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1.
Can Respir J ; 2020: 2045341, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-33005276

RESUMO

Objective: Coronavirus disease 2019 (COVID-19), caused by the novel coronavirus SARS-CoV-2, was first identified in December 2019 in Wuhan, China, and has since spread globally, resulting in an ongoing pandemic. However, the study of asymptomatic patients is still rare, and the understanding of its potential transmission risk is still insufficient. In this study, epidemiological investigations were conducted in the Zhejiang province to understand the epidemiology and clinical characteristics of asymptomatic patients with COVID-19. Methods: This retrospective study was carried out on 22 asymptomatic patients and 234 symptomatic patients with COVID-19 who were hospitalized in Zhejiang Duodi Hospital from January 21 to March 16, 2020. The characteristics of epidemiology, demography, clinical manifestations, and laboratory data of mild patients were compared and analyzed. Results: The median age was 28 years in asymptomatic patients and 48 years in symptomatic patients. The proportion who were female was 77.3% in asymptomatic patients and 36.3% in symptomatic patients (p < 0.001). The proportion of patients with coexisting diseases was 4.5% in asymptomatic patients and 38.0% in symptomatic patients (p=0.002). The proportion of patients with increased CRP was 13.6% in the asymptomatic group and 61.1% in the symptomatic group (p < 0.001). The proportion of patients received antiviral therapy was 45.5% in the asymptomatic group and 97.9% in the symptomatic group (p < 0.001). The proportion of patients received oxygen therapy was 22.7% in the asymptomatic group and 99.1% in symptomatic patients (p < 0.001). By March 16, 2020, all patients were discharged from the hospital, and no symptoms had appeared in the asymptomatic patients during hospitalization. The median course of infection to discharge was 21.5 days in asymptomatic patients and 22 days in symptomatic patients. Conclusions: Asymptomatic patients are also infectious; relying only on clinical symptoms, blood cell tests, and radiology examination will lead to misdiagnosis of most patients, leading to the spread of the virus. Investigation of medical history is the best strategy for screening asymptomatic patients, especially young people, women, and people without coexisting disease, who are more likely to be asymptomatic when infected. Although the prognosis is good, isolation is critical for asymptomatic patients, and it is important not to end isolation early before a nucleic acid test turns negative.


Assuntos
Doenças Assintomáticas , Infecções por Coronavirus , Transmissão de Doença Infecciosa/prevenção & controle , Pandemias , Pneumonia Viral , Medição de Risco/métodos , Adulto , Fatores Etários , Doenças Assintomáticas/epidemiologia , Doenças Assintomáticas/terapia , Betacoronavirus/isolamento & purificação , China/epidemiologia , Comorbidade , Infecções por Coronavirus/diagnóstico , Infecções por Coronavirus/tratamento farmacológico , Infecções por Coronavirus/epidemiologia , Infecções por Coronavirus/fisiopatologia , Infecções por Coronavirus/terapia , Erros de Diagnóstico/prevenção & controle , Feminino , Hospitalização/estatística & dados numéricos , Humanos , Masculino , Pessoa de Meia-Idade , Oxigenoterapia/estatística & dados numéricos , Pneumonia Viral/diagnóstico , Pneumonia Viral/epidemiologia , Pneumonia Viral/fisiopatologia , Pneumonia Viral/terapia , Prognóstico , Fatores Sexuais
2.
Ann Emerg Med ; 76(4): 442-453, 2020 10.
Artigo em Inglês | MEDLINE | ID: mdl-33012378

RESUMO

STUDY OBJECTIVE: The goal of this study is to create a predictive, interpretable model of early hospital respiratory failure among emergency department (ED) patients admitted with coronavirus disease 2019 (COVID-19). METHODS: This was an observational, retrospective, cohort study from a 9-ED health system of admitted adult patients with severe acute respiratory syndrome coronavirus 2 (COVID-19) and an oxygen requirement less than or equal to 6 L/min. We sought to predict respiratory failure within 24 hours of admission as defined by oxygen requirement of greater than 10 L/min by low-flow device, high-flow device, noninvasive or invasive ventilation, or death. Predictive models were compared with the Elixhauser Comorbidity Index, quick Sequential [Sepsis-related] Organ Failure Assessment, and the CURB-65 pneumonia severity score. RESULTS: During the study period, from March 1 to April 27, 2020, 1,792 patients were admitted with COVID-19, 620 (35%) of whom had respiratory failure in the ED. Of the remaining 1,172 admitted patients, 144 (12.3%) met the composite endpoint within the first 24 hours of hospitalization. On the independent test cohort, both a novel bedside scoring system, the quick COVID-19 Severity Index (area under receiver operating characteristic curve mean 0.81 [95% confidence interval {CI} 0.73 to 0.89]), and a machine-learning model, the COVID-19 Severity Index (mean 0.76 [95% CI 0.65 to 0.86]), outperformed the Elixhauser mortality index (mean 0.61 [95% CI 0.51 to 0.70]), CURB-65 (0.50 [95% CI 0.40 to 0.60]), and quick Sequential [Sepsis-related] Organ Failure Assessment (0.59 [95% CI 0.50 to 0.68]). A low quick COVID-19 Severity Index score was associated with a less than 5% risk of respiratory decompensation in the validation cohort. CONCLUSION: A significant proportion of admitted COVID-19 patients progress to respiratory failure within 24 hours of admission. These events are accurately predicted with bedside respiratory examination findings within a simple scoring system.


