Your browser doesn't support javascript.
Show: 20 | 50 | 100
Results 1 - 7 de 7
Filter
1.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-314865

ABSTRACT

Background: More detailed temporal analyses of complete (Full) blood count (CBC) parameters, their evolution and relationship to patient age, gender, co-morbidities and management outcomes in survivors and non-survivors with COVID-19 disease could help identify prognostic clinical biomarkers. Methods: From 29 January 2020 until 28 March 2020, we performed a longitudinal cohort study of COVID-19 inpatients at the Italian National Institute for Infectious Diseases, Rome, Italy. Nine CBC parameters as a continuous variable were studied [neutrophils, lymphocytes, monocytes, platelets, mean platelet volume, red blood cell count, haemoglobin concentration, mean red blood cell volume and red blood cell distribution width (RDW %)]. Model-based punctual estimates and difference between survivors and non-survivors, overall, and by co-morbidities, at specific times after symptoms, with relative 95% CI and P-values were obtained by marginal prediction and ANOVA-style joint tests. All analyses were carried out by STATA 15 statistical package. Main Findings: 379 COVID-19 patients [273 (72% were male;mean age was 61.67 (SD 15.60)] were enrolled and 1,805 measures per parameter were analysed. Neutrophil counts were on average significantly higher in non-survivors than in survivors (P<0.001) and lymphocytes were on average higher in survivors (P<0.001). These differences were time dependent. Reverse temporal trends were observed for lymphocyte and neutrophil counts in survivors and non-survivors. Average platelets counts (P<0.001) and median platelets volume (P<0.001) were significantly different in survivors and in non-survivors. The differences were time dependent and consistent with acute inflammation followed either by recovery or by death. Anaemia with anisocytosis were observed in the later phase of COVID-19 disease in non-survivors only. Mortality was significantly higher in patients with diabetes (p=0.005), obesity (p=0.010), chronic renal failure (p=0.001), COPD (p=0.033) cardiovascular diseases (p=0.001) and those >60 years(p=0.001). Age (p=0.042), obesity (p=0.002), chronic renal failure (p=0.002) and cardiovascular diseases (p=0.009) were independently associated with poor patient clinical outcome at 30 day after symptom onset. Interpretation: Increased neutrophil counts, reduced lymphocyte counts, higher median platelet volume, anemia with anisocytosis, in association with obesity, chronic renal failure, COPD, cardiovascular diseases and age >60 years predict poor prognosis in COVID19 patients.Funding Statement: Ricerca Corrente e Finalizzata Italy Ministry of Health, AIRC (IG2018-21880);Regione Lazio (Gruppi di ricerca, E56C18000460002).Declaration of Interests: The authors declare no competing interest.Ethics Approval Statement: This study was approved by the IRB of Italian National Institute for Infectious Diseases “Lazzaro Spallanzani” (INMI), in Rome (Italy).

2.
Viruses ; 13(6)2021 06 17.
Article in English | MEDLINE | ID: covidwho-1286941

ABSTRACT

In European countries, autochthonous acute hepatitis E cases are caused by Hepatitis E Virus (HEV) genotype 3 and are usually observed as sporadic cases. In mid/late September 2019, a hepatitis E outbreak caused by HEV genotype 3 was recognized by detection of identical/highly similar HEV sequences in some hepatitis E cases from two Italian regions, Abruzzo and Lazio, with most cases from this latter region showing a link with Abruzzo. Overall, 47 cases of HEV infection were finally observed with onsets from 8 June 2019 to 6 December 2019; they represent a marked increase as compared with just a few cases in the same period of time in the past years and in the same areas. HEV sequencing was successful in 35 cases. The phylogenetic analysis of the viral sequences showed 30 of them grouped in three distinct molecular clusters, termed A, B, and C: strains in cluster A and B were of subtype 3e and strains in cluster C were of subtype 3f. No strains detected in Abruzzo in the past years clustered with the strains involved in the present outbreak. The outbreak curve showed partially overlapped temporal distribution of the three clusters. Analysis of collected epidemiological data identified pork products as the most likely source of the outbreak. Overall, the findings suggest that the outbreak might have been caused by newly and almost simultaneously introduced strains not previously circulating in this area, which are possibly harbored by pork products or live animals imported from outside Abruzzo. This possibility deserves further studies in this area in order to monitor the circulation of HEV in human cases as well as in pigs and wild boars.


