Short-term impact of air pollution, noise and temperature on emergency hospital admissions in Madrid (Spain) due to liver and gallbladder diseases.

BACKGROUND: Very few epidemiological studies have explored the environmental and meteorological risk factors that influence liver diseases and gallbladder disorders, and no studies have addressed the specific case of Spain. METHODS: This is a retrospective ecological study conducted during 2013-2018. We analysed emergency admissions in the central area of the Region of Madrid for the following causes: Liver and gallbladder diseases (L&GB) (ICD-10: K70-K81); disorders of gallbladder (DGB) (ICD 10: K80-K81); liver disease (LD) (ICD 10: K70-K77); alcoholic liver disease (ALD) (ICD-10: K70); viral hepatitis (VH) (ICD10:B15-B19); and hepatic failure, not elsewhere classified (HFNS) (ICD-10: K72). Independent variables used: meteorological (maximum daily temperature (Tmax in °C), minimum daily temperature (Tmin in °C), and relative humidity (RH in %)); chemical air pollution (8-hO3, NO2, PM10, PM2.5 in µg/m3); and noise pollution (equivalent level of daily noise (Ld in dB(A)). Transformed variables: extreme heat in degrees (Theat); wet cold (WC); and high ozone. We fitted Poisson models, negative binomials and zero-inflated Poisson controlled for seasonality, day of the week, holidays, trend, and autoregressive trend. Based on these models, the percentage of cases attributable to statistically significant risk factors was then estimated. RESULTS: In L&GB emergency admissions daily noise is related to 4.4% (CI95%: 0.8 7.9) of admissions; NO2 to 2.9% (CI95%: 0.1 5.7) and wet cold to 0.2% (CI95%: 0.8 7.9). Heat wave temperature was only related to ALD. In addition, the wet cold association with L&GB is also related to HFNS attributing 1.0% (CI95%: 0.3 1.8) of admissions for this cause. CONCLUSIONS: Daily noise and NO2 are associated with more than 7% of urgent L&GB admissions. Both pollutants, are mainly emitted by road traffic. A reduction of traffic in cities would result in a reduction of emergency admissions due to this cause.

Radiographic morphology of canines tested for sexual dimorphism via convolutional-neural-network-based artificial intelligence.

The permanent left mandibular canines have been used for sexual dimorphism when human identification is necessary. Controversy remains whether the morphology of these teeth is actually useful to distinguish males and females. This study aimed to assess the sexual dimorphism of canines by means of a pioneering artificial intelligence approach to this end. A sample of 13,046 teeth radiographically registered from 5838 males and 7208 females between the ages of 6 and 22.99 years was collected. The images were annotated using Darwin V7 software. DenseNet121 was used and tested based on binary answers regarding the sex (male or female) of the individuals for 17 age categories of one year each (i.e. 6-6.99, 7.7.99… 22.22.99). Accuracy rates, receiver operating characteristic (ROC) curves and confusion matrices were used to quantify and express the artificial intelligence's classification performance. The accuracy rates across age categories were between 57-76% (mean: 68%±5%). The area under the curve (AUC) of the ROC analysis was between 0.58 and 0.77. The best performances were observed around the age of 12 years, while the worst were around the age of 7 years. The morphological analysis of canines for sex estimation should be restricted and allowed in practice only when other sources of dimorphic anatomic features are not available.

Short-term impact of noise, other air pollutants and meteorological factors on emergency hospital mental health admissions in the Madrid region.

