Analysis of the circumstances associated with death and predictors of mortality in Spanish adults with Down syndrome, 1997-2014.

OBJECTIVES: Characterise the circumstances associated with death during admission of adults with Down syndrome (DS) and to identify predictors of mortality. PATIENTS AND METHODS: Observational study based on data on all emergent admissions of adults with DS to hospitals of the Spanish National Health System between 1997 and 2014. We analysed epidemiological and clinical variables. RESULTS: We analysed admissions of 11,594 adults with DS, mean age 47 years. 1715 patients died (15%), being the highest mortality (35%) in individuals aged 50-59. A past medical history of cerebrovascular disease (aOR 2.95 [2.30-3.77]) or cancer (aOR 2.79 [2.07-3.75]), gross aspiration's admission (aOR 2.59 [2.20-3.04]), immobility (aOR 2.31 [1.46-3-62]), and readmission within 30 days (aOR 2.43 [2.06-2.86]) were identified as predictors of mortality. CONCLUSIONS: Adults with DS have a high in-hospital mortality rate. The main predictors of death were cerebrovascular disease, cancer, early readmission, and conditions commonly associated with advanced dementia.

Real life results of direct-acting oral anticoagulants recommended-dose in obese vs normal-weight patients with venous thromboembolism.

BACKGROUND: There is scarce evidence on the effectiveness and safety of recommended-dose direct acting oral anticoagulants (DOACs) in obese patients with venous thromboembolism (VTE). MATERIAL AND METHODS: We used the data in the RIETE registry to compare the rates of VTE recurrences and major bleeding during long-term therapy with DOACs at recommended doses in patients with body mass index ≥30 kg/m2 (obese) vs. those with BMI 18.5-24.9 kg/m2 (normal weight). We performed regression models with competing risks for death. RESULTS: From January 2013 through October 2022, 2885 obese patients and 2676 with normal weight in RIETE received rivaroxaban (n = 3020), apixaban (n = 1754), edoxaban (n = 636) or dabigatran (n = 151). Median age was 63 years and 52 % were female. At baseline, obese patients were more likely to have diabetes (18.6 % vs. 8.4 %), hypertension (51.9 % vs. 31.4 %) or pulmonary embolism (67.7 % vs. 61 %), and less likely to have renal insufficiency (5.3 % vs. 16 %) or anaemia (21.8 % vs. 28 %%). During anticoagulation (median, 147 vs. 101 days), the obese had a similar rate of VTE recurrences (1.71 vs. 2.14 events per 100 patients-years; hazard ratio (HR): 0.81; 95 % CI: 0.49-1.34) or major bleeding (1.45 vs. 1.76 per 100 patients-years; HR: 0.91; 95 % CI: 0.52-1.59) than those with normal weight. These findings persisted after multivariable analysis (recurrent VTE, HR: 0.80; 95 % CI: 0.48-1.32; major bleeding, HR: 1.11; 95 % CI: 0.60-2.07). CONCLUSION: The use of DOACs at recommended doses in obese patients with VTE was associated with similar rates of VTE recurrences or major bleeding than in patients with normal weight.

Weekend and holiday admissions for decompensated heart failure and in-hospital mortality. A cumulative effect of "nonworking" days?

INTRODUCTION AND OBJECTIVES: The aim of this study was to analyze whether nonelective admissions in patients with heart failure (HF) on nonworking days (NWD) are associated with higher in-hospital mortality. METHODS: We conducted a retrospective (2018-2019) observational study of episodes of nonelective admissions in patients aged 18 years and older discharged with a principal diagnosis of HF in acute general hospitals of the Spanish National Health System. NWD at admission were defined as Fridays after 14:00hours, Saturdays, Sundays, and national and regional holidays. In-hospital mortality was analyzed with logistic regression models. The length of NWD was considered as an independent continuous variable. Propensity score matching was used as a sensitivity analysis. RESULTS: We selected 235 281 episodes of nonelective HF admissions. When the NWD periods were included in the in-hospital mortality model, the increases in in-hospital mortality compared with weekday admission were as follows: 1 NWD day (OR, 1.11; 95%CI, 1.07-1.16); 2 days (OR, 1.13; 95%CI, 1.09-1.17); 3 (OR, 1.16; 95%CI, 1.05-1.27); and ≥4 days (OR, 1.20; 95%CI, 1.09-1.32). There was a statistically significant association between a linear increase in NWD and higher risk-adjusted in-hospital mortality (chi-square trend P=.0002). After propensity score matching, patients with HF admitted on NWD had higher in-hospital mortality than those admitted on weekdays (OR, 1.11; average treatment effect, 12.2% vs 11.1%; P<.001). CONCLUSIONS: We found an association between admissions for decompensated HF on an NWD and higher in-hospital mortality. The excess mortality is likely not explained by differences in severity. In this study, the "weekend effect" tended to increase as the NWD period became longer.

Performance of a multidisciplinary robotic surgery program at a university hospital (2012-2022).

