COVID-19 and pregnancy: A European study on pre- and post-infection medication use.

PURPOSE: The COVID-19 pandemic has impacted medication needs and prescribing practices, including those affecting pregnant women. Our goal was to investigate patterns of medication use among pregnant women with COVID-19, focusing on variations by trimester of infection and location. METHODS: We conducted an observational study using six electronic healthcare databases from six European regions (Aragon/Spain; France; Norway; Tuscany, Italy; Valencia/Spain; and Wales/UK). The prevalence of primary care prescribing or dispensing was compared in the 30-day periods before and after a positive COVID-19 test or diagnosis. RESULTS: The study included 294,126 pregnant women, of whom 8943 (3.0%) tested positive for, or were diagnosed with, COVID-19 during their pregnancy. A significantly higher use of antithrombotic medications was observed particularly after COVID-19 infection in the second and third trimesters. The highest increase was observed in the Valencia region where use of antithrombotic medications in the third trimester increased from 3.8% before COVID-19 to 61.9% after the infection. Increases in other countries were lower; for example, in Norway, the prevalence of antithrombotic medication use changed from around 1-2% before to around 6% after COVID-19 in the third trimester. Smaller and less consistent increases were observed in the use of other drug classes, such as antimicrobials and systemic corticosteroids. CONCLUSION: Our findings highlight the substantial impact of COVID-19 on primary care medication use among pregnant women, with a marked increase in the use of antithrombotic medications post-COVID-19. These results underscore the need for further research to understand the broader implications of these patterns on maternal and neonatal/fetal health outcomes.

Impact of the 2018 revised Pregnancy Prevention Programme by the European Medicines Agency on the use of oral retinoids in females of childbearing age in Denmark, Italy, Netherlands, and Spain: an interrupted time series analysis.

Background: In March 2018, the European pregnancy prevention programme for oral retinoids was updated as part of risk minimisation measures (RMM), emphasising their contraindication in pregnant women. Objective: To measure the impact of the 2018 revision of the RMMs in Europe by assessing the utilisation patterns of isotretinoin, alitretinoin and acitretin, contraceptive measures, pregnancy testing, discontinuation, and pregnancy occurrence concomitantly with a retinoid prescription. Methods: An interrupted time series (ITS) analysis to compare level and trend changes after the risk minimisation measures implementation was conducted on a cohort of females of childbearing age (12-55 years of age) from January 2010 to December 2020, derived from six electronic health data sources in four countries: Denmark, Netherlands, Spain, and Italy. Monthly utilisation figures (incidence rates [IR], prevalence rates [PR] and proportions) of oral retinoids were calculated, as well as discontinuation rates, contraception coverage, pregnancy testing, and rates of exposed pregnancies to oral retinoids, before and after the 2018 RMMs. Results: From 10,714,182 females of child-bearing age, 88,992 used an oral retinoid at any point during the study period (mean age 18.9-22.2 years old). We found non-significant level and trend changes in incidence or prevalence of retinoid use in females of child-bearing age after the 2018 RMMs. The reason of discontinuation was unknown in >95% of cases. Contraception use showed a significant increase trend in Spain; for other databases this information was limited. Pregnancy testing was hardly recorded thus was not possible to model ITS analyses. After the 2018 RMM, rates of pregnancy occurrence during retinoid use, and start of a retinoid during a pregnancy varied from 0.0 to 0.4, and from 0.2 to 0.8, respectively. Conclusion: This study shows a limited impact of the 2018 RMMs on oral retinoids utilisation patterns among females of child-bearing age in four European countries. Pregnancies still occur during retinoid use, and oral retinoids are still prescribed to pregnant women. Contraception and pregnancy testing information was limited in most databases. Regulators, policymakers, prescribers, and researchers must rethink implementation strategies to avoid any pregnancy becoming temporarily related to retinoid use.

Initial opioid prescription characteristics and risk of opioid misuse, poisoning and dependence: retrospective cohort study.

