Clinical trials that fail prematurely due to poor design are a waste of resources and deprives us of data for evaluating potentially effective interventions. This study used machine learning modelling to predict clinical trials’ success or failure and to understand feature contributions driving this result. Features to power the modelling were engineered using data collected from the National Institute for Health and Care Research Innovation Observatory’s ScanMedicine database.

Using ScanMedicine, a large dataset containing 641,079 clinical trial records from 11 global clinical trial registries, was extracted. Sixteen features were generated from the data based on fields relating to trial design and eligibility. Trials were labeled positive if they were completed (or target recruitment was achieved) or negative if terminated/withdrawn (or target recruitment was not achieved). To achieve optimal performance, phase-specific datasets were generated, and we focused on a subsample of Phase 2 trials (n=70,167). Ensemble models using bagging and boosting algorithms, including balanced random forest and extreme gradient boosting classifiers were used for training and evaluating predictive performance. Shapley Additive Explanations was used to explain the output of the best performing model and calculate feature contributions for individual studies.

We achieved a weighted F1-score of 0.88, Receiver Operator Characteristic Area under the Curve score of 0.75, and balanced accuracy of 0.75 on the test set with the xgBoost model. This result shows that the model can successfully distinguish between classes to predict if a trial will succeed or fail and subsequently output the features driving this outcome. The number of primary outcomes, whether the study was randomized, target sample size and number of exclusion criteria were the most important features affecting the model’s prediction.

This study is the first to use predictive modelling on a large sample of clinical trial data obtained from 11 international trial registries. The prediction outcomes achieved by our novel approach, which uses phase-specific trained models, outperforms previous modelling in this space.

The recent National Institute for Health and Care Excellence (NICE) consultation on methods for health technology evaluation (HTE) outlined plans to include guidance on the role of real-world evidence (RWE) in HTE. This is particularly pertinent for interventions where the evidence base consists of a single arm trial (SAT) design, which is more frequently observed in oncology. This study reviewed the influence of RWE submitted as part of the evidence base for NICE oncology appraisals.

A search for NICE HTEs was conducted for interventions supported by SATs from January 2017-November 2021. Evidence was stratified by submission packages with SAT evidence alone or in combination with randomized controlled trial (RCT) evidence, with or without RWE.

Thirty-two decisions for interventions supported by SATs were made by NICE between 2017-2021, all in oncology indications. Fifty percent were supported by SAT evidence and fifty percent by RCT plus SAT evidence, both with or without RWE. A lower proportion of RCT/ SAT HTEs submitted RWE compared to SAT HTEs (fifty vs ninety four percent). Seventy five percent and nineteen percent of SAT HTEs received a positive recommendation, with and without restrictions, irrespective of submitting RWE. One negative decision was observed for SATs supported by RWE. Sixty three percent and thirty eight percent of RCT/ SAT HTEs received a positive recommendation, with and without restrictions. Overall, the proportion of positive recommendations were lower for HTEs submitting RWE (ninety six percent) compared to HTEs not submitting RWE (one hundred percent), which is in contrast to recent findings specific to orphan oncology HTEs (one hundred versus seventy eight percent).

RWE was more commonly submitted to support SAT HTEs, than RCT HTEs. The use of RWE seems to be established as a necessity to supplement a SAT evidence base, whereas RWE is more generally a nice to have in RCT HTEs. However, RWE appears to positively influence decision-making for orphan oncology indications with a more neutral influence for non-orphan indications.

The Brazilian government has made efforts in systems to generate data from medical devices (MD). This work explores the main systems and data sources in the perspective of contributing as a source to generate real world data (RDW).

Document review of relevant national data sources for MD. In addition, a structured search was carried out in EMBASE using key descriptors for RWD applied to the regulatory context and to the management of health technologies, without date or language restrictions.

Eighteen primary federal government data sources for MD were identified. Not all sources are publicly accessible. Of the articles, the search returned 1,185 results, of which 29 titles were selected and 8 met the protocol’s objective. Included articles were from Europe, the United States and Canada. As in other countries, Brazil initially systematized DM administrative data to meet commercial and financial demands. With the evolution of health technology assessment methods, the use of RDW has become imperative to assess the value of MD to society. Common examples from these countries are implantable MD databases. Current challenges focus on data linkage and quality, in addition to standardized naming. The adoption of the Unique Device Identification (UDI) is one of the promising initiatives to facilitate traceability throughout the lifecycle proposed in the International Medical Device Regulators Forum (IMDRF) of which Brazil is a member. Among the systems, the following stand out: i) ConectSUS, which intends to provide access to health information centered on the patient, anywhere and at any time; ii) National implant registry that generates data on implanted prostheses and stents, surgical techniques used, the profile of patients and the health services involved.

