admission. This proportion could already be greater in some parts of the country and may increase if referrals of cases of self-poisoning increase faster than the facilities for their assessment and management. The provision of social work and psychiatric expertise in casualty departments may be one means of preventing unnecessary medical admissions without risk to the patients. Dr Blake's and Dr Bramble's figures do not demonstrate, however, that any advantage would attach to medical teams taking over assessment from psychiatrists except that, by implication, assessments would be completed sooner by staff working on the ward full time. What the figures actually suggest is that if assessment of overdoses were left to house doctors there would be an increase in admissions to psychiatric units (by 19°U), outpatients (by 5O°'), and referrals to social services (by 140o). So for house doctors to assess overdoses would provide no economy for the psychiatric or social services. The study does not tell us what the consequences would have been for the six patients who the psychiatrists would have admitted but to whom the house doctors would have offered outpatient appointments. E J SALTER

Vitamin D deficiency.

Objective To review and appraise the validity and usefulness of published and preprint reports of prediction models for diagnosing coronavirus disease 2019 (covid-19) in patients with suspected infection, for prognosis of patients with covid-19, and for detecting people in the general population at increased risk of covid-19 infection or being admitted to hospital with the disease. Design Living systematic review and critical appraisal by the COVID-PRECISE (Precise Risk Estimation to optimise covid-19 Care for Infected or Suspected patients in diverse sEttings) group. Data sources PubMed and Embase through Ovid, up to 1 July 2020, supplemented with arXiv, medRxiv, and bioRxiv up to 5 May 2020. Study selection Studies that developed or validated a multivariable covid-19 related prediction model. Data extraction At least two authors independently extracted data using the CHARMS (critical appraisal and data extraction for systematic reviews of prediction modelling studies) checklist; risk of bias was assessed using PROBAST (prediction model risk of bias assessment tool). Results 37 421 titles were screened, and 169 studies describing 232 prediction models were included. The review identified seven models for identifying people at risk in the general population; 118 diagnostic models for detecting covid-19 (75 were based on medical imaging, 10 to diagnose disease severity); and 107 prognostic models for predicting mortality risk, progression to severe disease, intensive care unit admission, ventilation, intubation, or length of hospital stay. The most frequent types of predictors included in the covid-19 prediction models are vital signs, age, comorbidities, and image features. Flu-like symptoms are frequently predictive in diagnostic models, while sex, C reactive protein, and lymphocyte counts are frequent prognostic factors. Reported C index estimates from the strongest form of validation available per model ranged from 0.71 to 0.99 in prediction models for the general population, from 0.65 to more than 0.99 in diagnostic models, and from 0.54 to 0.99 in prognostic models. All models were rated at high or unclear risk of bias, mostly because of non-representative selection of control patients, exclusion of patients who had not experienced the event of interest by the end of the study, high risk of model overfitting, and unclear reporting. Many models did not include a description of the target population (n=27, 12%) or care setting (n=75, 32%), and only 11 (5%) were externally validated by a calibration plot. The Jehi diagnostic model and the 4C mortality score were identified as promising models. Conclusion Prediction models for covid-19 are quickly entering the academic literature to support medical decision making at a time when they are urgently needed. This review indicates that almost all pubished prediction models are poorly reported, and at high risk of bias such that their reported predictive performance is probably optimistic. However, we have identified two (one diagnostic and one prognostic) promising models that should soon be validated in multiple cohorts, preferably through collaborative efforts and data sharing to also allow an investigation of the stability and heterogeneity in their performance across populations and settings. Details on all reviewed models are publicly available at https://www.covprecise.org/. Methodological guidance as provided in this paper should be followed because unreliable predictions could cause more harm than benefit in guiding clinical decisions. Finally, prediction model authors should adhere to the TRIPOD (transparent reporting of a multivariable prediction model for individual prognosis or diagnosis) reporting guideline. Systematic review registration Protocol https://osf.io/ehc47/, registration https://osf.io/wy245. Readers’ note This article is a living systematic review that will be updated to reflect emerging evidence. Updates may occur for up to two years from the date of original publication. This version is update 3 of the original article published on 7 April 2020 (BMJ 2020;369:m1328). Previous updates can be found as data supplements (https://www.bmj.com/content/369/bmj.m1328/related#datasupp). When citing this paper please consider adding the update number and date of access for clarity.

https://www.bmj.com/content/bmj/369/bmj.m1328.full.pdf

Prediction models for diagnosis and prognosis of covid-19: systematic review and critical appraisal

Reactive oxygen species

Transmission of COVID-19 virus by droplets and aerosols: A critical review on the unresolved dichotomy.

Effects of temperature variation and humidity on the death of COVID-19 in Wuhan, China.

