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1.
Anticancer Res ; 41(9): 4629-4636, 2021 Sep.
Artigo em Inglês | MEDLINE | ID: mdl-34475091

RESUMO

BACKGROUND/AIM: We aimed to develop a novel recurrence prediction model for stage II-III colon cancer using simple auto-artificial intelligence (AI) with improved accuracy compared to conventional statistical models. PATIENTS AND METHODS: A total of 787 patients who had undergone curative surgery for stage II-III colon cancer between 2000 and 2018 were included. Binomial logistic regression analysis was used to calculate the effect of variables on recurrence. The auto-AI software 'Prediction One' (Sony Network Communications Inc.) was used to predict recurrence with the same dataset used for the conventional statical model. Predictive accuracy was assessed by the area under the receiver operating characteristic curve (AUC). RESULTS: The AUC of the multivariate model was 0.719 (95%CI=0.655-0.784), whereas that of the AI model was 0.815, showing a significant improvement. CONCLUSION: This auto-AI prediction model demonstrates improved accuracy compared to the conventional model. It could be constructed by clinical surgeons who are not familiar with AI.


Assuntos
Neoplasias do Colo/patologia , Neoplasias do Colo/cirurgia , Recidiva Local de Neoplasia/patologia , Recidiva Local de Neoplasia/cirurgia , Adulto , Idoso , Idoso de 80 Anos ou mais , Área Sob a Curva , Inteligência Artificial , Progressão da Doença , Feminino , Humanos , Modelos Logísticos , Masculino , Pessoa de Meia-Idade , Análise Multivariada , Estadiamento de Neoplasias , Curva ROC , Medição de Risco , Resultado do Tratamento , Adulto Jovem
2.
Ann Acad Med Singap ; 50(8): 606-612, 2021 08.
Artigo em Inglês | MEDLINE | ID: mdl-34472555

RESUMO

INTRODUCTION: An antenatal scoring system for vaginal birth after caesarean section (VBAC) categorises patients into a low or high probability of successful vaginal delivery. It enables counselling and preparation before labour starts. The current study aims to evaluate the role of Grobman nomogram and the Kalok scoring system in predicting VBAC success in Singapore. METHODS: This is a retrospective study on patients of gestational age 37 weeks 0 day to 41 weeks 0 day who underwent a trial of labour after 1 caesarean section between September 2016 and September 2017 was conducted. Two scoring systems were used to predict VBAC success, a nomogram by Grobman et al. in 2007 and an additive model by Kalok et al. in 2017. RESULTS: A total of 190 patients underwent a trial of labour after caesarean section, of which 103 (54.2%) were successful. The Kalok scoring system (area under curve [AUC] 0.740) was a better predictive model than Grobman nomogram (AUC 0.664). Patient's age (odds ratio [OR] 0.915, 95% CI [confidence interval] 0.844-0.992), body mass index at booking (OR 0.902, 95% CI 0.845-0.962), and history of successful VBAC (OR 4.755, 95% CI 1.248-18.120) were important factors in predicting VBAC. CONCLUSION: Neither scoring system was perfect in predicting VBAC among local women. Further customisation of the scoring system to replace ethnicity with the 4 races of Singapore can be made to improve its sensitivity. The factors identified in this study serve as a foundation for developing a population-specific antenatal scoring system for Singapore women who wish to have a trial of VBAC.


Assuntos
Nascimento Vaginal Após Cesárea , Área Sob a Curva , Cesárea , Feminino , Humanos , Lactente , Gravidez , Estudos Retrospectivos , Prova de Trabalho de Parto
3.
Medicine (Baltimore) ; 100(36): e27146, 2021 Sep 10.
Artigo em Inglês | MEDLINE | ID: mdl-34516506