BACKGROUND: A number of environmental factors, such as air pollution, noise in urbanised settings and meteorological-type variables, may give rise to important effects on human health. In recent years, many studies have confirmed the relation between various mental disorders and these factors, with a possible impact on the increase in emergency hospital admissions due to these causes. The aim of this study was to analyse the impact of a range of environmental factors on daily emergency hospital admissions due to mental disorders in the Madrid Autonomous Region (MAR), across the period 2013-2018. METHODOLOGY: Longitudinal ecological time series study analysed by Generalised Linear Models with Poisson regression, with the dependent variable being daily Emergency Hospital Mental Health Admissions (EHMHA) in the MAR, and the independent variable being mean daily concentrations of chemical pollutants, noise levels and meteorological variables. RESULTS: EHMHA were related statistically significantly in the short term with diurnal noise levels. Relative risks (RRs) for total admissions due to mental disorders and self-inflicted injuries, in the case of diurnal noise was RR: 1.008 95%CI (1.003 1.013). Admissions attributable to diurnal noise account for 5.5% of total admissions across the study period. There was no association between hospital admissions and chemical air pollution. CONCLUSION: Noise is a variable that shows a statistically significant short-term association with EHMHA across all age groups in the MAR region. The results of this study may serve as a basis for drawing up public health guidelines and plans, which regard these variables as risk factors for mental disorders, especially in the case of noise, since this fundamentally depends on anthropogenic activities in highly urbanised areas with high levels of traffic density.

Short-term effects of air pollution and noise on emergency hospital admissions in Madrid and economic assessment.

INTRODUCTION: The aim of this study was to study the effect of air pollution and noise has on the population in Madrid Community (MAR) in the period 2013-2018, and its economic impact. METHODS: Time series study analysing emergency hospital admissions in the MAR due to all causes (ICD-10: A00-R99), respiratory causes (ICD-10: J00-J99) and circulatory causes (ICD-10: I00-I99) across the period 2013-2018. The main independent variables were mean daily PM2.5, PM10, NO2, 8-h ozone concentrations, and noise. We controlled for meteorological variables, Public Holidays, seasonality, and the trend and autoregressive nature of the series, and fitted generalised linear models with a Poisson regression link to ascertain the relative risks and attributable risks. In addition, we made an economic assessment of these hospitalisations. RESULTS: The following associations were found: NO2 with admissions due to natural (RR: 1.007, 95% CI: 1.004-1.011) and respiratory causes (RR: 1.012, 95% CI: 1.005-1.019); 8-h ozone with admissions due to natural (RR: 1.049, 95% CI: 1.014-1.046) and circulatory causes (RR: 1.088, 95% CI: 1.039-1.140); and diurnal noise (LAeq7-23h) with admissions due to natural (RR: 1.001, 95% CI: 1.001-1.002), respiratory (RR: 1.002, 95% CI: 1.001-1.003) and circulatory causes (RR: 1.003, 95% CI: 1.002-1.005). Every year, a total of 8246 (95% CI: 4580-11,905) natural-cause admissions are attributable to NO2, with an estimated cost of close on €120 million and 5685 (95% CI: 2533-8835) attributed to LAeq7-23h with an estimated cost of close on €82 million. CONCLUSIONS: Nitrogen dioxide, ozone and noise are the main pollutants to which a large number of hospitalisations in the MAR are attributed, and are thus responsible for a marked deterioration in population health and high related economic impact.

Short-term effects of tropospheric ozone and other environmental factors on emergency admissions due to pregnancy complications: A time-series analysis in the Madrid Region.

Air pollution has been linked to adverse neonatal outcomes, mainly in the case of prolonged exposures. This study focuses on the short-term effects on maternal health. We conducted a retrospective ecological time-series study in the Madrid Region covering the period 2013-2018. The independent variables were mean daily concentrations of tropospheric ozone (O3), particulate matter (PM10/PM2.5) and nitrogen dioxide (NO2), as well as noise levels. The dependent variables were daily emergency hospital admissions due to complications in pregnancy, childbirth and the puerperium. Poisson generalised linear regression models were fitted to quantify the relative and attributable risks, controlling for trend, seasonality, the autoregressive nature of the series, and a number of meteorological factors. There were 318 069 emergency hospital admissions due to obstetric complications across the 2191 days of study. Of this total: 13 164 (95%CI: 9930-16 398) admissions were attributable to exposure to O3, the only pollutant to show a statistically significant (p < 0.05) association with admissions due to hypertensive disorders; and 10 575 (95%CI: 3573-17 566) admissions were attributable to daytime noise levels, while admissions due to hyperemesis gravidarum and vomiting were related to exposure to night noise. Other pollutants which also displayed statistically significant associations were: NO2 concentrations, with admissions due to vomiting and preterm labour; PM10 concentrations, with premature rupture of membranes: and PM2.5 concentrations, with total complications. Exposure to a range of air pollutants, and ozone in particular, is associated with a higher number of emergency hospital admissions due to gestational complications. Hence, surveillance of environmental effects on maternal health should be intensified, and plans and strategies to minimise these should be drawn up.

