Efficacy of searching in biomedical databases beyond MEDLINE in identifying randomised controlled trials on hyperbaric oxygen treatment.

Introduction: Literature searches are routinely used by researchers for conducting systematic reviews as well as by healthcare providers, and sometimes patients, to quickly guide their clinical decisions. Using more than one database is generally recommended but may not always be necessary for some fields. This study aimed to determine the added value of searching additional databases beyond MEDLINE when conducting a literature search of hyperbaric oxygen treatment (HBOT) randomised controlled trials (RCTs). Methods: This study consisted of two phases: a scoping review of all RCTs in the field of HBOT, followed by a a statistical analysis of sensitivity, precision, 'number needed to read' (NNR) and 'number unique' included by individual biomedical databases. MEDLINE, Embase, Cochrane Central Register of Control Trials (CENTRAL), and Cumulated Index to Nursing and Allied Health Literature (CINAHL) were searched without date or language restrictions up to December 31, 2022. Screening and data extraction were conducted in duplicate by pairs of independent reviewers. RCTs were included if they involved human subjects and HBOT was offered either on its own or in combination with other treatments. Results: Out of 5,840 different citations identified, 367 were included for analysis. CENTRAL was the most sensitive (87.2%) and had the most unique references (7.1%). MEDLINE had the highest precision (23.8%) and optimal NNR (four). Among included references, 14.2% were unique to a single database. Conclusions: Systematic reviews of RCTs in HBOT should always utilise multiple databases, which at minimum include MEDLINE, Embase, CENTRAL and CINAHL.

DNA Bloom Filter enables anti-contamination and file version control for DNA-based data storage.

DNA storage is one of the most promising ways for future information storage due to its high data storage density, durable storage time and low maintenance cost. However, errors are inevitable during synthesizing, storing and sequencing. Currently, many error correction algorithms have been developed to ensure accurate information retrieval, but they will decrease storage density or increase computing complexity. Here, we apply the Bloom Filter, a space-efficient probabilistic data structure, to DNA storage to achieve the anti-error, or anti-contamination function. This method only needs the original correct DNA sequences (referred to as target sequences) to produce a corresponding data structure, which will filter out almost all the incorrect sequences (referred to as non-target sequences) during sequencing data analysis. Experimental results demonstrate the universal and efficient filtering capabilities of our method. Furthermore, we employ the Counting Bloom Filter to achieve the file version control function, which significantly reduces synthesis costs when modifying DNA-form files. To achieve cost-efficient file version control function, a modified system based on yin-yang codec is developed.

A study on pharmaceutical text relationship extraction based on heterogeneous graph neural networks.

Effective information extraction of pharmaceutical texts is of great significance for clinical research. The ancient Chinese medicine text has streamlined sentences and complex semantic relationships, and the textual relationships may exist between heterogeneous entities. The current mainstream relationship extraction model does not take into account the associations between entities and relationships when extracting, resulting in insufficient semantic information to form an effective structured representation. In this paper, we propose a heterogeneous graph neural network relationship extraction model adapted to traditional Chinese medicine (TCM) text. First, the given sentence and predefined relationships are embedded by bidirectional encoder representation from transformers (BERT fine-tuned) word embedding as model input. Second, a heterogeneous graph network is constructed to associate words, phrases, and relationship nodes to obtain the hidden layer representation. Then, in the decoding stage, two-stage subject-object entity identification method is adopted, and the identifier adopts a binary classifier to locate the start and end positions of the TCM entities, identifying all the subject-object entities in the sentence, and finally forming the TCM entity relationship group. Through the experiments on the TCM relationship extraction dataset, the results show that the precision value of the heterogeneous graph neural network embedded with BERT is 86.99% and the F1 value reaches 87.40%, which is improved by 8.83% and 10.21% compared with the relationship extraction models CNN, Bert-CNN, and Graph LSTM.

DNA as a universal chemical substrate for computing and data storage.