This work showed the similarities between Brazil and other countries in the management of MD data throughout its life cycle, as well as mapped the national primary data sources for MD.

Prostate cancer was the second most frequent cancer and the fifth leading cause of cancer death among men in 2020. The incidence rates vary substantially in countries with different Human Development Indexes (HDI), while the mortality rates decrease with improved access to the health system, availability of therapies and earlier detection. Worldwide, population-based cancer registries are important tools for planning and managing health systems. The Fundação Oncocentro de São Paulo (FOSP) is responsible to collect, clean and publicize data from cancer treatment institutions. This study aimed to describe retrospectively the demographic and clinical profile of prostate cancer (PC) in Brazil using this database. It is not an incidence study as data is representative only from specific institutions.

This was a retrospective observational study of the years 2000 to 2020 from analysis of the publicly available FOSP database (http://www.fosp.saude.sp.gov.br).

The records were extracted, merged, and cleaned using a fully documented and validated data process. Only patients included on the register with a primary PC diagnosis were considered.

From January 2010 to June 2020, there were 943,660 patients diagnosed with C61 in FOSP database for the considered time period. The majority of the FOSP database records are from patients who live and/or were born in SP (91.8 and 58.4%, respectively) or MG (2.8 and 10.5%, respectively). The mean age of PC at baseline was 69 years. Considering the stage of the disease, the mean ages are 55, 70, 67, 66 and 61, for stages 0, 1, 2, 3 and 4, respectively. This cohort was also analyzed in relation to treatments received, and status at the end of treatment (51.3% are disease-free, 18.4% are alive with cancer, and 30.3% are dead).

FOSP population-based cancer registries are a powerful tool to obtain information for planning, and improving the management of healthcare services especially for São Paulo.

The National Institute for Health and Care Excellence (NICE) intends to increasingly use real-world evidence in developing guidance. To increase trust in such evidence, NICE has developed a framework for developing and assessing real-world evidence studies, including understanding the value of the selected data source for the decision problem.

Starting with published high-quality studies about data quality, we developed a conceptual model of the elements needed to understand the quality of a data source. Results from a literature search were then mapped to the model. We used this to design a structured reporting tool, the data Suitability Assessment Tool (dataSAT), and tested it in several cases studies. Additionally, we engaged with internal and external stakeholders to obtain feedback on the tool and revised it accordingly.

DataSAT covers provenance of the data, assessment of data quality, and the data’s relevance to the research question. For data provenance, information is requested about the data source independent of the study’s interests, including the purpose, setting, dates of operation, funding, data specification, and management and quality assurance plans for the data sources. Data quality is covered by quantitively assessing the completeness and accuracy of the following key study elements to inform critical appraisal of the study: population inclusion and exclusion criteria; intervention; comparator; and outcomes and key covariates. The findings on data sources and data quality are then interpreted in terms of relevance to the decision problem. This includes relevance to the population in the United Kingdom, the treatment pathway and care setting, the availability of key study elements, time-related factors such as length of follow up, and the effects of sample size and missing data on the validity of findings.

DataSAT allows summary information on source data, including quality and relevance, to be reported in a structured manner, enabling decision makers to better understand how the data influence the robustness of analyses used in health technology assessment. This helps increase trust in the use of real-world evidence.

Recent reviews have shown that many real-world evidence (RWE) studies suffer from avoidable methodological flaws. Meanwhile, the National Institute for Health and Care Excellence (NICE) is seeing an increase in RWE submissions in Health Technology Appraisals and is keen to support the use of this evidence. However, limited guidance exists for the development and assessment of RWE, risking both missed opportunities for unbiased evidence generation and inconsistent decision making based on that evidence. As part of its RWE framework, NICE has developed methods guidance to provide clear expectations for the conduct and reporting of non-randomized comparative effects studies using real world data.

A conceptual model and draft framework were developed based on established international best practices in RWE and observational research. This was refined with focused literature searches, for example, on the use of external control arm studies. We then engaged with external stakeholders to incorporate their feedback and develop case studies. A reporting template was developed and tested on multiple use cases.