How heat waves, ozone and sunlight hours affect endocrine and metabolic diseases emergency admissions? A case study in the region of Madrid (Spain).

BACKGROUND: Studies which analyse the joint effect of acoustic or chemical air pollution variables and different meteorological variables on neuroendocrine disease are practically nonexistent. This study therefore sought to analyse the impact of air pollutants and environmental meteorological variables on daily unscheduled admissions due to endocrine and metabolic diseases in the Madrid Region from January 01, 2013 to December 31, 2018. MATERIAL AND METHODS: We conducted a longitudinal, retrospective, ecological study of daily time series analysed by Poisson regression, with emergency neuroendocrine-disease admissions in the Madrid Region as the dependent variable. The independent variables were: mean daily concentrations of PM10, PM2.5, NO2 and O3; acoustic pollution; maximum and minimum daily temperatures; hours of sunlight; relative humidity; wind speed; and air pressure above sea level. Estimators of the statistically significant variables were used to calculate the relative risks (RRs). RESULTS: A statistically significant association was found between the increase in temperatures in heat waves, RR: 1.123 95% CI (1.001-1.018), and the number of emergency admissions, making it the main risk factor. An association between a decrease in sunlight and an increase in hospital admissions, RR: 1.005 95% CI (1.002 1.008), was likewise observed. Similarly, ozone, in the form of mean daily concentrations in excess of 44 µg/m3, had an impact on admissions due to neuroendocrine disease, RR: 1.010 95% CI (1.007-1.035). The breakdown by sex showed that in the case of women, NO2 was also a risk factor, RR: 1.021 95% CI (1.007-1.035). CONCLUSION: The results obtained in this study serve to identify risk factors for this disease, such as extreme temperatures in heat waves, O3 or NO2. The robust association found between the decrease in sunlight and increase in hospital admissions due to neuroendocrine disease serves to spotlight an environmental factor which has received scant attention in public health until now.

30 years of the ABFO study: Reproduction in a Brazilian sample.

The ABFO study on third molar development is a benchmark in the scientific literature of dental age estimation. In its 30th anniversary, the study has been reproduced in the present external validation. Standardized comparative outcomes were obtained and discussed across studies. The sample consisted of 1.087 panoramic radiographs of Brazilian females (n=542, 49.87%) and males (n=545, 50.13%) between 14 and 22.9 years. All available third molars were classified into developmental stages following Mincer's adaptation of Demirjian's system (8 sequential stages, from A to H). The mean chronological age of individuals within each stage was assessed. The probability of an individual being ≥ 18 years was calculated for each third molar, sex and stage. Maxillary and mandibular third molars showed a similar development with an agreement between stages of about 90%. In general, males developed 0.5 years (6 months) earlier than females. The probability of being an adult increased considerably when at least one third molar is in stage G. Maxillary third molars had higher coefficients of determination (right: 0.704; left: 0.702), showing that statistical models with these teeth could explain better the age estimation outcomes. The reproducibility of the ABFO study on third molar development led to reference tables and probability measures for the studied Brazilian population.

Impact of the COVID-19 Pandemic on a Cancer Fast-Track Programme.