Robotic-assisted surgery has become widely adopted for its ability to expand the indications for minimally invasive procedures. This technology aims to improve precision, accuracy, and outcomes while reducing complications, blood loss, and recovery time. Successful implementation of a robotic surgery program requires careful initial design and a focus on maintenance and expansion to maximize its benefits. This article presents a comprehensive study conducted at a University Hospital on the robotic surgery program from December 2012 to December 2022. Data from hospital databases, including patient demographics, surgical department, surgical time, operating room occupancy, and primary diagnosis, were analyzed. The analysis covered various time periods (surgical sessions, weeks, months, and years) to assess the program's evolution over time. Over the 10-year period, a total of 1847 robotic-assisted interventions were performed across five surgical services. Urology accounted for 57% of the cases, general surgery 17%, gynecology 16%, otorhinolaryngology 6%, and thoracic surgery 4%. The most frequently performed procedures included robotic prostatectomies (643 cases), hysterectomies (261 cases), and colposacropexies (210 cases). The weekly volume of interventions showed a notable increase, rising from 2 cases per week in 2013-2014 cases in 2022. Moreover, the average surgical duration per intervention exhibited a progressive decrease from 275 min in 2013 to 184 min in 2022. This study highlights the potential of a well-managed robotic surgery program as a viable alternative to conventional surgical approaches. Effective coordination and resource utilization contribute to the program's efficiency. The findings underscore the successful integration of robotic-assisted surgery in diverse surgical specialties.

Influence of meteorological factors on the severity of COVID-19 in Spain: Observational ecological study.

Objectives: Evaluating whether meteorological and geographical variables could be associated with the severity of COVID-19 in Spain. Methods: An ecological study was performed to analyze the influence of meteorological and geographical factors in hospital admissions and deaths due to COVID-19 in the 52 provinces of Spain (24 coastal and 28 inland regions), during the first three pandemic waves. Medical and mortality data were collected from the Carlos III Health Institute (ISCIII) and meteorological variables were requested to the Spanish State Meteorological Agency (AEMET). Results: Regarding the diagnosed cases it is remarkable that the percentage of patients hospitalized for COVID-19 was lower in the coastal provinces than in the inland ones (8.7 ± 2.6% vs. 11.5 ± 2.6%; p = 9.9 × 10-5). Furthermore, coastal regions registered a lower percentage of mortality than inland regions (2.0 ± 0.6% vs. 3.1 ± 0.8%; p = 1.7 × 10-5). Mean air temperature was inversely correlated both with COVID-19 hospitalizations (Rho: -0.59; p = 3.0 × 10-6) and mortality (Rho: -0.70; p = 5.3 × 10-9). In those provinces with a mean air temperature <10 °C mortality by COVID-19 was twice that of those with >16 °C. Finally, we found an association between mortality and the location of the province (coastal/inland), altitude, patient age and the average air temperature; the latter was inversely and independently correlated with mortality (non standardised B coeff.: -0.24; IC 95%: -0.31 to -0.16; p = 2.38 × 10-8). Conclusions: The average air temperature was inversely associated with COVID-19 mortality in our country during the first three waves of the pandemic.

Objetivos: Evaluar si factores meteorológicos y geográficos pudieron relacionarse con la gravedad de la COVID-19 en España. Métodos: Estudio ecológico, a escala provincial, que analiza la influencia de factores meteorológicos y geográficos en la hospitalización y mortalidad por COVID-19 en las 52 provincias españolas (24 costeras y 28 del interior), durante las tres primeras olas. Los datos de hospitalizaciones y mortalidad se obtuvieron del Instituto de Salud Carlos III (ISCIII). Los datos epidemiológicos del Instituto Nacional Estadística (INE) y la Red Nacional de Vigilancia Epidemiológica (RENAVE). Las variables meteorológicas de la Agencia estatal de meteorología (AEMET). Resultados: El porcentaje de pacientes hospitalizados por COVID-19, del total de personas infectadas, fue inferior en las provincias costeras que en las del interior peninsular (8,7 ± 2,6% vs. 11,5 ± 2,6%; p = 9,9 × 10−5). De igual manera la costa registró menor porcentaje de mortalidad que el interior peninsular (2,0 ± 0,6% vs. 3,1 ± 0,8%; p = 1,7 × 10−5). La temperatura media correlacionó negativamente con la hospitalización (Rho: −0,59; p = 3,0 × 10−6) y la mortalidad por COVID-19 (Rho: −0,70; p = 5,3 × 10−9). Las provincias con una temperatura media <10 °C duplicaron la mortalidad por COVID respecto a las de >16 °C. La mortalidad se relacionó con la localización provincial (costa/interior), la altitud, la edad de la población y la temperatura media, siendo esta última la variable asociada de manera independiente (Coef. B no estandarizado: −0,24; IC 95%: −0,31 a −0,16; p = 2,38 × 10−8). Conclusiones: La mortalidad por COVID-19 durante las tres primeras olas de la pandemia en nuestro país se asoció inversamente con la temperatura media.