DNA computing and DNA data storage are emerging fields that are unlocking new possibilities in information technology and diagnostics. These approaches use DNA molecules as a computing substrate or a storage medium, offering nanoscale compactness and operation in unconventional media (including aqueous solutions, water-in-oil microemulsions and self-assembled membranized compartments) for applications beyond traditional silicon-based computing systems. To build a functional DNA computer that can process and store molecular information necessitates the continued development of strategies for computing and data storage, as well as bridging the gap between these fields. In this Review, we explore how DNA can be leveraged in the context of DNA computing with a focus on neural networks and compartmentalized DNA circuits. We also discuss emerging approaches to the storage of data in DNA and associated topics such as the writing, reading, retrieval and post-synthesis editing of DNA-encoded data. Finally, we provide insights into how DNA computing can be integrated with DNA data storage and explore the use of DNA for near-memory computing for future information technology and health analysis applications.

A transformer model with enhanced feature learning and its application in rotating machinery diagnosis.

Deep learning has become the prevailing trend of intelligent fault diagnosis for rotating machines. Compared to early-stage methods, deep learning methods use automatic feature extraction instead of manual feature design. However, conventional intelligent diagnosis models are trapped by a dilemma that simple models are unable to tackle difficult cases, while complicated models are likely to over-parameterize. In this paper, a transformer-based model, Periodic Representations for Transformers (PRT) is proposed. PRT uses a dense-overlapping split strategy to enhance the feature learning inside sequence patches. Combined with the inherent capability of capturing long range dependencies of transformer, and the further information extraction of class-attention, PRT has excellent feature extraction abilities and could capture characteristic features directly from raw vibration signals. Moreover, PRT adopts a two-stage positional encoding method to encode position information both among and inside patches, which could adapt to different input lengths. A novel inference method to use larger inference sample sizes is further proposed to improve the performance of PRT. The effectiveness of PRT is verified on two datasets, where it achieves comparable and even better accuracies than the benchmark and state-of-the-art methods. PRT has the least FLOPs among the best performing models and could be further improved by the inference strategy, reaching an accuracy near 100%.

Database coverage and their use in systematic reviews regarding spinal manipulative therapy: an exploratory study.

BACKGROUND: Systematic reviews (SRs) of randomized controlled trials (RCTs) are considered one of the most reliable study types. Through a systematic and thorough literature search, researchers aim to collect all research relevant to their purpose. The selection of databases can be challenging and depend on the topic of interest. The Cochrane Handbook suggests searching at least the following three databases: Cochrane Library, MEDLINE, and EMBASE. However, this is not always sufficient for reviews on the musculoskeletal field in general. This study aimed to examine the frequency and choice of databases used by researchers in SRs of spinal manipulative therapy (SMT). Secondly, to analyze the RCTs included in the SRs to determine the optimal combination of databases needed to conduct efficient literature searches for SRs of SMT. METHODS: SRs investigating the effect of SMT on any patient-reported outcome measure were identified through searches in PubMed and Epistemonikos (all entries till date of search February 25, 2022). For each SR, databases searched and included RCTs were collected. RCTs were searched individually in nine databases (Cochrane Library, MEDLINE/PubMed, EMBASE, Google Scholar, CINAHL, Web of Science, Index to Chiropractic Literature, PEDro, and AMED). Coverage rates were calculated using the number of retrieved RCTs by the database or combinations of databases divided by the total number of RCTs. RESULTS: Eighty-five SRs published met the inclusion criteria, and 442 unique RCTs were retrieved. The most frequently searched database was MEDLINE/PubMed. Cochrane Library had the highest overall coverage rate and contained the third most unique RCTs. While a 100% retrieval was not possible, as 18 RCTs could not be retrieved in any of the nine databases, the combination of Cochrane Library, Google Scholar, and PEDro retrieved all possible RCTs with a combined coverage rate of 95.9%. CONCLUSIONS: For SRs on SMT, we recommend using the combination suggested by the Cochrane Handbook of Cochrane Library, MEDLINE/PubMed, Embase, and in addition, PEDro and Index to Chiropractic Literature. Google Scholar might be used additionally as a tool for searching gray literature and quality assurance.

Data resource profile: children looked after administrative records in Wales.