Assuntos
Infecções por Coronavirus/complicações , Infecções por Coronavirus/diagnóstico , Serviço Hospitalar de Emergência , Pneumonia Viral/complicações , Pneumonia Viral/diagnóstico , Insuficiência Respiratória/virologia , Índice de Gravidade de Doença , Adolescente , Adulto , Idoso , Betacoronavirus , Técnicas de Laboratório Clínico , Infecções por Coronavirus/terapia , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Oxigenoterapia , Pandemias , Pneumonia Viral/terapia , Insuficiência Respiratória/terapia , Estudos Retrospectivos , Medição de Risco/métodos , Adulto Jovem
3.
Saudi Med J ; 41(10): 1090-1097, 2020 Oct.
Artigo em Inglês | MEDLINE | ID: mdl-33026050

RESUMO

OBJECTIVES: To elucidate the risk factors for hospital admission among COVID-19 patients with type 2 diabetes mellitus (T2DM). METHODS: This retrospective study was conducted at the Prince Sultan Military Medical City, Riyadh, Saudi Arabia between May 2020 and July 2020. Out of 7,260 COVID-19 patients, 920 were identified as T2DM. After the exclusion process, 806 patients with T2DM were included in this analysis. Patients' data were extracted from electronic medical records. A logistic regression model was performed to estimate the risk factors of hospital admission. Results: Of the total of 806 COVID-19 patients with T2DM, 48% were admitted in the hospital, 52% were placed under home isolation. Older age between 70-79 years (OR [odd ratio] 2.56; p=0.017), ≥80 years (OR 6.48; p=0.001) were significantly more likely to be hospitalized compared to less than 40 years. Similarly, patients with higher HbA1c level of ≥9% compared to less than 7%; (OR 1.58; p=0.047); patients with comorbidities such as, hypertension (OR 1.43; p=0.048), cardiovascular disease (OR 1.56; p=0.033), cerebrovascular disease (OR 2.38; p=0.016), chronic pulmonary disease (OR 1.51; p=0.018), malignancy (OR 2.45; p=0.025), chronic kidney disease (CKD) IIIa, IIIb, IV (OR 2.37; p=0.008), CKD V (OR 5.07; p=0.007) were significantly more likely to be hospitalized. Likewise, insulin-treated (OR 1.46; p=0.03) were more likely to require hospital admission compared to non-insulin treated patients. CONCLUSION: Among COVID-19 patients with diabetes, higher age, high HbA1c level, and presence of other comorbidities were found to be significant risk factors for the hospital admission.


Assuntos
Fatores Etários , Doença Crônica/epidemiologia , Infecções por Coronavirus , Diabetes Mellitus Tipo 2 , Hemoglobina A Glicada/análise , Hospitalização/estatística & dados numéricos , Pandemias , Pneumonia Viral , Adulto , Idoso , Betacoronavirus/isolamento & purificação , Comorbidade , Infecções por Coronavirus/epidemiologia , Infecções por Coronavirus/terapia , Diabetes Mellitus Tipo 2/sangue , Diabetes Mellitus Tipo 2/epidemiologia , Registros Eletrônicos de Saúde/estatística & dados numéricos , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Pneumonia Viral/epidemiologia , Pneumonia Viral/terapia , Estudos Retrospectivos , Medição de Risco/métodos , Fatores de Risco , Arábia Saudita/epidemiologia
4.
Acta Biomed ; 91(11-S): e2020003, 2020 09 15.
Artigo em Inglês | MEDLINE | ID: mdl-33004773

RESUMO

n December 2019, in Wuhan (Hubei, China), the first COVID-19 cases due to SARS-COV-2 had been reported. On July 1st 2020, more than 10.268.839 million people had developed the disease, with at least 506.064 deaths. At present, Italy is the third country considering the number of cases (n=240.760), after Spain, and the second for the cumulative number of deaths (n=249.271), after the United States. As regard pediatric COVID-19 cases, more than 4000 cases (have been reported; however, these figures are likely to be underestimated since they are influenced by the number of diagnostic tests carried out. Three pediatric deaths have been reported in Italy to date. We aimed to review the peculiar aspects of SARS-COV-2 infection in the pediatric population.


Assuntos
Betacoronavirus , Infecções por Coronavirus/epidemiologia , Estado Terminal/epidemiologia , Pandemias , Pneumonia Viral/epidemiologia , Medição de Risco/métodos , Criança , Saúde Global , Humanos , Morbidade/tendências
5.
Infect Dis Poverty ; 9(1): 139, 2020 Oct 07.
Artigo em Inglês | MEDLINE | ID: mdl-33028400

RESUMO

BACKGROUND: Health workers (HWs) are at increased risk for severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) infection and a possible source of nosocomial transmission clusters. Despite the increased risk, the best surveillance strategy and management of exposed HWs are not yet well known. The aim of this review was to summarize and critically analyze the existing evidence related to this topic in order to support public health strategies aimed at protecting HWs in the hospital setting. MAIN TEXT: A comprehensive computerized literature research from 1 January 2020 up to 22 May 2020 was made to identify studies analyzing the burden of infection, risk assessment, surveillance and management of HWs exposed to SARS-CoV-2. Among 1623 citation identified using MEDLINE, Embase, Google Scholar and manual search, we included 43 studies, 14 webpages and 5 ongoing trials. Health workers have a high risk of acquiring infection while caring for coronavirus disease 2019 (COVID-19) patients. In particular, some types exposures and their duration, as well as the inadequate or non-use of personal protective equipment (PPE) are associated with increased infection risk. Strict infection prevention and control procedures (IPC), adequate training programs on the appropriate use of PPE and close monitoring of HWs with symptom surveillance and testing are essential to significantly reduce the risk. At the moment there is not enough evidence to provide precise indications regarding pre-exposure prophylaxis (PrEP) and post-exposure prophylaxis (PEP). CONCLUSIONS: During the spread of COVID-19 outbreak, numerous published papers investigated the epidemiology, risk assessment and prevention and control of SARS-CoV-2. However, more high-quality studies are needed to provide valid recommendations for better management and for the clinical and microbiological surveillance of healthcare personnel.


