included time to procedure. RESULTS: There were 1865 EDT patients, 835 ORT patients, and 456 sternotomy patients who met the inclusion criteria. There were 349 EDT, 344 ORT, and 408 sternotomy patients in the matched analysis. On Cox multivariate regression, there was an increased risk of mortality with EDT versus sternotomy (HR 4.64, P < 0.0001), EDT versus ORT (HR 1.65, P < 0.0001), and ORT versus sternotomy (HR 2.81, P < 0.0001). Time to procedure was shorter with EDT versus sternotomy (22 min versus 34 min, P < 0.0001) and versus ORT (22 min versus 37 min, P < 0.0001). CONCLUSIONS: There was an association between sternotomy and ORT versus EDT and improved mortality. In select patients, operative approaches rather than the traditional EDT could be considered.

Real-world safety of Levetiracetam: Mining and analysis of its adverse drug reactions based on FAERS database.

INTRODUCTION: Levetiracetam is a relatively new and widely utilized anti-seizure medication; however, limited information is available regarding its adverse effects. This study aims to thoroughly investigate, evaluate, and present evidence on the safety profile of Levetiracetam, relying on data from the FDA Adverse Event Reporting System (FAERS) database to facilitate informed clinical decision-making. METHODS: We employed various statistical measures, including Reporting Odds Ratio (ROR), Proportionate Reporting Ratio (PRR), and analysis by the Medicines and Healthcare Products Regulatory Agency (MHRA), to identify signals of adverse reactions associated with Levetiracetam. Positive signals consistent with Designated Medical Event (DME) were singled out for focused comparison and discussion. RESULTS: The analysis of 26,182 adverse events linked to Levetiracetam as the primary suspected drug revealed 692 positive signals spanning 22 System Organ Classes (SOCs). Nervous system disorders were the most frequently reported, followed by psychiatric disorders, and general disorders and administration site conditions. 11 positive signals consistent with Preferred Terms (PTs) in DME were identified, predominantly concentrated in 6 SOCs. Among these, rhabdomyolysis, Stevens-Johnson syndrome (SJS), toxic epidermal necrolysis (TEN), drug reaction with eosinophilia and systemic symptoms (DRESS) exhibited relatively large values of A, ROR, and Chi-squared. Additionally, PTs related to spontaneous abortion, drug interaction, urethral atresia, ventricular septal defect, and atrial septal defect showed significant strength. CONCLUSIONS: The study indicates that Levetiracetam carries a potential risk of causing rhabdomyolysis, SJS, TEN, DRESS as well as spontaneous abortion. Signals related to drug interaction, urethral atresia, ventricular septal defect, and atrial septal defect warrant heightened attention in clinical use.

Validating methods used to identify non-adherence adverse drug events in Canadian administrative health data.

AIMS: Medication non-adherence is a type of adverse drug event that can lead to untreated and exacerbated chronic illness, and that drives healthcare utilization. Research using medication claims data has attempted to identify instances of medication non-adherence using the proportion of days covered or by examining gaps between medication refills. We sought to validate these measures compared to a gold standard diagnosis of non-adherence made in hospital. METHODS: This was a retrospective analysis of adverse drug events diagnosed during three prospective cohorts in British Columbia between 2008 and 2015 (n = 976). We linked prospectively identified adverse drug events to medication claims data to examine the sensitivity and specificity of typical non-adherence measures. RESULTS: The sensitivity of the non-adherence measures ranged from 22.4% to 37.5%, with a proportion of days covered threshold of 95% performing the best; the non-persistence measures had sensitivities ranging from 10.4% to 58.3%. While a 7-day gap was most sensitive, it classified 61.2% of the sample as non-adherent, whereas only 19.6% were diagnosed as such in hospital. CONCLUSIONS: The methods used to identify non-adherence in administrative databases are not accurate when compared to a gold standard diagnosis by healthcare providers. Research that has relied on administrative data to identify non-adherent patients both underestimates the magnitude of the problem and may label patients as non-adherent who were in fact adherent.