Introduction: Children who are 'looked after' by the State are considered one of the most vulnerable groups in society. Being in State care is associated with poor social, educational and health outcomes. Exploring how to improve the system and better support children in care is key to improving these outcomes. When children and young people come to the attention of children's social services a significant amount of information about their care experience is routinely collected by local authorities. In Wales, routine data are captured in the 'Children Looked After' Census which is submitted annually to the Welsh Government and has recently been shared with the Secure Anonymised Information Linkage (SAIL) Databank. Method: The aim of this paper is to provide an overview of the main 'Children Looked After' Census dataset and its subsets. These datasets contain rich, situational and individual level data on children looked after, such as information on placement types, education and leaving care. We outline the strengths and limitations of the available information and how to access the data. Results: The 'Children Looked After' Census has recently been made available for research purposes and access to it will enable researchers to explore and understand at population level the journey through the care system and outcomes of leaving care. There is also the opportunity, through the SAIL Databank, for data linkage to health, education and family justice datasets, allowing research to holistically explore other factors associated with being in care. Conclusion: These data provide a rich source of information about children and young people who have been in care in Wales. They offer researchers opportunities to better understand the care system and outcomes for this within it. Findings will have important implications for making improvements in children's social care policy and practice.

Compliance with recommended cancer patient pathway timeframes and choice of treatment differed by cancer type and place of residence among cancer patients in Norway in 2015-2016.

BACKGROUND: Cancer patient pathways (CPPs) were implemented in Norway to reduce unnecessary waiting times, regional variations, and to increase the predictability of cancer care for the patients. This study aimed to determine if 70% of cancer patients started treatment within the recommended time frames, and to identify potential delays. METHODS: Patients registered with a colorectal, lung, breast, or prostate cancer diagnosis at the Cancer Registry of Norway in 2015-2016 were linked with the Norwegian Patient Registry and Statistics Norway. Adjusting for sociodemographic variables, multivariable quantile (median) regressions were used to examine the association between place of residence and median time to start of examination, treatment decision, and start of treatment. RESULTS: The study included 20 668 patients. The proportions of patients who went through the CPP within the recommended time frames were highest among colon (84%) and breast (76%) cancer patients who underwent surgery and lung cancer patients who started systemic anticancer treatment (76%), and lowest for prostate cancer patients who underwent surgery (43%). The time from treatment decision to start of treatment was the main source of delay for all cancers. Travelling outside the resident health trust prolonged waiting time and was associated with a reduced odds of receiving surgery and radiotherapy for lung and rectal cancer patients, respectively. CONCLUSIONS: Achievement of national recommendations of the CCP times differed by cancer type and treatment. Identified bottlenecks in the pathway should be targeted to decrease waiting times. Further, CPP guidelines should be re-examined to determine their ongoing relevance.

The impact of symptom severity on the humanistic and economic burden of inflammatory bowel disease: a real-world data linkage study.

OBJECTIVE: Few studies have examined the association between inflammatory bowel disease (IBD) severity, and humanistic, and economic burden. We addressed this gap using a unique real-world data source that links self-reported patient data from the US National Health and Wellness Survey (NHWS) to claims data. METHODS: This cross-sectional study linked the 2015-2018 US NHWS data with medical, and pharmacy claims. Patients (≥18 years) who self-reported a physician diagnosis of IBD (ulcerative colitis [UC], or Crohn's disease [CD]) in the NHWS, and had a medical or pharmacy claim indicating a possible diagnosis of IBD were included. Disease symptom severity was defined by a weighted symptom score and main outcomes include health-related quality of life (HRQoL), work productivity (WPAI), healthcare resource use (HRU), and associated costs. RESULTS: Overall, 687 patients with IBD were included, of which 347 were identified with UC and 340 with CD. Validation analysis showed that 94.7% of UC and 88.7% of patients with CD who self-reported diagnosis of CD or UC in NHWS had evidence of diagnosis and/or treatment patterns in claims. Patients with both UC and CD with moderate or severe symptoms had significantly lower HRQoL, increased work productivity loss, greater HRU, and associated costs compared with patients with mild symptoms. CONCLUSIONS: Patients with moderate/severe UC or CD experience substantial humanistic, and economic burden compared with patients with mild UC or CD. These factors should be considered within treatment goals for patients in order to provide holistic care beyond the treatment of objective markers or disease severity and symptoms alone.