Assuntos
Infecções por Coronavirus/diagnóstico , Infecções por Coronavirus/terapia , Pessoal de Saúde/estatística & dados numéricos , Pneumonia Viral/diagnóstico , Pneumonia Viral/terapia , Betacoronavirus/isolamento & purificação , Infecções por Coronavirus/epidemiologia , Infecções por Coronavirus/transmissão , Bases de Dados Factuais , Gerenciamento Clínico , Monitoramento Epidemiológico , Hospitais , Humanos , Transmissão de Doença Infecciosa do Paciente para o Profissional , Pandemias , Pneumonia Viral/epidemiologia , Pneumonia Viral/transmissão , Profilaxia Pós-Exposição , Vigilância em Saúde Pública , Medição de Risco/métodos , Fatores de Risco
6.
Cardiol Rev ; 28(6): 295-302, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-33017364

RESUMO

The 2019 novel coronavirus, declared a pandemic, has infected 2.6 million people as of April 27, 2020, and has resulted in the death of 181,938 people. D-dimer is an important prognostic tool, is often elevated in patients with severe coronavirus disease-19 (COVID-19) infection and in those who suffered death. In this systematic review, we aimed to investigate the prognostic role of D-dimer in COVID-19-infected patients. We searched PubMed, Medline, Embase, Ovid, and Cochrane for studies reporting admission D-dimer levels in COVID-19 patients and its effect on mortality. Eighteen studies (16 retrospective and 2 prospective) with a total of 3682 patients met the inclusion criteria. The pooled weighted mean difference (WMD) demonstrated significantly elevated D-dimer levels in patients who died versus those who survived (WMD, 6.13 mg/L; 95% confidence interval [CI] 4.16-8.11; P < 0.001). Similarly, the pooled mean D-dimer levels were significantly elevated in patients with severe COVID-19 infection (WMD, 0.54 mg/L; 95% CI 0.28-0.80; P < 0.001). The risk of mortality was fourfold higher in patients with positive D-dimer versus negative D-dimer (risk ratio, 4.11; 95% CI, 2.48-6.84; P < 0.001) and the risk of developing severe disease was twofold higher in patients with positive D-dimer levels versus negative D-dimer (risk ratio, 2.04; 95% CI, 1.34-3.11; P < 0.001). Our meta-analysis demonstrates that patients with COVID-19 infection presenting with elevated D-dimer levels have an increased risk of severe disease and mortality.


Assuntos
Infecções por Coronavirus , Produtos de Degradação da Fibrina e do Fibrinogênio/análise , Pandemias , Pneumonia Viral , Betacoronavirus , Infecções por Coronavirus/sangue , Infecções por Coronavirus/diagnóstico , Infecções por Coronavirus/mortalidade , Humanos , Mortalidade , Pneumonia Viral/sangue , Pneumonia Viral/diagnóstico , Pneumonia Viral/mortalidade , Valor Preditivo dos Testes , Prognóstico , Medição de Risco/métodos
7.
Acta Med Indones ; 52(3): 246-254, 2020 Jul.
Artigo em Inglês | MEDLINE | ID: mdl-33020335

RESUMO

BACKGROUND: Coronavirus Disease 2019 is an emerging respiratory disease that is now a pandemic. Indonesia is experiencing a rapid surge of cases but the local data are scarce. METHODS: this is an analysis using data from the ongoing recapitulation of Epidemiological Surveillance (ES) by the Provincial Health Office of Jakarta from March 2nd to April 27th 2020. We evaluated demographic and clinical characteristics of all confirmed cases in association with death. RESULTS: of the 4,052 patients, 381 (9.4%) patients were deceased. Multivariable analysis showed that death was associated with older age (odds ratio [OR] 1.03; 95% confidence interval [CI] 1.02, 1.05, per year increase; p<0.001), dyspnea (OR 4.83; 95% CI 3.20, 7.29; p<0.001), pneumonia (OR 2.46; 95%CI 1.56, 3.88; p<0.001), and pre-existing hypertension (OR 1.86; 95% CI 1.24, 2.78; p=0.003). Death was highest in the week of April 6th 2020 and declined in the subsequent weeks, after a large-scale social restriction commenced. CONCLUSION: older age, dyspnea, pneumonia, and pre-existing hypertension were associated with death. Mortality was high, but may be reduced by lockdown.


Assuntos
Betacoronavirus , Infecções por Coronavirus/mortalidade , Pandemias , Pneumonia Viral/mortalidade , Medição de Risco/métodos , Adolescente , Adulto , Distribuição por Idade , Idoso , Criança , Estudos Epidemiológicos , Feminino , Seguimentos , Humanos , Incidência , Indonésia/epidemiologia , Masculino , Pessoa de Meia-Idade , Estudos Retrospectivos , Fatores de Risco , Distribuição por Sexo , Taxa de Sobrevida/tendências , Adulto Jovem
8.
J Orthop Trauma ; 34(10): e382-e388, 2020 10.
Artigo em Inglês | MEDLINE | ID: mdl-32947589

RESUMO

Orthopaedic trauma presents a unique and complex challenge in the initial phase of the coronavirus 2019 (COVID-19) global crisis. Little is currently known about the surgical practices in orthopaedic emergencies in the early days of the COVID-19 outbreak (1). This is a retrospective case series of 10 orthopaedic trauma patients who underwent fracture fixation in March 2020. Of the 10 patients testing COVID-19 positive, there were a total of 16 long bone fractures, 5 pelvic ring fractures, and 1 lumbar burst fracture. There were 7 (70%) males in this cohort. Two (20%) of the COVID-positive patients did not develop fever, leukocytosis, respiratory insufficiency, or positive imaging findings and were younger (average age 25.5 years) with fewer comorbidities (average 0.5) compared with the 8 symptomatic COVID-19-positive patients (56.6 years with 1.88 comorbidities). Advancement of COVID-19 pathogenesis with lung opacities and prolonged intubation occurred in all 5 patients who remained on ventilation postoperatively (range 9 hours-11 days). At the time of most recent follow-up, all patients survived, 1 continues to require ventilation support, 1 remains admitted without ventilation support, and 8 (80%) were discharged to home. LEVEL OF EVIDENCE:: Prognostic Level II. See Instructions for Authors for a complete description of levels of evidence.


