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1.
JCO Glob Oncol ; 7: 46-55, 2021 01.
Artigo em Inglês | MEDLINE | ID: mdl-33434066

RESUMO

PURPOSE: The COVID-19 pandemic remains a public health emergency of global concern. Determinants of mortality in the general population are now clear, but specific data on patients with cancer remain limited, particularly in Latin America. MATERIALS AND METHODS: A longitudinal multicenter cohort study of patients with cancer and confirmed COVID-19 from Oncoclínicas community oncology practice in Brazil was conducted. The primary end point was all-cause mortality after isolation of the SARS-CoV-2 by Real-Time Polymerase Chain Reaction (RT-PCR) in patients initially diagnosed in an outpatient environment. We performed univariate and multivariable logistic regression analysis and recursive partitioning modeling to define the baseline clinical determinants of death in the overall population. RESULTS: From March 29 to July 4, 2020, 198 patients with COVID-19 were prospectively registered in the database, of which 167 (84%) had solid tumors and 31 (16%) had hematologic malignancies. Most patients were on active systemic therapy or radiotherapy (77%), largely for advanced or metastatic disease (64%). The overall mortality rate was 16.7% (95% CI, 11.9 to 22.7). In univariate models, factors associated with death after COVID-19 diagnosis were age ≥ 60 years, current or former smoking, coexisting comorbidities, respiratory tract cancer, and management in a noncurative setting (P < .05). In multivariable logistic regression and recursive partitioning modeling, only age, smoking history, and noncurative disease setting remained significant determinants of mortality, ranging from 1% in cancer survivors under surveillance or (neo)adjuvant therapy to 60% in elderly smokers with advanced or metastatic disease. CONCLUSION: Mortality after COVID-19 in patients with cancer is influenced by prognostic factors that also affect outcomes of the general population. Fragile patients and smokers are entitled to active preventive measures to reduce the risk of SARS-CoV-2 infection and close monitoring in the case of exposure or COVID-19-related symptoms.


Assuntos
/mortalidade , Sobreviventes de Câncer/estatística & dados numéricos , Neoplasias/mortalidade , /isolamento & purificação , Adulto , Idoso , Idoso de 80 Anos ou mais , Brasil/epidemiologia , /virologia , Causas de Morte , Bases de Dados Factuais/estatística & dados numéricos , Feminino , Fragilidade/epidemiologia , Humanos , Estudos Longitudinais , Masculino , Oncologia/estatística & dados numéricos , Pessoa de Meia-Idade , Neoplasias/complicações , Prognóstico , Estudos Prospectivos , RNA Viral/isolamento & purificação , Medição de Risco/estatística & dados numéricos , Fatores de Risco , Fumar/epidemiologia , Adulto Jovem
2.
J Med Libr Assoc ; 109(1): 75-83, 2021 Jan 01.
Artigo em Inglês | MEDLINE | ID: mdl-33424467

RESUMO

Objective: There are concerns about nonscientific and/or unclear information on the coronavirus disease 2019 (COVID-19) that is available on the Internet. Furthermore, people's ability to understand health information varies and depends on their skills in reading and interpreting information. This study aims to evaluate the readability and creditability of websites with COVID-19-related information. Methods: The search terms "coronavirus," "COVID," and "COVID-19" were input into Google. The websites of the first thirty results for each search term were evaluated in terms of their credibility and readability using the Health On the Net Foundation code of conduct (HONcode) and Flesch-Kincaid Grade Level (FKGL), Simple Measure of Gobbledygook (SMOG), Gunning Fog, and Flesch Reading Ease Score (FRE) scales, respectively. Results: The readability of COVID-19-related health information on websites was suitable for high school graduates or college students and, thus, was far above the recommended readability level. Most websites that were examined (87.2%) had not been officially certified by HONcode. There was no significant difference in the readability scores of websites with and without HONcode certification. Conclusion: These results suggest that organizations should improve the readability of their websites and provide information that more people can understand. This could lead to greater health literacy, less health anxiety, and the provision of better preventive information about the disease.


Assuntos
/enfermagem , Compreensão , Informação de Saúde ao Consumidor/métodos , Confiabilidade dos Dados , Bases de Dados Factuais/estatística & dados numéricos , Letramento em Saúde/métodos , Internet , Autocuidado/métodos , Adulto , Idoso , Idoso de 80 Anos ou mais , Feminino , Humanos , Masculino , Pessoa de Meia-Idade
3.
J Surg Res ; 257: 161-166, 2021 01.
Artigo em Inglês | MEDLINE | ID: mdl-32829000

RESUMO

BACKGROUND: Full-thickness chest wall resection (FTCWR) is an underused modality for treating locally advanced primary or recurrent breast cancer invading the chest wall, for which little data exist regarding morbidity and mortality. We examined the postoperative complication rates in breast cancer patients undergoing FTCWR using a large multinational surgical outcomes database. METHODS: A retrospective cohort analysis was conducted using the American College of Surgeons National Surgical Quality Improvement Program database. All patients undergoing FTCWR for breast cancer between 2007 and 2016 were identified (n = 137). Primary outcome measures included 30-d postoperative morbidity, composite respiratory complications, and hospital length of stay (LOS). The secondary aim was to compare the postoperative morbidity of FTCWR to those of patients undergoing mastectomy. One-to-one coarsened exact matching was conducted between two groups, which were then compared with respect to morbidity, mortality, reoperations, readmissions, and LOS. RESULTS: The overall rate of postoperative morbidity was 11.7%. Two patients (1.5%) had respiratory complications requiring intubation. Median hospital LOS was 2 d. In the coarsened exact matching analysis, 122 patients were included in each of the two groups. Comparison of matched cohorts demonstrated an overall morbidity for the FTCWR group of 11.5% compared with 8.2% for the mastectomy group (8.2%) (P = 0.52). CONCLUSIONS: FTCWR for the local treatment of breast cancer can be performed with relatively low morbidity and respiratory complications. This is the largest study looking at postoperative complications for FTCWR in the treatment of breast cancer. Future studies are needed to determine the long-term outcomes of FTCWR in this patient population.


