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This Wednesday at 9pm CET, FC Barcelona take on Club de Fútbol Intercity in the Round of 32 of the Copa del Rey
It’s a club they have never played before and that very few fans will be familiar with
so here are the essentials on the team from Alicante
San Juan de Alicante is a primarily residential municipality on the northern outskirts of the Alicante/Elche metropolitan area
The main football club in the community was GCD Sant Joan
but in 2017 an investment group took it over and changed its name
the club has made quick progress from the local leagues to now play at a higher level than Hércules
which has traditionally been the biggest team in Alicante
It has also twice attempted to fast track this progress
It did this first by proposing a merger with Novelda (and thus taking their place)
but the move was impeded by the federation as the two clubs were not geographically close enough
And it was then beaten by FC Andorra when bidding to take the place of the defunct Reus Deportivo
It’s not the first time Intercity have met a Liga club in the Copa del Rey
Intercity are now playing in the third tier of Spanish football, Primera Division RFEF, which is divided into two regionalised leagues. Theirs is the same one as Barça Atlétic. They have been struggling at the higher level and are currently in the relegation zone, seven points below the FC Barcelona reserves, with whom they drew 0-0 earlier this season
They reached the last 32 of the Copa del Rey thanks to a 2-0 defeat of second division Mirandés
Although they usually play at the 2,500 capacity Estadio Antonio Solana
due to the huge crowd expected for this game
it has been moved to the 29,500 capacity Estadio José Rico Pérez
This ground hosted two of Argentina’s games in the 1982 World Cup
Intercity has two players that have won full international caps
who played 142 games for Mallorca and also had a spell in England with Middlesbrough and then Birmingham City
has represented his father’s home nation of Equatorial Guinea 32 times
There are also a surprising number of players in the team that have spent time at FC Barcelona in the past
Striker Benja played 64 times for Barça B between 2008 and 2011
around the same time that winger Pol Roigé was playing youth football at La Masia
winger Carlos Carmona played for two years in the blaugrana reserves before departing for Sporting Gijón
And midfielder Xemi Fernández (below) joined Barça B in 2016 before going to Oxford United
right back Guillem Jaime (below) grew up at La Masia and played 22 games for the Barça reserves last season
and Cameroon-born midfielder Frank Angong was on the Barça B books for the last two seasons
With Oriol Soldevila and Cristian Herrera also having a Barça past
that's no fewer than eight such players in the current squad
Gustavo Siviero played his football at the highest level in Argentina
and then came to Spain where he was in the Mallorca side that beat Barça in the 1998 Spanish Super Cup
hitting Alicante for the first time in 2017 at Hércules’ manager
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Jose Garcia of CF Intercity competes for the ball with Raul Garcia of Athletic Club de Bilbao in Elche
2021 at 4:52 AM EDTBookmarkSaveLock This article is for subscribers only.A sporting minnow poised to become Spain’s first listed soccer club may blaze a trail for bigger teams to follow suit
according to a fund manager investing in much bigger European clubs
Last month, shareholders of CF Intercity backed plans to list the Spanish fourth-division team based in Sant Joan d’Alacant
was killed in a training accident on Thursday
The incident happened while the military man was cleaning a submachine gun after completing an exercise at the Rabasa barracks in Alicante
As news outlet TodoAlicante reported the Guardia Civil received an alert at 1.21pm
Medical services sent to the Alférez Rojas Navarrete complex were unable to save the young man
Roldán joined the army in May 2018 at the Nº1 Training Centre in Cáceres
Since April 2021 he had been assigned to the Special Operations Group Valencia III of the Special Operations Command
A statement said the army's priority is focused on caring for the family and colleagues of the deceased at this time
This is the fifth fatal accident in the last five years suffered by this elite unit of the army
Eduardo García Molinero lost his life after being hit by an armoured vehicle
a 33-year-old female soldier from Extremadura
died during a training exercise in Santa Pola
In October 2022 Gavalda Macías died when a vehicle overturned
died from a gunshot wound during shooting practice in Agost
Comentar es una ventaja exclusiva para registrados
Metrics details
the COVID-19 pandemic followed a two-wave pattern in most countries
Hospital admission for COVID-19 in one wave or another could have affected mortality
The objective of this study was to evaluate whether the admission of older patients during the different waves
before SARS-CoV-2 vaccination was available
We compared the mortality rates of patients hospitalized during 2020 before (first wave) and after (second wave) July 7