Assuntos
Betacoronavirus , Infecções por Coronavirus/epidemiologia , Transmissão de Doença Infecciosa/prevenção & controle , Fixação de Fratura/métodos , Fraturas Ósseas/complicações , Pneumonia Viral/epidemiologia , Medição de Risco/métodos , Adolescente , Adulto , Idoso , Idoso de 80 Anos ou mais , Infecções por Coronavirus/complicações , Infecções por Coronavirus/transmissão , Feminino , Seguimentos , Fraturas Ósseas/epidemiologia , Fraturas Ósseas/cirurgia , Humanos , Incidência , Masculino , Pessoa de Meia-Idade , Pandemias , Pneumonia Viral/complicações , Pneumonia Viral/transmissão , Estudos Retrospectivos , Fatores de Tempo , Resultado do Tratamento , Estados Unidos/epidemiologia , Adulto Jovem
10.
BMJ Open ; 10(9): e039338, 2020 09 24.
Artigo em Inglês | MEDLINE | ID: mdl-32973066

RESUMO

OBJECTIVES: A number of studies have shown that the airborne transmission route could spread some viruses over a distance of 2 meters from an infected person. An epidemic model based only on respiratory droplets and close contact could not fully explain the regional differences in the spread of COVID-19 in Italy. On March 16th 2020, we presented a position paper proposing a research hypothesis concerning the association between higher mortality rates due to COVID-19 observed in Northern Italy and average concentrations of PM10 exceeding a daily limit of 50 µg/m3. METHODS: To monitor the spreading of COVID-19 in Italy from February 24th to March 13th (the date of the Italian lockdown), official daily data for PM10 levels were collected from all Italian provinces between February 9th and February 29th, taking into account the maximum lag period (14 days) between the infection and diagnosis. In addition to the number of exceedances of the daily limit value of PM10, we also considered population data and daily travelling information for each province. RESULTS: Exceedance of the daily limit value of PM10 appears to be a significant predictor of infection in univariate analyses (p<0.001). Less polluted provinces had a median of 0.03 infections over 1000 residents, while the most polluted provinces showed a median of 0.26 cases. Thirty-nine out of 41 Northern Italian provinces resulted in the category with the highest PM10 levels, while 62 out of 66 Southern provinces presented low PM10 concentrations (p<0.001). In Milan, the average growth rate before the lockdown was significantly higher than in Rome (0.34 vs 0.27 per day, with a doubling time of 2.0 days vs 2.6, respectively), thus suggesting a basic reproductive number R0>6.0, comparable with the highest values estimated for China. CONCLUSION: A significant association has been found between the geographical distribution of daily PM10 exceedances and the initial spreading of COVID-19 in the 110 Italian provinces.


Assuntos
Poluição do Ar , Betacoronavirus/isolamento & purificação , Infecções por Coronavirus , Transmissão de Doença Infecciosa , Pandemias , Material Particulado/análise , Pneumonia Viral , Poluição do Ar/análise , Poluição do Ar/estatística & dados numéricos , Infecções por Coronavirus/epidemiologia , Infecções por Coronavirus/prevenção & controle , Infecções por Coronavirus/transmissão , Correlação de Dados , Transmissão de Doença Infecciosa/prevenção & controle , Transmissão de Doença Infecciosa/estatística & dados numéricos , Humanos , Itália/epidemiologia , Avaliação de Resultados em Cuidados de Saúde , Pandemias/prevenção & controle , Pneumonia Viral/epidemiologia , Pneumonia Viral/prevenção & controle , Pneumonia Viral/transmissão , Saúde Pública/métodos , Saúde Pública/estatística & dados numéricos , Medição de Risco/métodos
11.
BMJ Open ; 10(9): e040729, 2020 09 25.
Artigo em Inglês | MEDLINE | ID: mdl-32978207

RESUMO

OBJECTIVES: Several physiological abnormalities that develop during COVID-19 are associated with increased mortality. In the present study, we aimed to develop a clinical risk score to predict the in-hospital mortality in COVID-19 patients, based on a set of variables available soon after the hospitalisation triage. SETTING: Retrospective cohort study of 516 patients consecutively admitted for COVID-19 to two Italian tertiary hospitals located in Northern and Central Italy were collected from 22 February 2020 (date of first admission) to 10 April 2020. PARTICIPANTS: Consecutive patients≥18 years admitted for COVID-19. MAIN OUTCOME MEASURES: Simple clinical and laboratory findings readily available after triage were compared by patients' survival status ('dead' vs 'alive'), with the objective of identifying baseline variables associated with mortality. These were used to build a COVID-19 in-hospital mortality risk score (COVID-19MRS). RESULTS: Mean age was 67±13 years (mean±SD), and 66.9% were male. Using Cox regression analysis, tertiles of increasing age (≥75, upper vs <62 years, lower: HR 7.92; p<0.001) and number of chronic diseases (≥4 vs 0-1: HR 2.09; p=0.007), respiratory rate (HR 1.04 per unit increase; p=0.001), PaO2/FiO2 (HR 0.995 per unit increase; p<0.001), serum creatinine (HR 1.34 per unit increase; p<0.001) and platelet count (HR 0.995 per unit increase; p=0.001) were predictors of mortality. All six predictors were used to build the COVID-19MRS (Area Under the Curve 0.90, 95% CI 0.87 to 0.93), which proved to be highly accurate in stratifying patients at low, intermediate and high risk of in-hospital death (p<0.001). CONCLUSIONS: The COVID-19MRS is a rapid, operator-independent and inexpensive clinical tool that objectively predicts mortality in patients with COVID-19. The score could be helpful from triage to guide earlier assignment of COVID-19 patients to the most appropriate level of care.