COVID-19 is having a great impact on public health, mortality and economy worldwide, in spite of the efforts to prevent its epidemy. The SARS-CoV-2 genome is different from that of MERS-CoV and SARS-CoV, although also expected to spread differently according to meteorological conditions. Our main goal is to investigate the role of some meteorological variables on the expansion of this outbreak. In this study, an exponential model relating the number of accumulated confirmed cases and time was considered. The rate of COVID-19 spread, using as criterion the doubling time of the number of confirmed cases, was used as dependent variable in a linear model that took four independent meteorological variables: temperature, humidity, precipitation and wind speed. Only China cases were considered, to control both cultural aspects and containment policies. Confirmed cases and the 4 meteorological variables were gathered between January 23 and March 1 (39 days) for the 31 provinces of Mainland China. Several periods of time were sampled for each province, obtaining more than one value for the rate of disease progression. Two different periods of time were tested, of 12 and 15 days, along with 3 and 5 different starting points in time, randomly chosen. The median value for each meteorological variable was computed, using the same time period; models with were selected. The rate of progression and doubling time were computed and used to fit a linear regression model. Models were evaluated using α = 0.05. Results indicate that the doubling time correlates positively with temperature and inversely with humidity, suggesting that a decrease in the rate of progression of COVID-19 with the arrival of spring and summer in the north hemisphere. A 20°C increase is expected to delay the doubling time in 1.8 days. Those variables explain 18% of the variation in disease doubling time; the remaining 82% may be related to containment measures, general health policies, population density, transportation or cultural aspects.

/pdf/role-of-temperature-and-humidity-in-the-modulation-of-the-21nxnd0ku0.pdf

Role of temperature and humidity in the modulation of the doubling time of COVID-19 cases

Since late December 2019 a new epidemic outbreak has emerged from Whuhan, China. Rapidly the new coronavirus has spread worldwide. China CDC has reported results of a descriptive exploratory analysis of all cases diagnosed until the 11th February 2020, presenting the epidemiologic curves and geo-temporal spread of COVID-19 along with case fatality rate according to some baseline characteristics, such as age, gender and several well-established high prevalence comorbidities. Despite this, we intend to increase even further the predictive value of that manuscript by presenting the odds ratio for mortality due to COVID-19 adjusted for the presence of those comorbidities and baseline characteristics such as age and gender. Besides, we present a way to determine the risk of each particular patient, given his characteristics. We found that age is the variable that presents higher risk of COVID-19 mortality, where 60 or older patients have an OR = 18.8161 (CI95%[7.1997; 41.5517]). Regarding comorbidities, cardiovascular disease appears to be the riskiest (OR= 12.8328 CI95%[10.2736; 15.8643], along with chronic respiratory disease (OR=7.7925 CI95%[5.5446; 10.4319]). Males are more likely to die from COVID-19 (OR=1.8518 (CI95%[1.5996; 2.1270]). Some limitations such as the lack of information about the correct prevalence of gender per age or about comorbidities per age and gender or the assumption of independence between risk factors are expected to have a small impact on results. A final point of paramount importance is that the equation presented here can be used to determine the probability of dying from COVID-19 for a particular patient, given its age interval, gender and comorbidities associated.

https://medrxiv.org/content/10.1101/2020.02.24.20027268v1.full.pdf

Estimation of risk factors for COVID-19 mortality - preliminary results

The present work integrates concentrations of potentially toxic elements (PTE) (i.e. As, Cd, Cr, Cu, Hg, Ni, Pb and Zn) from (i) environmental media (i.e. soil, crops) and (ii) human hair. The aim was to assess whether agricultural soil and vegetable quality are related to risks to human health from different exposures pathways and if there are any signs of it in human hair. Domestic vegetable gardens in the surroundings Estarreja chemical complex (ECC), Municipality of Estarreja, central Portugal, were the selected for the current study. Data analysis of two soil fractions (2 mm and   55 years old) showed that agricultural soil-dust ingestion induces a high-non-carcinogenic risk (HI) for As (HI up to 41 and 4.4, for children and adult, respectively), Pb (HI up to 2.5 for children) and Hg (HI up to 1.3 for children) and carcinogenic risk (CR) for As (10−3 for both age groups). Exposure through consumption of tomatoes and potatoes grown in the study soils does not present a high health hazard. However, exposure to As through consumption of cabbage presents both carcinogenic and non-carcinogenic health risks for both studied age groups (CR > 10−4 and HI > 1.1). It is likely that hair As and Hg concentrations increases in both children and adults can be related to the ingestion of agricultural soil and cabbage, and inhalation or dermal contact with contaminated soil. Nonetheless, this assumption requires further investigation, including on other potential sources of contaminants for the local population, such as dietary intake of other foodstuffs. Hair Cr content in the adult group of residents showed maximum values above the normal range for non-exposed individuals, as well as high mean and median values which may be related to the high Cr content in the studied foods. The exposure study results are in agreement with As and Hg concentrations in both children and adults hair and validate it as a biomarker of As and Hg local environmental exposure.

https://repositorio-aberto.up.pt/bitstream/10216/127260/2/399811.pdf

Human Health Risk Assessment Due to Agricultural Activities and Crop Consumption in the Surroundings of an Industrial Area

Background 
Faces play a key role in signaling social cues such as signals of trustworthiness. Although several studies identify the amygdala as a core brain region in social cognition, quantitative approaches evaluating its role are scarce.