retrospective cohort of patients admitted to 126 Spanish hospitals for COVID-19
A multivariate logistic regression analysis was performed to control for changes in either the patient or disease profile
22,494 patients had been included (17,784 from the first wave and 4710 from the second one)
Overall mortality was 20.4% in the first wave and 17.2% in the second wave (risk difference (RD) − 3.2%; 95% confidence interval (95% CI) − 4.4 to − 2.0)
Only patients aged 70 and older (10,973 patients: 8571 in the first wave and 2386 in the second wave) had a significant reduction in mortality (RD − 7.6%; 95% CI − 9.7 to − 5.5) (unadjusted relative risk reduction: 21.6%)
variables related to the severity of the disease
admission during the second wave remained a protective factor
patients aged 70 years and older admitted during the second wave of the COVID-19 pandemic had a significantly lower risk of mortality
except in severely dependent persons in need of corticosteroid treatment
This effect is independent of patient characteristics
This suggests a protective effect of a better standard of care
or a lesser degree of healthcare system overload
most countries experienced at least two waves of the pandemic
after controlling for known mortality factors
there was still a lower mortality rate in the second wave
we hypothesized that hospital admission in the different waves could affect the mortality of patients with COVID-19
The primary aim of the study was to evaluate whether the admission of older patients during the different waves of 2020 was associated with a different mortality rate and whether this could be explained by differences in the characteristics of either the patients or the severity of the disease
Case Fatality Rate (CFR) according to age in patients hospitalized during the first and second waves of COVID-19
expressed as percentage (deceased patients/total patients)
The diamonds indicate the point estimate of the risk difference
and the horizontal bars represent its 95% confidence interval
The differences in baseline characteristics (demographics and comorbidities), clinical presentation upon admission, and treatments received between waves were analyzed (Table 1)
There were some differences in demographics in second-wave patients
including older age (second wave: 82.0 vs first wave: 80.8 years)
a greater proportion of women (second wave: 48.2% vs first wave: 45.2%)
a higher proportion of patients with hypertension (second wave: 73.7% vs first wave: 71.3%) and diabetes (second wave: 30.9% vs first wave: 26.3%)
and a slightly higher degree of comorbidity (Charlson Comorbidity Index in the second wave: 5.7 vs first wave: 5.4)
The clinical manifestations were also slightly different
Laboratory results showed some differences: blood glucose and creatinine values were higher in patients admitted in the second wave whereas hemoglobin was lower
A high-risk inflammatory pattern was more frequent in the first wave
there was greater use of corticosteroids (79.3% vs 39.5%) and remdesivir (12.6% vs 0.4%)
Some of these aforementioned variations could be considered protective (e.g.
a lower-risk inflammatory pattern) whereas others (higher age
higher creatinine levels) would suggest higher risk of mortality
A univariate analysis of mortality was performed. Almost all variables were statistically associated with mortality, denoting the large sample size. Table 2 shows data on demographics
Although some of the associations were strong
The variables and interactions included in the maximal logistic regression model estimated are shown in Table 3
The odds ratios and risk ratios of mortality of being admitted in the second wave versus the first one for the four different combinations of interaction covariates values are shown in Table 4
The protective effect of being admitted during the second wave of COVID-19 is highest for patients without severe dependence who are not treated with corticosteroids
and it diminishes when either of these circumstances is present
This study confirms a difference in mortality in patients hospitalized for COVID-19 in Spain between the first and the second wave of the pandemic
The lower mortality rate observed in the second wave is due to the lower mortality in patients ≥ 70 years; no differences in mortality were observed among younger subjects
this is a novel finding that has not been previously described
This reduced mortality rate found in older patients hospitalized during the second wave of the COVID-19 pandemic compared to the first wave could be due to some unmeasured or unknown confounders which may be broadly grouped into three categories: differences in the patients
or differences in treatment and overall management
the lower mortality in the second wave was unchanged after adjusting for the use of these therapies
Our results suggest that there may be some factor (or, more probably, combination of factors), associated with hospitalization that influences mortality and changed between the waves. Some potential candidates are changes in the overall management of patients, improvements in clinical expertise, and a lesser degree of hospital overload (Fig. 2).