The guidance stresses the central importance of a target trial approach to study design, e.g., adopting an active comparator, new user design, where possible. Target trial emulation is a useful tool to improve the quality and transparency of RWE studies, helping to overcome selection and confounding biases. Various other study design and analytical approaches are outlined for addressing confounding bias and biases due to missing data, measurement error, or misclassification, which are common challenges in RWE. Alongside traditional approaches to sensitivity analysis, the framework promotes quantitative bias analyses which includes a range of methods to assess and communicate the potential impact of remaining bias to study findings by quantifying the direction, magnitude, and uncertainty of bias. A reporting template, based on common methodological pitfalls, is provided to help evidence developers consider key areas of bias in their work and to inform reviewers of any approaches used to investigate or resolve these.

Randomized controlled trials (RCTs) are typically considered the gold standard source of clinical evidence for reimbursement submissions, but they can often be resource-intensive, expensive, and may not always be appropriate. For example, it may be unethical to assign patients to an untreated or undiagnosed control group, or blinding may not be feasible when assessing medical devices. Evidence for medical devices is therefore often limited to nonrandomized studies. We explored the use and value of real-world evidence (RWE) in the reimbursement of medical devices across several health technology assessment (HTA) agencies.

A narrative review was completed to compare the acceptability of RWE for the HTA evaluation of medical devices across a convenience sample of countries. English-language published guidance documents were reviewed, and study design preferences extracted.

In Australia, France, Germany, Ireland, Norway, and Scotland, HTA agencies prefer RCT evidence but accept RWE as supporting data. In England, there is no preferred study design, with directly observed clinical outcomes, evidence syntheses, nonclinical, and modelling studies accepted. Notably, methods and processes for HTA programs are being reviewed and are expected to place a greater emphasis on RWE. In Australia, pseudo-randomized trials, comparative cohort studies, case series, and other study designs are permitted. In France, nonrandomized or nonblinded trials, patient preference cohorts, prospective comparative observational studies, and propensity score matched cohorts are permitted, accompanied by justification. In Scotland, lived experiences, RWE, and systematic reviews are accepted. In Germany, nonrandomized studies are deemed to provide “minimum”, “very low” or “low” certainty of results. In Norway, RWE may be accepted if no RCT data are available, or to support RCTs.

In the assessment of medical devices, where RCTs are unsuitable, RWE can form a feasible alternative. Real-world evidence is increasingly being recognized as a valuable source of evidence for medical interventions and is accepted by a number of HTA agencies. No funding was received for this study.

Appropriate resource utilization is crucial for cancer screening programs. Overscreening is defined as screening provided beyond the upper age limit of the target age or at a shorter interval than recommended in national programs. In Japan, there are no upper age limits set for cancer screening programs, and the recommended screening interval for cervical and breast cancer screening is 2 years. To examine the efficient use of resources for cervical and breast cancer screening, we investigated how often overscreening occurred in both programs.

The target age for this study was defined as 20-69 years for cervical cancer screening and 40-69 years for breast cancer screening. We used the national report for cancer screening in 2017 in Japan and estimated the number of participants over 70 years old or those who participated in screening annually. The percentage of overscreening was compared between cervical cancer and breast cancer screening by chi-square test.

The number of participants was 4,294,127 for cervical cancer screening and 3,087,781 for breast cancer screening in 2017. The percentage of overscreening in total participants was 38.0 percent for cervical cancer screening and 35.7 percent for breast cancer screening (p<0.01). The percentage of screening at overage was higher in breast cancer screening than in cervical cancer screening (21.1% vs. 13.9%, p<0.01), whereas more frequent screening was seen more often in cervical cancer screening than in breast cancer screening (29.7% vs. 19.6%, p<0.01). If the resources used in overscreening could be used for the target population, it was estimated that the participation rate could increase by 4.1% for cervical cancer screening and 4.3% for breast cancer screening.

In Japan, screening for overage participants and short intervals may have contributed to unnecessary screening for cervical cancer and breast cancer. These resources used for overscreening could be allocated to screening for the target population.

Hepatocellular cancer (HCC) is a severe condition with poor prognosis and a significant burden. Selective internal radiation therapy (SIRT) is recommended as an alternative treatment option to overcome some limitations of current treatments. This analysis estimated the cost-effectiveness of SIRT using Y-90 resin microspheres for the treatment of unresectable HCC in Brazil.

