Nevin Manimala

BMJ Open. 2021 Dec 6;11(12):e054222. doi: 10.1136/bmjopen-2021-054222.

ABSTRACT

OBJECTIVES: Patients undergoing surgery for severe aortic stenosis (SAS) can be treated with either transcatheter aortic valve implantation (TAVI) or surgical aortic valve replacement (SAVR). The choice of procedure depends on several factors, including the clinical judgement of the heart team and patient preferences, which are captured by actively informing and involving patients in a process of shared decision making (SDM). We synthesised the most up-to-date and accessible evidence on the benefits and risks that may be associated with TAVI versus SAVR to support SDM in this highly personalised decision-making process.

DESIGN: Systematic review and meta-analysis.

DATA SOURCES: MEDLINE (Ovid), Embase (Ovid) and the Cochrane Central Register of Controlled Trials (CENTRAL; Wiley) were searched from January 2000 to August 2020 with no language restrictions. Reference lists of included studies were searched to identify additional studies.

ELIGIBILITY CRITERIA: Randomised controlled trials (RCTs) that compared TAVI versus SAVR in patients with SAS and reported on all-cause or cardiovascular mortality, length of stay in intensive care unit or hospital, valve durability, rehospitalisation/reintervention, stroke (any stroke or major/disabling stroke), myocardial infarction, major vascular complications, major bleeding, permanent pacemaker (PPM) implantation, new-onset or worsening atrial fibrillation (NOW-AF), endocarditis, acute kidney injury (AKI), recovery time or pain were included.

DATA EXTRACTION AND SYNTHESIS: Two independent reviewers were involved in data extraction and risk of bias (ROB) assessment using the Cochrane tool (one reviewer extracted/assessed the data, and the second reviewer checked it). Dichotomous data were pooled using the Mantel-Haenszel method with random-effects to generate a risk ratio (RR) with 95% CI. Continuous data were pooled using the inverse-variance method with random-effects and expressed as a mean difference (MD) with 95% CI. Heterogeneity was assessed using the I² statistic.

RESULTS: 8969 records were retrieved and nine RCTs (61 records) were ultimately included (n=8818 participants). Two RCTs recruited high-risk patients, two RCTs recruited intermediate-risk patients, two RCTs recruited low-risk patients, one RCT recruited high-risk (≥70 years) or any-risk (≥80 years) patients; and two RCTs recruited all-risk or ‘operable’ patients. While there was no overall change in the risk of dying from any cause (30 day: RR 0.89, 95% CI 0.65 to 1.22; ≤1 year: RR 0.90, 95% CI 0.79 to 1.03; 5 years: RR 1.09, 95% CI 0.98 to 1.22), cardiovascular mortality (30 day: RR 1.03, 95% CI 0.77 to 1.39; ≤1 year: RR 0.90, 95% CI 0.76 to 1.06; 2 years: RR 0.96, 95% CI 0.83 to 1.12), or any type of stroke (30 day: RR 0.83, 95% CI 0.61 to 1.14;≤1 year: RR 0.94, 95% CI 0.72 to 1.23; 5 years: RR 1.07, 95% CI 0.88 to 1.30), the risk of several clinical outcomes was significantly decreased (major bleeding, AKI, NOW-AF) or significantly increased (major vascular complications, PPM implantation) for TAVI vs SAVR. TAVI was associated with a significantly shorter hospital stay vs SAVR (MD -3.08 days, 95% CI -4.86 to -1.29; 4 RCTs, n=2758 participants). Subgroup analysis generally favoured TAVI patients receiving implantation via the transfemoral (TF) route (vs non-TF); receiving a balloon-expandable (vs self-expanding) valve; and those at low-intermediate risk (vs high risk). All RCTs were rated at high ROB, predominantly due to lack of blinding and selective reporting.

CONCLUSIONS: No overall change in the risk of death from any cause or cardiovascular mortality was identified but 95% CIs were often wide, indicating uncertainty. TAVI may reduce the risk of certain side effects while SAVR may reduce the risk of others. Most long-term (5-year) results are limited to older patients at high surgical risk (ie, early trials), therefore more data are required for low risk populations. Ultimately, neither surgical technique was considered dominant, and these results suggest that every patient with SAS should be individually engaged in SDM to make evidence-based, personalised decisions around their care based on the various benefits and risks associated with each treatment.