RESUMO

ABSTRACT: To evaluate the value of the combination schemes of 10 serological markers in the clinical diagnosis of acute cerebral infarction.The level of total cholesterol, triglycerides, high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol, high-sensitivity C-reactive protein, homocysteine (HCY), lipoprotein-related phospholipase A2, ischemia-modified albumin, complement C1q, and lipoprotein a were analyzed in 154 patients with acute ischemic cerebral infarction. The optimized diagnostic combination for acute cerebral infarction was explored by calculating the maximum area under the receiver operating characteristic curves (AUC).The levels of total cholesterol, triglycerides, low-density lipoprotein cholesterol, high-sensitivity C-reactive protein, HCY, lipoprotein-related phospholipase A2, ischemia-modified albumin, complement C1q, and lipoprotein a were significantly higher in the patient vs the control group. Moreover, the positive rate of HCY reached 89.9%. The analysis of the receiver operating characteristic curve of each index and their combinations showed that the minimum AUC of HDL-C alone was 0.543, while the maximum AUC of HCY was 0.853. A multiple logistic regression analysis indicated that HDL-C was a slightly significant variate in the diagnosis of acute cerebral infarction.The value of individual serological markers in the diagnosis of acute cerebral infarction was slightly significant, while the combination of the markers significantly improved the efficiency of its diagnosis.


Assuntos
Biomarcadores/sangue , Isquemia Encefálica/diagnóstico , Doença Aguda , Área Sob a Curva , Isquemia Encefálica/sangue , Proteína C-Reativa/metabolismo , HDL-Colesterol/sangue , LDL-Colesterol/sangue , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Valor Preditivo dos Testes , Albumina Sérica Humana , Triglicerídeos/sangue
4.
Sci Rep ; 11(1): 17489, 2021 09 01.
Artigo em Inglês | MEDLINE | ID: mdl-34471180

RESUMO

Rapid and sensitive screening tools for SARS-CoV-2 infection are essential to limit the spread of COVID-19 and to properly allocate national resources. Here, we developed a new point-of-care, non-contact thermal imaging tool to detect COVID-19, based on advanced image processing algorithms. We captured thermal images of the backs of individuals with and without COVID-19 using a portable thermal camera that connects directly to smartphones. Our novel image processing algorithms automatically extracted multiple texture and shape features of the thermal images and achieved an area under the curve (AUC) of 0.85 in COVID-19 detection with up to 92% sensitivity. Thermal imaging scores were inversely correlated with clinical variables associated with COVID-19 disease progression. In summary, we show, for the first time, that a hand-held thermal imaging device can be used to detect COVID-19. Non-invasive thermal imaging could be used to screen for COVID-19 in out-of-hospital settings, especially in low-income regions with limited imaging resources.


Assuntos
COVID-19/diagnóstico por imagem , Processamento de Imagem Assistida por Computador/instrumentação , Adulto , Idoso , Algoritmos , Área Sob a Curva , Progressão da Doença , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Sistemas Automatizados de Assistência Junto ao Leito , Sensibilidade e Especificidade , Smartphone
5.
Adv Ther ; 38(9): 4798-4814, 2021 09.
Artigo em Inglês | MEDLINE | ID: mdl-34347254

RESUMO

INTRODUCTION: In this study, we assessed the pharmacokinetics (PK), bioequivalence, and safety of 150 mg capecitabine compared to the branded reference formulation in colorectal or breast cancer patients receiving a high-fat diet. METHODS: This was a multicenter, open, random, balanced, three-period, three-sequence and semi-repetitive cross study with 48 subjects. In each study period, the eligible subject received the test or reference formulation, followed by a 1-day washout period. Serial blood samples for pharmacokinetic assessment were collected at predose up to 8 h postdose. The plasma concentrations of capecitabine were analyzed by LC/MS-MS. Pharmacokinetic parameters (non-compartmental model) were assessed with WinNonlin software. The pharmacokinetic parameters assessed were the area under the plasma concentration-time curve from time 0 to the time of last measurable concentration (AUC0-t), the AUC from time zero to infinity (AUC0-∞), the peak plasma concentration of the drug (Cmax), the time needed to reach maximum concentration (Tmax), the elimination half-life (t1/2), and the terminal elimination rate (λz). All were analyzed using an analysis of variance (ANOVA) model after logarithmic transformation of the data. To establish the bioequivalence (BE) for capecitabine, reference-scaled average bioequivalence (RSABE) acceptance criteria and average bioequivalence (ABE) acceptance criteria were used. Safety and tolerability were assessed during the entire study period. RESULTS: Reference scaled maximum plasma concentration (Cmax) was higher than 0.294, permitting use of RSABE. The within-subject SDs of the reference intervention (SWR) for AUC0-t and AUC0-∞ were < 0.294, meeting ABE criteria. The point estimate for the geometric least squares mean (GLSM) ratio for the point estimate of Cmax was 0.962, within the range of 0.80-1.25. The 90% upper confidence boundary for the test/reference of GLSM ratios was 97.84-105.40% for AUC0-t and 97.33-103.51% for AUC0-∞, all of which were within the prespecified limits. The 90% confidence intervals for AUC0-t and AUC0-∞ and 95% upper confidence limit for Cmax indicated bioequivalence. No serious adverse events were found among the subjects. CONCLUSIONS: According to the criteria for bioequivalence, the test formulation was bioequivalent to the reference formulation in terms of the rate and extent of absorption under fed conditions by measurement of total capecitabine and was safe and well tolerated. TRIAL REGISTRATION: NCT04420871.