Assuntos
Betacoronavirus/isolamento & purificação , Infecções por Coronavirus , Cuidados Críticos , Procedimentos Clínicos , Pandemias , Pneumonia Viral , Medição de Risco/métodos , Triagem , Idoso , Infecções por Coronavirus/sangue , Infecções por Coronavirus/diagnóstico , Infecções por Coronavirus/mortalidade , Infecções por Coronavirus/fisiopatologia , Cuidados Críticos/métodos , Cuidados Críticos/estatística & dados numéricos , Procedimentos Clínicos/organização & administração , Procedimentos Clínicos/normas , Feminino , Mortalidade Hospitalar , Hospitalização/estatística & dados numéricos , Humanos , Itália/epidemiologia , Masculino , Pessoa de Meia-Idade , Pneumonia Viral/sangue , Pneumonia Viral/diagnóstico , Pneumonia Viral/mortalidade , Pneumonia Viral/fisiopatologia , Prognóstico , Respiração Artificial/estatística & dados numéricos , Estudos Retrospectivos , Triagem/métodos , Triagem/estatística & dados numéricos
12.
BMJ Open ; 10(9): e041370, 2020 09 28.
Artigo em Inglês | MEDLINE | ID: mdl-32988953

RESUMO

OBJECTIVES: To use Population Health Management (PHM) methods to identify and characterise individuals at high-risk of severe COVID-19 for which shielding is required, for the purposes of managing ongoing health needs and mitigating potential shielding-induced harm. DESIGN: Individuals at 'high risk' of COVID-19 were identified using the published national 'Shielded Patient List' criteria. Individual-level information, including current chronic conditions, historical healthcare utilisation and demographic and socioeconomic status, was used for descriptive analyses of this group using PHM methods. Segmentation used k-prototypes cluster analysis. SETTING: A major healthcare system in the South West of England, for which linked primary, secondary, community and mental health data are available in a system-wide dataset. The study was performed at a time considered to be relatively early in the COVID-19 pandemic in the UK. PARTICIPANTS: 1 013 940 individuals from 78 contributing general practices. RESULTS: Compared with the groups considered at 'low' and 'moderate' risk (ie, eligible for the annual influenza vaccination), individuals at high risk were older (median age: 68 years (IQR: 55-77 years), cf 30 years (18-44 years) and 63 years (38-73 years), respectively), with more primary care/community contacts in the previous year (median contacts: 5 (2-10), cf 0 (0-2) and 2 (0-5)) and had a higher burden of comorbidity (median Charlson Score: 4 (3-6), cf 0 (0-0) and 2 (1-4)). Geospatial analyses revealed that 3.3% of rural and semi-rural residents were in the high-risk group compared with 2.91% of urban and inner-city residents (p<0.001). Segmentation uncovered six distinct clusters comprising the high-risk population, with key differentiation based on age and the presence of cancer, respiratory, and mental health conditions. CONCLUSIONS: PHM methods are useful in characterising the needs of individuals requiring shielding. Segmentation of the high-risk population identified groups with distinct characteristics that may benefit from a more tailored response from health and care providers and policy-makers.


Assuntos
Infecções por Coronavirus , Sistemas de Informação em Saúde/estatística & dados numéricos , Pandemias , Pneumonia Viral , Gestão da Saúde da População , Medição de Risco/métodos , Gestão de Riscos , Idoso , Betacoronavirus , Infecções por Coronavirus/epidemiologia , Infecções por Coronavirus/prevenção & controle , Estudos Transversais , Demografia , Inglaterra/epidemiologia , Feminino , Medicina Geral/estatística & dados numéricos , Humanos , Masculino , Pessoa de Meia-Idade , Determinação de Necessidades de Cuidados de Saúde , Pandemias/prevenção & controle , Pneumonia Viral/epidemiologia , Pneumonia Viral/prevenção & controle , Fatores de Risco , Gestão de Riscos/métodos , Gestão de Riscos/organização & administração , Índice de Gravidade de Doença
13.
PLoS One ; 15(8): e0238315, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-32866202

RESUMO

BACKGROUND: In low resource settings recall of the date of the mother's last menstrual period may be unreliable and due to limited availability of prenatal ultrasound, gestational age of newborns may not be assessed reliably. Preterm babies are at high risk of morbidity and mortality so an alternative strategy is to identify them soon after birth is needed for early referral and management. OBJECTIVE: The objective of this study was to assess the accuracy in assessing prematurity of newborn, over and above birthweight, using a pictorial Simplified Gestational Age Score adapted for use as a Tablet App. METHODS: Two trained nurse midwives, blinded to each other's assessment and the actual gestational age of the baby used the app to assess gestational age at birth in 3 hospitals based on the following 4 parameters-newborn's posture, skin texture, breast and genital development. Inter-observer variation was evaluated and the optimal scoring cut-off to detect preterm birth was determined. Sensitivity and specificity of gestational age score using the tablet was estimated using combinations of last menstrual period and ultrasound as reference standards to assess preterm birth. The predictive accuracy of the score using the area under a receiver operating characteristic curve was also determined. To account for potential reference standard bias, we also evaluated the score using latent class models. RESULTS: A total of 8,591 live singleton births whose gestational age by last menstrual period and ultrasound was within 1 weeks of each other were enrolled. There was strong agreement between assessors (concordance correlation coefficient 0.77 (95% CI 0.76-0.78) and Fleiss' kappa was 0.76 (95% CI 0.76-0.78). The optimal cut-off for the score to predict preterm was 13. Irrespective of the reference standard, the specificity of the score was 90% and sensitivity varied from 40-50% and the predictive accuracy between 74%-79% for the reference standards. The likelihood ratio of a positive score varied between 3.75-4.88 while the same for a negative likelihood ratio consistently varied between 0.57-0.72. Latent class models showed similar results indicating no reference standard bias. CONCLUSION: Gestational age scores had strong inter-observer agreement, robust prediction of preterm births simplicity of use by nurse midwives and can be a useful tool in resource-limited scenarios. TRIAL REGISTRATION: The Tablet App for the Simplified Gestational Age Score (T-SGAS) study was registered at ClinicalTrials.gov NCT02408783.