OBJECTIVE: To identify individual and initial prescription-related factors associated with an increased risk for opioid-related misuse, poisoning and dependence (MPD) in patients with non-cancer pain. METHODS: Cohort study linking several databases covering 5 million inhabitants of the region of Valencia, Spain, including all adults initiating prescription opioids in the period 2012-2018. To ascertain the association between the characteristics of the initial prescription choice and the risk of opioid MPD, we used shared frailty Cox regression models. We additionally considered death as a competing risk in sensitivity analyses. RESULTS: 958 019 patients initiated opioid prescription from 2012 to 2018, of which 0.13% experienced MPD. Most patients were prescribed tramadol as initial opioid (76.7%) followed by codeine (16.3%), long-acting opioids (6.7%), short-acting opioids (0.2%) and ultrafast opioids (0.1%). Initiation with ultrafast (HR 7.2; 95% CI 4.1 to 12.6), short-acting (HR 4.8; 95% CI 2.3 to 10.2) and long-acting opioids (HR 1.5; 95% CI 1.2 to 1.9) were associated with a higher risk of MPD when compared with tramadol. Initial prescriptions covering 4-7 days (HR 1.3; 95% CI 1.0 to 1.8), 8-14 days (HR 1.4; 95% CI 1.0 to 1.9), 15-30 days (HR 1.7; 95% CI 1.2 to 2.3) and more than one a month (HR 1.8; 95% CI 1.3 to 2.5) were associated with more MPD risk than initial prescriptions for 1-3 days. Treatments with >120 daily morphine milligram equivalents (MME) increased MPD risk (vs <50 MME, HR 1.6; 95% CI 1.1 to 2.2). Main individual factors associated with increased risk of MPD risk were male sex (HR 2.4; 95% CI 2.1 to 2.7), younger age (when compared with patients aged 18-44 years, patients aged 45-64 years, HR 0.4; 95% CI 0.4 to 0.5; patients aged 65-74 years, HR 0.4; 95% CI 0.3 to 0.5 and patients aged 75 years old and over, HR 0.7; 95% CI 0.6 to 0.8), lack of economic resources (2.1; 95% CI 1.8 to 2.5) and registered misuse of alcohol (2.9; 95% CI 2.4 to 3.5). Sensitivity analyses yielded overall comparable results. CONCLUSIONS: Our study identifies riskier patterns of opioid prescription initiation for non-cancer indications, as well as patient subgroups with higher risk of misuse, poisoning and dependence.

Real-world patterns of opioid therapy initiation in Spain, 2012-2018: A population-based, retrospective cohort study with 957,080 patients and 1,509,488 initiations.

Introduction: Europe has seen a steady increase in the use of prescription opioids, especially in non-cancer indications. Epidemiological data on the patterns of use of opioids is required to optimize prescription. We aim to describe the patterns of opioid therapy initiation for non-cancer pain and characteristics of patients treated in a region with five million inhabitants in the period 2012 to 2018. Methods: Population-based retrospective cohort study of all adult patients initiating opioid therapy for non-cancer pain in the region of Valencia. We described patient characteristics at baseline and the characteristics of baseline and subsequent treatment initiation. We used multinominal regression models to identify individual factors associated with initiation. Results: A total of 957,080 patients initiated 1,509,488 opioid treatments (957,080 baseline initiations, 552,408 subsequent initiations). For baseline initiations, 738,749 were with tramadol (77.19%), 157,098 with codeine (16.41%) 58,436 (6.11%) with long-acting opioids, 1,518 (0.16%) with short-acting opioids and 1,279 (0.13%) with ultrafast drugs. When compared to tramadol, patients initiating with short-acting, long-acting and ultrafast opioids were more likely to be older and had more comorbidities, whereas initiators with codeine were more prone to be healthier and younger. Treatments lasting less than 7 days accounted for 41.82% of initiations, and 11.89% lasted more than 30 days. 19.55% of initiators with ultrafast fentanyl received more than 120 daily Morphine Milligram Equivalents (MME), and 16.12% of patients initiating with long-acting opioids were prescribed more than 90 daily MME (p < 0.001). Musculoskeletal indications accounted for 65.05% of opioid use. Overlap with benzodiazepines was observed in 24.73% of initiations, overlap with gabapentinoids was present in 11.04% of initiations with long-acting opioids and 28.39% of initiators with short-acting opioids used antipsychotics concomitantly. In subsequent initiations, 55.48% of treatments included three or more prescriptions (vs. 17.60% in baseline initiations) and risk of overlap was also increased. Conclusion: Opioids are initiated for a vast array of non-oncological indications, and, despite clinical guidelines, short-acting opioids are used marginally, and a significant number of patients is exposed to potentially high-risk patterns of initiation, such as treatments lasting more than 14 days, treatments surpassing 50 daily MMEs, initiating with long-acting opioids, or hazardous overlapping with other therapies.

Side effects during the week after first dose vaccination with four Covid-19 vaccines. Results of the ProVaVac Survey Study with 13,837 people in Spain.