Assuntos
Neoplasias da Mama/cirurgia , Mastectomia/efeitos adversos , Recidiva Local de Neoplasia/cirurgia , Complicações Pós-Operatórias/epidemiologia , Parede Torácica/cirurgia , Idoso , Neoplasias da Mama/patologia , Bases de Dados Factuais/estatística & dados numéricos , Feminino , Humanos , Tempo de Internação/estatística & dados numéricos , Mastectomia/métodos , Pessoa de Meia-Idade , Invasividade Neoplásica , Recidiva Local de Neoplasia/patologia , Complicações Pós-Operatórias/etiologia , Estudos Prospectivos , Reoperação/efeitos adversos , Reoperação/métodos , Estudos Retrospectivos , Parede Torácica/patologia , Estados Unidos/epidemiologia
4.
JAMA Netw Open ; 3(12): e2030072, 2020 12 01.
Artigo em Inglês | MEDLINE | ID: mdl-33315115

RESUMO

Importance: Resource limitations because of pandemic or other stresses on infrastructure necessitate the triage of time-sensitive care, including cancer treatments. Optimal time to treatment is underexplored, so recommendations for which cancer treatments can be deferred are often based on expert opinion. Objective: To evaluate the association between increased time to definitive therapy and mortality as a function of cancer type and stage for the 4 most prevalent cancers in the US. Design, Setting, and Participants: This cohort study assessed treatment and outcome information from patients with nonmetastatic breast, prostate, non-small cell lung (NSCLC), and colon cancers from 2004 to 2015, with data analyzed January to March 2020. Data on outcomes associated with appropriate curative-intent surgical, radiation, or medical therapy were gathered from the National Cancer Database. Exposures: Time-to-treatment initiation (TTI), the interval between diagnosis and therapy, using intervals of 8 to 60, 61 to 120, 121 to 180, and greater than 180 days. Main Outcomes and Measures: 5-year and 10-year predicted all-cause mortality. Results: This study included 2 241 706 patients (mean [SD] age 63 [11.9] years, 1 268 794 [56.6%] women, 1 880 317 [83.9%] White): 1 165 585 (52.0%) with breast cancer, 853 030 (38.1%) with prostate cancer, 130 597 (5.8%) with NSCLC, and 92 494 (4.1%) with colon cancer. Median (interquartile range) TTI by cancer was 32 (21-48) days for breast, 79 (55-117) days for prostate, 41 (27-62) days for NSCLC, and 26 (16-40) days for colon. Across all cancers, a general increase in the 5-year and 10-year predicted mortality was associated with increasing TTI. The most pronounced mortality association was for colon cancer (eg, 5 y predicted mortality, stage III: TTI 61-120 d, 38.9% vs. 181-365 d, 47.8%), followed by stage I NSCLC (5 y predicted mortality: TTI 61-120 d, 47.4% vs 181-365 d, 47.6%), while survival for prostate cancer was least associated (eg, 5 y predicted mortality, high risk: TTI 61-120 d, 12.8% vs 181-365 d, 14.1%), followed by breast cancer (eg, 5 y predicted mortality, stage I: TTI 61-120 d, 11.0% vs. 181-365 d, 15.2%). A nonsignificant difference in treatment delays and worsened survival was observed for stage II lung cancer patients-who had the highest all-cause mortality for any TTI regardless of treatment timing. Conclusions and Relevance: In this cohort study, for all studied cancers there was evidence that shorter TTI was associated with lower mortality, suggesting an indirect association between treatment deferral and mortality that may not become evident for years. In contrast to current pandemic-related guidelines, these findings support more timely definitive treatment for intermediate-risk and high-risk prostate cancer.


Assuntos
Protocolos Antineoplásicos , Neoplasias da Mama , Neoplasias do Colo , Neoplasias Pulmonares , Neoplasias da Próstata , Tempo para o Tratamento , Idoso , Neoplasias da Mama/mortalidade , Neoplasias da Mama/patologia , Neoplasias da Mama/terapia , /prevenção & controle , Estudos de Coortes , Neoplasias do Colo/mortalidade , Neoplasias do Colo/patologia , Neoplasias do Colo/terapia , Bases de Dados Factuais/estatística & dados numéricos , Feminino , Humanos , Neoplasias Pulmonares/mortalidade , Neoplasias Pulmonares/patologia , Neoplasias Pulmonares/terapia , Masculino , Pessoa de Meia-Idade , Mortalidade , Estadiamento de Neoplasias , Prognóstico , Neoplasias da Próstata/mortalidade , Neoplasias da Próstata/patologia , Neoplasias da Próstata/terapia , Tempo para o Tratamento/normas , Tempo para o Tratamento/estatística & dados numéricos , Estados Unidos/epidemiologia
5.
JAMA ; 324(16): 1640-1650, 2020 10 27.
Artigo em Inglês | MEDLINE | ID: mdl-33107944