differences in COVID-19 severity and management could confound the estimation of mortality between waves
differences in the outcome could be explained by unmeasured patient characteristics and COVID-19 severity factors
the analysis of the interactions between severe dependency and systemic corticosteroid treatment with the hospital admission wave has allowed us to discover that the protective effect of the second wave on mortality is highest when both factors are absent
somewhat reduced when either of them is present
that explain an average protective effect of the second wave
may not succeed in improving the prognosis of the most fragile and severe patients
such as those requiring corticosteroid treatment
We have learned that there are a lot of “intangibles” that influence the prognosis of COVID-19 hospitalization
Quick identification of respiratory failure
and more have become the new standard of care and are potential uncontrolled factors that could explain the better prognosis in the second wave
Most of these factors will have a greater impact on the older people
as they are frailer and thus prone to physical deconditioning
paralyzing non-emergency surgical procedures
leading to a smaller impact on hospital occupancy and healthcare activity
It may well be that the lower mortality in the second wave is mainly a reflection of less healthcare system overload
As our study does not include data on the true workload borne by the hospitals
healthcare system overload leads to shortages
which can also have a greater effect on the older persons due to implementation of triage criteria
If it were confirmed that healthcare system overload causes greater mortality in the older persons
it would be a moral imperative for us as a society to quickly adopt robust preventative measures as soon as another wave is upon us and there is risk of healthcare system overload
Our registry cannot answer this crucial question
as we lack data on hospital or ICU patient loads at the time of the patients’ admissions
In terms of limitations regarding treatment-related variables
the effect of remdesivir and tocilizumab on mortality are strongly time-dependent with a narrow window of opportunity and both tocilizumab and corticosteroids are indicated for a worsening respiratory or inflammatory condition
Our registry includes data on the timing of the drug initiation but does not include clinical and laboratory findings at that moment
so it is not possible to evaluate the exact effect of the drugs
The deleterious effect of corticosteroids or tocilizumab in our multivariate analysis should be interpreted as a marker of the patient’s worsening condition
The strengths of this study include its multicenter
nationwide design as well as the large number of patients included
The consecutive inclusion of patients in each center limits selection bias
mortality in the older patients hospitalized in Spain with COVID-19 has been significantly lower in the second wave even after adjusting for baseline clinical condition
and pharmacological treatment with proven benefits in treating COVID-19
Our results suggest that this reduction of mortality could be related to a better standard of care
though other unknown confounding factors cannot be ruled out
This is a retrospective cohort study comparing the first and second waves of the COVID-19 epidemic in Spain
The first wave was defined as the period between January 1 and July 7
The second wave was defined as the period between July 8
The final weeks of the first wave and the initial weeks of the second one thus defined periods with a low incidence of COVID-19 and few hospital admissions
this cut-off point reflects the transition from the greater healthcare system overload which occurred in the initial months to the lesser healthcare system overload of the later months
Inclusion criteria for the registry were age ≥ 18 years and first hospital discharge with a confirmed diagnosis of COVID-19
Exclusion criteria were subsequent admissions of the same patient and denial or withdrawal of informed consent