BACKGROUND: In 2021, four vaccines against Covid-19 (BNT162b2, mRNA-1273, ChAdOx1nCoV-19, and JNJ-78436735) were employed in the region of Valencia, Spain. We conducted a survey to identify real-world, self-reported frequency and severity of side effects during the week after vaccination. METHODS: Survey data was obtained from April 19, 2021, to October 6, 2021, at three different moments in time: day one, day three and day seven after vaccination. Answers were linked to individual-level, personal and clinical information. Respondents were stratified by the vaccine they received and reported effects were presented over time and stratified by severity. We compared our results per vaccine with the frequencies stated in each Summary of Product Characteristics (SmPC). We used binomial logistic models to identify associations between respondent characteristics and side effects. RESULTS: No symptoms were reported by 1,986 respondents (14.35 %), 6,254 informed exclusively mild symptoms (45.20 %), 3,444 up to moderate symptoms (24.89 %), and 2,153 people (15.56 %) notified also severe symptoms. Among the latter, the more frequent were extreme tiredness (7.0 %), and nausea or vomiting (7.1 %). The reported frequency of facial paralysis (0.4 %) was much higher than reflected in SmPCs. Female sex, younger age, previous positive Active Infection Diagnostic Test, chronicity, and vaccination with other than the BNT162b2 vaccine were associated to an increased risk of side effects (p < 0.001). CONCLUSIONS: Side effects after vaccination are common in the real-world. However, they are principally mild, and their frequency declines after a few days. Providing patients with dependable, beforehand information about side effects may improve outcomes and reinforce vaccination programs.

Assessing Concurrent Adherence to Combined Essential Medication and Clinical Outcomes in Patients With Acute Coronary Syndrome. A Population-Based, Real-World Study Using Group-Based Trajectory Models.

Aim: Adherence to multiple medications recommended for secondary prevention of cardiovascular conditions represents a challenge. We aimed to identify patterns of concurrent adherence to combined therapy and assess their impact on clinical outcomes in a cohort of patients with acute coronary syndrome (ACS). Methods: Population-based retrospective cohort of all patients discharged after hospitalization for ACS (2009-2011), prescribed ≥3 therapeutic groups within the first month. We assessed monthly concurrent adherence (≥24 days of medication out of 30) to ≥3 medications during the first year, and patterns were identified through group-based trajectory models. A composite clinical outcome during the second year was constructed. The association between adherence patterns and traditional refill adherence metrics [e.g., the proportion of days covered (PDC)], and outcomes were assessed through a multivariable Cox proportional hazards model. Results: Among 15,797 patients discharged alive, 12,057 (76.32%) initiated treatment with ≥3 therapeutic groups after discharge. We identified seven adherence trajectories to ≥3 medications: Adherent (52.94% of patients); Early Gap (6.64%); Middle Gap (5.67%); Late Decline (10.93%); Occasional Users (5.45%); Early Decline (8.79%); Non-Adherent (9.58%). Compared to the Adherent group, patients belonging to Early Gap (HR:1.30, 95%CI 1.07;1.60), Late decline (hazards ratio (HR): 1.31, 95% CI 1.1; 1.56), and Non-Adherent trajectories (HR: 1.36, 95% CI 1.14; 1.63) had a greater risk of adverse clinical outcomes, which was also different to the risk ascertained through concurrent PDC < 80 (HR: 1.13, 95% CI 1.01; 1.27). Conclusion: Overall, seven adherence trajectories to ≥3 drugs were identified, with three distinct adherence patterns being at higher risk of adverse outcomes. The identification of patterns of concurrent adherence, a more comprehensive approach than traditional measurements, may be useful to target interventions to improve adherence to multiple medications.

Predictive Performance of the FRAX Tool Calibrated for Spain vs. an Age and Sex Model: Prospective Cohort Study with 9082 Women and Men Followed for up to 8 Years.

In Spain, the Fracture Risk Assessment Tool (FRAX) was adapted using studies with a small number of patients, and there are only a few external validation studies that present limitations. In this prospective cohort study, we compared the performance of FRAX and a simple age and sex model. We used data from the ESOSVAL cohort, a cohort composed of a Mediterranean population of 11,035 women and men aged 50 years and over, followed for up to 8 years, to compare the discrimination, calibration, and reclassification of FRAX calibrated for Spain and a logistic model including only age and sex as variables. We found virtually identical AUC, 83.55% for FRAX (CI 95%: 80.46, 86.63) and 84.10% for the age and sex model (CI 95%: 80.91, 87.29), and there were similar observed-to-predicted ratios. In the reclassification analyses, patients with a hip fracture that were reclassified correctly as high risk by FRAX, compared to the age and sex model, were -2.86%, using either the 3% threshold or the observed incidence, 1.54% (95%CI: -8.44, 2.72 for the 3% threshold; 95%CI: -7.68, 1.97 for the incidence threshold). Remarkably simple and inexpensive tools that are easily transferable into electronic medical record environments may offer a comparable predictive ability to that of FRAX.