RESUMO

Importance: Current guidelines recommend ticagrelor as the preferred P2Y12 platelet inhibitor for patients with acute coronary syndrome (ACS), primarily based on a single large randomized clinical trial. The benefits and risks associated with ticagrelor vs clopidogrel in routine practice merits attention. Objective: To determine the association of ticagrelor vs clopidogrel with ischemic and hemorrhagic events in patients undergoing percutaneous coronary intervention (PCI) for ACS in clinical practice. Design, Setting, and Participants: A retrospective cohort study of patients with ACS who underwent PCI and received ticagrelor or clopidogrel was conducted using 2 United States electronic health record-based databases and 1 nationwide South Korean database from November 2011 to March 2019. Patients were matched using a large-scale propensity score algorithm, and the date of final follow-up was March 2019. Exposures: Ticagrelor vs clopidogrel. Main Outcomes and Measures: The primary end point was net adverse clinical events (NACE) at 12 months, composed of ischemic events (recurrent myocardial infarction, revascularization, or ischemic stroke) and hemorrhagic events (hemorrhagic stroke or gastrointestinal bleeding). Secondary outcomes included NACE or mortality, all-cause mortality, ischemic events, hemorrhagic events, individual components of the primary outcome, and dyspnea at 12 months. The database-level hazard ratios (HRs) were pooled to calculate summary HRs by random-effects meta-analysis. Results: After propensity score matching among 31 290 propensity-matched pairs (median age group, 60-64 years; 29.3% women), 95.5% of patients took aspirin together with ticagrelor or clopidogrel. The 1-year risk of NACE was not significantly different between ticagrelor and clopidogrel (15.1% [3484/23 116 person-years] vs 14.6% [3290/22 587 person-years]; summary HR, 1.05 [95% CI, 1.00-1.10]; P = .06). There was also no significant difference in the risk of all-cause mortality (2.0% for ticagrelor vs 2.1% for clopidogrel; summary HR, 0.97 [95% CI, 0.81-1.16]; P = .74) or ischemic events (13.5% for ticagrelor vs 13.4% for clopidogrel; summary HR, 1.03 [95% CI, 0.98-1.08]; P = .32). The risks of hemorrhagic events (2.1% for ticagrelor vs 1.6% for clopidogrel; summary HR, 1.35 [95% CI, 1.13-1.61]; P = .001) and dyspnea (27.3% for ticagrelor vs 22.6% for clopidogrel; summary HR, 1.21 [95% CI, 1.17-1.26]; P < .001) were significantly higher in the ticagrelor group. Conclusions and Relevance: Among patients with ACS who underwent PCI in routine clinical practice, ticagrelor, compared with clopidogrel, was not associated with significant difference in the risk of NACE at 12 months. Because the possibility of unmeasured confounders cannot be excluded, further research is needed to determine whether ticagrelor is more effective than clopidogrel in this setting.


Assuntos
Síndrome Coronariana Aguda/cirurgia , Clopidogrel/efeitos adversos , Intervenção Coronária Percutânea , Antagonistas do Receptor Purinérgico P2Y/efeitos adversos , Ticagrelor/efeitos adversos , Síndrome Coronariana Aguda/mortalidade , Adulto , Idoso , Idoso de 80 Anos ou mais , Algoritmos , Aspirina/administração & dosagem , Estudos de Casos e Controles , Causas de Morte , Clopidogrel/administração & dosagem , Bases de Dados Factuais/estatística & dados numéricos , Dispneia/induzido quimicamente , Feminino , Hemorragia/induzido quimicamente , Humanos , Isquemia/induzido quimicamente , Masculino , Pessoa de Meia-Idade , Infarto do Miocárdio/epidemiologia , Metanálise em Rede , Pontuação de Propensão , Antagonistas do Receptor Purinérgico P2Y/administração & dosagem , Recidiva , República da Coreia , Estudos Retrospectivos , Acidente Vascular Cerebral/epidemiologia , Ticagrelor/administração & dosagem , Estados Unidos
6.
BMJ ; 371: m3731, 2020 10 20.
Artigo em Inglês | MEDLINE | ID: mdl-33082154

RESUMO

OBJECTIVE: To derive and validate a risk prediction algorithm to estimate hospital admission and mortality outcomes from coronavirus disease 2019 (covid-19) in adults. DESIGN: Population based cohort study. SETTING AND PARTICIPANTS: QResearch database, comprising 1205 general practices in England with linkage to covid-19 test results, Hospital Episode Statistics, and death registry data. 6.08 million adults aged 19-100 years were included in the derivation dataset and 2.17 million in the validation dataset. The derivation and first validation cohort period was 24 January 2020 to 30 April 2020. The second temporal validation cohort covered the period 1 May 2020 to 30 June 2020. MAIN OUTCOME MEASURES: The primary outcome was time to death from covid-19, defined as death due to confirmed or suspected covid-19 as per the death certification or death occurring in a person with confirmed severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in the period 24 January to 30 April 2020. The secondary outcome was time to hospital admission with confirmed SARS-CoV-2 infection. Models were fitted in the derivation cohort to derive risk equations using a range of predictor variables. Performance, including measures of discrimination and calibration, was evaluated in each validation time period. RESULTS: 4384 deaths from covid-19 occurred in the derivation cohort during follow-up and 1722 in the first validation cohort period and 621 in the second validation cohort period. The final risk algorithms included age, ethnicity, deprivation, body mass index, and a range of comorbidities. The algorithm had good calibration in the first validation cohort. For deaths from covid-19 in men, it explained 73.1% (95% confidence interval 71.9% to 74.3%) of the variation in time to death (R2); the D statistic was 3.37 (95% confidence interval 3.27 to 3.47), and Harrell's C was 0.928 (0.919 to 0.938). Similar results were obtained for women, for both outcomes, and in both time periods. In the top 5% of patients with the highest predicted risks of death, the sensitivity for identifying deaths within 97 days was 75.7%. People in the top 20% of predicted risk of death accounted for 94% of all deaths from covid-19. CONCLUSION: The QCOVID population based risk algorithm performed well, showing very high levels of discrimination for deaths and hospital admissions due to covid-19. The absolute risks presented, however, will change over time in line with the prevailing SARS-C0V-2 infection rate and the extent of social distancing measures in place, so they should be interpreted with caution. The model can be recalibrated for different time periods, however, and has the potential to be dynamically updated as the pandemic evolves.