This study was conducted from the Brazilian payer perspective according to local guidelines, with a lifetime horizon. The use of SIRT in patients with intermediate- or advanced-stage HCC, without extrahepatic disease and ineligible to transarterial chemoembolization, was compared with sorafenib, the commonly used HCC systemic treatment in Brazil. A sensitivity analysis included the subgroup of patients with low tumour burden and preserved liver function.

A partitioned-survival model was developed, which included a tunnel state for patients downstaged to receive a treatment with a curative intent such as liver surgery, transplantation or ablation. Survival curves, utilities and adverse events incidence were extracted from published sources of pivotal randomized control trials. Effectiveness of health interventions was measured in quality-adjusted-life-years (QALYs) and life-years (LYs). Local costs from Brazil were applied. Future costs and effects were discounted at five percent. A willingness-to-pay threshold of USD 53,936 was used, based on a 2017 review of healthcare technology adoption in Brazil.

LYs and QALYs were higher for SIRT using Y-90 resin microspheres versus sorafenib (0.27 and 0.20 incremental LYs and QALYs, respectively) and costs were slightly higher for SIRT (USD 3,056 incremental costs). The incremental cost-effectiveness ratio (ICER) was USD 14,948 per QALY in the basecase.

One-way and probabilistic sensitivity analyses confirmed the robustness of the analyses. Scenario analyses tested different model assumptions and reinforced the basecase results indicating that SIRT using Y-90 resin microspheres was highly likely to be cost-effective compared with sorafenib. Also, the ICER was lower in the subgroup compared with the overall population.

SIRT using Y-90 resin microspheres represents a cost-effective option compared with sorafenib in Brazil.

Therapeutic drug monitoring (TDM) is a cost-effective tool to increase treatments’ efficacy and safety. Analyses of pharmacokinetics proprieties of tyrosine kinase inhibitors (TKI) used for chronic myeloid leukemia (CML) can contribute towards effective TDM, development of tailored treatments and new dosing regimens. We aimed to synthesize the available evidence on pharmacokinetic parameters of imatinib, nilotinib, bosutinib, ponatinib in healthy individuals vs. CML patients.

Systematic searches were conducted in PubMed, Scopus and Web of Science. We included in vivo studies addressing TKIs’ pharmacokinetics, including maximum observed concentration (Cmax), time of maximum observed concentration (Tmax) and half-life (t1/2). Meta-analyses of event rates (mixed-effect models) were performed for the parameters of interest: area under the concentration-time curve from time zero to the last measurable concentration (AUC0-t) and from time zero to infinity (AUC 0-∞). Results were presented as event rates with 95 percent confidence intervals. Heterogeneity was assessed using chi-square and I2 statistical tests and considered significant when p<0.05 and high when I2>75 percent (Comprehensive Meta-Analysis v.2 Biostat-Englewood, NJ).

Overall, 50 articles were included for analyses (n=26 imatinib, n=11 nilotinib, n=8 bosutinib, n=5 ponatinib). Most studies were performed in the United States (46.0%), designed as open-label trials (70.0%). Several significant interactions between TKI with enzyme inhibitors (ketoconazole, midazolam, aprepitant, metoprolol, grapefruit juice), proton pump inhibitors (esomeprazole, lanzoprazole, omeprazole), antacids, H2 antagonists (famotidine) and enzyme inducers (St. John’s, rifampicin) were found (p<0.001). Given the significant increase in AUC and Cmax in patients with hepatic/liver impairments currently using TKI, strict therapeutic monitoring is paramount to maintain safety. The between study heterogeneity was rated as moderate to high (I2=75-90%) due the limited number of trials for some drugs, different study design, and populations.

The co-administration of TKI with hepatic enzyme inducers or inhibitors, proton pump inhibitors, antacids, H2 antagonists, as well as in patients with hepatic/liver failures requires caution and additional monitoring. Further well-designed trials are needed to strengthen this evidence for some TKIs, namely bosutinib and ponatinib.

Non-palpable breast cancers require intraoperative localization to guide the surgical procedure. The radio-guided occult lesion localization (ROLL) and radioactive seed localization (RSL) techniques use radioactive material (technetium-99m labeled macroaggregated albumin and iodine-125 seeds, respectively) implanted at the lesion site. The success of conservative surgery depends on complete tumor excision with negative surgical margins. The objective of this study was to perform a meta-analysis of the surgical effectiveness of the ROLL and RSL techniques with respect to rates of positive surgical margins, reoperation, and recurrence.

