Category: Statistics

Sci Rep. 2021 Nov 26;11(1):22970. doi: 10.1038/s41598-021-00083-2.

ABSTRACT

Several vaccines with different efficacies and effectivenesses are currently being distributed across the world to control the COVID-19 pandemic. Having enough doses from the most efficient vaccines in a short time is not possible for all countries. Hence, policymakers may propose using various combinations of available vaccines to control the pandemic with vaccine-induced herd immunity by vaccinating a fraction of the population. The classic vaccine-induced herd-immunity threshold suggests that we can stop spreading the disease by vaccinating a fraction of the population. However, that classic threshold is defined only for a single vaccine and may be invalid and biased when we have multi-vaccine strategies for a disease or multiple variants, potentially leading policymakers to suboptimal vaccine-allocation policies. Here, we determine which combination of multiple vaccines may lead to herd immunity. We show that simplifying the problem and considering the vaccination of the population as a single-vaccine strategy whose effectiveness is the sample mean of all effectivenesses would not be ideal, because many multi-vaccine strategies with a smaller herd-immunity threshold can be proposed. We show that the herd-immunity threshold may vary due to changes in vaccine-uptake proportions. Moreover, we propose methods to determine the optimal combination of multiple vaccines in order to achieve herd immunity and apply our results to the issue of multiple variants. In addition, we determine a condition for reaching herd immunity in the presence of new emerging variants of concern. We show by example that new variants could influence our estimation of the vaccination reproduction number. It follows that the herd-immunity threshold must be updated not only when multi-vaccine strategies are used but also when multiple variants coexist in the population.

PMID:34836984 | DOI:10.1038/s41598-021-00083-2

Sci Rep. 2021 Nov 26;11(1):22996. doi: 10.1038/s41598-021-02040-5.

ABSTRACT

Multiple N-methyl-D-aspartate (NMDA) receptor enhancing agents have had promising effects on cognition among patients with dementia. However, the results remain inconsistent. This exploratory meta-analysis investigated the effectiveness of NMDA receptor enhancing agents for cognitive function. PubMed, the Cochrane Central Register of Controlled Trials, and the Cochrane Database of Systematic Reviews were searched for randomized controlled trials (RCTs). Controlled trials assessing add-on NMDA receptor enhancing agent treatment in patients with dementia and using cognition rating scales were eligible and pooled using a random-effect model for comparisons. The standardized mean difference (SMD) was calculated in each study from the effect size; positive values indicated that NMDA receptor enhancing agent treatment improved cognitive function. Funnel plots and the I2 statistic were evaluated for statistical heterogeneity. Moderators were evaluated using meta-regression. We identified 14 RCTs with 2224 participants meeting the inclusion criteria. Add-on NMDA receptor enhancing agents had small positive significant effects on overall cognitive function among patients with dementia (SMD = 0.1002, 95% CI 0.0105-0.1900, P = 0.02860). Subgroup meta-analysis showed patients with Alzheimer’s Disease and trials using the Alzheimer Disease Assessment Scale-cognitive subscale as the primary outcome had small positive significant effects (SMD = 0.1042, 95% CI 0.0076-0.2007, P = 0.03451; SMD = 0.1267, 95% CI 0.0145-0.2388, P = 0.2686). This exploratory meta-analysis showed a very small, positive, and significant effect on overall cognition function in patients with dementia. Studies with larger samples are needed to evaluate different cognitive domains and phases of dementia.

PMID:34836972 | DOI:10.1038/s41598-021-02040-5

Sci Data. 2021 Nov 26;8(1):304. doi: 10.1038/s41597-021-01081-9.