INTRODUCTION: The COVID-19 pandemic has disrupted many aspects of clinical practice in oncology, particularly regarding early cancer diagnosis, sparking public health concerns that possible delays could increase the proportion of patients diagnosed at advanced stages. In 2009, a cancer fast-track program (CFP) was implemented at the Clinico-Malvarrosa Health Department in Valencia, Spain with the aim of shortening waiting times between suspected cancer symptoms, diagnosis and therapy initiation. OBJECTIVES: The study aimed to explore the effects of the COVID-19 pandemic on our cancer diagnosis fast-track program. METHODS: The program workflow (patients included and time periods) was analysed from the beginning of the state of alarm on March 16th, 2020 until March 15th, 2021. Data was compared with data from the same period of time from the year before (2019). RESULTS: During the pandemic year, 975 suspected cancer cases were submitted to the CFP. The number of submissions only decreased during times of highest COVID-19 incidence and stricter lockdown, and overall, referrals were slightly higher than in the previous 2 years. Cancer diagnosis was confirmed in 197 (24.1%) cases, among which 33% were urological, 23% breast, 16% gastrointestinal and 9% lung cancer. The median time from referral to specialist appointment was 13 days and diagnosis was reached at a median of 18 days. In confirmed cancer cases, treatment was started at around 30 days from time of diagnosis. In total, 61% of cancer disease was detected at early stage, 20% at locally advanced stage, and 19% at advanced stage, displaying time frames and case proportions similar to pre-pandemic years. CONCLUSIONS: Our program has been able to maintain normal flow and efficacy despite the challenges of the current pandemic, and has proven a reliable tool to help primary care physicians referring suspected cancer patients.

Improving medication adherence and effective prescribing through a patient-centered prescription model in patients with multimorbidity.

PURPOSE: This study aimed to assess the impact of the patient-centered prescription (PCP) model in medication adherence and effective prescribing in patients with multimorbidity. METHODS: Uncontrolled before-after study in an intermediate care facility in a mixed urban-rural district. Inpatients aged ≥ 65 years with multimorbidity exposed to polypharmacy before hospital admission were consecutively enrolled. Every patient's treatment plan was analyzed through the PCP model, which includes interventions aimed at improving medication adherence. The primary endpoint was the change in the proportion of adherent patients between pre-admission and after discharge for all regularly scheduled long-term medications, using the proportion of days covered (PDC). Secondary endpoints included the change on mean PDC for all long-term medications, number of long-term medications, proportion of patients with hyperpolypharmacy, medication regimen complexity index (MRCI) score, drug burden index (DBI) score, number of potential inappropriate prescribing (PIP), and proportion of patients with ≥ 2 PIPs. RESULTS: Ninety-three non-institutionalized patients were included (mean age 83.0 ± SD 6.1 years). The proportion of adherent patients increased from 22.1 to 51.9% (P < 0.001). Intervention also improved mean PDC [mean difference (95% CI) 10.6 (7.7, 13.5)] and effective prescribing through a reduction on the number of long-term medications [- 1.3 (- 1.7, - 0.9)], proportion of patients exposed to hyperpolypharmacy (- 16.1%, P < 0.001), MRCI score [- 2.2 (- 3.4, - 1.0)], DBI score [- 0.16 (- 1.8, - 1.3)], number of PIPs [- 1.6 (- 1.8, - 1.3)], and proportion of patients with ≥ 2 PIPs (- 53.7%, P < 0.001). CONCLUSION: Studied intervention provides significant effective prescribing and medication adherence enhancements in non-institutionalized older patients with multimorbidity and polypharmacy.

Analysis of vulnerability to heat in rural and urban areas in Spain: What factors explain Heat's geographic behavior?