Subject(s)
Disease Outbreaks , Genotype , Hepatitis E virus/classification , Hepatitis E virus/genetics , Hepatitis E/epidemiology , Hepatitis E/transmission , Adult , Aged , Aged, 80 and over , Animals , Female , Hepatitis E/virology , Hepatitis E virus/pathogenicity , Humans , Italy/epidemiology , Male , Middle Aged , Phylogeny , Pork Meat/virology , RNA, Viral , Risk Factors , Sus scrofa/virology , Swine , Swine Diseases/transmission , Swine Diseases/virology
3.
Epidemiol Prev ; 44(5-6 Suppl 2): 144-151, 2020.
Article in Italian | MEDLINE | ID: covidwho-1068134

ABSTRACT

BACKGROUND: one of the most affected European countries by the COVID-19 epidemic is Italy; data show the strong geographical heterogeneity of the epidemic. OBJECTIVES: to propose an analysis strategy to ascertain the non-random nature of the spatial spread of COVID-19 cases infection and identify any territorial aggregations, in order to enhance contact tracing activities in specific areas of the Lazio Region (Central Italy) and a large urban area as Rome. METHODS: all cases of COVID-19 of the Lazio Region notified to the Regional Service for Epidemiology, Surveillance, and Control of Infectious Diseases (Seresmi) with daily updates from the beginning of the epidemic to April 27, 2020 were considered. The analyses were carried out considering two periods (the first from the beginning of the epidemic to April 6 and the second from the beginning of the epidemic to April 27) and two different levels of spatial aggregation: the entire Lazio region excluding the Municipality of Rome, where the 377 municipalities represent the area units, and the Municipality of Rome, where the area units under study are the 155 urban areas (ZUR). The Scan statistic of Kulldorff was used to ascertain the non-random nature of the spatial spread of infected cases and to identify any territorial aggregations of cases of COVID-19 infection, using a retrospective spatial analysis in two overlapping periods. RESULTS: analysis was conducted at regional level in the two survey periods and revealed the presence of 7 localized clusters. In the Municipality of Rome, a single cluster (Historic Centre) was identified in the first period which includes 7 urban areas, while in the second period two distinct clusters (Omo and Farnesina) were observed. CONCLUSIONS: Scan statistics are an important surveillance tool for monitoring disease outbreaks during the active phase of the epidemic and a useful contribution to epidemiological surveillance during the COVID-19 epidemic in a specific territory.


Subject(s)
COVID-19/epidemiology , Pandemics , SARS-CoV-2 , Spatial Analysis , COVID-19/transmission , Cluster Analysis , Geography, Medical , Humans , Italy/epidemiology , Population Surveillance , Retrospective Studies , Rome/epidemiology , Urban Health
4.
PLoS One ; 15(12): e0244129, 2020.
Article in English | MEDLINE | ID: covidwho-999830

ABSTRACT

BACKGROUND: Detailed temporal analyses of complete (full) blood count (CBC) parameters, their evolution and relationship to patient age, gender, co-morbidities and management outcomes in survivors and non-survivors with COVID-19 disease, could identify prognostic clinical biomarkers. METHODS: From 29 January 2020 until 28 March 2020, we performed a longitudinal cohort study of COVID-19 inpatients at the Italian National Institute for Infectious Diseases, Rome, Italy. 9 CBC parameters were studied as continuous variables [neutrophils, lymphocytes, monocytes, platelets, mean platelet volume, red blood cell count, haemoglobin concentration, mean red blood cell volume and red blood cell distribution width (RDW %)]. Model-based punctual estimates, as average of all patients' values, and differences between survivors and non-survivors, overall, and by co-morbidities, at specific times after symptoms, with relative 95% CI and P-values, were obtained by marginal prediction and ANOVA- style joint tests. All analyses were carried out by STATA 15 statistical package. MAIN FINDINGS: 379 COVID-19 patients [273 (72% were male; mean age was 61.67 (SD 15.60)] were enrolled and 1,805 measures per parameter were analysed. Neutrophils' counts were on average significantly higher in non-survivors than in survivors (P<0.001) and lymphocytes were on average higher in survivors (P<0.001). These differences were time dependent. Average platelets' counts (P<0.001) and median platelets' volume (P<0.001) were significantly different in survivors and non-survivors. The differences were time dependent and consistent with acute inflammation followed either by recovery or by death. Anaemia with anisocytosis was observed in the later phase of COVID-19 disease in non-survivors only. Mortality was significantly higher in patients with diabetes (OR = 3.28; 95%CI 1.51-7.13; p = 0.005), obesity (OR = 3.89; 95%CI 1.51-10.04; p = 0.010), chronic renal failure (OR = 9.23; 95%CI 3.49-24.36; p = 0.001), COPD (OR = 2.47; 95% IC 1.13-5.43; p = 0.033), cardiovascular diseases (OR = 4.46; 95%CI 2.25-8.86; p = 0.001), and those >60 years (OR = 4.21; 95%CI 1.82-9.77; p = 0.001). Age (OR = 2.59; 95%CI 1.04-6.45; p = 0.042), obesity (OR = 5.13; 95%CI 1.81-14.50; p = 0.002), renal chronic failure (OR = 5.20; 95%CI 1.80-14.97; p = 0.002) and cardiovascular diseases (OR 2.79; 95%CI 1.29-6.03; p = 0.009) were independently associated with poor clinical outcome at 30 days after symptoms' onset. INTERPRETATION: Increased neutrophil counts, reduced lymphocyte counts, increased median platelet volume and anaemia with anisocytosis, are poor prognostic indicators for COVID19, after adjusting for the confounding effect of obesity, chronic renal failure, COPD, cardiovascular diseases and age >60 years.