Influencia de los factores meteorológicos en la gravedad de la COVID-19 en España: estudio observacional ecológico / Influence of meteorological factors on the severity of COVID-19 in Spain: Observational ecological study

Objetivos: Evaluar si factores meteorológicos y geográficos pudieron relacionarse con la gravedad de la COVID-19 en España.MétodosEstudio ecológico, a escala provincial, que analiza la influencia de factores meteorológicos y geográficos en la hospitalización y en la mortalidad por COVID-19 en las 52 provincias españolas (24 costeras y 28 del interior) durante las tres primeras olas. Los datos de hospitalizaciones y de mortalidad se obtuvieron del Instituto de Salud CarlosIII (ISCIII); los datos epidemiológicos, del Instituto Nacional de Estadística (INE) y de la Red Nacional de Vigilancia Epidemiológica (RENAVE), y las variables meteorológicas, de la Agencia Estatal de Meteorología (AEMET).ResultadosEl porcentaje de pacientes hospitalizados por COVID-19, del total de personas infectadas, fue inferior en las provincias costeras que en las del interior peninsular (8,7±2,6% vs. 11,5±2,6%; p=9,9×10−5). De igual manera, la costa registró menor porcentaje de mortalidad que el interior peninsular (2,0±0,6% vs. 3,1±0,8%; p=1,7×10−5). La temperatura media correlacionó negativamente con la hospitalización (Rho: −0,59; p=3,0×10−6) y la mortalidad por COVID-19 (Rho: −0,70; p=5,3×10−9). Las provincias con una temperatura media <10°C duplicaron la mortalidad por COVID respecto a las de >16°C. La mortalidad se relacionó con la localización provincial (costa/interior), la altitud, la edad de la población y la temperatura media, siendo esta última la variable asociada de manera independiente (Coef.B no estandarizado: −0,24; IC95%: −0,31 a −0,16; p=2,38×10−8). (AU)

Objectives: Evaluating whether meteorological and geographical variables could be associated with the severity of COVID-19 in Spain.MethodsAn ecological study was performed to analyze the influence of meteorological and geographical factors in hospital admissions and deaths due to COVID-19 in the 52 provinces of Spain (24 coastal and 28 inland regions), during the first three pandemic waves. Medical and mortality data were collected from the CarlosIII Health Institute (ISCIII) and meteorological variables were requested to the Spanish State Meteorological Agency (AEMET).ResultsRegarding the diagnosed cases it is remarkable that the percentage of patients hospitalized for COVID-19 was lower in the coastal provinces than in the inland ones (8.7±2.6% vs. 11.5±2.6%; P=9.9×10−5). Furthermore, coastal regions registered a lower percentage of mortality than inland regions (2.0±0.6% vs. 3.1±0.8%; P=1.7×10−5). Mean air temperature was inversely correlated both with COVID-19 hospitalizations (Rho: −0.59; P=3.0×10−6) and mortality (Rho: −0.70; P=5.3×10−9). In those provinces with a mean air temperature <10°C mortality by COVID-19 was twice that of those with >16°C. Finally, we found an association between mortality and the location of the province (coastal/inland), altitude, patient age and the average air temperature; the latter was inversely and independently correlated with mortality (non-standardized β coeff.: −0.24; 95%CI: −0.31 to −0.16; P=2.38×10−8).ConclusionsThe average air temperature was inversely associated with COVID-19 mortality in our country during the first three waves of the pandemic. (AU)

Temporal Series Analysis of Population Cycle Threshold Counts as a Predictor of Surge in Cases and Hospitalizations during the SARS-CoV-2 Pandemic.

Tools to predict surges in cases and hospitalizations during the COVID-19 pandemic may help guide public health decisions. Low cycle threshold (CT) counts may indicate greater SARS-CoV-2 concentrations in the respiratory tract, and thereby may be used as a surrogate marker of enhanced viral transmission. Several population studies have found an association between the oscillations in the mean CT over time and the evolution of the pandemic. For the first time, we applied temporal series analysis (Granger-type causality) to validate the CT counts as an epidemiological marker of forthcoming pandemic waves using samples and analyzing cases and hospital admissions during the third pandemic wave (October 2020 to May 2021) in Madrid. A total of 22,906 SARS-CoV-2 RT-PCR-positive nasopharyngeal swabs were evaluated; the mean CT value was 27.4 (SD: 2.1) (22.2% below 20 cycles). During this period, 422,110 cases and 36,727 hospital admissions were also recorded. A temporal association was found between the CT counts and the cases of COVID-19 with a lag of 9-10 days (p ≤ 0.01) and hospital admissions by COVID-19 (p < 0.04) with a lag of 2-6 days. According to a validated method to prove associations between variables that change over time, the short-term evolution of average CT counts in the population may forecast the evolution of the COVID-19 pandemic.

Cross-Sectional Analysis of Risk Factors for Outbreak of COVID-19 in Nursing Homes for Older Adults in the Community of Madrid.