INTRODUCTION: There is currently little knowledge and few published works on the subject of vulnerability to heat in rural environments at the country level. Therefore, the objective of this study was to determine whether rural areas are more vulnerable to extreme heat than urban areas in Spain. This study aimed to analyze whether a pattern of vulnerability depends on contextual, environmental, demographic, economic and housing variables. METHODS: An ecological, longitudinal and retrospective study was carried out based on time series data between January 01, 2000 and December 31, 2013 in 42 geographic areas in 10 provinces in Spain. We first analyzed the functional relationship between the mortality rate per million inhabitants and maximum daily temperature (Tmax). We then determined the summer temperature threshold (Pthreshold) (June-September) at which increases in mortality are produced that are attributable to heat. In a second phase, based on Pthreshold, a vulnerability variable was calculated, and its distribution was analyzed using mixed linear models from the Poisson family (link = log). In these models, the dependent variable was vulnerability, and the independent variables were exposure to high temperatures, aridity of the climate, deprivation index, percentage of people over age 65, rurality index, percentage of housing built prior to 1980 and condition of dwellings. RESULTS: Rurality was a protective factor, and vulnerability in urban areas was six times greater. In contrast, risk factors included aridity (RR = 5.89 (2.26 15.36)), living in cool summer zones (2.69 (1.23, 5.91)), poverty (4.05 (1.91 8.59)) and the percentage of dysfunctional housing (1.13 (1.04 1.24)). CONCLUSIONS: Rural areas are less vulnerable to extreme heat than the urban areas analyzed. Also, population groups with worse working conditions and higher percentages of dwellings in poor conditions are more vulnerable.

Effects of local factors on adaptation to heat in Spain (1983-2018).

The European Union is currently immersed in policy development to address the effects of climate change around the world. Key plans and processes for facilitating adaptation to high temperatures and for reducing the adverse effects on health are among the most urgent measures. Therefore, it is necessary to understand those factors that influence adaptation. The aim of this study was to provide knowledge related to the social, climate and economic factors that are related to the evolution of minimum mortality temperatures (MMT) in Spain in the rural and urban contexts, during the 1983-2018 time period. For this purpose, local factors were studied regarding their relationship to levels of adaptation to heat. MMT is an indicator that allows for establishing a relationship to between mortality and temperature, and is a valid indicator to assess the capacity of adaptation to heat of a certain population. MMT is obtained through the maximum daily temperature and daily mortality of the study period. The evolution of MMT values for Spain was established in a previous paper. An ecological, longitudinal and retrospective study was carried out. Generalized linear models (GLM) were performed to identify the variables that appeared to be related to adaptation. The adaptation was calculated as the difference in variation in MMT based on the average increase in maximum daily temperatures. In terms of adaptation to heat, urban populations have adapted more than non-urban populations. Seventy-nine percent (n = 11) of urban provinces have adapted to heat, compared to twenty-one percent (n = 3) of rural provinces that have not adapted. In terms of urban zones, income level and habituation to heat (values over the 95th percentile) were variables shown to be related to adaptation. In contrast, among non-urban provinces, a greater number of housing rehabilitation licenses and a greater number of health professionals were variables associated with higher increases in MMT, and therefore, with adaptation. These results highlight the need to carry out studies that allow for identifying the local factors that are most relevant and influential in population adaptation. More studies carried out at a small scale are needed.

Gender differences in adaptation to heat in Spain (1983-2018).

In Spain the average temperature has increased by 1.7 °C since pre-industrial times. There has been an increase in heat waves both in terms of frequency and intensity, with a clear impact in terms of population health. The effect of heat waves on daily mortality presents important territorial differences. Gender also affects these impacts, as a determinant that conditions social inequalities in health. There is evidence that women may be more susceptible to extreme heat than men, although there are relatively few studies that analyze differences in the vulnerability and adaptation to heat by sex. This could be related to physiological causes. On the other hand, one of the indicators used to measure vulnerability to heat in a population and its adaptation is the minimum mortality temperature (MMT) and its temporal evolution. The aim of this study was to analyze the values of MMT in men and women and its temporal evolution during the 1983-2018 period in Spain's provinces. An ecological, longitudinal retrospective study was carried out of time series data, based on maximum daily temperature and daily mortality data corresponding to the study period. Using cubic and quadratic fits between daily mortality rates and the temperature, the minimum values of these functions were determined, which allowed for determining MMT values. Furthermore, we used an improved methodology that provided for the estimation of missing MMT values when polynomial fits were inexistent. This analysis was carried out for each year. Later, based on the annual values of MMT, a linear fit was carried out to determine the rate of evolution of MMT for men and for women at the province level. Average MMT for all of Spain's provinces was 29.4 °C in the case of men and 28.7 °C in the case of women. The MMT for men was greater than that of women in 86 percent of the total provinces analyzed, which indicates greater vulnerability among women. In terms of the rate of variation in MMT during the period analyzed, that of men was 0.39 °C/decade, compared to 0.53 °C/decade for women, indicating greater adaptation to heat among women, compared to men. The differences found between men and women were statistically significant. At the province level, the results show great heterogeneity. Studies carried out at the local level are needed to provide knowledge about those factors that can explain these differences at the province level, and to allow for incorporating a gender perspective in the implementation of measures for adaptation to high temperatures.