ABSTRACT

Remote sensing satellite imagery has the potential to monitor and understand dynamic environmental phenomena by retrieving information about Earth’s surface. Marine ecosystems, however, have been studied with less intensity than terrestrial ecosystems due, in part, to data limitations. Data on sea surface temperature (SST) and Chlorophyll-a (Chlo-a) can provide quantitative information of environmental conditions in coastal regions at a high spatial and temporal resolutions. Using the exclusive economic zone of coastal regions as the study area, we compiled monthly and annual statistics of SST and Chlo-a globally for 2003 to 2020. This ready-to-use dataset aims to reduce the computational time and costs for local-, regional-, continental-, and global-level studies of coastal areas. Data may be of interest to researchers in the areas of ecology, oceanography, biogeography, fisheries, and global change. Target applications of the database include environmental monitoring of biodiversity and marine microorganisms, and environmental anomalies.

PMID:34836949 | DOI:10.1038/s41597-021-01081-9

Nat Commun. 2021 Nov 26;12(1):6920. doi: 10.1038/s41467-021-26556-6.

ABSTRACT

Bone marrow is a preferred metastatic site for multiple solid tumours and is associated with poor prognosis and significant morbidity. Accumulating evidence indicates that cancer cells colonise specialised niches within the bone marrow to support their long-term propagation, but the precise location and mechanisms that mediate niche interactions are unknown. Using breast cancer as a model of solid tumour metastasis to the bone marrow, we applied large-scale quantitative three-dimensional imaging to characterise temporal changes in the bone marrow microenvironment during disease progression. We show that mouse mammary tumour cells preferentially home to a pre-existing metaphyseal domain enriched for type H vessels. Metastatic lesion outgrowth rapidly remodelled the local vasculature through extensive sprouting to establish a tumour-supportive microenvironment. The evolution of this tumour microenvironment reflects direct remodelling of the vascular endothelium through tumour-derived granulocyte-colony stimulating factor (G-CSF) in a hematopoietic cell-independent manner. Therapeutic targeting of the metastatic niche by blocking G-CSF receptor inhibited pathological blood vessel remodelling and reduced bone metastasis burden. These findings elucidate a mechanism of ‘host’ microenvironment hijacking by mammary tumour cells to subvert the local microvasculature to form a specialised, pro-tumorigenic niche.

PMID:34836954 | DOI:10.1038/s41467-021-26556-6

BMJ Glob Health. 2021 Nov;6(11):e007405. doi: 10.1136/bmjgh-2021-007405.

ABSTRACT

Global surveys have built-in gender-related biases associated with data missingness across the gender dimensions of people’s lives, imbalanced or incomplete representation of population groups, and biased ways in which gender information is elicited and used. While increasing focus is being placed on the integration of sex-disaggregated statistics into national programmes and on understanding effects of gender-based disparities on the health of all people, the data necessary for elucidating underlying causes of gender disparities and designing effective intervention programmes continue to be lacking. Approaches exist, however, that can reasonably address some shortcomings, such as separating questions of gender identification from biological sex. Qualitative research can elucidate ways to rephrase questions and translate gendered terms to avoid perpetuating historical gender biases and prompting biased responses. Non-health disciplines may offer lessons in collecting gender-related data. Ultimately, multidisciplinary global collaborations are needed to advance this evolving field and to set standards for how we measure gender in all its forms.

PMID:34836912 | DOI:10.1136/bmjgh-2021-007405

Nat Commun. 2021 Nov 26;12(1):6923. doi: 10.1038/s41467-021-27292-7.

ABSTRACT

Nationwide nonpharmaceutical interventions (NPIs) have been effective at mitigating the spread of the novel coronavirus disease (COVID-19), but their broad impact on other diseases remains under-investigated. Here we report an ecological analysis comparing the incidence of 31 major notifiable infectious diseases in China in 2020 to the average level during 2014-2019, controlling for temporal phases defined by NPI intensity levels. Respiratory diseases and gastrointestinal or enteroviral diseases declined more than sexually transmitted or bloodborne diseases and vector-borne or zoonotic diseases. Early pandemic phases with more stringent NPIs were associated with greater reductions in disease incidence. Non-respiratory diseases, such as hand, foot and mouth disease, rebounded substantially towards the end of the year 2020 as the NPIs were relaxed. Statistical modeling analyses confirm that strong NPIs were associated with a broad mitigation effect on communicable diseases, but resurgence of non-respiratory diseases should be expected when the NPIs, especially restrictions of human movement and gathering, become less stringent.