INTRODUCTION: Nursing homes for older adults have been hot spots for SARS-CoV-2 infections and mortality. Factors that facilitate COVID-19 outbreaks in these settings need to be assessed. METHODS: A retrospective cross-sectional study of a cohort of residents and workers in nursing homes taking occasion of a point seroprevalence survey was done in the Community of Madrid. Factors related to outbreaks in these facilities were analyzed. RESULTS: A total of 369 nursing homes for older adults, making a population of 23,756 residents and 20,795 staff members, were followed from July to December 2020. There were 54.2% SARS-CoV-2 IgG+ results in residents and in 32.2% of workers. Sixty-two nursing homes (16.8%) had an outbreak during the follow-up. Nursing homes with outbreaks had more residents than those without (median number of 81 [IQR, 74] vs. 50 [IQR, 56], p < 0.001). Seropositivity for SARS-CoV-2 was lower in facilities with versus without outbreaks, for residents (42.2% [IQR, 55.7] vs. 58.7% [IQR, 43.4], p = 0.002) and for workers (23.9% [IQR, 26.4] vs. 32.8% [IQR, 26.3], p = 0.01). For both residents and staff, the number of infections in outbreaks was larger in centers with lower, as compared with intermediate or high seroprevalence. The size of the facility did not correlate with the number of cases in the outbreak. Taking the incidence of cases in the community as a time-dependent variable (p = 0.03), a Cox analysis (HR [95% CI], p) showed that intermediate or high seroprevalence among residents in the facility was related to a reduction of 55% (0.45 [0.25-0.80], p = 0.007) and 78% (0.22 [0.10-0.48], p < 0.001) in the risk of outbreaks, respectively, as compared with low sero-prevalence. Also, as compared with smaller, medium (1.91 [1.00-3.65], p = 0.05) or large centers (4.57 [2.38-8.75], p < 0.001) had more respective risk of outbreaks. CONCLUSIONS: The size of the facility and the seroprevalence among residents in nursing homes, and the incidence of infections in the community, are associated with the risk of outbreaks of COVID-19. Facilities with greater proportion of seropositives had smaller number of cases. Monitoring of immunity in nursing homes may help detect those at a greater risk of future cases.

[Influence of meteorological factors on the severity of COVID-19 in Spain: Observational ecological study]. / Influencia de los factores meteorológicos en la gravedad de la COVID-19 en España: estudio observacional ecológico.

OBJECTIVES: Evaluating whether meteorological and geographical variables could be associated with the severity of COVID-19 in Spain. METHODS: An ecological study was performed to analyze the influence of meteorological and geographical factors in hospital admissions and deaths due to COVID-19 in the 52 provinces of Spain (24 coastal and 28 inland regions), during the first three pandemic waves. Medical and mortality data were collected from the CarlosIII Health Institute (ISCIII) and meteorological variables were requested to the Spanish State Meteorological Agency (AEMET). RESULTS: Regarding the diagnosed cases it is remarkable that the percentage of patients hospitalized for COVID-19 was lower in the coastal provinces than in the inland ones (8.7±2.6% vs. 11.5±2.6%; P=9.9×10-5). Furthermore, coastal regions registered a lower percentage of mortality than inland regions (2.0±0.6% vs. 3.1±0.8%; P=1.7×10-5). Mean air temperature was inversely correlated both with COVID-19 hospitalizations (Rho: -0.59; P=3.0×10-6) and mortality (Rho: -0.70; P=5.3×10-9). In those provinces with a mean air temperature <10°C mortality by COVID-19 was twice that of those with >16°C. Finally, we found an association between mortality and the location of the province (coastal/inland), altitude, patient age and the average air temperature; the latter was inversely and independently correlated with mortality (non-standardized ß coeff.: -0.24; 95%CI: -0.31 to -0.16; P=2.38×10-8). CONCLUSIONS: The average air temperature was inversely associated with COVID-19 mortality in our country during the first three waves of the pandemic.

What brings adults with Down syndrome to the hospital? A retrospective review of a Spanish cohort between 1997 and 2014.

OBJECTIVES: To describe the clinical and epidemiological characteristics of adult patients with Down syndrome admitted to Spanish hospitals between 1997 and 2014. Secondary goals were to study trend changes over time, and to analyse differences between patients admitted to medical and surgical departments. PATIENTS AND METHODS: Retrospective observational study on data collected from the Minimum Basic Dataset (MBDS, Conjunto Mínimo Básico de Datos [CMBD]) of admissions of adults with Down syndrome to hospitals belonging to the Spanish National Health System from 1 January 1997 through 31 December 2014. We analysed epidemiological and clinical variables. RESULTS: We analysed 28,716 admissions of 16,874 adult patients with Down syndrome. Men accounted for 58.2% of the sample, and the mean age on admission was 41 ± 13 years, with an 11-year increase in mean age during the study period. Admissions among persons with Down syndrome increased by 5% during the study period, with a noticeable rise in admissions of older adults and to medical departments. Almost one-third of patients (31.8%) were admitted more than once. Age-adjusted mortality was 15.7%. The most common comorbid conditions were chronic obstructive pulmonary disease (25%), hypothyroidism (18.6%), and epilepsy (14.3%). The departments with the highest numbers of admissions were internal medicine (26.3%), pulmonary medicine (6.9%), and general surgery (5.25%). CONCLUSION: Hospital admissions among Spanish adults with Down syndrome have increased in recent decades, especially in older patients. We identified substantial differences between patients admitted to medical and surgical departments.

Influence of weather factors on the incidence of COVID-19 in Spain.