Analysis of the impact of heat waves on daily mortality in urban and rural areas in Madrid.

The objective of this study was to analyze and compare the effect of high temperatures on daily mortality in the urban and rural populations in Madrid. Data were analyzed from municipalities in Madrid with a population of over 10,000 inhabitants during the period from January 1, 2000 to December 31, 2020. Four groups were generated: Urban Metropolitan Center, Rural Northern Mountains, Rural Center, and Southern Rural. The dependent variable used was the rate of daily mortality due to natural causes per million inhabitants (CIE-X: A00-R99) between the months of June and September for the period. The primary independent variable was maximum daily temperature. Social and demographic "context variables" were included: population >64 years of age (%), deprivation index and housing indicators. The analysis was carried out in three phases: 1) determination of the threshold definition temperature of a heat wave (Tumbral) for each study group; 2) determination of relative risks (RR) attributable to heat for each group using Poisson linear regression (GLM), and 3) calculation of odds ratios (OR) using binomial family GLM for the frequency of the appearance of heat waves associated with context variables. The resulting percentiles (for the series of maximum daily temperatures for the summer months) corresponding to Tthreshold were: 74th percentile for Urban Metropolitan Center, 76th percentile for Southern Rural, 83rd for Rural Northern Mountains and 98th percentile for Center Rural (98). Greater vulnerability was found for the first two. In terms of context variables that explained the appearance of heat waves, deprivation index level, population >64 years of age and living in the metropolitan area were found to be risk factors. Rural and urban areas behaved differently, and socioeconomic inequality and the composition of the population over age 64 were found to best explain the vulnerability of the Rural Center and Southern Rural zones.

A review on impedimetric immunosensors for pathogen and biomarker detection.

Since the discovery of antibiotics in the first quarter of the twentieth century, their use has been the principal approach to treat bacterial infection. Modernized medicine such as cancer therapy, organ transplantation or advanced major surgeries require effective antibiotics to manage bacterial infections. However, the irresponsible use of antibiotics along with the lack of development has led to the emergence of antimicrobial resistance which is considered a serious global threat due to the rise of multidrug-resistant bacteria (Wang et al. in Antibiotic resistance: a rundown of a global crisis, pp. 1645-1658, 2018). Currently employed diagnostics techniques are microscopy, colony counting, ELISA, PCR, RT-PCR, surface-enhanced Raman scattering and others. These techniques provide satisfactory selectivity and sensitivity (Joung et al. in Sens Actuators B Chem 161:824-831, 2012). Nevertheless, they demand specialized personnel and expensive and sophisticated machinery which can be labour-intensive and time-consuming, (Malvano et al. in Sensors (Switzerland) 18:1-11, 2018; Mantzila et al. in Anal Chem 80:1169-1175, 2008). To get around these problems, new technologies such as biosensing and lab-on-a-chip devices have emerged in the last two decades. Impedimetric immunosensors function by applying electrochemical impedance spectroscopy to a biosensor platform using antibodies or other affinity proteins such as Affimers (Tiede et al. in Elife 6(c):1-35, 2017) or other binding proteins (Weiss et al. in Electrochim Acta 50:4248-4256, 2005) as bioreceptors, which provide excellent sensitivity and selectivity. Pre-enrichment steps are not required and this allows miniaturization and low-cost. In this review different types of impedimetric immunosensors are reported according to the type of electrode and their base layer materials, either self-assembled monolayers or polymeric layers, composition and functionalization for different types of bacteria, viruses, fungi and disease biomarkers. Additionally, novel protein scaffolds, both antibody derived and non-antibody derived, used to specifically target the analyte are considered.