A systematic search of the PubMed, Embase, LILACS, SciELO, and Web of Science databases was performed on 2 August 2021. A standard form was used to extract data from the studies selected in the screening process. The ROBINS-I tool was used to analyze risk of bias and RevMan 5.4 software was used to perform the meta-analysis.

Four observational studies met the inclusion criteria. The overall evidence quality was moderate. The studies included women aged from 28 to 91 years with non-palpable breast cancer. The results demonstrated similar effectiveness between RSL and ROLL for rates of positive surgical margins (risk ratio [RR] 0.83, 95% confidence interval [CI]: 0.50, 1.39; 763 patients) and reoperation (RR 1.14, 95% CI: 0.75, 1.74; 1,550 patients). Regarding the rate of disease recurrence, RSL was superior to ROLL (RR 0.50, 95% CI: 0.29, 0.87; 939 patients).

The results demonstrate that the ROLL and RSL techniques are equivalent with respect to rates of positive surgical margins and reoperation, although patients undergoing RSL had lower rates of disease recurrence. However, there is a tendency to favor the RSL technique because of the longer interval between implantation and surgery, which is possible due to the longer half-life of iodine-125 (59.4 days). This also means that radioactive seed implantation can occur before neoadjuvant chemotherapy, so the tumor bed remains marked if further interventions are required, obviating the need for another invasive procedure before surgery.

There were an estimated 55,102 new cases of colorectal cancer (CRC) in Brazil in 2020, comprising 9.3 percent of all newly diagnosed cancers, and making it the third most common cancer in the Brazilian population. Up to half of all patients with CRC will develop liver metastases, and the prognosis for these patients is poor. The objective of the present analysis was to evaluate the cost-utility of selective internal radiation therapy (SIRT) using Y-90 resin microspheres versus best supportive care (BSC) in patients with unresectable, liver-dominant, chemotherapy-refractory metastatic CRC (mCRC).

A three-state partitioned survival model was developed in Microsoft Excel to evaluate the cost-utility of SIRT using Y-90 resin microspheres versus BSC. Membership of the three model states of pre-progression, post-progression and death was governed by parametric models of Kaplan-Meier data from a retrospective, interventional study. Costs associated with SIRT using Y-90 resin microspheres, BSC, and adverse events were obtained from Brazilian sources and reported in 2021 United States dollars (USD). Future costs and effects were discounted at 5 percent. One-way and probabilistic sensitivity analyses (PSA) were performed. A willingness-to-pay threshold of USD 53,936 was used based on a 2017 review of Brazilian healthcare technology adoption.

The base case analysis showed that Y-90 resin microspheres would result in an increase of 0.76 QALYs versus BSC, increasing quality-adjusted life expectancy from 0.67 QALYs to 1.43 QALYs. The improvement in quality-adjusted life expectancy was accompanied by an increase in costs from USD 9,884 to USD 40,399 over the model time horizon, corresponding to an increase of USD 30,515, and yielding an incremental cost-utility ratio (ICUR) of USD 40,265 per QALY gained. PSA showed there was a 90.8 percent likelihood of cost-effectiveness at USD 53,936 per QALY gained.

SIRT using Y-90 resin microspheres was cost-effective versus BSC in the treatment of unresectable, liver-dominant mCRC patients and should be considered for incorporation in the Brazilian Private Healthcare System.

We aimed to develop and validate machine learning (ML) -based algorithms to predict COVID-19 diagnosis as well as to identify new biomarkers associated with the disease.

Initially, 96 blood samples of patients diagnosed with COVID-19 (Thaizhou Hospital, China) were analyzed through liquid chromatography coupled to mass spectrometry. Samples of patients presenting other pneumonias or severe acute respiratory syndrome, but with negative RT-PCR for SARS-CoV-2, were used as positive controls. Samples from healthy volunteers were used as negative controls. The final database included around 1000 metabolites. Exploratory analyses for the development of ML-based models using principal component analysis (PCA) were performed. Leverage plot versus studentized residuals method was used to detect outliers. Three supervised ML-based models were developed: discriminant analysis by partial least squares (PLS-DA), artificial neural networks discriminant analysis (ANNDA) and k-nearest neighbors (KNN). Samples for the training (70%) and testing sets (30%) were randomly selected using the Kenrad Stone algorithm. Models’ performance was evaluated considering accuracy, sensitivity and specificity. Analyses were conducted in SOLO (Eigenvector-Research).