Introduction: Several studies have analyzed the influence of meteorological and geographical factors on the incidence of COVID-19. Seasonality could be important in the transmission of SARS-CoV-2. This study aims to evaluate the geographical pattern of COVID-19 in Spain and its relationship with different meteorological variables. Methods: A provincial ecological study analyzing the influence of meteorological and geographical factors on the cumulative incidence of COVID-19 in the 52 (24 coastal and 28 inland) Spanish provinces during the first three waves was carried out. The cumulative incidence was calculated with data from the National Statistical Institute (INE) and the National Epidemiological Surveillance Network (RENAVE), while the meteorological variables were obtained from the Spanish Meteorological Agency (AEMET). Results: The total cumulative incidence, in all three waves, was lower in the coastal provinces than in the inland ones (566 ± 181 vs. 782 ± 154; P = 2.5 × 10-5). The cumulative incidence correlated negatively with mean air temperature (r = -0.49; P = 2.2 × 10-4) and rainfall (r = -0.33; P = .01), and positively with altitude (r = 0.56; P = 1.4 × 10-5). The Spanish provinces with an average temperature <10 °C had almost twice the cumulative incidence than the provinces with temperatures >16 °C. The mean air temperature and rainfall were associated with the cumulative incidence of COVID-19, regardless of other factors (Beta Coefficient of -0.62; P = 3.7 × 10-7 and -0.47; P = 4.2 × 10-5 respectively). Conclusions: Meteorological and geographical factors could influence the evolution of the pandemic in Spain. Knowledge regarding the seasonality of the virus would help to predict new waves of COVID-19 infections.

Introducción: Varios estudios han analizado la influencia de factores meteorológicos y geográficos en la incidencia de COVID-19. La estacionalidad podría tener importancia en la transmisión de SARS-CoV-2. Nuestro estudio evalúa el patrón geográfico de la COVID-19 en España y su relación con las distintas variables meteorológicas. Métodos: Estudio ecológico a escala provincial que analiza la influencia de factores meteorológicos y geográficos en la incidencia acumulada de COVID-19 en las 52 provincias españolas (24 costeras y 28 del interior) durante las tres primeras olas. La incidencia acumulada se calculó con los datos del Instituto Nacional Estadística (INE) y la Red Nacional de Vigilancia Epidemiológica (RENAVE), las variables meteorológicas se obtuvieron de la Agencia estatal de meteorología (AEMET). Resultados: La incidencia acumulada total, en los tres periodos, fue menor en las provincias costeras que en las del interior (566 ± 181 vs. 782 ± 154; P = 2,5 × 10−5). La incidencia acumulada correlacionó negativamente con la temperatura media (r = −0,49; P = 2,2 × 10−4) y las precipitaciones (r = −0,33; P = ,01), y positivamente con la altitud (r = 0,56; P = 1,4 × 10−5). Las provincias españolas con una temperatura media <10 °C tuvieron casi el doble de incidencia acumulada que las provincias con temperaturas >16 °C. La temperatura media y las precipitaciones fueron las variables asociadas con la incidencia acumulada provincial de COVID-19, con independencia de otros factores (Coeficiente Beta de −0,62; P = 3,7 × 10−7 y −0,47; P = 4,2 × 10−5 respectivamente). Conclusiones: Los factores meteorológicos y geográficos podrían influir en la evolución de la pandemia en España. El reconocimiento de la estacionalidad del COVID-19 ayudaría a predecir nuevas olas.

Influencia de los factores meteorológicos en la incidencia de COVID-19 en España / Influence of weather factors on the incidence of COVID-19 in Spain

Introducción: Varios estudios han analizado la influencia de factores meteorológicos y geográficos en la incidencia de COVID-19. La estacionalidad podría tener importancia en la transmisión de SARS-CoV-2. Nuestro estudio evalúa el patrón geográfico de la COVID-19 en España y su relación con las distintas variables meteorológicas.MétodosEstudio ecológico a escala provincial que analiza la influencia de factores meteorológicos y geográficos en la incidencia acumulada de COVID-19 en las 52 provincias españolas (24 costeras y 28 del interior) durante las tres primeras olas. La incidencia acumulada se calculó con los datos del Instituto Nacional de Estadística (INE) y la Red Nacional de Vigilancia Epidemiológica (RENAVE), las variables meteorológicas se obtuvieron de la Agencia Estatal de Meteorología (AEMET).ResultadosLa incidencia acumulada total, en los tres periodos, fue menor en las provincias costeras que en las del interior (566±181 vs. 782±154; p=2,5×10-5). La incidencia acumulada correlacionó negativamente con la temperatura media (r=-0,49; p=2,2×10-4) y las precipitaciones (r=-0,33; p=0,01), y positivamente con la altitud (r=0,56; p=1,4×10-5). Las provincias españolas con una temperatura media <10°C tuvieron casi el doble de incidencia acumulada que las provincias con temperaturas >16°C. La temperatura media y las precipitaciones fueron las variables asociadas con la incidencia acumulada provincial de COVID-19, con independencia de otros factores (Coeficiente Beta de -0,62; p=3,7×10-7 y -0,47; p=4,2x10-5, respectivamente).ConclusionesLos factores meteorológicos y geográficos podrían influir en la evolución de la pandemia en España. El reconocimiento de la estacionalidad del COVID-19 ayudaría a predecir nuevas olas. (AU)

