Biperiden for prevention of post-traumatic epilepsy: A protocol of a double-blinded placebo-controlled randomized clinical trial (BIPERIDEN trial).

BACKGROUND: Traumatic brain injury (TBI) is one of the most important causes of acquired structural epilepsy, post-traumatic epilepsy (PTE), however, efficient preventative measures and treatment are still not available to patients. Preclinical studies indicated biperiden, an anticholinergic drug, as a potential drug to modify the epileptogenic process. The main objective of this clinical trial is to evaluate the efficacy of biperiden as an antiepileptogenic agent in patients that suffered TBI. METHODS: This prospective multicenter (n = 10) interventional study will include 312 adult patients admitted to emergency care units with a diagnosis of moderate or severe TBI. Following inclusion and exclusion criteria, patients will be randomized, using block randomization, to receive double-blind treatment with placebo or biperiden for 10 days. Follow-up will occur at specific time windows up to 2 years. Main outcomes are incidence of PTE after TBI and occurrence of severe adverse events. Other outcomes include exploratory investigation of factors that might have benefits for the treatment or might influence its results, such as genetic background, clinical progression, electroencephalographic abnormalities, health-related quality of life and neuropsychological status. Analyses will be conducted following the safety, intention-to-treat and efficacy concepts. DISCUSSION: We hypothesize that biperiden treatment will be effective to prevent or mitigate the development of post-traumatic epilepsy in TBI patients. Other health measures from this population also may benefit from treatment with biperiden. TRIAL REGISTRATION: ClinicalTrials.gov, NCT04945213. Registered on June 30, 2021.

High quality (certainty) evidence changes less often than low-quality evidence, but the magnitude of effect size does not systematically differ between studies with low versus high-quality evidence.

RATIONALE, AIMS, AND OBJECTIVES: It is generally believed that evidence from low quality of evidence generate inaccurate estimates about treatment effects more often than evidence from high (certainty) quality evidence (CoE). As a result, we would expect that (a) estimates of effects of health interventions initially based on high CoE change less frequently than the effects estimated by lower CoE (b) the estimates of magnitude of effect size differ between high and low CoE. Empirical assessment of these foundational principles of evidence-based medicine has been lacking. METHODS: We reviewed the Cochrane Database of Systematic Reviews from January 2016 through May 2021 for pairs of original and updated reviews for change in CoE assessments based on the Grading of Recommendations Assessment, Development and Evaluation (GRADE) method. We assessed the difference in effect sizes between the original versus updated reviews as a function of change in CoE, which we report as a ratio of odds ratio (ROR). We compared ROR generated in the studies in which CoE changed from very low/low (VL/L) to moderate/high (M/H) versus M/H to VL/L. Heterogeneity and inconsistency were assessed using the tau and I2 statistic. We also assessed the change in precision of effect estimates (by calculating the ratio of standard errors) (seR), and the absolute deviation in estimates of treatment effects (aROR). RESULTS: Four hundred and nineteen pairs of reviews were included of which 414 (207 × 2) informed the CoE appraisal and 384 (192 × 2) the assessment of effect size. We found that CoE originally appraised as VL/L had 2.1 [95% confidence interval (CI): 1.19-4.12; p = 0.0091] times higher odds to be changed in the future studies than M/H CoE. However, the effect size was not different (p = 1) when CoE changed from VL/L → M/H [ROR = 1.02 (95% CI: 0.74-1.39)] compared with M/H → VL/L (ROR = 1.02 [95% CI: 0.44-2.37]). Similar overlap in aROR between the VL/L → M/H versus M/H → VL/L subgroups was observed [median (IQR): 1.12 (1.07-1.57) vs. 1.21 (1.12-2.43)]. We observed large inconsistency across ROR estimates (I2 = 99%). There was larger imprecision in treatment effects when CoE changed from VL/L → M/H (seR = 1.46) than when it changed from M/H → VL/L (seR = 0.72). CONCLUSIONS: We found that low-quality evidence changes more often than high CoE. However, the effect size did not systematically differ between the studies with low versus high CoE. The finding that the effect size did not differ between low and high CoE indicate urgent need to refine current EBM critical appraisal methods.

Open data and data sharing in articles about COVID-19 published in preprint servers medRxiv and bioRxiv.

This study aimed to analyze the content of data availability statements (DAS) and the actual sharing of raw data in preprint articles about COVID-19. The study combined a bibliometric analysis and a cross-sectional survey. We analyzed preprint articles on COVID-19 published on medRxiv and bioRxiv from January 1, 2020 to March 30, 2020. We extracted data sharing statements, tried to locate raw data when authors indicated they were available, and surveyed authors. The authors were surveyed in 2020-2021. We surveyed authors whose articles did not include DAS, who indicated that data are available on request, or their manuscript reported that raw data are available in the manuscript, but raw data were not found. Raw data collected in this study are published on Open Science Framework (https://osf.io/6ztec/). We analyzed 897 preprint articles. There were 699 (78%) articles with Data/Code field present on the website of a preprint server. In 234 (26%) preprints, data/code sharing statement was reported within the manuscript. For 283 preprints that reported that data were accessible, we found raw data/code for 133 (47%) of those 283 preprints (15% of all analyzed preprint articles). Most commonly, authors indicated that data were available on GitHub or another clearly specified web location, on (reasonable) request, in the manuscript or its supplementary files. In conclusion, preprint servers should require authors to provide data sharing statements that will be included both on the website and in the manuscript. Education of researchers about the meaning of data sharing is needed. Supplementary Information: The online version contains supplementary material available at 10.1007/s11192-022-04346-1.