Assuntos
Recém-Nascido Prematuro/fisiologia , Parto/fisiologia , Nascimento Prematuro/diagnóstico , Nascimento Prematuro/fisiopatologia , Peso ao Nascer/fisiologia , Estudos Transversais , Feminino , Idade Gestacional , Humanos , Recém-Nascido de Baixo Peso/fisiologia , Recém-Nascido , Aplicativos Móveis , Gravidez , Medição de Risco/métodos , Sensibilidade e Especificidade , Ultrassonografia Pré-Natal/métodos
14.
Ren Fail ; 42(1): 950-957, 2020 Nov.
Artigo em Inglês | MEDLINE | ID: mdl-32924707

RESUMO

BACKGROUND: Novel coronavirus disease (COVID-19) is spreading rapidly, which poses great challenges to patients on maintenance hemodialysis. Here we report the clinical features of 66 hemodialysis patients with laboratory confirmed COVID-19 infection. DESIGN, SETTING, PARTICIPANTS, AND MEASUREMENTS: Retrospective, single-center case series of the 66 hemodialysis patients with confirmed COVID-19 from 1 January to 5 March 2020; the final date of follow-up was 25 March 2020. RESULTS: The clinical data were collected from 66 hemodialysis patients with confirmed COVID-19. The incidence of COVID-19 in our center was 11.0% (66/602), of which 18 patients died. According to different prognosis, hemodialysis patients with COVID-19 were divided into the survival and death group. A higher incidence of fever and dyspnea was found in the death group compared with the survival group. Meanwhile, patients in the death group were often accompanied by higher white blood cell count, prolonged PT time, increased D-dimer (p < .05). More patients in the death group showed hepatocytes and cardiomyocytes damage. Furthermore, logistic regression analysis suggested that fever, dyspnea, and elevated D-dimer were independent risk factors for death in hemodialysis patients with COVID-19 (OR, 1.077; 95% CI, 1.014 to 1.439; p = .044; OR, 1.146; 95% CI, 1.026 to 1.875; p = .034, OR, 4.974; 95% CI, 3.315 to 6.263; p = .007, respectively). CONCLUSIONS: The potential risk factors of fever, dyspnea, and elevated D-dimer could help clinicians to identify hemodialysis patients with poor prognosis at an early stage of COVID-19 infection.


Assuntos
Infecções por Coronavirus , Dispneia , Febre , Produtos de Degradação da Fibrina e do Fibrinogênio/análise , Falência Renal Crônica , Pandemias , Pneumonia Viral , Medição de Risco/métodos , Betacoronavirus/isolamento & purificação , China/epidemiologia , Comorbidade , Infecções por Coronavirus/diagnóstico , Infecções por Coronavirus/mortalidade , Infecções por Coronavirus/fisiopatologia , Dispneia/diagnóstico , Dispneia/epidemiologia , Feminino , Febre/diagnóstico , Febre/epidemiologia , Unidades Hospitalares de Hemodiálise/estatística & dados numéricos , Humanos , Falência Renal Crônica/epidemiologia , Falência Renal Crônica/terapia , Masculino , Pessoa de Meia-Idade , Mortalidade , Pneumonia Viral/diagnóstico , Pneumonia Viral/mortalidade , Pneumonia Viral/fisiopatologia , Prognóstico , Diálise Renal/métodos , Estudos Retrospectivos , Fatores de Risco
15.
Medicine (Baltimore) ; 99(35): e21700, 2020 Aug 28.
Artigo em Inglês | MEDLINE | ID: mdl-32871887

RESUMO

The coronavirus disease 2019 (COVID-19) outbreak has become a global health threat and will likely be one of the greatest global challenges in the near future. The battle between clinicians and the COVID-19 outbreak may be a "protracted war."The objective of this study was to investigate the risk factors for in-hospital mortality in patients with COVID-19, so as to provide a reference for the early diagnosis and treatment.This study retrospectively enrolled 118 patients diagnosed with COVID-19, who were admitted to Eastern District of Renmin Hospital of Wuhan University from February 04, 2020 to March 04, 2020. The demographics and laboratory data were collected and compared between survivors and nonsurvivors. The risk factors of in-hospital mortality were explored by univariable and multivariable logistic regression to construct a clinical prediction model, the prediction efficiency of which was verified by receiver-operating characteristic (ROC) curve.A total of 118 patients (49 males and 69 females) were included in this study; the results revealed that the following factors associated with in-hospital mortality: older age (odds ratio [OR] 1.175, 95% confidence interval [CI] 1.073-1.287, P = .001), neutrophil count greater than 6.3 × 10 cells/L (OR 7.174, (95% CI 2.295-22.432, P = .001), lymphocytopenia (OR 0.069, 95% CI 0.007-0.722, P = .026), prothrombin time >13 seconds (OR 11.869, 95% CI 1.433-98.278, P = .022), D-dimer >1 mg/L (OR 22.811, 95% CI 2.224-233.910, P = .008) and procalcitonin (PCT) >0.1 ng/mL (OR 23.022, 95% CI 3.108-170.532, P = .002). The area under the ROC curve (AUC) of the above indicators for predicting in-hospital mortality were 0.808 (95% CI 0.715-0.901), 0.809 (95% CI 0.710-0.907), 0.811 (95% CI 0.724-0.898), 0.745 (95% CI 0.643-0.847), 0.872 (95% CI 0.804-0.940), 0.881 (95% CI 0.809-0.953), respectively. The AUC of combined diagnosis of these aforementioned factors were 0.992 (95% CI 0.981-1.000).In conclusion, older age, increased neutrophil count, prothrombin time, D-dimer, PCT, and decreased lymphocyte count at admission were risk factors associated with in-hospital mortality of COVID-19. The prediction model combined of these factors could improve the early identification of mortality risk in COVID-19 patients.