PROSPERO REGISTRATION NUMBER: CRD42019138171.

PMID:34873012 | DOI:10.1136/bmjopen-2021-054222

BMJ Open. 2021 Dec 6;11(12):e053674. doi: 10.1136/bmjopen-2021-053674.

ABSTRACT

OBJECTIVE: To review biomarker discovery studies using omics data for patient stratification which led to clinically validated FDA-cleared tests or laboratory developed tests, in order to identify common characteristics and derive recommendations for future biomarker projects.

DESIGN: Scoping review.

METHODS: We searched PubMed, EMBASE and Web of Science to obtain a comprehensive list of articles from the biomedical literature published between January 2000 and July 2021, describing clinically validated biomarker signatures for patient stratification, derived using statistical learning approaches. All documents were screened to retain only peer-reviewed research articles, review articles or opinion articles, covering supervised and unsupervised machine learning applications for omics-based patient stratification. Two reviewers independently confirmed the eligibility. Disagreements were solved by consensus. We focused the final analysis on omics-based biomarkers which achieved the highest level of validation, that is, clinical approval of the developed molecular signature as a laboratory developed test or FDA approved tests.

RESULTS: Overall, 352 articles fulfilled the eligibility criteria. The analysis of validated biomarker signatures identified multiple common methodological and practical features that may explain the successful test development and guide future biomarker projects. These include study design choices to ensure sufficient statistical power for model building and external testing, suitable combinations of non-targeted and targeted measurement technologies, the integration of prior biological knowledge, strict filtering and inclusion/exclusion criteria, and the adequacy of statistical and machine learning methods for discovery and validation.

CONCLUSIONS: While most clinically validated biomarker models derived from omics data have been developed for personalised oncology, first applications for non-cancer diseases show the potential of multivariate omics biomarker design for other complex disorders. Distinctive characteristics of prior success stories, such as early filtering and robust discovery approaches, continuous improvements in assay design and experimental measurement technology, and rigorous multicohort validation approaches, enable the derivation of specific recommendations for future studies.

PMID:34873011 | DOI:10.1136/bmjopen-2021-053674

BMJ Open. 2021 Dec 6;11(12):e053497. doi: 10.1136/bmjopen-2021-053497.

ABSTRACT

INTRODUCTION: Alcohol use is a major risk factor for mortality. Previous studies suggest that the alcohol-attributable mortality burden is higher in lower socioeconomic strata. This project will test the hypothesis that the 2017 increase of alcohol excise taxes linked to lower all-cause mortality rates in previous analyses will reduce socioeconomic mortality inequalities.

METHODS AND ANALYSIS: Data on all causes of deaths will be obtained from Statistics Lithuania. Record linkage will be implemented using personal identifiers combining data from (1) the 2011 whole-population census, (2) death records between 1 March 2011 (census date) and 31 December 2019, and (3) emigration records, for individuals aged 40-70 years. The analyses will be performed separately for all-cause and for alcohol-attributable deaths. Monthly age-standardised mortality rates will be calculated by sex, education and three measures of socioeconomic status (SES). Inequalities in mortality will be assessed using absolute and relative indicators between low and high SES groups. We will perform interrupted time series analyses, and test the impact of the 2017 rise in alcohol excise taxation using generalised additive mixed models. In these models, we will control for secular trends for economic development.

ETHICS AND DISSEMINATION: This work is part of project grant 1R01AA028224-01 by the National Institute on Alcohol Abuse and Alcoholism. It has been granted research ethics approval 050/2020 by Centre for Addiction and Mental Health Research Ethics Board on 17 April 2020, renewed on 30 March 2021. The time series of mortality inequalities as well as the statistical code will be made publicly available, allowing other researchers to adapt the proposed method to other jurisdictions.

PMID:34873010 | DOI:10.1136/bmjopen-2021-053497

BMJ Open. 2021 Dec 6;11(12):e053169. doi: 10.1136/bmjopen-2021-053169.