The PCA model was able to distinguish the three classes of patients’ samples (positive for COVID-19, negative controls, positive controls) with an overall accumulated variance of 94.27 percent. The PLS-DA model presented the best performance (accuracy, sensitivity, and specificity of 93%, 98% and 88%, respectively). Increased levels of the biomarkers uridine (linked to glucose homeostasis, lipid, and amino acid metabolisms), 4-hydroxyphenylacetoylcarnitine (metabolite from the tyrosine metabolism; probably associated with anorexia) and ribothymidine (resulting from oral and fecal microbiota alterations) were significantly associated with COVID-19.

Three different and updated ML-based algorithms were developed to predict COVID-19 diagnosis; PLS-DA led to the most accurate results. High levels of some metabolites were found as potentially predictors of the disease. These biomarkers should be further evaluated as potential therapeutic targets in well-designed clinical trials. These ML-based models can help the early diagnosis of COVID-19 and guide the development of tailored interventions.

We aimed to map and synthesize the available evidence on neuron-specific biomarkers related to COVID-19.

A systematic review and qualitative evidence mapping synthesis was performed (PROSPERO-CRD42021266995). Searches were conducted in PubMed and Scopus, and complemented by manual search (July 2021). We included observational studies of any design assessing neurological biomarkers in adult patients (>18 years; with or without neurological comorbidities) diagnosed with COVID-19. Methodological quality of nonrandomized studies (case-control, cohorts) was assessed using the Newcastle-Ottawa Scale.

Overall, 14 studies (n=485 patients) conducted in Sweden (n=4 articles, 28.5%), Germany (n=3; 21.4%), USA (n=3; 21.4%), Canada, France, Italy and Norway (n=1 study each) were included. The most reported neurological symptoms (n=13 studies, 92.8%) were headache, confusion, general weakness, loss of smell/taste, cognitive impairments and behavioral changes. Prevalent neurological conditions included encephalopathies, neuropathies, myopathies, and delirium; most critical cases presented cerebrovascular events (n=4 studies, 28.5%). Hypertension, diabetes, obesity, dyslipidemia, and chronic lung disease were the most reported comorbidities. Eight different neuron-specific biomarkers were found in primary studies: neurofilament-light chain – NfL (n=10 studies; 71.4%), glial fibrillary acidic-protein – GFAp (n=5; 35.7%), tau protein (n=5; 35.7%), neurofilament-heavy chain – NfH, S100B protein, ubiquitin C-terminal hydrolase L1 - UCH-L1, neuron-specific enolase and beta protein-amyloid – Aβ (n=1 study each). These biomarkers were found both in cerebrospinal fluid and blood/plasma samples even without an evident cytokine storm. In patients with COVID-19, NfL and GFAp can act as sensitive indicators of neuroaxonal and astrocytic damages, respectively. Increased levels of NfL were significantly associated with severe COVID-19, unconsciousness and longer stay in the intensive care unit (p<0.05). Studies had an overall poor to moderate methodological quality.

We identified eight neuron-specific biomarkers that should be further studied as prognostic factors of COVID-19. These findings can also guide the development of targeted therapies against SARS-CoV-2. Additional well-designed clinical trials are needed to strengthen this evidence and help understand the mechanisms of neurological symptoms and sequelae after COVID-19 infection.

Patients with chronic kidney disease (CKD) and COVID-19 are at high risk of adverse outcomes due to the presence of comorbidities. However, it is still unclear whether dialysis therapy is associated with a worse prognosis in patients infected with SARS-CoV-2. The objectives were to assess mortality and risk factors associated with a worse prognosis of these patients (e.g., age, sex, comorbidities, Intensive Care Admission [ICU] admission, and need for invasive mechanical ventilation [IMV]).

An observational, descriptive, retrospective study was conducted in the private healthcare maintenance organization (Unimed-BH) of Belo Horizonte and 33 surrounding cities in Brazil. We used data collected from the organization’s database. We included adult inpatients with CKD on previous dialysis therapy who tested positive for COVID-19, from February 2020 to June 2021.