Assuntos
Infecções por Coronavirus , Produtos de Degradação da Fibrina e do Fibrinogênio/análise , Contagem de Leucócitos , Pandemias , Pneumonia Viral , Pró-Calcitonina/análise , Tempo de Protrombina , Adulto , Idoso , Betacoronavirus , China/epidemiologia , Infecções por Coronavirus/sangue , Infecções por Coronavirus/imunologia , Infecções por Coronavirus/mortalidade , Feminino , Mortalidade Hospitalar , Hospitalização/estatística & dados numéricos , Humanos , Contagem de Leucócitos/métodos , Contagem de Leucócitos/estatística & dados numéricos , Masculino , Pneumonia Viral/sangue , Pneumonia Viral/imunologia , Pneumonia Viral/mortalidade , Valor Preditivo dos Testes , Prognóstico , Tempo de Protrombina/métodos , Tempo de Protrombina/estatística & dados numéricos , Estudos Retrospectivos , Medição de Risco/métodos , Fatores de Risco
16.
Zhonghua Liu Xing Bing Xue Za Zhi ; 41(8): 1324-1327, 2020 Aug 10.
Artigo em Chinês | MEDLINE | ID: mdl-32867444

RESUMO

Objective: To analyze the predictive ability of HIV infection risk assessment tool for men who have sex with men (MSM). Sentinel surveillance data of MSM in Taizhou prefecture of Zhejiang province was used. Methods: MSM involved in AIDS sentinel surveillance program in Taizhou from 2013 to 2017 were included in the study and items listed in the HIV infection risk assessment tool for MSM was revised. Related data on questions and options involved in sentinel surveillance was collected and individual risk scores were calculated. We determined the predictive ability of this tool by comprehensive analyzing the HIV infection status and individual risk scores. Results: A total of 1 944 MSM were included in the study, with an average age of (35.04±13.28)years old. Most of them were recruited from the venues (55.7%) and 48.2% were never married. Among these MSM, HIV infection rate was 12.6%(245/1 944) with the median of risk score as 23.99, versus 20.36 from the HIV negative ones. Significant differences appeared on the risk scores between the target populations that with different HIV status (Mann-Whitney test, P=0.007). According to the principle of decision tree, MSM were divided into two groups according to risk scores: ≤18.66 and >18.66. It appeared that the risk scores were in parallel with the rates of HIV infection (χ(2)=13.102, P<0.001). Results from the multivariate analysis showed that MSM with higher risk score were more likely to be infected with HIV (>18.66 vs. ≤18.66: aOR=1.72, 95%CI: 1.27-2.32, P<0.001). Area under the ROC curve (AUC) for HIV infection was 0.553 (95%CI: 0.516-0.590, P=0.007). At the point of risk score 19.01, Youden's index appeared the maximum, with sensitivity as 0.69 and specificity as 0.43, of this tool. Conclusions: The HIV infection risk assessment tool for MSM developed based on Delphi method can predict the risk of HIV infection in MSM to some extent. MSM with higher risk score seemed likely to be infected with HIV. Items of this tool need to be adjusted for the verification of the tool through cohort studies in the near future.


Assuntos
Infecções por HIV/epidemiologia , Homossexualidade Masculina/estatística & dados numéricos , Medição de Risco/métodos , Vigilância de Evento Sentinela , Adulto , China/epidemiologia , Técnica Delfos , Humanos , Masculino , Pessoa de Meia-Idade , Reprodutibilidade dos Testes , Adulto Jovem
18.
PLoS One ; 15(9): e0239536, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-32997700

RESUMO

BACKGROUND: The 2019 novel coronavirus disease (COVID-19) has created unprecedented medical challenges. There remains a need for validated risk prediction models to assess short-term mortality risk among hospitalized patients with COVID-19. The objective of this study was to develop and validate a 7-day and 14-day mortality risk prediction model for patients hospitalized with COVID-19. METHODS: We performed a multicenter retrospective cohort study with a separate multicenter cohort for external validation using two hospitals in New York, NY, and 9 hospitals in Massachusetts, respectively. A total of 664 patients in NY and 265 patients with COVID-19 in Massachusetts, hospitalized from March to April 2020. RESULTS: We developed a risk model consisting of patient age, hypoxia severity, mean arterial pressure and presence of kidney dysfunction at hospital presentation. Multivariable regression model was based on risk factors selected from univariable and Chi-squared automatic interaction detection analyses. Validation was by receiver operating characteristic curve (discrimination) and Hosmer-Lemeshow goodness of fit (GOF) test (calibration). In internal cross-validation, prediction of 7-day mortality had an AUC of 0.86 (95%CI 0.74-0.98; GOF p = 0.744); while 14-day had an AUC of 0.83 (95%CI 0.69-0.97; GOF p = 0.588). External validation was achieved using 265 patients from an outside cohort and confirmed 7- and 14-day mortality prediction performance with an AUC of 0.85 (95%CI 0.78-0.92; GOF p = 0.340) and 0.83 (95%CI 0.76-0.89; GOF p = 0.471) respectively, along with excellent calibration. Retrospective data collection, short follow-up time, and development in COVID-19 epicenter may limit model generalizability. CONCLUSIONS: The COVID-AID risk tool is a well-calibrated model that demonstrates accuracy in the prediction of both 7-day and 14-day mortality risk among patients hospitalized with COVID-19. This prediction score could assist with resource utilization, patient and caregiver education, and provide a risk stratification instrument for future research trials.