Consecutive patients who required hospital admission and who had SARS-CoV-2 infection confirmed by a positive result on real-time polymerase chain reaction (RT-PCR) testing of a nasopharyngeal
or sputum sample and who provided verbal consent were included in the registry
the inclusion criteria were expanded with two modifications: antigen testing was accepted as a method for confirming diagnosis and reinfections (> 3 months from the initial infection) of the same patient were accepted for inclusion
a total of 22,494 patients from 126 hospitals throughout the country were included in the registry
Patients were treated at their attending physician’s discretion according to local protocols and clinical judgment
Patients included in open-label clinical trials could be included in the registry provided that all information about treatment was available
the registry caused no inconvenience to the patients included
Clinical investigators all over the country collected data from medical records using a standardized online data capture system (DCS)
The DCS includes both a database manager and the set of procedures for the verification of data
Patient identifiable data are dissociated and pseudonymized using an alphanumeric sequence and each researcher keeps a protected registry (patient log) for the purpose of data verification and quality control
The database platform is hosted in a secure server and both the database and each client–server transfer are encrypted
The pseudonymization system allows for safeguarding patient privacy while also complying with ethical considerations and data protection regulations
The low-risk category was defined as lactate dehydrogenase (LDH)
and D-dimer (DD) values in the first tercile and lymphocyte count in the third tercile
The high-risk category was defined as any LDH
or DD values in the third tercile or lymphocyte count in the first tercile
The moderate-risk category was defined as patients who did not meet the criteria of the low- or high-risk categories
Continuous variables were expressed as mean and standard deviation or median and interquartile range (IQR)
according to distribution assessed by the Shapiro–Wilk test and standardized normal probability plots
Categorical variables were expressed as frequencies and percentages
Differences between groups were compared using Student’s t-test or the Mann–Whitney U test for continuous variables and the likelihood-ratio chi-square test for categorical variables
A univariate analysis was performed to explore possible risk factors for all-cause death during admission or the next 30 days from discharge and variables associated with the exposure (pandemic wave) using binomial logistic regressions
The variables were chosen from an array of clinical and laboratory findings
and treatments received according to local protocols
almost all variables showed significant differences in the comparisons between exposure and outcome groups in the univariate analysis
We created a logistic regression model to assess the effect of being admitted during the first or second wave on all-cause mortality risk
We selected a series of predictors associated with the exposure (pandemic wave) and the outcome (mortality) as potential confounding factors
The selection criteria also took theoretical arguments or findings from other studies into consideration in order to adjust for factors that could explain a potential difference in the risk of death between the two waves
The admitting variables that were ultimately included as possible confounders of the wave effect were age (categorized into decades from 70 years)
age-adjusted Charlson Comorbidity Index (reference: moderate comorbidity)
degree of dependence (reference: none or mild dependence)
arterial stiffness (pulse pressure ≥ 60 mmHg)
risk category based on the pattern of inflammation
and bilateral pneumonia as well as tocilizumab
or corticosteroid therapy during hospitalization