Assuntos
Algoritmos , Regras de Decisão Clínica , Infecções por Coronavirus , Hospitalização/estatística & dados numéricos , Mortalidade , Pandemias , Pneumonia Viral , Medição de Risco , Adulto , Idoso de 80 Anos ou mais , Betacoronavirus/isolamento & purificação , Estudos de Coortes , Infecções por Coronavirus/mortalidade , Infecções por Coronavirus/terapia , Bases de Dados Factuais/estatística & dados numéricos , Inglaterra/epidemiologia , Feminino , Humanos , Masculino , Pneumonia Viral/mortalidade , Pneumonia Viral/terapia , Prognóstico , Reprodutibilidade dos Testes , Medição de Risco/métodos , Medição de Risco/normas
7.
Pediatrics ; 146(5)2020 11.
Artigo em Inglês | MEDLINE | ID: mdl-33082284

RESUMO

BACKGROUND AND OBJECTIVES: Road traffic accidents are a leading cause of child deaths in the United States. Although this has been examined at the national and state levels, there is more value in acquiring information at the county level to guide local policies. We aimed to estimate county-specific child mortality from road traffic accidents in the United States. METHODS: We queried the Fatality Analysis Reporting System database, 2010-2017, for road traffic accidents that resulted in a death within 30 days of the auto crash. We included all children <15 years old who were fatally injured. We estimated county-specific age- and sex-standardized mortality. We evaluated the impact of the availability of trauma centers and urban-rural classification of counties on mortality. RESULTS: We included 9271 child deaths. Among those, 45% died at the scene. The median age was 7 years. The overall mortality was 1.87 deaths per 100 000 children. County-specific mortality ranged between 0.25 and 21.91 deaths per 100 000 children. The availability of a trauma center in a county was associated with decreased mortality (adult trauma center [odds ratio (OR): 0.59; 95% credibility interval (CI), 0.52-0.66]; pediatric trauma center [OR: 0.56; 95% CI, 0.46-0.67]). Less urbanized counties were associated with higher mortality, compared with large central metropolitan counties (noncore counties [OR: 2.33; 95% CI, 1.85-2.91]). CONCLUSIONS: There are marked differences in child mortality from road traffic accidents among US counties. Our findings can guide targeted public health interventions in high-risk counties with excessive child mortality and limited access to trauma care.


Assuntos
Acidentes de Trânsito/mortalidade , Mortalidade da Criança , Centros de Traumatologia/provisão & distribução , Adolescente , Teorema de Bayes , Criança , Pré-Escolar , Bases de Dados Factuais/estatística & dados numéricos , Escolaridade , Feminino , Humanos , Renda , Governo Local , Masculino , Razão de Chances , Distribuição de Poisson , População Rural/estatística & dados numéricos , Distribuição por Sexo , Análise de Pequenas Áreas , Centros de Traumatologia/classificação , Estados Unidos/epidemiologia , População Urbana/estatística & dados numéricos
8.
Artigo em Inglês | MEDLINE | ID: mdl-32872616

RESUMO

This study used the Korean National Health Insurance (NHI) claims database from 2011 to 2017 to estimate the incidence and the incidence-based cost of cervical cancer and carcinoma in situ of cervix uteri (CIS) in Korea. The primary outcome was the direct medical cost per patient not diagnosed with cervical cancer (C53) or CIS (D06) 2 years prior to the index date in the first year after diagnosis. A regression analysis was conducted to adjust for relevant covariates. The incidence of cervical cancer tended to decrease from 2013 to 2016, while that of CIS increased. In particular, the incidence rate of CIS in women in their 20 s and 30 s increased by 56.8% and 28.4%, respectively, from 2013 to 2016. The incidence-based cost of cervical cancer and CIS was USD 13,058 and USD 2695 in 2016, respectively, which increased from 2013. Multivariate regression analysis suggested that age was the most influential variable of the cost in both patient groups, and the cost was highest in those aged over 60, i.e., the medical cost was significantly lower in younger women than their older counterparts. These findings suggest that targeting younger women in cervical cancer prevention is a reasonable option from both economic and public health perspectives.


Assuntos
Custos de Cuidados de Saúde/estatística & dados numéricos , Neoplasias do Colo do Útero , Adulto , Fatores Etários , Carcinoma in Situ/economia , Carcinoma in Situ/epidemiologia , Efeitos Psicossociais da Doença , Bases de Dados Factuais/estatística & dados numéricos , Feminino , Humanos , Incidência , Pessoa de Meia-Idade , Programas Nacionais de Saúde/economia , Programas Nacionais de Saúde/estatística & dados numéricos , Lesões Pré-Cancerosas/economia , Lesões Pré-Cancerosas/epidemiologia , República da Coreia/epidemiologia , Projetos de Pesquisa , Neoplasias do Colo do Útero/economia , Neoplasias do Colo do Útero/epidemiologia , Adulto Jovem
9.
IEEE J Biomed Health Inform ; 24(10): 2806-2813, 2020 10.
Artigo em Inglês | MEDLINE | ID: mdl-32915751

RESUMO

The pandemic of coronavirus disease 2019 (COVID-19) has lead to a global public health crisis spreading hundreds of countries. With the continuous growth of new infections, developing automated tools for COVID-19 identification with CT image is highly desired to assist the clinical diagnosis and reduce the tedious workload of image interpretation. To enlarge the datasets for developing machine learning methods, it is essentially helpful to aggregate the cases from different medical systems for learning robust and generalizable models. This paper proposes a novel joint learning framework to perform accurate COVID-19 identification by effectively learning with heterogeneous datasets with distribution discrepancy. We build a powerful backbone by redesigning the recently proposed COVID-Net in aspects of network architecture and learning strategy to improve the prediction accuracy and learning efficiency. On top of our improved backbone, we further explicitly tackle the cross-site domain shift by conducting separate feature normalization in latent space. Moreover, we propose to use a contrastive training objective to enhance the domain invariance of semantic embeddings for boosting the classification performance on each dataset. We develop and evaluate our method with two public large-scale COVID-19 diagnosis datasets made up of CT images. Extensive experiments show that our approach consistently improves the performanceson both datasets, outperforming the original COVID-Net trained on each dataset by 12.16% and 14.23% in AUC respectively, also exceeding existing state-of-the-art multi-site learning methods.