Optimal Measures for Primary Care Physician Encounters after Stroke and Association with Survival: A Data Linkage Study.

BACKGROUND AND PURPOSE: Primary care physicians (PCPs) provide ongoing management after stroke. However, little is known about how best to measure physician encounters with reference to longer term outcomes. We aimed to compare methods for measuring regularity and continuity of PCP encounters, based on survival following stroke using linked healthcare data. METHODS: Data from the Australian Stroke Clinical Registry (2010-2014) were linked with Australian Medicare claims from 2009 to 2016. Physician encounters were ascertained within 18 months of discharge for stroke. We calculated three separate measures of continuity of encounters (consistency of visits with primary physician) and three for regularity of encounters (distribution of service utilization over time). Indices were compared based on 1-year survival using multivariable Cox regression models. The best performing measures of regularity and continuity, based on model fit, were combined into a composite "optimal care" variable. RESULTS: Among 10,728 registrants (43% female, 69% aged ≥65 years), the median number of encounters was 17. The measures most associated with survival (hazard ratio [95% confidence interval], Akaike information criterion [AIC], and Bayesian information criterion [BIC]) were the Continuity of Care Index (COCI, as a measure of continuity; 0.88 [0.76-1.02], p = 0.099, AIC = 13,746, BIC = 13,855) and our persistence measure of regularity (encounter at least every 6 months; 0.80 [0.67-0.95], p = 0.011, AIC = 13,742, BIC = 13,852). Our composite measure, persistent plus COCI ≥80% (24% of registrants; 0.80 [0.68-0.94], p = 0.008, AIC = 13,742, BIC = 13,851), performed marginally better than our persistence measure alone. CONCLUSIONS: Our persistence measure of regularity or composite measure may be useful when measuring physician encounters following stroke.

Ten-year trends in cardiac implantable electronic devices in New Zealand: a national data linkage study (ANZACS-QI 51).

BACKGROUND: Implant rates for cardiac implantable electronic devices (CIED), including permanent pacemakers (PPM) and implantable cardioverter defibrillators (ICD), have increased globally in recent decades. AIMS: This is the first national study providing a contemporary analysis of national CIED implant trends by sex-specific age groups over an extended period. METHODS: Patient characteristics and device type were identified for 10 years (2009-2018) using procedure coding in the National Minimum Datasets, which collects all New Zealand (NZ) public hospital admissions. CIED implant rates represent implants/million population. RESULTS: New PPM implant rates increased by 4.6%/year (P < 0.001), increasing in all age groups except patients <40 years. Males received 60.1% of new PPM implants, with higher implant rates across all age groups compared with females. The annual increase in age-standardised implant rates was similar for males and females (3.4% vs 3.0%; P = 0.4). By 2018 the overall PPM implant rate was 538/million. New ICD implant rates increased by 4.2%/year (P < 0.001), increasing in all age groups except patients <40 and ≥ 80 years. Males received 78.1% of new ICD implants, with higher implant rates across all age groups compared to females. The annual increase in age-standardised implant rates was higher in males compared with females (3.5% vs 0.7%; P < 0.001). By 2018 the overall ICD implant rate was 144/million. CONCLUSION: CIED implant rates have increased steadily in NZ over the past decade but remain low compared with international benchmarks. Males had substantially higher CIED implant rates compared with females, with a growing gender disparity in ICD implant rates.

[Report standards for clinical comprehensive evaluation of Chinese patent medicine].