first-order interactions between the waves and all potential confounding factors were included in the initial model
Multicollinearity was detected for several terms of interaction
A chunk test for the rest of interaction terms did show statistical significance (p < 0.001)
so individual likelihood ratio tests were performed for every one of them
Three interactions with the variable "Wave" remained statistically significant: severe dependency
In order to achieve an interpretable estimation and reduce the number of combinations for which to calculate the wave effect on mortality
we decided to omit the interaction of the wave with ventilatory support
the final logistic regression model included all the confusion terms and the interactions of Wave with Severe dependence and Systemic corticosteroid therapy
We did not conduct variable selection once the model was estimated
as this maximal model is the best fit for calculating the wave's effect on mortality
Adjusted odds ratios and risk ratios were estimated for each combination of the values of interaction terms
Adjusted risk ratios were calculated with delta-method standard errors for the wave covariate
All analyses were conducted using Stata version 18.0 (StataCorp
The SEMI-COVID-19 Registry was approved by the Provincial Research Ethics Committee of Málaga (Spain) on March 27
2020 (Ethics Committee code: SEMI-COVID-19 27/03/20)
All experimental protocols were approved by Ethic Committee of Infanta Cristina University Hospital
Ethic Committee of Gregorio Marañón University Hospital
Ethic Committee of Complejo Hospitalario Universitario de Albacete
Ethic Committee of Hospital Universitario La Paz
Ethic Committee of Hospital Royo Villanova
Ethic Committee of Complejo Hospitalario Universitario de Santiago
Ethic Committee of Hospital Universitario Puerta de Hierro
Ethic Committee of Hospital Universitario Doctor Peset
Ethic Committee of Hospital Clínico San Carlos
Ethic Committee of Complejo Asistencial de Segovia
Ethic Committee of Complejo Hospital Universitario de Badajoz
Ethic Committee of Hospital Universitario Miguel Servet
Ethic Committee of Hospital Universitario de la Princesa
Ethic Committee of Hospital Universitario Infanta Sofía
Ethic Committee of Complexo Hospitalario Universitario A Coruña
Ethic Committee of Hospital de Sant Joan Despí Moisès Broggi
and Ethic Committee of 12 de Octubre University Hospital
The processing of personal data strictly complied with Spanish Law 14/2007
on Biomedical Research; Regulation (EU) 2016/679 of the European Parliament
on the protection of natural persons with regard to the processing of personal data and on the free movement of such data
and repealing Directive 95/46/EC (General Data Protection Regulation); and Spanish Organic Law 3/2018
on the Protection of Personal Data and the Guarantee of Digital Rights
In the periods of maximum hospital care pressure with high number of cases admitted
a written informed consent was not possible to obtain if overwork left no time to explain informed consent
prepared the written documentation and keep safe it for overwork (March to April 2020
it was noted noted on the medical record that a written informed consent was not possible to obtain
as such procedure was approved by the ethics committees
The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request
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We gratefully acknowledge all the investigators who participate in the SEMI-COVID-19 Registry (A complete list of the SEMI-COVID-19 Network members is provided at the end of the paper)
These authors contributed equally: José-Manuel Casas-Rojo and Juan-Miguel Antón-Santos
A list of authors and their affiliations appears at the end of the paper
Juan Vicente de la Sota & Javier Villanueva-Martínez
Instituto de Investigación Sanitaria Puerta de Hierro-Segovia de Arana (IDIPHISA)
Gracia Villarreal & María Zurita Etayo
Biomedical Research Institute of Málaga (IBIMA)
José-Manuel Ramos-Rincón & José-Manuel Ramos-Rincón
Jose María Mora-Luján & Manuel Rubio-Rivas