PMID:34836947 | DOI:10.1038/s41467-021-27292-7

BMJ Open. 2021 Nov 26;11(11):e056436. doi: 10.1136/bmjopen-2021-056436.

ABSTRACT

OBJECTIVE: Patients treated with long-term opioid therapy (LTOT) are known to have compromised immune systems and respiratory function, both of which make them particularly susceptible to the SARS-CoV-2 virus. The objective of this study was to assess the risk of developing severe clinical outcomes among COVID-19 non-cancer patients on LTOT, compared with those without LTOT.

DESIGN AND DATA SOURCES: A retrospective cohort design using electronic health records in the TriNetX research database.

PARTICIPANTS AND SETTING: 418 216 adults diagnosed with COVID-19 in January-December 2020 from 51 US healthcare organisations: 9558 in the LTOT and 408 658 in the control cohort. They did not have cancer diagnoses; only a small proportion might have been treated with opioid maintenance for opioid use disorder.

RESULTS: Patient on LTOT had a higher risk ratio (RR) than control patients to visit an emergency department (RR 2.04, 95% CI 1.93 to 2.16) and be hospitalised (RR 2.91, 95% CI 2.69 to 3.15). Once admitted, LTOT patients were more likely to require intensive care (RR 3.65, 95% CI 3.10 to 4.29), mechanical ventilation (RR 3.47, 95% CI 2.89 to 4.15) and vasopressor support (RR 5.28, 95% CI 3.70 to 7.53) and die within 30 days (RR 1.96, 95% CI 1.67 to 2.30). The LTOT group also showed increased risk (RRs from 2.06 to 3.98, all significant to 95% CI) of more-severe infection (eg, cough, dyspnoea, fever, hypoxaemia, thrombocytopaenia and acute respiratory distress syndrome). Statistically significant differences in several laboratory results and other vital signs appeared clinically negligible.

CONCLUSION: COVID-19 patients on LTOT were at higher risk of increased morbidity, mortality and healthcare utilisation. Interventions to reduce the need for LTOT and to increase compliance with COVID-19 protective measures may improve outcomes and reduce healthcare cost in this population. Prospective studies need to confirm and refine these findings.

PMID:34836910 | DOI:10.1136/bmjopen-2021-056436

BMJ Open. 2021 Nov 26;11(11):e052140. doi: 10.1136/bmjopen-2021-052140.

ABSTRACT

DESIGN AND OBJECTIVES: A cross-sectional study to evaluate the impact of COVID-19 on the psychosocial sphere in both the general population and healthcare workers (HCWs).

METHODS: The study was conducted in Catalonia (Spain) during the first wave of the COVID-19 pandemic when strict lockdown was in force. The study population included all people aged over 16 years who consented to participate in the study and completed the survey, in this case a 74-question questionnaire shared via social media using snowball sampling. A total of 56 656 completed survey questionnaires were obtained between 3 and 19 April 2020.The primary and secondary outcome measures included descriptive statistics for the non-psychological questions and the psychological impact of the pandemic, such as depression, anxiety, stress and post-traumatic stress disorder question scores.

RESULTS: A n early and markedly negative impact on family finances, fear of working with COVID-19 patients and ethical issues related to COVID-19 care among HCWs was observed. A total of seven target groups at higher risk of impaired mental health and which may therefore benefit from an intervention were identified, namely women, subjects aged less than 42 years, people with a care burden, socioeconomically deprived groups, people with unskilled or unqualified jobs, patients with COVID-19 and HCWs working with patients with COVID-19.