ABSTRACT

BACKGROUND: Blood culture negative infective endocarditis (BCNIE) poses both a diagnostic and therapeutic challenge. High rates of BCNIE reported in South Africa have been attributed to antibiotic use prior to blood culture sampling.

OBJECTIVES: To assess the impact of a systematic approach to organism detection and identify the causes of infective endocarditis (IE), in particular causes of BCNIE.

DESIGN: Prospective cohort study.

METHODS: The Tygerberg Endocarditis Cohort study prospectively enrolled patients with IE between November 2019 and February 2021. A set protocol for organism detection with management of patients by an endocarditis team was employed. This prospective cohort was compared with a retrospective cohort of patients with IE admitted between January 2017 and December 2018.

RESULTS: One hundred and forty patients with IE were included, with 75 and 65 patients in the retrospective and prospective cohorts, respectively. Baseline demographic characteristics were similar with a mean age of 39.6 years and male predominance (male sex=67.1%). The rate of BCNIE was lower in the prospective group (28/65 or 43.1%) compared with the retrospective group (47/75 or 62.7%; p=0.039). The BCNIE in-hospital mortality rate in the retrospective cohort was 23.4% compared with 14.2% in the prospective cohort (p=0.35). A cause was identified (including non-culture techniques) in 86.2% of patients in the prospective cohort, with Staphylococcus aureus (26.2%), Bartonella species (20%) and the viridans streptococci (15.3%) being most common.

CONCLUSION: The introduction of a set protocol for organism detection, managed by an endocarditis team, has identified Staphylococcusaureus as the most common cause of IE and identified non-culturable organisms, in particular Bartonella quintana, as an important cause of BCNIE. A reduction in in-hospital mortality in patients with BCNIE was observed, but did not reach statistical significance.

PMID:34873007 | DOI:10.1136/bmjopen-2021-053169

BMJ Open. 2021 Dec 6;11(12):e052417. doi: 10.1136/bmjopen-2021-052417.

ABSTRACT

INTRODUCTION: China has the largest number of adults with diabetes aged 20-79 years (116.4 million) in 2019. Due to the socioeconomic condition or a lack of awareness of diabetic complications, many adults with diabetes have proliferative diabetic retinopathy (PDR) or renal function impairment at their first visit to the clinic for a sudden loss of vision, and pars plana vitrectomy (PPV) is required for their treatment. Risk factors for the outcomes and complications of PPV surgery in PDR patients have been widely explored in many epidemiological studies and clinical trials. However, few prospective studies have analysed the association between renal function and surgical outcomes in PDR.

METHODS AND ANALYSIS: This is a single-centre, prospective cohort study of PDR patients with type 2 diabetes mellitus who have definite indications for PPV surgery with or without renal function impairment. We will consecutively enrol PDR patients who meet the inclusion and exclusion criteria from November 2020 to December 2023. Each participant will be followed up for at least 6 months after surgery. Clinical data from medical records and vitreous fluid will be collected.Demographic characteristics and study outcomes will be summarised using descriptive statistics. The variation will be described and evaluated using the χ² test or Kruskal-Wallis test. Generalise additive mixed models will be used to explore the association between the renal profile and surgical outcomes including BCVA, and retinal and choroidal microvasculature/microstructure. Multivariate ordinal regression analysis will be used to detect the independent association between renal profile and BCVA changes, and smooth curve fitting will be employed to briefly present the tendency.

ETHICS AND DISSEMINATION: The trial has received ethical approval from the West China Hospital of Sichuan University. Results of this trial will be disseminated through publication in peer-reviewed journals and presentations at local and international meetings.

TRIAL REGISTRATION NUMBER: ChiCTR2000039698.

PMID:34873003 | DOI:10.1136/bmjopen-2021-052417

BMJ Open. 2021 Dec 6;11(12):e051853. doi: 10.1136/bmjopen-2021-051853.