Miller-Fisher syndrome after SARS-CoV-2 infection.

INTRODUCTION: On March 11th, 2020, the WHO declared the SARS-Cov-2 pandemic. Syndromes have been detected in relation to COVID-19 such as encephalitis, acute necrotizing hemorrhagic encephalopathy and cerebrovascular complications. There are also cases of peripheral nervous system involvement. METHODS: Our case would be the 3rd patient with MFS associated with COVID-19 as far as we know. RESULTS: We present a 51 years old female diagnosed with MFS two weeks after COVID-19. RTPCR to SARS-CoV-2 was negative but IgG was positive. CONCLUSION: Most of the cases were mild or moderate with typical signs and symptoms. All were treated with IV immunoglobulin with good response in most cases. Despite the short evolution time of the cases surviving the current pandemic, the description of cases of post-infectious neurological syndromes suggests that this is probably not an infrequent complication in the subacute stage of Covid-19 disease.

Implications of grey zone results for routine hepatitis C virus screening with the ARCHITECT HCV-Ag assay.

AIMS: Hepatitis C virus antigen (HCV-Ag) detection requires retesting for samples with grey zone results (GzR), adding cost and time and decreasing reliability. Our aim in this study was to evaluate the frequency and significance of GzR during the use of the automated Architect HCV-Ag assay in routine clinical practice. METHODS AND RESULTS: We studied HCV-Ag levels in 952 serum samples using the ARCHITECT HCV-Ag assay. GzR were detected in 33 samples; 25 were reactive on retesting and 19 were anti-HCV positive. Seventeen of these 19 samples were tested for HCV-RNA and were all reactive (viral loads <104  IU ml-1 ). The remaining six samples were anti-HCV nonreactive and had undetectable HCV-RNA. Eight GzR samples were nonreactive on retesting, seven were anti-HCV nonreactive (three underwent HCV-RNA quantification and were all nonreactive), and one was anti-HCV reactive (HCV-RNA nonreactive). No significant differences were found on comparing HCV-Ag values. CONCLUSIONS: Grey zone results found to be negative on retesting do not need additional technique testing, except in donor screening scenarios, where the use of molecular methods would be advisable. SIGNIFICANCE AND IMPACT OF THE STUDY:  The proposed diagnostic algorithm confirms that, eventhough GzR occur, hepatitis C virus antigen is a robust alternative to HCV-RNA detection in the active detection of infections.

The impact of heat waves on daily mortality in districts in Madrid: The effect of sociodemographic factors.

Although there is significant scientific evidence on the impact of heat waves, there are few studies that analyze the effects of sociodemographic factors on the impact of heat waves below the municipal level. The objective of this study was to analyze the role of income level, percent of the population over age 65, existence of air conditioning units and hectares (Ha) of green zones in districts in Madrid, in the impact of heat on daily mortality between January 1, 2010 and December 31, 2013. Seventeen districts were analyzed, and Generalized Linear (GLM) Poisson Regression Models were used to calculate relative risks (RR) and attributable risks (RA) for the impact of heat waves on mortality due to natural causes (CIEX:A00-R99). The pattern of risks obtained was analyzed using GLM univariates and multivariates of the binomial family (link logit), introducing the socioeconomic and demographic variables mentioned above. The results indicate that heat wave had an impact in only three of the districts analyzed. In the univariate models, all of the variables were statistically significant, but Ha of green zones lost significance in the multivariate model. Income level, existence of air conditioning units, and percent of the population over age 65 in the district remained as variables that modulate the impact of heat wave on daily mortality in the municipality of Madrid. Income level was the key variable that explained this behavior. The results obtained in this study show that there are factors at levels below the municipal level (district level) that should be considered as focus areas for health policy in order to decrease the impact of heat and promote the process of adaptation to heat in the context of climate change.