CONCLUSIONS: Active implementation of specific strategies to increase resilience and to prepare an adequate organisational response should be encouraged for the seven groups identified as high risk and susceptible to benefit from an intervention.

TRIAL REGISTRATION NUMBER: NCT04378452.

PMID:34836903 | DOI:10.1136/bmjopen-2021-052140

BMJ Open. 2021 Nov 26;11(11):e054131. doi: 10.1136/bmjopen-2021-054131.

ABSTRACT

INTRODUCTION: The postdischarge suicide risk among psychiatric patients is significantly higher than it is among patients with other diseases and general population. The brief contact interventions (BCIs) are recommended to decrease suicide risk in areas with limited mental health service resources like China. This study aims to develop a postdischarge suicide intervention strategy based on BCIs and evaluate its implementability under the implementation outcome framework.

METHODS AND ANALYSIS: This study will invite psychiatric patients and family members, clinical and community mental health service providers as the community team to develop a postdischarge suicide intervention strategy. The study will recruit 312 patients with psychotic symptoms and 312 patients with major depressive disorder discharged from Shenzhen Kangning Hospital (SKH) in a Sequential Multiple Assignment Randomised Trial. Participants will be initially randomised into two intervention groups to receive BCIs monthly and weekly, and they will be rerandomised into three intervention groups to receive BCIs monthly, biweekly and weekly at 3 months after discharge according to the change of their suicide risk. Follow-ups are scheduled at 1, 3, 6 and 12 months after discharge. With the intention-to-treat approach, generalised estimating equation and survival analysis will be applied. This study will also collect qualitative and quantitative information on implementation and service outcomes from the community team.

ETHICS/DISSEMINATION: This study has received ethical approval from the Ethics Committee Review Board of SKH. All participants will provide written informed consent prior to enrolment. The findings of the study will be disseminated through peer-reviewed scientific journals, conference presentations. A project report will be submitted to the National Natural Science Foundation of China as the concluding report of this funded project, and to the mental health authorities in the Shenzhen to refine and apply evidence-based and pragmatic interventions into health systems for postdischarge suicide prevention.

TRIAL REGISTRATION NUMBER: NCT04907669.

PMID:34836907 | DOI:10.1136/bmjopen-2021-054131

BMJ Open. 2021 Nov 26;11(11):e050989. doi: 10.1136/bmjopen-2021-050989.

ABSTRACT

OBJECTIVE: Aiming to investigate diabetic retinopathy (DR) risk factors and predictive models by machine learning using a large sample dataset.

DESIGN: Retrospective study based on a large sample and a high dimensional database.

SETTING: A Chinese central tertiary hospital in Beijing.

PARTICIPANTS: Information on 32 452 inpatients with type-2 diabetes mellitus (T2DM) were retrieved from the electronic medical record system from 1 January 2013 to 31 December 2017.

METHODS: Sixty variables (including demography information, physical and laboratory measurements, system diseases and insulin treatments) were retained for baseline analysis. The optimal 17 variables were selected by recursive feature elimination. The prediction model was built based on XGBoost algorithm, and it was compared with three other popular machine learning techniques: logistic regression, random forest and support vector machine. In order to explain the results of XGBoost model more visually, the Shapley Additive exPlanation (SHAP) method was used.

RESULTS: DR occurred in 2038 (6.28%) T2DM patients. The XGBoost model was identified as the best prediction model with the highest AUC (area under the curve value, 0.90) and showed that an HbA1c value greater than 8%, nephropathy, a serum creatinine value greater than 100 µmol/L, insulin treatment and diabetic lower extremity arterial disease were associated with an increased risk of DR. A patient’s age over 65 was associated with a decreased risk of DR.

CONCLUSIONS: With better comprehensive performance, XGBoost model had high reliability to assess risk indicators of DR. The most critical risk factors of DR and the cut-off of risk factors can be found by SHAP method to render the output of the XGBoost model clinically interpretable.

PMID:34836899 | DOI:10.1136/bmjopen-2021-050989