The clinical comprehensive evaluation of drugs is an important basis for the return of clinical value, decision-making of medical and health authorities, and allocation of medical resources. In July 2021, the National Health Commission issued the Guidelines for the Management of Clinical Comprehensive Evaluation of Drugs(trial version 2021), which required the evaluation to be implemented from the six dimensions(safety, effectiveness, economy, innovation, suitability, and accessibility), and made detailed arrangements for the clinical comprehensive evaluation of drugs. As Chinese patent medicine differs from chemical medicines in terms of effective components and action modes, the clinical comprehensive evaluation of Chinese patent medicine should highlight the characteristics and advantages of traditional Chinese medicine(TCM) on the basis of general requirements of comprehensive clinical evaluation of drugs. At present, in the clinical comprehensive evaluation of Chinese patent medicine, unified report standards have not yet been generated, resulting in the uneven quality of existing reports. To standardize the clinical comprehensive evaluation report of Chinese patent medicine and improve its quality, the editorial team, based on the relevant policy documents of clinical comprehensive evaluation of drugs, formulated the clinical comprehensive evaluation report standards for Chinese patent medicine in combination with the previous practice and expert opinions. The report standards, containing seven sections with 15 items determined, focus on data source, evaluation content, evidence synthesis, quality control, and evaluation results supported with detailed interpretations to help researchers better understand and apply the report standards for clinical comprehensive evaluation of Chinese patent medicine, improve the report quality, and provide references for the decision-making by the national medical management authorities.

Quantifying the Costs to Different Funders over Five-Years for Women Diagnosed with Breast Cancer in Queensland, Australia: A Data Linkage Study.

Individuals diagnosed with breast cancer have the highest rates of survival among all cancer types. Due to high survival, the costs of breast cancer to different healthcare funders are of interest. This study aimed to describe the cost to public hospital and private health funders and individuals due to hospital and emergency department (ED) admissions, as well Medicare items and pharmaceuticals over five years for Queensland women with breast cancer. We used a linked administrative dataset, CancerCostMod, limited to Queensland female breast cancer diagnoses between July 2011 and June 2013 aged 18 years or over who survived for 5 years (n = 5383). Each record was linked to Queensland Health Admitted Patient Data Collection, Emergency Department Information Systems, Medicare Benefits Schedule, and Pharmaceutical Benefits Scheme records between July 2011 and June 2018. Total costs for different healthcare funders as a result of breast cancer diagnoses were reported, with high costs and service use identified in the first six months following a breast cancer diagnosis. After the first six months post-diagnosis, the financial burdens incurred by different healthcare funders for breast cancer diagnoses in Queensland remain steady over a long period. Recommendations for reducing long term costs are discussed.

E-cigarette-associated Severe Pneumonia in Korea Using Data Linkage between the Korea National Health and Nutrition Examination Survey (KNHANES, 2013-2019) and the National Health Insurance Service (NHIS) Claims Database.

BACKGROUND: This study aimed to investigate the association between e-cigarette (EC) use and development of acute severe pneumonia in the Korean population using a national database. METHODS: We conducted a retrospective analysis using linkage of data between the Korean National Health and Nutrition Examination Survey (KNHANES) and the National Health Insurance Service (NHIS) administrative claims database. The primary endpoint of this study was development of severe pneumonia requiring hospital admission according to EC use during the study period. The secondary endpoints were in-hospital mortality, intensive care unit (ICU) admission, ventilator care, and days of hospital stay. RESULTS: The final analysis included 28,950 individuals, of which 578 (2.0%) were EC users. EC users were younger and more often male than non-EC users. The EC users showed higher level of education and household income and had fewer comorbidities. Severe pneumonia was noted in 37 of 28,372 non-EC users (0.13%), but there were no occurrences of severe pneumonia in EC users. The incidence of pneumonia occurrence was not different between the two groups (P = 1.000). CONCLUSIONS: Since e-cigarette or vaping use-associated lung injury (EVALI) is most likely included in acute severe pneumonia occurring within 3 months of EC use, it is considered that there might be no EVALI patients in Korea during the investigation period. A large-scale, prospective study is necessary to evaluate the association between EC use and acute lung injury.

Effect of nutritionally modified infant formula on academic performance: linkage of seven dormant randomised controlled trials to national education data.