Optimizing drug therapy in frail patients with type 2 diabetes mellitus.

BACKGROUND: Type 2 diabetes mellitus (T2DM) is closely linked with ageing. In frail diabetic patients, the risks of intensive antidiabetic therapy outweigh the potential benefits. AIMS: To study the prevalence of T2DM in frail elderly patients, to identify inappropriate prescription (IP) of antidiabetic drugs and to study the relationship between patients' frailty index (FI) with polypharmacy and IP. METHODS: This was a prospective, descriptive, observational study of elderly patients. Each patient's antidiabetic treatment was analysed by applying the patient-centred prescription model (PCP), which centres therapeutic decisions on the patient's global assessment and individual therapeutic goal. RESULTS: 210 patients with T2DM were included (25.15% prevalence). They were characterised by high multimorbidity and frailty. 93.3% presented polypharmacy and 51% excessive polypharmacy. IP was identified in 66.2% of patients. A statistically significant relationship was found between the progression in FI degree and IP prevalence (p < 0.05. During the admission, drug therapy regimens were modified in 97.1% of cases with IP (n = 136). DISCUSSION: These results suggest that in clinical practice T2DM treatment is not individualised, but rather is based on the same general recommendations for the population as a whole. CONCLUSIONS: There is a high prevalence of T2DM in the elderly. As the frailty of patients increases, so does the prevalence of IP. The application of PCP model enables drug therapy optimization in frail patients according to their main therapeutic goal, and contributes to provide clinical evidences on the applicability of a set of knowledge areas from the theoretical framework to the daily clinical practice.

[Case fatality of COVID-19 in patients with neurodegenerative dementia]. / Análisis de letalidad por COVID-19 en pacientes con demencia neurodegenerativa.

Introduction: The elderly population is the group most threatened by COVID-19, with the highest mortality rates. This study aims to analyse the case fatality of COVID-19 in a cohort of patients with degenerative dementia. Methods: We conducted a descriptive case-control study of a sample of patients diagnosed with primary neurodegenerative dementia. Results: Twenty-four of the 88 patients with COVID-19 included in the study died: 10/23 (43.4%) patients diagnosed with dementia and 14/65 (21.5%) controls; this difference was statistically significant. Discussion: Our results suggest that case fatality of COVID-19 is significantly higher among patients with primary degenerative dementia than in other patients with similar mean ages and comorbidities.

Single-shot slightly off-axis digital holographic microscopy with add-on module based on beamsplitter cube.

Slightly off-axis digital holographic microscopy (SO-DHM) has recently emerged as a novel experimental arrangement for quantitative phase imaging (QPI). It offers improved capabilities in conventional on-axis and off-axis interferometric configurations. In this contribution, we report on a single-shot SO-DHM approach based on an add-on module adapted to the exit port of a regular microscope. The module employs a beamsplitter (BS) cube interferometer and includes, in addition, a Stokes lens (SL) for astigmatism compensation. Each recorded frame contains two fields of view (FOVs) of the sample, where each FOV is a hologram which is phase shifted by π rads with respect to the other. These two simultaneously recorded holograms are numerically processed, in order to retrieve complex amplitude distribution with enhanced quality. The tradeoff is done in the FOV which becomes penalized as a consequence of the simultaneous recording of the two holograms in a single snapshot. Experimental validation is presented for a wide variety of samples using a regular Olympus BX-60 upright microscope. The proposed approach provides an optimized use of the imaging system, in terms of the space-bandwidth product, in comparison with off-axis configuration; allows the analysis of fast-dynamic events, owing to its single-shot capability when compared with on-axis arrangement; and becomes easily implementable in conventional white-light microscopes for upgrading them into holographic microscopes for QPI.