During the period, 16182 patients were admitted to Unimed-BH with a diagnosis of COVID-19. Of these, 333 (2%) had dialysis CKD. Male patients were 180 (54%), age ranged from 22.85 to 95.75 years and the mean was 60.91 years. Of the 333 patients, 109 (32.7%) were admitted to the ICU, and 56 (16.8%) required IMV. Among the 14 comorbidities analysed, the mean number of comorbidities was 6, with 93 (27.9%) dyslipidaemia, 74 (22%) diabetic, 270 (81%) hypertensive, 25 (7.5%) asthmatic, 42 (12.6%) with chronic pulmonary disease (CPD) and 122 (36.6%) with congestive heart failure (CHF). There were 66 (19.8%) deaths, 29 (43.9%) were male, the mean age was 60.8 years, and 23 patients (34.8%) were elderly (>60 years). Among the patients who died, 55 (83.3%) were in the ICU and 46 (69.7%) on IMV. The mean number of comorbidities was 9.27 being 16 (24.2%) dyslipidaemia, 44 (66.6%) diabetic, 60 (90.9%) hypertensive, 5 (7%) asthmatic, 10 (15%) with CPD and 32 (48.5%) with CHF.

Dialysis patients appear more susceptible to unfavourable outcomes than the general population. Our findings are similar to those reported in the world literature which is still scarce. It is important to conduct more studies on this population.

Life expectancy is increasing worldwide. However, during the COVID-19 pandemic, people 100 years or more (centenaries) were challenged by a potentially fatal disease. We evaluated the outcome of centenaries hospitalized due to COVID-19 in a private healthcare system of Belo Horizonte/Brazil (Unimed-BH).

Administrative data were collected from the hospital database. Patients were included if they had a severe adult respiratory syndrome due to coronavirus type 2 (SARS-CoV-2) ribonucleic acid identified by quantitative real-time reverse transcriptase polymerase chain reaction (RT-qPCR) or by the International Code of Disease-10th review (ICD-10) hospitalization codes U07.1, B34.2, or B97.2.

From March 1 2020 to October 31 2021, 316.4 ± 12.9 centenaries/month were registered. Eighteen hospitalizations due to COVID-19 were identified. Median age was 101.8 years (inter-quartile range [IQR]:100.7,103.0). Most patients were female (83%). There was a median of 6.0 morbidities per patient (IQR:5.3,7.8), range 2-12 morbidities, among 71 possible morbidities. The most described morbidities were systemic arterial hypertension (94%), dementia (61%), and congestive heart failure (61%). Median length of hospitalization was 6.5 days (IQR:3.3,8.0). No patient was dialyzed. Seven (39%) patients died during hospitalization, of whom 3 (17%) were admitted to the Intensive Care Unit and 2 (11%) were oxygenated by invasive mechanical ventilation. No other patients were admitted to the Intensive Care Unit or invasively mechanically ventilated.

Although the hospitalization rate was low, the mortality rate during hospitalization was high among centenaries. Further research is required to evaluate the actual risks of centenaries to be infected by SARS-CoV-2 and the subsequent outcomes.

The aim of this EUnetHTA (European Network for Health Technology Assessment) Rolling Collaborative Review on high dose vitamin D for the treatment of COVID-19 was to inform health policy at an early stage in the life cycle of therapies and to monitor ongoing studies in the format of a Living Document.

The systematic literature search was conducted in Medline, Pubmed, medRxiv, bioRxiv, arXivso, Cochrane COVID-19 Study Register, ClinicalTrials.gov, ISRCTN Registry, EU Clinical Trials Register. The first search was done in January 2021, and the last in November 2021. English and German randomized controlled studies (RCTs) investigating treatment of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infected individuals with high dose vitamin D2, D3 or their metabolites were included if examining mortality, length of hospital stay, viral burden, clinical progression, hospitalization rates, intensive care unit (ICU) admission, mechanical ventilation, quality of life or adverse events. Two reviewers independently screened search results and assessed risk of bias and certainty of evidence. One reviewer extracted study data, checked by another.

Of the nine RCTs published to date, two investigate calcifediol, one calcitriol and six vitamin D3. All used different dosing regimens. Disease severity and proportion of vitamin D deficiency varied between studies. Calcifediol treated patients in one study required significantly less ICU admissions than untreated patients. Vitamin D3 in another study led to significantly more SARS-CoV-2 PCR-negative patients before day 21 than placebo. There were no other significant differences between groups. Twenty-five RCTs are ongoing, five of them with over 1,000 patients.