Victoria Nuñez Rodriguez & Julián Olalla Sierra
María Luisa Taboada Martínez & Lara María Tamargo Chamorro
Complejo Hospitalario Universitario de Albacete
Jose Luis Beato Pérez & Maria Lourdes Sáez Méndez
Marta Varas Mayoral & Julia Vásquez Manau
Raul Martínez Murgui & Marta Teresa Matía Sanz
Maimonides Biomedical Research Institute of Córdoba (IMIBIC)
CIBER Fisiopatología de la Obesidad y Nutrición (CIBEROBN)
Juan Luis Romero Cabrera & José David Torres-Peña
Complejo Hospitalario Universitario de Santiago
María Pazo Nuñez & Paula Maria Pesqueira Fontan
Hospital Universitario Puerta de Hierro Majadahonda
Jose Manuel Vázquez Comendador & Juan Antonio Vargas Núñez
Adela Maria Pina Belmonte & Alba Viana García
Andrea María Vellisca González & Miguel Villar Martínez
Eva María Ferreira Pasos & Alba Varela García
Complejo Hospital Universitario de Badajoz
Francisco Javier Monreal Periáñez & Maria Josefa Pascual Perez
Jesús Javier González Igual & Rosa García Fenoll
Macarena Vargas Tirado & Almudena Villa Marti
Inés Suárez García & Llanos Soler Rangel
Complexo Hospitalario Universitario A Coruña
Francisco Javier Sanmartín Pensado & David Vieito Porto
Nicolas Rhyman & Nuria Vázquez Piqueras
Azucena Sempere Mira & Philip Wikman-Jorgensen
Marcos Sánchez Fernández & Javier Tejada Montes
Nuria Ramírez Perea & Andrea Torregrosa García
Marina Prieto Dehesa & Pablo Sanz Espinosa
Cristina Salazar Mosteiro & Andrea Silva Asiain
Mª Soledad Azcona Losada & Beatriz Ruiz Estévez
Jesús Vázquez Clemente & Carmen Yera Bergua
Andrés de la Peña Fernández & Almudena Hernández Milián
Ainara Coduras Erdozain & Ane Labirua-Iturburu Ruiz
Alvaro Sánchez dedel AlcazarRío & Leire Toscano Ruiz
Jose Luís Peña Somovilla & Elisa Rabadán Pejenaute
Nahum Jacobo Torres Yebes & Vanessa Vento
Adrian Viteri-Noël & Svetlana Zhilina Zhilina
Maria Sanchez Ledesma & Rosa Juana Tejera Pérez
Isabel Jiménez Martínez & Teresa García Delange
Lara Rey González & Laura Rodrigo Lara
Carlos Puig Navarro & José Antonio Todolí Parra
Luis Arribas Pérez & Emilia Martínez Velado
Ainhoa Rex Guzmán & Aleix Serrallonga Fustier
Manuel Lorenzo López Reboiro & Cristina Sardiña González
Jose María Pascual Izuel & Zineb Karroud Zamrani
Maria del Carmen Vázquez Friol & Laura Vilariño Maneiro
Maria de la Sierra Navas Alcántara & Raimundo Tirado-Miranda
Alba Barragán Mateos & Andrés Astur Treceño García
Julia Marfil Daza & Marcelino Hayek Peraza
Verónica Alfaro Lara & Aurora González Estrada
Javier Ena & José Enrique Gómez Segado
Virginia Gracia Lorenzo & Raquel Monsalvo Arroyo
Marcos Guzmán García & Francisco Javier Vicente Hernández
Manuel Martín Regidor & Raquel Rodríguez Díez
Iris El Attar Acedo & Carmen Mar Sánchez Cano
Virginia Herrero García & Berta Román Bernal
Cristina Gabara Xancó & Olga Rodríguez Núñez
Anyuli Gracia Gutiérrez & Leticia Esther Royo Trallero
Jessica Ramírez Taboada & Mar Rivero Rodríguez
Carmen Yllera Gutiérrez & Maria Martinez Sela
Julia Lobo García & Antía Pérez Piñeiro
Nuria Tornador Gaya & Jorge Usó Blasco
Angeles Martinez Pascual & Leyre Jorquer Vidal
José Marchena Romero & Anabel Martin-Urda Diez-Canseco
Bernardino Soldan Belda & David Vicente Navarro
Bethania Pérez Alves & Natalia Vicente López
Ana Roda Santacruz & Ana Valverde Muñoz
Selene Núñez Gaspar & Antonio González Nieto
Raquel Gómez Méndez & Ana Rodríguez Álvarez
Paula Ortega Toledo & Esther Martin Ponce
Cristina Novoa Fernández & Pablo Tellería Gómez
Agnés Rivera Austrui & Alberto Zamora Cervantes
Diana Sande Llovo & Maria Begoña Valle Feijoo
Manuel Jesus Soriano Pérez & Encarna Sánchez Martín
Victoria Marquez Fernandez & Ada Viviana Romero Echevarry
Lucia Paz Fajardo & Tomás de Vega Santos
and the members of the SEMI-COVID-19 Network
Analysis and interpretation of data: J.M.C.R.
Critical revision of the manuscript for important intellectual content: J.M.N.C.
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DOI: https://doi.org/10.1038/s41598-023-42735-5
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