Assuntos
Betacoronavirus , Técnicas de Laboratório Clínico/estatística & dados numéricos , Infecções por Coronavirus/diagnóstico por imagem , Infecções por Coronavirus/diagnóstico , Aprendizado Profundo , Pandemias , Pneumonia Viral/diagnóstico por imagem , Pneumonia Viral/diagnóstico , Tomografia Computadorizada por Raios X/estatística & dados numéricos , Biologia Computacional , Sistemas Computacionais , Infecções por Coronavirus/classificação , Bases de Dados Factuais/estatística & dados numéricos , Humanos , Aprendizado de Máquina , Pandemias/classificação , Pneumonia Viral/classificação , Interpretação de Imagem Radiográfica Assistida por Computador/estatística & dados numéricos
10.
IEEE J Biomed Health Inform ; 24(10): 2776-2786, 2020 10.
Artigo em Inglês | MEDLINE | ID: mdl-32750973

RESUMO

Fast and accurate diagnosis is essential for the efficient and effective control of the COVID-19 pandemic that is currently disrupting the whole world. Despite the prevalence of the COVID-19 outbreak, relatively few diagnostic images are openly available to develop automatic diagnosis algorithms. Traditional deep learning methods often struggle when data is highly unbalanced with many cases in one class and only a few cases in another; new methods must be developed to overcome this challenge. We propose a novel activation function based on the generalized extreme value (GEV) distribution from extreme value theory, which improves performance over the traditional sigmoid activation function when one class significantly outweighs the other. We demonstrate the proposed activation function on a publicly available dataset and externally validate on a dataset consisting of 1,909 healthy chest X-rays and 84 COVID-19 X-rays. The proposed method achieves an improved area under the receiver operating characteristic (DeLong's p-value < 0.05) compared to the sigmoid activation. Our method is also demonstrated on a dataset of healthy and pneumonia vs. COVID-19 X-rays and a set of computerized tomography images, achieving improved sensitivity. The proposed GEV activation function significantly improves upon the previously used sigmoid activation for binary classification. This new paradigm is expected to play a significant role in the fight against COVID-19 and other diseases, with relatively few training cases available.


Assuntos
Algoritmos , Betacoronavirus , Técnicas de Laboratório Clínico/métodos , Infecções por Coronavirus/diagnóstico , Pandemias , Pneumonia Viral/diagnóstico , Teorema de Bayes , Técnicas de Laboratório Clínico/estatística & dados numéricos , Biologia Computacional , Infecções por Coronavirus/diagnóstico por imagem , Infecções por Coronavirus/epidemiologia , Bases de Dados Factuais/estatística & dados numéricos , Aprendizado Profundo , Humanos , Redes Neurais de Computação , Pneumonia Viral/diagnóstico por imagem , Pneumonia Viral/epidemiologia , Interpretação de Imagem Radiográfica Assistida por Computador/métodos , Tomografia Computadorizada por Raios X/estatística & dados numéricos
11.
BMJ ; 370: m2980, 2020 07 30.
Artigo em Inglês | MEDLINE | ID: mdl-32732190

RESUMO

OBJECTIVE: To compare the effects of treatments for coronavirus disease 2019 (covid-19). DESIGN: Living systematic review and network meta-analysis. DATA SOURCES: US Centers for Disease Control and Prevention COVID-19 Research Articles Downloadable Database, which includes 25 electronic databases and six additional Chinese databases to 20 July 2020. STUDY SELECTION: Randomised clinical trials in which people with suspected, probable, or confirmed covid-19 were randomised to drug treatment or to standard care or placebo. Pairs of reviewers independently screened potentially eligible articles. METHODS: After duplicate data abstraction, a bayesian random effects network meta-analysis was conducted. Risk of bias of the included studies was assessed using a modification of the Cochrane risk of bias 2.0 tool, and the certainty of the evidence using the grading of recommendations assessment, development and evaluation (GRADE) approach. For each outcome, interventions were classified in groups from the most to the least beneficial or harmful following GRADE guidance. RESULTS: 23 randomised controlled trials were included in the analysis performed on 26 June 2020. The certainty of the evidence for most comparisons was very low because of risk of bias (lack of blinding) and serious imprecision. Glucocorticoids were the only intervention with evidence for a reduction in death compared with standard care (risk difference 37 fewer per 1000 patients, 95% credible interval 63 fewer to 11 fewer, moderate certainty) and mechanical ventilation (31 fewer per 1000 patients, 47 fewer to 9 fewer, moderate certainty). These estimates are based on direct evidence; network estimates for glucocorticoids compared with standard care were less precise because of network heterogeneity. Three drugs might reduce symptom duration compared with standard care: hydroxychloroquine (mean difference -4.5 days, low certainty), remdesivir (-2.6 days, moderate certainty), and lopinavir-ritonavir (-1.2 days, low certainty). Hydroxychloroquine might increase the risk of adverse events compared with the other interventions, and remdesivir probably does not substantially increase the risk of adverse effects leading to drug discontinuation. No other interventions included enough patients to meaningfully interpret adverse effects leading to drug discontinuation. CONCLUSION: Glucocorticoids probably reduce mortality and mechanical ventilation in patients with covid-19 compared with standard care. The effectiveness of most interventions is uncertain because most of the randomised controlled trials so far have been small and have important study limitations. SYSTEMATIC REVIEW REGISTRATION: This review was not registered. The protocol is included as a supplement. READERS' NOTE: This article is a living systematic review that will be updated to reflect emerging evidence. Updates may occur for up to two years from the date of original publication.