ABSTRACT

OBJECTIVES: In the International Classification of Diseases, Tenth Edition (ICD-10), hypochondriasis (illness anxiety disorder) and dysmorphophobia (body dysmorphic disorder) share the same diagnostic code (F45.2). However, the Swedish ICD-10 allows for these disorders to be coded separately (F45.2 and F45.2A, respectively), potentially offering unique opportunities for register-based research on these conditions. We assessed the validity and reliability of their ICD-10 codes in the Swedish National Patient Register (NPR).

DESIGN: Retrospective chart review.

METHODS: Six hundred individuals with a diagnosis of hypochondriasis or dysmorphophobia (300 each) were randomly selected from the NPR. Their medical files were requested from the corresponding clinics, located anywhere in Sweden. Two independent raters assessed each file according to ICD-10 definitions and Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision and Fifth Edition criteria. Raters also completed the Clinical Global Impression-Severity (CGI-S) and the Global Assessment of Functioning (GAF).

PRIMARY OUTCOME MEASURE: Per cent between-rater agreement and positive predictive value (PPV). Intraclass correlation coefficients for the CGI-S and the GAF.

RESULTS: Eighty-four hypochondriasis and 122 dysmorphophobia files were received and analysed. The inter-rater agreement rate regarding the presence or absence of a diagnosis was 95.2% for hypochondriasis and 92.6% for dysmorphophobia. Sixty-seven hypochondriasis files (79.8%) and 111 dysmorphophobia files (91.0%) were considered ‘true positive’ cases (PPV=0.80 and PPV=0.91, respectively). CGI-S scores indicated that symptoms were moderately to markedly severe, while GAF scores suggested moderate impairment for hypochondriasis cases and moderate to serious impairment for dysmorphophobia cases. CGI-S and GAF inter-rater agreement were good for hypochondriasis and moderate for dysmorphophobia.

CONCLUSIONS: The Swedish ICD-10 codes for hypochondriasis and dysmorphophobia are sufficiently valid and reliable for register-based studies. The results of such studies should be interpreted in the context of a possible over-representation of severe and highly impaired cases in the register, particularly for dysmorphophobia.

PMID:34873001 | DOI:10.1136/bmjopen-2021-051853

BMJ Open. 2021 Dec 6;11(12):e051434. doi: 10.1136/bmjopen-2021-051434.

ABSTRACT

OBJECTIVES: The number of modern healthcare providers in Bangladesh has increased and they are well equipped with modern medical instruments and infrastructures. Despite this development, patients seeking treatment from alternative healthcare providers are ongoing. Hence, this study aims to determine the underlying predictors of patients’ choosing modern healthcare providers and health facilities for getting treatments.

SETTING: Data from the nationally representative Household Income and Expenditure Survey 2016-2017 conducted by the Bangladesh Bureau of Statistics were used.

PARTICIPANTS: 34 512 respondents sought treatment for their illnesses from different types of available healthcare providers.

PRIMARY AND SECONDARY OUTCOME MEASURE: Patients’ choice of healthcare providers (primary) and predictors of patients’ choice of modern healthcare providers (secondary).

RESULTS: The study found that 40% of the patients visit modern healthcare providers primarily on having symptoms of illness, and the remainder goes to alternative healthcare providers. Patients living in urban areas (adjusted OR (AOR)=1.11, 95% CI 1.05 to 1.17, p<0.01), and if the travel time was between 1 and 2 hours (AOR=1.11, 95% CI 1.00 to 1.22, p<0.05) compared with travel time less than 1 hour, were positively associated to utilisation of modern healthcare facilities for their first consultation. The statistical models show that the predisposing and need factors do not significantly impact patients’ choice of modern healthcare providers.

CONCLUSIONS: The distribution of modern healthcare providers should be even across the country to eliminate the rural-urban divide in modern healthcare utilisation. Enhancing the digital provision of modern healthcare services could reduce travel time, omit transportation costs and save waiting time for treatment by the modern healthcare providers. Policymakers can think of introducing a national health insurance programme in Bangladesh as a potential policy instrument.

PMID:34873000 | DOI:10.1136/bmjopen-2021-051434

BMJ Open. 2021 Dec 6;11(12):e049086. doi: 10.1136/bmjopen-2021-049086.