Subject(s)
COVID-19/blood , Biomarkers/blood , Blood Cell Count , COVID-19/immunology , Cohort Studies , Demography/methods , Erythrocyte Indices/immunology , Female , Humans , Inflammation/blood , Inflammation/immunology , Leukocyte Count/methods , Longitudinal Studies , Lymphocytes/immunology , Male , Mean Platelet Volume/methods , Middle Aged , Neutrophils/immunology , Prognosis , Rome , Survivors
5.
SSRN; 2020.
Preprint | SSRN | ID: ppcovidwho-705

ABSTRACT

Background: Italy is undergoing an unprecedented COVID-1 epidemic - one of the largest and most lethal outbreaks outside China. The higher death rate observed c

6.
Emerg Infect Dis ; 26(11): 2709-2712, 2020 11.
Article in English | MEDLINE | ID: covidwho-762400

ABSTRACT

Coronavirus disease has disrupted tuberculosis services globally. Data from 33 centers in 16 countries on 5 continents showed that attendance at tuberculosis centers was lower during the first 4 months of the pandemic in 2020 than for the same period in 2019. Resources are needed to ensure tuberculosis care continuity during the pandemic.


Subject(s)
Continuity of Patient Care/trends , Coronavirus Infections/epidemiology , Facilities and Services Utilization/trends , Global Health/trends , Pneumonia, Viral/epidemiology , Tuberculosis/therapy , Betacoronavirus , COVID-19 , Humans , Pandemics , SARS-CoV-2 , Tuberculosis/epidemiology
7.
Euro Surveill ; 25(11)2020 03.
Article in English | MEDLINE | ID: covidwho-10076

ABSTRACT

Data concerning the transmission of the novel severe acute respiratory syndrome coronavirus (SARS-CoV-2) in paucisymptomatic patients are lacking. We report an Italian paucisymptomatic case of coronavirus disease 2019 with multiple biological samples positive for SARS-CoV-2. This case was detected using the World Health Organization protocol on cases and contact investigation. Current discharge criteria and the impact of extra-pulmonary SARS-CoV-2 samples are discussed.


Subject(s)
Asymptomatic Infections , Coronavirus Infections/diagnosis , Coronavirus/isolation & purification , Feces/virology , Lung/diagnostic imaging , Nasopharynx/virology , Pneumonia, Viral/diagnosis , Travel , Virus Shedding , Antibodies, Viral/immunology , Betacoronavirus , COVID-19 , COVID-19 Testing , China , Clinical Laboratory Techniques , Contact Tracing , Coronavirus/genetics , Coronavirus Infections/transmission , Coronavirus Infections/virology , Humans , Italy , Lung/pathology , Male , Pandemics , Pneumonia, Viral/therapy , Pneumonia, Viral/transmission , Pneumonia, Viral/virology , Quarantine , Radiography, Thoracic , Real-Time Polymerase Chain Reaction , SARS-CoV-2 , Tomography, X-Ray Computed , World Health Organization , Young Adult
SELECTION OF CITATIONS
SEARCH DETAIL