Assuntos
Infecções por Coronavirus/mortalidade , Modelos Logísticos , Pneumonia Viral/mortalidade , Medição de Risco/métodos , Idoso , Idoso de 80 Anos ou mais , Betacoronavirus , Feminino , Mortalidade Hospitalar , Hospitalização , Humanos , Masculino , Massachusetts , Pessoa de Meia-Idade , New York , Pandemias , Curva ROC , Análise de Regressão , Estudos Retrospectivos , Fatores de Risco , Estados Unidos
19.
Acta Biomed ; 91(3): e2020021, 2020 09 07.
Artigo em Inglês | MEDLINE | ID: mdl-32921718

RESUMO

The COVID-19 epidemic initially started in Wuhan, China in December 2019 due to SARS-CoV-2. SARS-CoV-2 is genetically similar to the bat beta-coronavirus genus, but the novel specie of this genus can infect humans. The most common clinical features of COVID-19 are fever, cough, myalgia, fatigue, expectoration, and dyspnea. The primary reported mortality rate was about 2-3% in China; however, it reached up to 10% among patients with underlying cardiovascular diseases. The primary epidemiological investigations showed a high prevalence of underlying cardiovascular diseases in more than 40% of infected patients. A high prevalence of hypertension, ischemic heart disease, and diabetes were reported among deceased patients in Italy. Previous experiments in different pandemic situations showed that the cardiovascular system has been affected in many ways. Previous studies on SARS-CoV and MERS-CoV reported that cardiovascular co-morbidities had a direct correlation with the risk of infection, the severity of disease, and the mortality rate. Therefore, brief and available protocols for controlling the negative effects of this novel respiratory infection on the cardiovascular system, especially in a high-risk populations with underlying cardiovascular conditions, is one of the most serious concerns among healthcare providers. Herein, we aimed to review the available data on the cardiac manifestation of COVID-19. Besides, we described useful maps for the better treatment of COVID-19 infection in patients with underlying cardiovascular conditions, as a high-risk group of patients.


Assuntos
Betacoronavirus , Doenças Cardiovasculares/epidemiologia , Infecções por Coronavirus/epidemiologia , Pandemias , Pneumonia Viral/epidemiologia , Medição de Risco/métodos , Causas de Morte/tendências , Comorbidade , Saúde Global , Humanos , Taxa de Sobrevida/tendências
20.
Int J Med Sci ; 17(15): 2257-2263, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-32922189

RESUMO

Background: Corona Virus Disease 2019 (COVID-19) has become a global pandemic. This study established prognostic scoring models based on comorbidities and other clinical information for severe and critical patients with COVID-19. Material and Methods: We retrospectively collected data from 51 patients diagnosed as severe or critical COVID-19 who were admitted between January 29, 2020, and February 18, 2020. The Charlson (CCI), Elixhauser (ECI), and age- and smoking-adjusted Charlson (ASCCI) and Elixhauser (ASECI) comorbidity indices were used to evaluate the patient outcomes. Results: The mean hospital length of stay (LOS) of the COVID-19 patients was 22.82 ± 12.32 days; 19 patients (37.3%) were hospitalized for more than 24 days. Multivariate analysis identified older age (OR 1.064, P = 0.018, 95%CI 1.011-1.121) and smoking (OR 3.696, P = 0.080, 95%CI 0.856-15.955) as positive predictors of a long LOS. There were significant trends for increasing hospital LOS with increasing CCI, ASCCI, and ASECI scores (OR 57.500, P = 0.001, 95%CI 5.687-581.399; OR 71.500, P = 0.001, 95%CI 5.689-898.642; and OR 19.556, P = 0.001, 95%CI 3.315-115.372, respectively). The result was similar for the outcome of critical illness (OR 21.333, P = 0.001, 95%CI 3.565-127.672; OR 13.000, P = 0.009, 95%CI 1.921-87.990; OR 11.333, P = 0.008, 95%CI 1.859-69.080, respectively). Conclusions: This study established prognostic scoring models based on comorbidities and clinical information, which may help with the graded management of patients according to prognosis score and remind physicians to pay more attention to patients with high scores.


Assuntos
Comorbidade , Infecções por Coronavirus/mortalidade , Estado Terminal/mortalidade , Modelos Estatísticos , Pneumonia Viral/mortalidade , Índice de Gravidade de Doença , Adulto , Idoso , Idoso de 80 Anos ou mais , Betacoronavirus/isolamento & purificação , Betacoronavirus/patogenicidade , Tomada de Decisão Clínica , Infecções por Coronavirus/diagnóstico , Infecções por Coronavirus/terapia , Infecções por Coronavirus/virologia , Feminino , Mortalidade Hospitalar , Humanos , Tempo de Internação/estatística & dados numéricos , Masculino , Pessoa de Meia-Idade , Pandemias , Pneumonia Viral/diagnóstico , Pneumonia Viral/terapia , Pneumonia Viral/virologia , Prognóstico , Estudos Retrospectivos , Medição de Risco/métodos
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