OBJECTIVE: To compare differences in academic performance between adolescents who were randomised in infancy to modified or standard infant formula. DESIGN: Linkage of seven dormant randomised controlled trials to national education data. SETTING: Five hospitals in England, 11 August 1993 to 29 October 2001, and schools in England, September 2002 to August 2016. PARTICIPANTS: 1763 adolescents (425 born preterm, 299 born at term and small for gestational age, 1039 born at term) who took part in one of seven randomised controlled trials of infant formula in infancy. INTERVENTIONS: Nutrient enriched versus standard term formula (two trials), long chain polyunsaturated fatty acid (LCPUFA) supplemented versus unsupplemented formula (two trials), high versus low iron follow-on formula (one trial), high versus low sn-2 palmitate formula (one trial), and nucleotide supplemented versus unsupplemented formula (one trial). MAIN OUTCOME MEASURES: The primary outcome, determined by linkage of trial data to school data, was the mean difference in standard deviation scores for mandated examinations in mathematics at age 16 years. Secondary outcomes included differences in standard deviation scores in English (16 and 11 years) and mathematics (11 years). Analysis was by intention to treat with multiple imputation for participants missing the primary outcome. RESULTS: 1607 (91.2%) participants were linked to school records. No benefit was found for performance in mathematics examinations at age 16 years for any modified formula: nutrient enriched in preterm infants after discharge from hospital, standard deviation score 0.02 (95% confidence interval -0.22 to 0.27), and nutrient enriched in small for gestational age term infants -0.11 (-0.33 to 0.12); LCPUFA supplemented in preterm infants -0.19 (-0.46 to 0.08) and in term infants -0.14 (-0.36 to 0.08); iron follow-on formula in term infants -0.12 (-0.31 to 0.07); and sn-2 palmitate supplemented formula in term infants -0.09 (-0.37 to 0.19). Participants from the nucleotide trial were too young to have sat their General Certificate of Secondary Education (GCSE) examinations at the time of linkage to school data. Secondary outcomes did not differ for nutrient enriched, high iron, sn-2 palmitate, or nucleotide supplemented formulas, but at 11 years, preterm and term participants randomised to LCPUFA supplemented formula scored lower in English and mathematics. CONCLUSIONS: Evidence from these randomised controlled trials indicated that the infant formula modifications did not promote long term cognitive benefit compared with standard infant formulas.

AMFormulaS: an intelligent retrieval system for traditional Chinese medicine formulas.

BACKGROUND: Formula is an important means of traditional Chinese medicine (TCM) to treat diseases and has great research significance. There are many formula databases, but accessing rich information efficiently is difficult due to the small-scale data and lack of intelligent search engine. METHODS: We selected 38,000 formulas from a semi-structured database, and then segmented text, extracted information, and standardized terms. After that, we constructed a structured formula database based on ontology and an intelligent retrieval engine by calculating the weight of decoction pieces of formulas. RESULTS: The intelligent retrieval system named AMFormulaS (means Ancient and Modern Formula system) was constructed based on the structured database, ontology, and intelligent retrieval engine, so the retrieval and statistical analysis of formulas and decoction pieces were realized. CONCLUSIONS: AMFormulaS is a large-scale intelligent retrieval system which includes a mass of formula data, efficient information extraction system and search engine. AMFormulaS could provide users with efficient retrieval and comprehensive data support. At the same time, the statistical analysis of the system can enlighten scientific research ideas and support patent review as well as new drug research and development.

Comparative Effectiveness Research for CAR-T Therapies in Multiple Myeloma: Appropriate Comparisons Require Careful Considerations of Data Sources and Patient Populations.

BACKGROUND AND OBJECTIVE: Registrational trials for ciltacabtagene autoleucel [cilta-cel]) and idecabtagene vicleucel [ide-cel] chimeric antigen receptor T-cell (CAR-T) therapies were single-arm studies conducted with relapse refractory multiple myeloma (MM) patients who were triple-class-exposed (TCE) or triple-class-refractory (TCR). It is critical for researchers conducting comparative effectiveness research (CER) to carefully consider the most appropriate data sources and comparable patient populations. The aim of this study was to identify potential data sources and populations for comparing to single-arm CAR-T trials CARTITUDE-1 (cilta-cel) and KarMMa (ide-cel). METHODS: A 2-part global systematic literature search produced a review of (1) clinical trials of National Comprehensive Cancer Network (NCCN) guideline preferred regimens in previously treated MM, and (2) real-world data cohorts of TCE or TCR populations, published between 1/1/2015 and 12/10/2020, with sample sizes of > 50 patients and reporting survival-related outcomes. Implications on CER and accepted best practices are discussed. RESULTS: Nine clinical trials of NCCN preferred regimens were identified along with five real-world data-based publications. No clinical trials evaluated patients with TCE or TCR MM. Among the real-world data-based publications, two evaluated patients exclusively with TCR MM, two analyzed a mixed population of patients with TCE or TCR MM, and one publication assessed patients exclusively with TCE MM. Real-world data treatment patterns were heterogeneous. CONCLUSION: Current NCCN preferred regimens were not specifically studied in TCE or TCR MM patients, although some studies do include a proportion of these types of patients. Therefore, appropriate matching of populations using either real-world data or patient level clinical trial data is critical to putting trials of novel CAR-Ts (i.e., CARTITUDE-1 or KarMMa) into appropriate comparative context.