Assuntos
Neoplasias da Mama , Neoplasias Colorretais , Área Sob a Curva , Neoplasias da Mama/tratamento farmacológico , Capecitabina/efeitos adversos , Estudos Cross-Over , Feminino , Humanos , Comprimidos , Equivalência Terapêutica
6.
J R Soc Interface ; 18(181): 20210284, 2021 08.
Artigo em Inglês | MEDLINE | ID: mdl-34343454

RESUMO

Current COVID-19 screening efforts mainly rely on reported symptoms and the potential exposure to infected individuals. Here, we developed a machine-learning model for COVID-19 detection that uses four layers of information: (i) sociodemographic characteristics of the individual, (ii) spatio-temporal patterns of the disease, (iii) medical condition and general health consumption of the individual and (iv) information reported by the individual during the testing episode. We evaluated our model on 140 682 members of Maccabi Health Services who were tested for COVID-19 at least once between February and October 2020. These individuals underwent, in total, 264 516 COVID-19 PCR tests, out of which 16 512 were positive. Our multi-layer model obtained an area under the curve (AUC) of 81.6% when evaluated over all the individuals in the dataset, and an AUC of 72.8% when only individuals who did not report any symptom were included. Furthermore, considering only information collected before the testing episode-i.e. before the individual had the chance to report on any symptom-our model could reach a considerably high AUC of 79.5%. Our ability to predict early on the outcomes of COVID-19 tests is pivotal for breaking transmission chains, and can be used for a more efficient testing policy.


Assuntos
COVID-19 , Área Sob a Curva , Humanos , Aprendizado de Máquina , SARS-CoV-2
7.
PLoS One ; 16(8): e0256784, 2021.
Artigo em Inglês | MEDLINE | ID: mdl-34460840

RESUMO

Viral sepsis has been proposed as an accurate term to describe all multisystemic dysregulations and clinical findings in severe and critically ill COVID-19 patients. The adoption of this term may help the implementation of more accurate strategies of early diagnosis, prognosis, and in-hospital treatment. We accurately quantified 110 metabolites using targeted metabolomics, and 13 cytokines/chemokines in plasma samples of 121 COVID-19 patients with different levels of severity, and 37 non-COVID-19 individuals. Analyses revealed an integrated host-dependent dysregulation of inflammatory cytokines, neutrophil activation chemokines, glycolysis, mitochondrial metabolism, amino acid metabolism, polyamine synthesis, and lipid metabolism typical of sepsis processes distinctive of a mild disease. Dysregulated metabolites and cytokines/chemokines showed differential correlation patterns in mild and critically ill patients, indicating a crosstalk between metabolism and hyperinflammation. Using multivariate analysis, powerful models for diagnosis and prognosis of COVID-19 induced sepsis were generated, as well as for mortality prediction among septic patients. A metabolite panel made of kynurenine/tryptophan ratio, IL-6, LysoPC a C18:2, and phenylalanine discriminated non-COVID-19 from sepsis patients with an area under the curve (AUC (95%CI)) of 0.991 (0.986-0.995), with sensitivity of 0.978 (0.963-0.992) and specificity of 0.920 (0.890-0.949). The panel that included C10:2, IL-6, NLR, and C5 discriminated mild patients from sepsis patients with an AUC (95%CI) of 0.965 (0.952-0.977), with sensitivity of 0.993(0.984-1.000) and specificity of 0.851 (0.815-0.887). The panel with citric acid, LysoPC a C28:1, neutrophil-lymphocyte ratio (NLR) and kynurenine/tryptophan ratio discriminated severe patients from sepsis patients with an AUC (95%CI) of 0.829 (0.800-0.858), with sensitivity of 0.738 (0.695-0.781) and specificity of 0.781 (0.735-0.827). Septic patients who survived were different from those that did not survive with a model consisting of hippuric acid, along with the presence of Type II diabetes, with an AUC (95%CI) of 0.831 (0.788-0.874), with sensitivity of 0.765 (0.697-0.832) and specificity of 0.817 (0.770-0.865).