Frequency, signs and symptoms, and criteria adopted for long COVID-19: A systematic review.

AIMS: To identify, systematically evaluate and summarise the best available evidence on the frequency of long COVID-19 (post-acute COVID-19 syndrome), its clinical manifestations, and the criteria used for diagnosis. METHODS: Systematic review conducted with a comprehensive search including formal databases, COVID-19 or SARS-CoV-2 data sources, grey literature, and manual search. We considered for inclusion clinical trials, observational longitudinal comparative and non-comparative studies, cross-sectional, before-and-after, and case series. We assessed the methodological quality by specific tools based on the study designs. We presented the results as a narrative synthesis regarding the frequency and duration of long COVID-19, signs and symptoms, criteria used for diagnosis, and potential risk factors. RESULTS: We included 25 observational studies with moderate to high methodological quality, considering 5440 participants. The frequency of long COVID-19 ranged from 4.7% to 80%, and the most prevalent signs/symptoms were chest pain (up to 89%), fatigue (up to 65%), dyspnea (up to 61%), and cough and sputum production (up to 59%). Temporal criteria used to define long COVID-19 varied from 3 to 24 weeks after acute phase or hospital discharge. Potentially associated risk factors were old age, female sex, severe clinical status, a high number of comorbidities, hospital admission, and oxygen supplementation at the acute phase. However, limitations related to study designs added uncertainty to this finding. None of the studies assessed the duration of signs/symptoms. CONCLUSION: The frequency of long COVID-19 reached up to 80% over the studies included and occurred between 3 and 24 weeks after acute phase or hospital discharge. Chest pain, fatigue, dyspnea, and cough were the most reported clinical manifestations attributed to the condition. Based on these systematic review findings, there is an urgent need to understand this emerging, complex and challenging medical condition. Proposals for diagnostic criteria and standard terminology are welcome.

Impact of Strategies for Mitigating Delays and Disruptions in Cancer Care Due to COVID-19: Systematic Review.

PURPOSE: Delays and disruptions in health systems because of the COVID-19 pandemic were identified by a previous systematic review from our group. For improving the knowledge about the pandemic consequences for cancer care, this article aims to identify the effects of mitigation strategies developed to reduce the impact of such delays and disruptions. METHODS: Systematic review with a comprehensive search including formal databases, cancer and COVID-19 data sources, gray literature, and manual search. We considered clinical trials, observational longitudinal studies, cross-sectional studies, before-and-after studies, case series, and case studies. The selection, data extraction, and methodological assessment were performed by two independent reviewers. The methodological quality of the included studies was assessed by specific tools. The mitigation strategies identified were described in detail and their effects were summarized narratively. RESULTS: Of 6,692 references reviewed, 28 were deemed eligible, and 9 studies with low to moderate methodological quality were included. Five multiple strategies and four single strategies were reported, and the possible effects of mitigating delays and disruptions in cancer care because of COVID-19 are inconsistent. The only comparative study reported a 48.7% reduction observed in the number of outpatient visits to the hospital accompanied by a small reduction in imaging and an improvement in radiation treatments after the implementation of a multiple organizational strategy. CONCLUSION: The findings emphasize the infrequency of measuring and reporting mitigation strategies that specifically address patients' outcomes and thus a scarcity of high-quality evidence to inform program development. This review reinforces the need of adopting standardized measurement methods to monitor the impact of the mitigation strategies proposed to reduce the effects of delays and disruptions in cancer health care because of COVID-19.

Delays and Disruptions in Cancer Health Care Due to COVID-19 Pandemic: Systematic Review.

PURPOSE: There has been noteworthy concern about the impact of COVID-19 pandemic on health services including the management of cancer. In addition to being considered at higher risk for worse outcomes from COVID-19, people with cancer may also experience disruptions or delays in health services. This systematic review aimed to identify the delays and disruptions to cancer services globally. METHODS: This is a systematic review with a comprehensive search including specific and general databases. We considered any observational longitudinal and cross-sectional study design. The selection, data extraction, and methodological assessment were performed by two independent reviewers. The methodological quality of the studies was assessed by specific tools. The delays and disruptions identified were categorized, and their frequency was presented. RESULTS: Among the 62 studies identified, none exhibited high methodological quality. The most frequent determinants for disruptions were provider- or system-related, mainly because of the reduction in service availability. The studies identified 38 different categories of delays and disruptions with impact on treatment, diagnosis, or general health service. Delays or disruptions most investigated included reduction in routine activity of cancer services and number of cancer surgeries; delay in radiotherapy; and delay, reschedule, or cancellation of outpatient visits. Interruptions and disruptions largely affected facilities (up to 77.5%), supply chain (up to 79%), and personnel availability (up to 60%). CONCLUSION: The remarkable frequency of delays and disruptions in health care mostly related to the reduction of the COVID-19 burden unintentionally posed a major risk on cancer care worldwide. Strategies can be proposed not only to mitigate the main delays and disruptions but also to standardize their measurement and reporting. As a high number of publications continuously are being published, it is critical to harmonize the upcoming reports and constantly update this review.