Introduction: Several studies have analyzed the influence of meteorological and geographical factors on the incidence of COVID-19. Seasonality could be important in the transmission of SARS-CoV-2. This study aims to evaluate the geographical pattern of COVID-19 in Spain and its relationship with different meteorological variables.MethodsA provincial ecological study analyzing the influence of meteorological and geographical factors on the cumulative incidence of COVID-19 in the 52 (24 coastal and 28 inland) Spanish provinces during the first three waves was carried out. The cumulative incidence was calculated with data from the National Statistical Institute (INE) and the National Epidemiological Surveillance Network (RENAVE), while the meteorological variables were obtained from the Spanish Meteorological Agency (AEMET).ResultsThe total cumulative incidence, in all three waves, was lower in the coastal provinces than in the inland ones (566±181 vs. 782±154; p=2.5×10−5). The cumulative incidence correlated negatively with mean air temperature (r=−0.49; p=2.2×10−4) and rainfall (r=−0.33; p=0.01), and positively with altitude (r=0.56; p=1. 4×10−5). The Spanish provinces with an average temperature <10°C had almost twice the cumulative incidence than the provinces with temperatures >16°C. The mean air temperature and rainfall were associated with the cumulative incidence of COVID-19, regardless of other factors (Beta Coefficient of −0.62; p=3.7×10−7 and −0.47; p=4.2×10–5 respectively).ConclusionsMeteorological and geographical factors could influence the evolution of the pandemic in Spain. Knowledge regarding the seasonality of the virus would help to predict new waves of COVID-19 infections. (AU)

Identification of seasonal variation in the diagnosis of acute myeloid leukaemia: a population-based study.

Until now, the role that seasonal factors play in the aetiology of acute myeloid leukaemia (AML) has been unclear. Demonstration of seasonality in AML diagnosis would provide supportive evidence of an underlying seasonal aetiology. To investigate the potential seasonal and long-term trends in AML diagnosis in an overall population and in subgroups according to sex and age, we used population-based data from a Spanish hospital discharge registry. We conducted a larger study than any to date of 26 472 cases of AML diagnosed in Spain between 2004 and 2015. Using multivariable Poisson generalized linear autoregressive moving average modelling, we found an upward long-term trend, with monthly incidence rates of AML annually increasing by 0.4% [95% confidence interval (CI), 0.2%-0.6%; p = 0.0011]. January displayed the highest incidence rate of AML, with a minimum average difference of 7% when compared to February (95% CI, 2%-12%; p = 0.0143) and a maximum average difference of 16% compared to November (95% CI, 11%-21%; p < 0.0001) and August (95% CI, 10%-21%; p < 0.0001). Such seasonal effect was consistent among subgroups according to sex and age. Our finding that AML diagnosis is seasonal strongly implies that seasonal factors, such as infectious agents or environmental triggers, influence the development and/or proliferation of disease, pointing to prevention opportunities.

Humoral and Cellular Response after mRNA Vaccination in Nursing Homes: Influence of Age and of History of COVID-19.

Background: Most residents and staff in nursing homes have received full vaccination. Factors related to the immune response to vaccination might be related to the risk of future severe COVID-19 and may guide the need for vaccine boosters. Design: Nursing homes that were tested in a point survey in July-October 2020 were again analyzed after a vaccination campaign in June-July 2021. Immune responses according to IgG against nucleocapsid and spike antigens, and CD4 and CD8 interferon-gamma release assay against spike antigens, were evaluated. Results: A total of 1973 subjects were tested (61.7% residents, 48.3% staff), with a mean (SD) follow-up of 46.4 (3.6) weeks between assessments. More than half of residents and more than a third of staff had evidence of COVID-19 before vaccination; 26.9% and 22.7% had seroreversion of IgG-N, and 8.9% and 4.6% had IgG-N seroconversion at second assessment, respectively. Up to 96.8% of residents and 98.1% of workers had positive IgG-S after a mean of 19.9 (2.1) weeks after vaccination. In residents with vs without a history of COVID-19, IgG-S titers were 4.11 (0.54) vs. 2.73 (0.74) logAU/mL (p < 0.001); in workers these titers were 3.89 (0.61) vs. 3.15 (0.64) logAU/mL (p < 0.001). Linear regression analysis showed that younger age (OR: −0.03 per 10 years-older [95% CI, −0.04 to −0.02], p < 0.001) and evidence of COVID-19 (OR: 1.14 [95% CI, 1.08 to 1.20], p < 0.001) are associated with greater IgG-S titers after vaccination. A direct association was found between IgG-S titers and the intensity of IFN-gamma response against spike antigens. Conclusions: Waning of humoral response and reinfection seems to be more frequent in older as compared to younger adults, although cellular responses shortly after vaccination are comparable between these groups. Younger age and prior COVID-19 are related to greater humoral response after vaccination against SARS-CoV-2.

Venous Thrombosis within 30 Days after Vaccination against SARS-CoV-2 in a Multinational Venous Thromboembolism Registry.