Impact of Three Safety Interventions Targeting Off-Label Use of Immediate-Release Fentanyl on Prescription Trends: Interrupted Time Series Analysis.

Background: The Spanish health authorities are concerned by the off-label use of immediate-release formulations of fentanyl (IRF) in noncancer pain and cancer pain in patients with no chronic pain therapy. Aim: To evaluate the impact of different interventions to improve appropriateness of IRF prescription on off-label prescription. Patients and methods: We used interrupted time series (ITS) to estimate immediate and trend changes of IRF prescription for noncancer pain (NCP) and breakthrough cancer pain (BCP) in patients with and without chronic cancer pain therapy associated with two medication reviews (I1 and I2) and the issue of a safety warning letter (I3) with data from a Spanish region with 5 million inhabitants, from 2015 to 2018. Results: The use of IRF for NCP in the region Valencia was reduced from about 1,800 prescriptions per week to around 1,400. The first medication review was followed by an immediate level change of -192.66 prescriptions per week (p < 0.001) and a downward trend change of -6.75 prescriptions/week (p < 0.001), resulting in a post-intervention trend of -1.99 (p < 0.001). I2 was associated with a trend change of -23.07 (p < 0.001) prescriptions/week. After I3, the trend changed markedly to 27.23 additional prescriptions/week, for a final post-intervention trend of 2.17 (p < 0.001). Controlled-ITS provided comparable results. For potentially inappropriate BCP use, the second medication review was followed by a downward, immediate level change of -10.10 prescriptions/week (p = 0.011) and a trend change of 2.31 additional prescriptions/week (p < 0.001) and the issue of the safety warning (I3) was followed by a downward trend change of -2.09 prescriptions/week (p = 0.007). Conclusion: Despite IRF prescription for NCP decreased, the interventions showed modest and temporary effect on off-label prescription. Our results call for a review of the design and implementation of safety interventions addressing inappropriate opioid use.

Gene-environment interaction analysis of redox-related metals and genetic variants with plasma metabolic patterns in a general population from Spain: The Hortega Study.

BACKGROUND: Limited studies have evaluated the joint influence of redox-related metals and genetic variation on metabolic pathways. We analyzed the association of 11 metals with metabolic patterns, and the interacting role of candidate genetic variants, in 1145 participants from the Hortega Study, a population-based sample from Spain. METHODS: Urine antimony (Sb), arsenic, barium (Ba), cadmium (Cd), chromium (Cr), cobalt (Co), molybdenum (Mo) and vanadium (V), and plasma copper (Cu), selenium (Se) and zinc (Zn) were measured by ICP-MS and AAS, respectively. We summarized 54 plasma metabolites, measured with targeted NMR, by estimating metabolic principal components (mPC). Redox-related SNPs (N = 291) were measured by oligo-ligation assay. RESULTS: In our study, the association with metabolic principal component (mPC) 1 (reflecting non-essential and essential amino acids, including branched chain, and bacterial co-metabolism versus fatty acids and VLDL subclasses) was positive for Se and Zn, but inverse for Cu, arsenobetaine-corrected arsenic (As) and Sb. The association with mPC2 (reflecting essential amino acids, including aromatic, and bacterial co-metabolism) was inverse for Se, Zn and Cd. The association with mPC3 (reflecting LDL subclasses) was positive for Cu, Se and Zn, but inverse for Co. The association for mPC4 (reflecting HDL subclasses) was positive for Sb, but inverse for plasma Zn. These associations were mainly driven by Cu and Sb for mPC1; Se, Zn and Cd for mPC2; Co, Se and Zn for mPC3; and Zn for mPC4. The most SNP-metal interacting genes were NOX1, GSR, GCLC, AGT and REN. Co and Zn showed the highest number of interactions with genetic variants associated to enriched endocrine, cardiovascular and neurological pathways. CONCLUSIONS: Exposures to Co, Cu, Se, Zn, As, Cd and Sb were associated with several metabolic patterns involved in chronic disease. Carriers of redox-related variants may have differential susceptibility to metabolic alterations associated to excessive exposure to metals.

Predicting Posttraumatic Stress Disorder Among Survivors of Recent Interpersonal Violence.