Multimorbidity in Antineutrophil Cytoplasmic Antibody-Associated Vasculitis: Results From a Longitudinal, Multicenter Data Linkage Study.

OBJECTIVE: Antineutrophil cytoplasmic antibody-associated vasculitis (AAV) is considered a chronic, relapsing condition. To date, no studies have investigated multimorbidity in AAV nationally. This study was undertaken to characterize temporal trends in multimorbidity and report excess health care expenditures associated with multimorbidities in a national AAV cohort from Scotland. METHODS: Eligible patients with AAV were diagnosed between 1997 and 2017. Each patient was matched with up to 5 general population controls. Linked morbidity and health care expenditure data were retrieved from a Scottish national hospitalization repository and from published national cost data. Multimorbidity was defined as the development of ≥2 disorders. Prespecified morbidities, individually and together, were analyzed for risks and associations over time using modified Poisson regression, discrete interval analysis, and chi-square test for trend. The relationship between multimorbidities and health care expenditure was investigated using multivariate linear regression. RESULTS: In total, 543 patients with AAV (median age 58.7 years [range 48.9-68.0 years]; 53.6% male) and 2,672 general population controls (median age 58.7 years [range 48.9-68.0 years]; 53.7% male) were matched and followed up for a median of 5.1 years. AAV patients were more likely to develop individual morbidities at all time points, but especially <2 years after diagnosis. The highest proportional risk observed was for osteoporosis (adjusted incidence rate ratio 8.0, 95% confidence interval [95% CI] 4.5-14.2). After 1 year, 23.0% of AAV patients and 9.3% of controls had developed multimorbidity (P < 0.0001). After 10 years, 37.0% of AAV patients and 17.3% of controls were reported to have multimorbidity (P < 0.0001). Multimorbidity was associated with disproportionate increases in health care expenditures in AAV patients. Health care expenditure was highest for AAV patients with ≥3 morbidities (3.89-fold increase in costs, 95% CI 2.83-5.31; P < 0.001 versus no morbidities). CONCLUSION: These findings emphasize the importance of holistic care in patients with AAV, and may identify a potentially critical opportunity to consider early screening.

Impact of literature reports on drug safety signals.

BACKGROUND: Signal management is considered an important activity in pharmacovigilance and should be performed using any available source of data, including scientific literature. The main aim of this study was to assess the role of scientific literature in both indexed and unindexed journals and compare the relevance of both in the signal management process. METHODS: The study was a retrospective analysis of safety data. For the purposes of the study, drugs for which safety signals were evaluated by European Medicine Agency (EMA) were chosen. A match analysis of data collected in the EudraVigilance (EV) database with data from bibliographic databases such as MEDLINE, Embase or EBSCO (International Pharmaceutical Abstracts, IPA and the Allied and the Complementary Medicine Database, AMED) was performed. RESULTS: A total of 73 drug event associations (DEA) and 4160 individual case safety reports (ICSRs) were analyzed. About 33% of ICSRs were created based on scientific literature. A total of 1196 ICSRs were submitted to the EV database based on journals indexed in global bibliographic databases Embase (86.00%) or MEDLINE (81.96%) or EBSCO (IPA or AMED, 0.66%). CONCLUSION: This study underlines the importance of scientific literature for the signal management process in addition to other data sources. Most literature ICSRs from this analysis were created based on scientific journals indexed in bibliographic databases; therefore, it can be concluded that a systematic review of bibliographic databases, such as Embase or MEDLINE is highly relevant for the signal management process.