ABSTRACT

OBJECTIVES: To gain insights into the impact of the COVID-19 pandemic on ongoing health research projects, using projects from a selected funding programme in Germany as an example.

DESIGN: Online survey and validation workshop.

SETTING: Lockdowns and social distancing policies impact on clinical and public health research in various forms, especially if unrelated to COVID-19. Research institutions have reduced onsite activities, data are often collected remotely, and during the height of the crisis, clinical researchers were partially forced to abandon their projects in favour of front-line care.

PARTICIPANTS SURVEY: 120 investigators of health research projects across Germany, performed between 15 and 25 May 2020; workshop: 32 investigators, performed on 28 May 2020.

RESULTS: The response rate (78%) showed that the survey generated significant interest among investigators. 85 responses were included for analysis, and the majority of investigators (93%) reported that their projects were affected by the pandemic, with many (80%) stating that data collection was not possible as planned, and they could not carry out interventions as intended (67%). Other impacts were caused by staff being unavailable, for example, through child or elder care commitments or because of COVID-19 quarantine or illness. Investigators also reported that publications were delayed or not feasible at all (56%), and some experienced problems with PhD or Masters theses (18%). The majority of investigators had mitigation strategies in place such as adjustment of data collection methods using digital tools (46%) or of project implementation in general (46%), others made changes in research design or research questions (27%).

CONCLUSIONS: The COVID-19 pandemic has severely impacted on health research projects. The main challenge is now to mitigate negative effects and to improve long-term resilience in health research. The pandemic has also acted as a driver of innovation and change, for example, by accelerating the use of digital methods.

PMID:34872995 | DOI:10.1136/bmjopen-2021-049086

Nucleic Acids Res. 2021 Dec 6:gkab1147. doi: 10.1093/nar/gkab1147. Online ahead of print.

ABSTRACT

Data alignment is one of the first key steps in single cell analysis for integrating multiple datasets and performing joint analysis across studies. Data alignment is challenging in extremely large datasets, however, as the major of the current single cell data alignment methods are not computationally efficient. Here, we present VIPCCA, a computational framework based on non-linear canonical correlation analysis for effective and scalable single cell data alignment. VIPCCA leverages both deep learning for effective single cell data modeling and variational inference for scalable computation, thus enabling powerful data alignment across multiple samples, multiple data platforms, and multiple data types. VIPCCA is accurate for a range of alignment tasks including alignment between single cell RNAseq and ATACseq datasets and can easily accommodate millions of cells, thereby providing researchers unique opportunities to tackle challenges emerging from large-scale single-cell atlas.

PMID:34871454 | DOI:10.1093/nar/gkab1147

J Econ Entomol. 2021 Dec 6;114(6):2524-2533. doi: 10.1093/jee/toab192.

ABSTRACT

Australia is the third largest exporting country of cereals and a leader in other major commodity crops, yet little data exist on pesticide usage patterns in agriculture. This knowledge gap limits the management of off-target chemical impacts, such as the evolution of pesticide resistance. Here, for the first time, we quantify spatial patterns in neonicotinoid applications in Australia by coalescing land use data with sales and market research data contributed by agrichemical and agribusiness companies. An example application to resistance management is explored through the development of recommendations for the cosmopolitan crop pest, Myzus persicae (Sulzer) (Hemiptera: Aphididae), utilizing spatial statistical models. This novel dataset identified Australian neonicotinoid usage patterns, with most neonicotinoid products in Australia applied as cereal, canola, cotton and legume seed treatments and soil applications in sugarcane. Importantly, there were strong regional differences in pesticide applications, which will require regionally specific strategies to manage off-target impacts. Indeed, the estimated spatial grid of neonicotinoid usage demonstrated a statistically significant influence on the distribution of M. persicae neonicotinoid resistance, indicating off-target impacts are unevenly distributed in space. Future research on neonicotinoid usage will be supported by the spatial grids generated and made available through this study. Overall, neonicotinoid pesticides are widely relied upon throughout Australia’s plant production systems but will face increasing pressure from resistance evolution, emerging research on off-target impacts, and stricter regulatory pressures.

PMID:34871446 | DOI:10.1093/jee/toab192