Assuntos
Antivirais/uso terapêutico , Betacoronavirus/isolamento & purificação , Infecções por Coronavirus/terapia , Pneumonia Viral/terapia , Respiração Artificial/estatística & dados numéricos , Monofosfato de Adenosina/análogos & derivados , Monofosfato de Adenosina/uso terapêutico , Alanina/análogos & derivados , Alanina/uso terapêutico , Betacoronavirus/patogenicidade , Centers for Disease Control and Prevention, U.S./estatística & dados numéricos , China/epidemiologia , Infecções por Coronavirus/diagnóstico , Infecções por Coronavirus/tratamento farmacológico , Infecções por Coronavirus/mortalidade , Infecções por Coronavirus/virologia , Bases de Dados Factuais/estatística & dados numéricos , Combinação de Medicamentos , Medicina Baseada em Evidências/métodos , Medicina Baseada em Evidências/estatística & dados numéricos , Glucocorticoides/uso terapêutico , Humanos , Hidroxicloroquina/uso terapêutico , Lopinavir/uso terapêutico , Metanálise em Rede , Pandemias , Pneumonia Viral/diagnóstico , Pneumonia Viral/mortalidade , Pneumonia Viral/virologia , Ensaios Clínicos Controlados Aleatórios como Assunto , Ritonavir/uso terapêutico , Índice de Gravidade de Doença , Padrão de Cuidado , Resultado do Tratamento , Estados Unidos/epidemiologia
12.
IEEE J Biomed Health Inform ; 24(10): 2798-2805, 2020 10.
Artigo em Inglês | MEDLINE | ID: mdl-32845849

RESUMO

Chest computed tomography (CT) becomes an effective tool to assist the diagnosis of coronavirus disease-19 (COVID-19). Due to the outbreak of COVID-19 worldwide, using the computed-aided diagnosis technique for COVID-19 classification based on CT images could largely alleviate the burden of clinicians. In this paper, we propose an Adaptive Feature Selection guided Deep Forest (AFS-DF) for COVID-19 classification based on chest CT images. Specifically, we first extract location-specific features from CT images. Then, in order to capture the high-level representation of these features with the relatively small-scale data, we leverage a deep forest model to learn high-level representation of the features. Moreover, we propose a feature selection method based on the trained deep forest model to reduce the redundancy of features, where the feature selection could be adaptively incorporated with the COVID-19 classification model. We evaluated our proposed AFS-DF on COVID-19 dataset with 1495 patients of COVID-19 and 1027 patients of community acquired pneumonia (CAP). The accuracy (ACC), sensitivity (SEN), specificity (SPE), AUC, precision and F1-score achieved by our method are 91.79%, 93.05%, 89.95%, 96.35%, 93.10% and 93.07%, respectively. Experimental results on the COVID-19 dataset suggest that the proposed AFS-DF achieves superior performance in COVID-19 vs. CAP classification, compared with 4 widely used machine learning methods.


Assuntos
Betacoronavirus , Técnicas de Laboratório Clínico/estatística & dados numéricos , Infecções por Coronavirus/diagnóstico por imagem , Infecções por Coronavirus/diagnóstico , Pneumonia Viral/diagnóstico por imagem , Pneumonia Viral/diagnóstico , Tomografia Computadorizada por Raios X/estatística & dados numéricos , Biologia Computacional , Infecções por Coronavirus/classificação , Bases de Dados Factuais/estatística & dados numéricos , Aprendizado Profundo , Humanos , Redes Neurais de Computação , Pandemias/classificação , Pneumonia Viral/classificação , Interpretação de Imagem Radiográfica Assistida por Computador/estatística & dados numéricos , Radiografia Torácica/estatística & dados numéricos
13.
PLoS Comput Biol ; 16(7): e1007897, 2020 07.
Artigo em Inglês | MEDLINE | ID: mdl-32645081

RESUMO

Network-based intervention strategies can be effective and cost-efficient approaches to curtailing harmful contagions in myriad settings. As studied, these strategies are often impractical to implement, as they typically assume complete knowledge of the network structure, which is unusual in practice. In this paper, we investigate how different immunization strategies perform under realistic conditions-where the strategies are informed by partially-observed network data. Our results suggest that global immunization strategies, like degree immunization, are optimal in most cases; the exception is at very high levels of missing data, where stochastic strategies, like acquaintance immunization, begin to outstrip them in minimizing outbreaks. Stochastic strategies are more robust in some cases due to the different ways in which they can be affected by missing data. In fact, one of our proposed variants of acquaintance immunization leverages a logistically-realistic ongoing survey-intervention process as a form of targeted data-recovery to improve with increasing levels of missing data. These results support the effectiveness of targeted immunization as a general practice. They also highlight the risks of considering networks as idealized mathematical objects: overestimating the accuracy of network data and foregoing the rewards of additional inquiry.


Assuntos
Bases de Dados Factuais , Epidemias , Imunização , Algoritmos , Biologia Computacional , Simulação por Computador , Coleta de Dados , Bases de Dados Factuais/normas , Bases de Dados Factuais/estatística & dados numéricos , Epidemias/prevenção & controle , Epidemias/estatística & dados numéricos , Saúde Global , Humanos , Imunização/métodos , Imunização/estatística & dados numéricos
14.
J Shoulder Elbow Surg ; 29(7S): S115-S125, 2020 Jul.
Artigo em Inglês | MEDLINE | ID: mdl-32646593