A substantial minority of women who experience interpersonal violence will develop posttraumatic stress disorder (PTSD). One critical challenge for preventing PTSD is predicting whose acute posttraumatic stress symptoms will worsen to a clinically significant degree. This 6-month longitudinal study adopted multilevel modeling and exploratory machine learning (ML) methods to predict PTSD onset in 58 young women, ages 18 to 30, who experienced an incident of physical and/or sexual assault in the three months prior to baseline assessment. Women completed baseline assessments of theory-driven cognitive and neurobiological predictors and interview-based measures of PTSD diagnostic status and symptom severity at 1-, 3-, and 6-month follow-ups. Higher levels of self-blame, generalized anxiety disorder severity, childhood trauma exposure, and impairment across multiple domains were associated with a pattern of high and stable posttraumatic stress symptom severity over time. Predictive performance for PTSD onset was similarly strong for a gradient boosting machine learning model including all predictors and a logistic regression model including only baseline posttraumatic stress symptom severity. The present findings provide directions for future work on PTSD prediction among interpersonal violence survivors that could enhance early risk detection and potentially inform targeted prevention programs.

Real-World Management and Clinical Outcomes of Stroke Survivors With Atrial Fibrillation: A Population-Based Cohort in Spain.

Objective: Despite the continuous update of clinical guidelines, little is known about the real-world management of patients with atrial fibrillation (AF) who survived a stroke. We aimed to assess patterns of therapeutic management of stroke survivors with AF and clinical outcomes using data from routine practice in a large population-based cohort. Methods: A population-based retrospective cohort study of all patients with AF who survived a stroke, from January 2010 to December 2017 in the Valencia region, Spain (n = 10,986), was carried out. Treatment strategies and mean time to treatment initiation are described. Temporal trends are shown by the management pattern during the study period. Factors associated with each pattern (including no treatment) vs. oral anticoagulant (OAC) treatment were identified using logistic multivariate regression models. Incidence rates of clinical outcomes (mortality, stroke/TIA, GI bleeding, and ACS) were also estimated by the management pattern. Results: Among stroke survivors with AF, 6% were non-treated, 23% were prescribed antiplatelets (APT), 54% were prescribed OAC, and 17% received OAC + APT at discharge. Time to treatment was 8.0 days (CI 7.6-8.4) for APT, 9.86 (CI 9.52-10.19) for OAC, and 16.47 (CI 15.86-17.09) for OAC + APT. Regarding temporal trends, management with OAC increased by 20%, with a decrease of 50% for APT during the study period. No treatment and OAC + APT remained relatively stable. The strongest predictor of no treatment and APT treatment was having the same management strategy pre-stroke. Those treated with APT had the highest rates of GI bleeding and recurrent stroke/TIA, and untreated patients showed the highest rates of mortality. Conclusion: In this large population-based cohort using real-world data, nearly 30% of AF patients who suffered a stroke were untreated or treated with APT, which overall is not recommended. Treatment was started within 2 weeks as recommended, except for OAC + APT, which was started later. The strong association of APT treatment or non-treatment with the same treatment strategy before stroke occurrence suggests a strong therapeutic inertia and opposes recommendations. Patients under these two strategies had the highest rates of adverse outcomes. An inadequate prescription poses a great risk on patients with AF and stroke; thus monitoring their management is necessary and should be setting-specific.

Predicting pain among female survivors of recent interpersonal violence: A proof-of-concept machine-learning approach.

Interpersonal violence (IPV) is highly prevalent in the United States and is a major public health problem. The emergence and/or worsening of chronic pain are known sequelae of IPV; however, not all those who experience IPV develop chronic pain. To mitigate its development, it is critical to identify the factors that are associated with increased risk of pain after IPV. This proof-of-concept study used machine-learning strategies to predict pain severity and interference in 47 young women, ages 18 to 30, who experienced an incident of IPV (i.e., physical and/or sexual assault) within three months of their baseline assessment. Young women are more likely than men to experience IPV and to subsequently develop posttraumatic stress disorder (PTSD) and chronic pain. Women completed a comprehensive assessment of theory-driven cognitive and neurobiological predictors of pain severity and pain-related interference (e.g., pain, coping, disability, psychiatric diagnosis/symptoms, PTSD/trauma, executive function, neuroendocrine, and physiological stress response). Gradient boosting machine models were used to predict symptoms of pain severity and pain-related interference across time (Baseline, 1-,3-,6- follow-up assessments). Models showed excellent predictive performance for pain severity and adequate predictive performance for pain-related interference. This proof-of-concept study suggests that machine-learning approaches are a useful tool for identifying predictors of pain development in survivors of recent IPV. Baseline measures of pain, family life impairment, neuropsychological function, and trauma history were of greatest importance in predicting pain and pain-related interference across a 6-month follow-up period. Present findings support the use of machine-learning techniques in larger studies of post-IPV pain development and highlight theory-driven predictors that could inform the development of targeted early intervention programs. However, these results should be replicated in a larger dataset with lower levels of missing data.