BACKGROUND: Venous thromboembolism (VTE)-including deep vein thrombosis, pulmonary embolism, and cerebral venous sinus thrombosis (CVST)-may occur early after vaccination against the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). We sought to describe the site, clinical characteristics, and outcomes of VTE after vaccination against SARS-CoV-2. METHODS: In a prospective study using the Registro Informatizado de Enfermedad TromboEmbólica (RIETE) platform, patients with VTE 4-30 days after vaccination against SARS-CoV-2 (1 February 2021 through 30 April 2021) were included. VTE patients recruited from the same centers into RIETE in the same months in 2018-2019 were selected as the reference group. All-cause mortality and major bleeding were the main study outcomes. RESULTS: As of 30 April 2020, 102 patients with post-vaccination VTEs had been identified (28 after adenovirus-based vaccination [ChAdOx1 nCov-19; AstraZeneca] and 74 after mRNA-based vaccination [mRNA-1273; Moderna, and BNT162b2; Pfizer]). Compared with 911 historical controls, patients with VTE after adenovirus-based vaccination more frequently had CVST (10.7% vs. 0.4%, p < 0.001) or thrombosis at multiple sites (17.9% vs. 1.3%, p < 0.001), more frequently had thrombocytopenia (40.7% vs. 14.7%, p < 0.001), and had higher 14-day mortality (14.3% vs. 0.7%; odds ratio [OR]: 25.1; 95% confidence interval [CI]: 6.7-94.9) and major bleeding rates (10.3% vs. 1.0%, OR: 12.03, 95% CI: 3.07-47.13). The site of thrombosis, accompanying thrombocytopenia, and 14-day mortality rates were not significantly different for patients with VTE after mRNA-based vaccination, compared with historical controls. CONCLUSIONS: Compared with historical controls, VTE after adenovirus-based vaccination against SARS-CoV-2 is accompanied by thrombocytopenia, occurs in unusual sites, and is associated with worse clinical outcomes.

A Pilot Study for the Evaluation of an Interferon Gamma Release Assay (IGRA) To Measure T-Cell Immune Responses after SARS-CoV-2 Infection or Vaccination in a Unique Cloistered Cohort.

Assessment of T-cell responses to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antigens may be of value to determine long-lasting protection to breakthrough infections or reinfections. Interferon gamma release assay is a validated method to test cellular immunity in mycobacterial infections and has been proposed for patients with SARS-CoV-2 infection or vaccination. Quantitative IgG to spike and qualitative IgG to nucleocapsid antigens were determined by chemiluminescence microparticle immunoassay using the Architect platform (Abbott), and interferon gamma release assays against two Qiagen proprietary mixes of SARS-CoV-2 spike protein (antigen 1 and antigen 2) were performed for a selected group of subjects. A total of 121 subjects in a cloistered institution after a COVID-19 outbreak was studied. IgG spike levels and interferon gamma concentrations were highest among subjects after two doses of vaccine, followed by patients with a longer history of past COVID-19 and no vaccination. The best cutoff for the interferon gamma assay was 25 IU/L for all subgroups of individuals and the two sets of SARS-CoV-2 antigens studied. Testing T-cell response may be of clinical utility to determine immunity after exposure to SARS-CoV-2 antigens, with the interferon gamma concentration of 25 IU/L as the best cutoff either after infection or vaccination.

Influence of weather factors on the incidence of COVID-19 in Spain. / Influencia de los factores meteorológicos en la incidencia de COVID-19 en España.

INTRODUCTION: Several studies have analyzed the influence of meteorological and geographical factors on the incidence of COVID-19. Seasonality could be important in the transmission of SARS-CoV-2. This study aims to evaluate the geographical pattern of COVID-19 in Spain and its relationship with different meteorological variables. METHODS: A provincial ecological study analyzing the influence of meteorological and geographical factors on the cumulative incidence of COVID-19 in the 52 (24 coastal and 28 inland) Spanish provinces during the first three waves was carried out. The cumulative incidence was calculated with data from the National Statistical Institute (INE) and the National Epidemiological Surveillance Network (RENAVE), while the meteorological variables were obtained from the Spanish Meteorological Agency (AEMET). RESULTS: The total cumulative incidence, in all three waves, was lower in the coastal provinces than in the inland ones (566±181 vs. 782±154; p=2.5×10-5). The cumulative incidence correlated negatively with mean air temperature (r=-0.49; p=2.2×10-4) and rainfall (r=-0.33; p=0.01), and positively with altitude (r=0.56; p=1. 4×10-5). The Spanish provinces with an average temperature <10°C had almost twice the cumulative incidence than the provinces with temperatures >16°C. The mean air temperature and rainfall were associated with the cumulative incidence of COVID-19, regardless of other factors (Beta Coefficient of -0.62; p=3.7×10-7 and -0.47; p=4.2×10-5 respectively). CONCLUSIONS: Meteorological and geographical factors could influence the evolution of the pandemic in Spain. Knowledge regarding the seasonality of the virus would help to predict new waves of COVID-19 infections.