RESUMO

BACKGROUND: Prescription opioids are standard of care for postoperative pain management after musculoskeletal surgery, but there is no guideline or consensus on best practices. Variability in the intensity of opioids prescribed for postoperative recovery has been documented, but it is unclear whether this variability is clinically motivated or associated with provider practice patterns, or how this variation is associated with patient outcomes. This study described variation in the intensity of opioids prescribed for patients undergoing rotator cuff repair (RCR) and examined associations with provider prescribing patterns and patients' long-term opioid use outcomes. METHODS: Medicare data from 2010 to 2012 were used to identify 16,043 RCRs for patients with new shoulder complaints in 2011. Two measures of perioperative opioid use were created: (1) any opioid fill occurring 3 days before to 7 days after RCR and (2) total morphine milligram equivalents (MMEs) of all opioid fills during that period. Patient outcomes for persistent opioid use after RCR included (1) any opioid fill from 90 to 180 days after RCR and (2) the lack of any 30-day gap in opioid availability during that period. Generalized linear regression models were used to estimate associations between provider characteristics and opioid use for RCR, and between opioid use and outcomes. All models adjusted for patient clinical and demographic characteristics. Separate analyses were done for patients with and without opioid use in the 180 days before RCR. RESULTS: In this sample, 54% of patients undergoing RCR were opioid naive at the time of RCR. Relative to prior users, a greater proportion of opioid naive users had any opioid fill (85.7% vs. 75.4%), but prior users received more MMEs than naive users (565 vs. 451 MMEs). Providers' opioid prescribing for other patients was associated with the intensity of perioperative opioids received for RCR. Total MMEs received for RCR were associated with higher odds of persistent opioid use 90-180 days after RCR. CONCLUSIONS: The intensity of opioids received by patients for postoperative pain appears to be partially determined by the prescribing habits of their providers. Greater intensity of opioids received is, in turn, associated with greater odds of patterns of chronic opioid use after surgery. More comprehensive, patient-centered guidance on opioid prescribing is needed to help surgeons provide optimal postoperative pain management plans, balancing needs for short-term symptom relief and risks for long-term outcomes.


Assuntos
Analgésicos Opioides/uso terapêutico , Prescrições de Medicamentos/estatística & dados numéricos , Transtornos Relacionados ao Uso de Opioides/epidemiologia , Cirurgiões Ortopédicos/estatística & dados numéricos , Dor Pós-Operatória/tratamento farmacológico , Padrões de Prática Médica/estatística & dados numéricos , Lesões do Manguito Rotador/cirurgia , Idoso , Analgésicos Opioides/efeitos adversos , Artroplastia/estatística & dados numéricos , Bases de Dados Factuais/estatística & dados numéricos , Feminino , Humanos , Masculino , Medicare/estatística & dados numéricos , Pessoa de Meia-Idade , Transtornos Relacionados ao Uso de Opioides/etiologia , Dor Pós-Operatória/epidemiologia , Estudos Retrospectivos , Lesões do Manguito Rotador/epidemiologia , Estados Unidos/epidemiologia
15.
PLoS One ; 15(7): e0235714, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-32628718

RESUMO

BACKGROUND: Peptic ulcer is a widespread disease, frequently complicated by perforation and bleeding. Administrative databases are useful tool to perform epidemiological and drug utilization studies, but they need a validation process based on a comparison with the original data contained in the medical charts. Our aim was to evaluate the accuracy of the ICD-9 codes in identifying patients with peptic ulcer and gastrointestinal hemorrhage in the regional administrative database of Umbria. METHODS: The index test of our study was the hospital discharge abstract database of the Umbria region (Italy), while the reference standard was the clinical information collected in the medical charts. The study population were adult patients with a hospital discharge for peptic ulcer or gastrointestinal hemorrhage in the period 2012-2014. A random sample of cases and non-cases was selected and the corresponding medical charts were reviewed. Cases of peptic ulcer were confirmed based on endoscopy, radiology, and surgery, while adjudication of gastrointestinal hemorrhage was based on presence of hematemesis, melena, and rectal bleeding. RESULTS: Overall, we reviewed 445 clinical charts of cases and 80 clinical charts of non-cases. The diagnostic accuracy results were: code 531 (gastric ulcer), sensitivity and NPV 98%, specificity 88%, and PPV 91%; code 532 (duodenal ulcer), sensitivity and NPV 100%, specificity and PPV 98%; code 534 (gastrojejunal ulcer), sensitivity and NPV 100%, specificity 70%, and PPV 45%; code 578 (gastrointestinal hemorrhage), sensitivity 96%, specificity 90%, PPV and NPV 94%. CONCLUSIONS: Our results showed a high level of diagnostic accuracy for most of the codes considered. The ICD-9 code 534 of gastrojejunal ulcer had a lower level of specificity and PPV due to false positives, being mainly misclassifications for coding errors. These validated codes can be used for future epidemiological studies and for health services research.


Assuntos
Codificação Clínica/normas , Bases de Dados Factuais/estatística & dados numéricos , Hemorragia Gastrointestinal/diagnóstico , Classificação Internacional de Doenças/normas , Úlcera Péptica/diagnóstico , Idoso , Idoso de 80 Anos ou mais , Feminino , Humanos , Itália , Masculino , Pessoa de Meia-Idade
16.
Biomed Pharmacother ; 129: 110451, 2020 Sep.
Artigo em Inglês | MEDLINE | ID: mdl-32603887

RESUMO

Here we present the results of a bibliometric survey of peer-reviewed and pre-print papers published in the English language on issues related to COVID-19 within the first three months since a cluster of a severe acute respiratory disease of unknown etiology was officially confirmed by the Chinese Center for Disease Control and Prevention on 31 December 2019. A systematic search using PubMed/Medline and Scopus databases and preprint servers was performed. The articles were classified according to their type, subject and country of origin. Up to 31 March 2020, a total of 2062 papers published in 578 peer-reviewed journals and 1425 preprints posted mostly on medRxiv (55.4 %), were identified. The mean number of published journal papers and preprints per day in the considered period was 27 and 12, respectively, and reached a maximum of 51 and 46 per day in March, respectively. The identified articles, journal papers and preprints, mostly covered the epidemiology of COVID-19 (35.7 %), clinical aspects of infection (21.0 %), preventative measures (12.8 %), treatment options (12.5 %), diagnostics (12.2 %), mathematical modeling of disease transmission and mitigation (9.6 %), and molecular biology and pathogenesis of SARS-CoV-2 (8.7 %). The majority of the journal papers were commentaries (38.5 %), reviews (33.6 %) and original research (21.3 %), while preprints predominantly presented original results (89.8 %). Chinese scientists contributed the highest share of original research and were responsible for 32.9 % journal papers and 43.9 % preprints published in the considered period. A high number of contributions was also seen from the United States, the United Kingdom, and Italy. The benefits and potential risks of such a massive publication output are discussed. The scientific response seen during the first 3 months of the COVID-19 outbreak is a demonstration of the capabilities of modern science to react rapidly to emerging global health threats by providing and discussing the essential information for understanding the etiological factor, its spread, preventative measures, and mitigation strategies.