The current evidence is heterogenous regarding form and dosage of vitamin D, baseline disease severity and baseline vitamin D deficiency. There is currently no standardized/recommended level of what constitutes a (beneficial) “high dose”. Most results did not show significant differences between vitamin D treated groups and no vitamin D / placebo groups. Many of the studies are very small and certainty of evidence is predominantly low or very low.

The outbreak of the COVID-19 pandemic generated the need to adapt patients’ access to health services, given the rapid and exponential increase in demand at all levels of care, making social distancing one of the few weapons available in this fight. In this scenario, telehealth proved to be a fundamental tool in tracking and guiding patients with suspected or confirmed disease. This work presents the demographic profile of the people attended, the most prevalent clinical situations in care and the clinical outcomes of the remote care.

This was an observational, descriptive, cross-sectional, retrospective study carried out at Unimed Belo Horizonte, a medical work cooperative, from March 2020 to May 2021. We analyzed anonymized data on remote care from electronic medical records provided by the operator, with the remote contacts of these patients being spontaneous.

In the period evaluated, 380,663 remote calls were made, with a monthly average of 36,888 calls. Of these visits, 59.5% were carried out by women and 40.5% by men. There were, 13,211 (3.5%) consultations with patients aged 0 to 9 years, 19,933 (5.2%) 10 to 19 years, 319,882 (84%) in people aged 20 to 59 years, and 27,633 (7.3%) aged 60 years or older. There were 64,348 (17%) consultations in patients with confirmed COVID-19 and 40,997 (11%) with suspected COVID-19. There were 194,746 (51.2%) consultations due to respiratory complaints and 14% of consultations due to other causes, but whose initial care was due to signs and symptoms suggestive of COVID-19. Of people assisted remotely, 29,734 (7.8%) attended the emergency room within 3 days, while 38,685 (10.2%) sought the emergency room within 14 days. There were 2,846 (0.7%) consultations in the emergency room that resulted in the hospitalization of patients.

Telehealth proved to be resolute and an important tool for accessing health services during the pandemic.

The COVID-19 pandemic has affected thousands of people worldwide. The collapse of health systems led to increased difficulties in accessing health care for people with disabilities. The objective was to define strategies to support the implementation of health care for people with disabilities.

The protocol for the systematic review was registered on PROSPERO (CRD42021266341). Searches were done in seven databases, using MeSH terms related to COVID-19 and disability, in 2021. We included interventions that addressed health, education and social assistance.

Twenty-nine studies were included. A meta-synthesis identified strategies to assist individuals with disabilities: creation of emergency accommodation and protection programs; flexible work arrangements; cash transfer programs; community participation in planning; establishment of support networks; social assistance even in periods of health emergency; teleconsultation services, telerehabilitation and systems that facilitate the use of digital technologies for telemedicine; inclusive guidelines for computer literacy and learning. The main implementation action was comprehensive health care centered on the needs of people with disabilities, with a focus on training community informants, continuing education of health professionals and caregivers for emergency situations, decentralization of care, identification and elimination of barriers to access.

Even though the focus was on telehealth and social assistance, achieving comprehensive healthcare requires a range of interventions that together will support the reduction of inequity faced by people with disabilities.

The self-test for COVID-19 has been a widely used strategy in some countries, especially in the context of back to face-to-face work and educational activities. However, it is necessary to discuss the accuracy of antigen tests for the diagnosis of COVID-19.

A systematic review was carried out. The strategy was defined by the researchers using the terms “Covid-19” and “Self-testing” and their respective synonyms, including studies with data collection from 01/01/2021. Searches were carried out on October 20, 2021, in several databases.

A total of 504 studies were identified, four of which were included in this review: two self-tests of nasopharyngeal collection antigen compared to reverse transcriptase polymerase chain reaction (RT-PCR); a supervised and self-collected anterior nasal smear self-test; and a study that evaluated the performance of six self-collected rapid antigen tests against quantitative RT-PCR (gargle, sputum, and spit). Saliva self-tests were found to have low sensitivity (<45%), while anterior nasal or nasopharyngeal swab self-tests had greater than 80 percent sensitivity. In all self-tests, the specificity was less than 85 percent. The diagnostic accuracy of self-tests for the different SARS-CoV-2 variants was not identified.

The use of self-tests as a screening strategy is recommended, being a strategy with a significant impact on the surveillance and control of SARS-CoV-2 transmission. Further studies are needed to assess: (i) accuracy considering the concern variants, (ii) safety of tests with self-collection of biological material, and (iii) disposal of biological waste.