Volumen renal total y función renal en pacientes nefrectomizados por neoplasias renales / Total renal volume and renal function after radical nephrectomy in renal neoplasm

Introducción: La reducción de la masa renal tras la nefrectomía radical en pacientes con neoplasias renales puede producir la hipertrofia compensadora del riñón contralateral. La capacidad de compensación determinará la evolución de la función renal. La medición del volumen renal total (VRT) del riñón remanente antes y después de la nefrectomía puede ayudar a evaluar la evolución de la función renal. Objetivos: Determinar la correlación entre el VRT pre y posnefrectomía con la función renal al año de seguimiento. Materiales y métodos: Estudio retrospectivo de observación en 47 pacientes adultos con neoplasias renales que fueron sometidos a nefrectomía radical. El VRT pre y posnefrectomía (al año de seguimiento) fue calculado mediante la ecuación de la elipsoide (TAC y/o RNM), que fueron comparados con datos clínicos y analíticos. Los resultados fueron analizados mediante regresión lineal uni y multivariante. Resultados:La mediana de edad al momento de la nefrectomía fue de 70 años (44-88). La mayoría fueron hombres (66%). El filtrado glomerular estimado (FGe) pre y posnefrectomía fue de 78 (40-100) y 53,3ml/min/m2 (20-90) respectivamente (p=0,01). El VRT pre y posnefrectomía fue de 168,2ml (100,4-257,2) y 187,8ml (115,5-273,1) respectivamente (p=0,001). El FGe prenefrectomía (β=0,62; p=0,034) y el VRT pre (β=1,08; p<0,0001) se correlacionaron positivamente con el VRT posnefrectomía. Sin embargo, el FGe al año se correlacionó negativamente (β=–1,18; p=0,047). Conclusiones: En pacientes con neoplasias renales tratados con nefrectomía radical la medición del VRT pre y posnefrectomía pueden ayudar a predecir la evolución de la función renal al año de seguimiento. (AU)

Introduction: The reduction of renal mass after radical nephrectomy (RN) for renal neoplasm, could be associated with compensatory hypertrophy of the contralateral kidney. The capacity of compensation will determine the renal function (RF) evolution. Measuring of total renal volume (TRV) of the remaining kidney pre and post RN can help assess the RF evolution. Objectives: To determine the correlation between TRV pre and post nephrectomy (a year of follow-up) with RF. Materials and methods: A retrospective cohort study was carried out in 47 patients who had undergone RN from 2014 to 2018, due to renal cell carcinoma (confirmed by histopathology). The TRV was calculated, pre and post (a year of follow-up) RN, using ellipsoid formula equation, which were compared with clinical and analytical data. The results were analyzed by multivariate linear logistic models. Results: The median age at the time of RN was 70 years old (range, 40-88 years). Most of them were men, 66%. The estimated glomerular filtration rate (eGFR) pre and post nephrectomy was 78 (40-100) and 53.3ml/min/ m2 (30-90) respectively (P=.01). The TRV pre and post-nephrectomy was 168.2ml (100.4-257.2) and 187.8ml (115.5-273.1) respectively (P=.001). The pre-nephrectomy eGFR (β=0.62; P=.034) and the TRV (β=1.08; P<.0001) were positively correlated with the post-nephrectomy TRV, while the eGFR at year of follow-up was correlated negatively (β=–1.18; P=.047) Conclusions: The measurement of pre and post nephrectomy TRV can help to predict renal function evolution at a year of follow-up. (AU)

The demography and characteristics of SARS-CoV-2 seropositive residents and staff of nursing homes for older adults in the Community of Madrid: the SeroSOS study.

BACKGROUND: Nursing homes for older adults have concentrated large numbers of severe cases and deaths for coronavirus disease 2019 (COVID-19). METHODS: Point seroprevalence study of nursing homes to describe the demography and characteristic of severe acute respiratory syndrome by coronavirus 2 (SARS-CoV-2) immunoglobulin G (IgG)-positive residents and staff. RESULTS: Clinical information and blood samples were available for 9,332 residents (mean age 86.7 ± 8.1 years, 76.4% women) and 10,614 staff (mean age 45.6 ± 11.5, 86.2% women). Up to 84.4% of residents had frailty, 84.9% co-morbidity and 69.3% cognitive impairment; 65.2% of workers were health-aides.COVID-19 seroprevalence was 55.4% (95% confidence interval (CI), 54.4-56.4) for older adults and 31.5% (30.6-32.4) for staff. In multivariable analysis, frailty of residents was related with seropositivity (odds ratio (OR): 1.19, P = 0.02). In the case of staff, age > 50 years (2.10, P < 0.001), obesity (1.19, P = 0.01), being a health-aide (1.94, P < 0.001), working in a center with high seroprevalence in residents (3.49, P < 0.001) and contact with external cases of COVID-19 (1.52, P < 0.001) were factors associated with seropositivity. Past symptoms of COVID-19 were good predictors of seropositivity for residents (5.41, P < 0.001) and staff (2.52, P < 0.001). CONCLUSIONS: Level of dependency influences risk of COVID-19 among residents. Individual and work factors, contacts outside the nursing home are associated with COVID-19 exposure in staff members. It is key to strengthen control measures to prevent the introduction of COVID-19 into care facilities from the community.