Assuntos
Infecções por Coronavirus , Pandemias , Publicações Periódicas como Assunto/estatística & dados numéricos , Pneumonia Viral , Publicações/estatística & dados numéricos , Bibliometria , Bases de Dados Factuais/estatística & dados numéricos , Surtos de Doenças , Humanos
17.
Eur Respir J ; 56(2)2020 08.
Artigo em Inglês | MEDLINE | ID: mdl-32616598
18.
Med Care ; 58(7): 658-662, 2020 07.
Artigo em Inglês | MEDLINE | ID: mdl-32520839

RESUMO

BACKGROUND: Single-center comparative effectiveness studies evaluating outcomes that can occur posthospitalization may become biased if outcomes diagnosed at other facilities are not ascertained. Administrative datasets that link patients' records across facilities may improve outcome ascertainment. OBJECTIVE: To determine whether use of linked administrative data significantly augments thromboembolic outcome ascertainment. RESEARCH DESIGN: Retrospective cohort study. SUBJECTS: Patients with an acute isolated calf deep vein thrombosis (DVT) diagnosed at 1 Californian center during 2010-2013. MEASURES: Proximal DVT or pulmonary embolism (PE) within 180 days. We ascertained outcomes from linked California hospitalization, emergency department, and ambulatory surgery data and compared this information to outcomes previously identified from review of the center's medical records. RESULTS: Among 384 patients with an isolated calf DVT, 333 could be linked to longitudinal administrative data records. Ten patients had a possible proximal DVT or PE (4 more clearly so) from administrative data; all were unknown from medical record review. Eleven patients with known outcomes from medical record review had no outcome from administrative data. The adjusted odds ratio of proximal DVT or PE with therapeutic anticoagulation attenuated from 0.33 [95% confidence interval (CI), 0.12-0.87] using only medical record review to 0.64 (95% CI, 0.29-1.40) using both medical record review and possible outcomes from administrative data. Restricting the outcome to diagnoses clearly involving proximal DVT or PE, the adjusted odds ratio was 0.46 (95% CI, 0.19-1.10). CONCLUSIONS: Use of linked hospital administrative data augmented detection of outcomes but imperfect linkage, nonspecific diagnoses, and documentation/coding errors introduced uncertainty regarding the accuracy of outcome ascertainment.


Assuntos
Anticoagulantes/uso terapêutico , Organização e Administração/estatística & dados numéricos , Avaliação de Resultados em Cuidados de Saúde/normas , Tromboembolia Venosa/tratamento farmacológico , Adulto , Idoso , California , Estudos de Coortes , Bases de Dados Factuais/estatística & dados numéricos , Feminino , Humanos , Extremidade Inferior/irrigação sanguínea , Extremidade Inferior/fisiopatologia , Masculino , Pessoa de Meia-Idade , Razão de Chances , Avaliação de Resultados em Cuidados de Saúde/estatística & dados numéricos , Qualidade da Assistência à Saúde/normas , Qualidade da Assistência à Saúde/estatística & dados numéricos , Estudos Retrospectivos , Fatores de Risco , Tromboembolia Venosa/prevenção & controle
19.
J Pediatr Orthop ; 40(6): 277-282, 2020 Jul.
Artigo em Inglês | MEDLINE | ID: mdl-32501908

RESUMO

BACKGROUND: Isolated pediatric femur fractures have historically been treated at local hospitals. Pediatric referral patterns have changed in recent years, diverting patients to high volume centers. The purpose of this investigation was to assess the treatment location of isolated pediatric femur fractures and concomitant trends in length of stay and cost of treatment. METHODS: A cross-sectional analysis of surgical admissions for femoral shaft fracture was performed using the 2000 to 2012 Kids' Inpatient Database. The primary outcome was hospital location and teaching status. Secondary outcomes included the length of stay and mean hospital charges. Polytrauma patients were excluded. Data were weighted within each study year to produce national estimates. RESULTS: A total of 35,205 pediatric femoral fracture cases met the inclusion criteria. There was a significant shift in the treatment location over time. In 2000, 60.1% of fractures were treated at urban, teaching hospitals increasing to 81.8% in 2012 (P<0.001). Mean length of stay for all hospitals decreased from 2.59 to 1.91 days (P<0.001). Inflation-adjusted total charges increased during the study from $9499 in 2000 to $25,499 in 2012 per episode of treatment (P<0.001). Total charges per hospitalization were ∼$8000 greater at urban, teaching hospitals in 2012. CONCLUSIONS: Treatment of isolated pediatric femoral fractures is regionalizing to urban, teaching hospitals. Length of stay has decreased across all institutions. However, the cost of treatment is significantly greater at urban institutions relative to rural hospitals. This trend does not consider patient outcomes but the observed pattern appears to have financial implications. LEVEL OF EVIDENCE: Level III-case series, database study.


Assuntos
Fraturas do Fêmur , Hospitais Rurais/economia , Hospitais de Ensino/economia , Inovação Organizacional/economia , Criança , Análise Custo-Benefício , Estudos Transversais , Bases de Dados Factuais/estatística & dados numéricos , Feminino , Fraturas do Fêmur/economia , Fraturas do Fêmur/epidemiologia , Fraturas do Fêmur/cirurgia , Hospitalização/economia , Hospitalização/estatística & dados numéricos , Humanos , Masculino , Estados Unidos
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