Objectives 
This review aimed to assess the role of the amygdala in the processing of facial trustworthiness, by analyzing its amplitude BOLD response polarity to untrustworthy versus trustworthy facial signals under fMRI tasks through a Meta-analysis of effect sizes (MA). Activation Likelihood Estimation (ALE) analyses were also conducted.


Data sources 
Articles were retrieved from MEDLINE, ScienceDirect and Web-of-Science in January 2016. Following the PRISMA statement guidelines, a systematic review of original research articles in English language using the search string “(face OR facial) AND (trustworthiness OR trustworthy OR untrustworthy OR trustee) AND fMRI” was conducted.


Study selection and data extraction 
The MA concerned amygdala responses to facial trustworthiness for the contrast Untrustworthy vs. trustworthy faces, and included whole-brain and ROI studies. To prevent potential bias, results were considered even when at the single study level they did not survive correction for multiple comparisons or provided non-significant results. ALE considered whole-brain studies, using the same methodology to prevent bias. A summary of the methodological options (design and analysis) described in the articles was finally used to get further insight into the characteristics of the studies and to perform a subgroup analysis. Data were extracted by two authors and checked independently.


Data synthesis 
Twenty fMRI studies were considered for systematic review. An MA of effect sizes with 11 articles (12 studies) showed high heterogeneity between studies [Q(11) = 265.68, p < .0001; I2 = 95.86%, 94.20% to 97.05%, with 95% confidence interval, CI]. Random effects analysis [RE(183) = 0.851, .422 to .969, 95% CI] supported the evidence that the (right) amygdala responds preferentially to untrustworthy faces. Moreover, two ALE analyses performed with 6 articles (7 studies) identified the amygdala, insula and medial dorsal nuclei of thalamus as structures with negative correlation with trustworthiness. Six articles/studies showed that posterior cingulate and medial frontal gyrus present positive correlations with increasing facial trustworthiness levels. Significant effects considering subgroup analysis based on methodological criteria were found for experiments using spatial smoothing, categorization of trustworthiness in 2 or 3 categories and paradigms which involve both explicit and implicit tasks.


Limitations 
Significant heterogeneity between studies was found in MA, which might have arisen from inclusion of studies with smaller sample sizes and differences in methodological options. Studies using ROI analysis / small volume correction methods were more often devoted specifically to the amygdala region, with some results reporting uncorrected p-values based on mainly clinical a priori evidence of amygdala involvement in these processes. Nevertheless, we did not find significant evidence for publication bias.


Conclusions and implications of key findings 
Our results support the role of amygdala in facial trustworthiness judgment, emphasizing its predominant role during processing of negative social signals in (untrustworthy) faces. This systematic review suggests that little consistency exists among studies’ methodology, and that larger sample sizes should be preferred.

https://estudogeral.sib.uc.pt/bitstream/10316/47824/1/Santos-Almeida-etal-2016-journal.pone.0167276.pdf

The Role of the Amygdala in Facial Trustworthiness Processing: A Systematic Review and Meta-Analyses of fMRI Studies

The imbalance between reactive oxygen species (ROS) production and their elimination by antioxidants leads to oxidative stress. Depending on their concentration, ROS can trigger apoptosis or stimulate cell proliferation. We hypothesized that oxidative stress and mitochondrial dysfunction may participate not only in apoptosis detected in some myelodysplastic syndrome (MDS) patients, but also in increasing proliferation in other patients. We investigated the involvement of oxidative stress and mitochondrial dysfunction in MDS pathogenesis, as well as assessed their diagnostic and prognostic values. Intracellular peroxides, superoxide, superoxide/peroxides ratio, reduced glutathione (GSH), and mitochondrial membrane potential (Δψ(mit)) levels were analyzed in bone marrow cells from 27 MDS patients and 12 controls, by flow cytometry. We observed that all bone marrow cell types from MDS patients had increased intracellular peroxide levels and decreased GSH content, compared with control cells. Moreover, oxidative stress levels were MDS subtype- and risk group-dependent. Low-risk patients had the highest ROS levels, which can be related with their high apoptosis; and intermediate-2-risk patients had high Δψ(mit) that may be associated with their proliferative potential. GSH levels were negatively correlated with transfusion dependency, and peroxide levels were positively correlated with serum ferritin level. GSH content proved to be an accurate parameter to discriminate patients from controls. Finally, patients with high ROS or low GSH levels, as well as high superoxide/peroxides ratio had lower overall survival. Our results suggest that oxidative stress and mitochondrial dysfunction are involved in MDS development, and that oxidative stress parameters may constitute novel diagnosis and/or prognosis biomarkers for MDS.

Bárbara Oliveiros

Papers

Role of temperature and humidity in the modulation of the doubling time of COVID-19 cases

Estimation of risk factors for COVID-19 mortality - preliminary results

Human Health Risk Assessment Due to Agricultural Activities and Crop Consumption in the Surroundings of an Industrial Area

The Role of the Amygdala in Facial Trustworthiness Processing: A Systematic Review and Meta-Analyses of fMRI Studies

Oxidative stress and mitochondrial dysfunction play a role in myelodysplastic syndrome development, diagnosis, and prognosis: A pilot study