Assuntos
COVID-19/patologia , Metabolômica , Sepse/diagnóstico , Adulto , Área Sob a Curva , COVID-19/complicações , COVID-19/virologia , Quimiocinas/sangue , Citocinas/sangue , Feminino , Humanos , Cinurenina/sangue , Linfócitos/citologia , Masculino , Pessoa de Meia-Idade , Neutrófilos/citologia , Curva ROC , Estudos Retrospectivos , Fatores de Risco , SARS-CoV-2/isolamento & purificação , Sepse/etiologia , Índice de Gravidade de Doença , Triptofano/sangue
8.
PLoS One ; 16(8): e0256447, 2021.
Artigo em Inglês | MEDLINE | ID: mdl-34464393

RESUMO

BACKGROUND: SARS-CoV-2 testing capacity is important to monitor epidemic dynamics and as a mitigation strategy. Given difficulties of large-scale quantitative reverse transcription polymerase chain reaction (qRT-PCR) implementation, rapid antigen tests (Rapid Ag-T) have been proposed as alternatives in settings like Mexico. Here, we evaluated diagnostic performance of Rapid Ag-T for SARS-CoV-2 infection and its associated clinical implications compared to qRT-PCR testing in Mexico. METHODS: We analyzed data from the COVID-19 registry of the Mexican General Directorate of Epidemiology up to April 30th, 2021 (n = 6,632,938) and cases with both qRT-PCR and Rapid Ag-T (n = 216,388). We evaluated diagnostic performance using accuracy measures and assessed time-dependent changes in the Area Under the Receiver Operating Characteristic curve (AUROC). We also explored test discordances as predictors of hospitalization, intubation, severe COVID-19 and mortality. RESULTS: Rapid Ag-T is primarily used in Mexico City. Rapid Ag-T have low sensitivity 37.6% (95%CI 36.6-38.7), high specificity 95.5% (95%CI 95.1-95.8) and acceptable positive 86.1% (95%CI 85.0-86.6) and negative predictive values 67.2% (95%CI 66.2-69.2). Rapid Ag-T has optimal diagnostic performance up to days 3 after symptom onset, and its performance is modified by testing location, comorbidity, and age. qRT-PCR (-) / Rapid Ag-T (+) cases had higher risk of adverse COVID-19 outcomes (HR 1.54 95% CI 1.41-1.68) and were older, qRT-PCR (+)/ Rapid Ag-T(-) cases had slightly higher risk or adverse outcomes and ≥7 days from symptom onset (HR 1.53 95% CI 1.48-1.59). Cases detected with rapid Ag-T were younger, without comorbidities, and milder COVID-19 course. CONCLUSIONS: Rapid Ag-T could be used as an alternative to qRT-PCR for large scale SARS-CoV-2 testing in Mexico. Interpretation of Rapid Ag-T results should be done with caution to minimize the risk associated with false negative results.


Assuntos
Antígenos Virais/análise , Teste Sorológico para COVID-19 , COVID-19/diagnóstico , SARS-CoV-2/metabolismo , Adulto , Área Sob a Curva , COVID-19/epidemiologia , COVID-19/virologia , Teste de Ácido Nucleico para COVID-19 , Feminino , Hospitalização/estatística & dados numéricos , Humanos , Masculino , México/epidemiologia , Pessoa de Meia-Idade , Modelos de Riscos Proporcionais , RNA Viral/análise , RNA Viral/metabolismo , Curva ROC , Sistema de Registros , Estudos Retrospectivos , SARS-CoV-2/isolamento & purificação , Sensibilidade e Especificidade , Adulto Jovem
9.
Adv Clin Exp Med ; 30(8): 789-795, 2021 Aug.
Artigo em Inglês | MEDLINE | ID: mdl-34405969

RESUMO

BACKGROUND: MicroRNA (miR) influences the biological activities of cirrhotic patients with recurrent portal hypertension. OBJECTIVES: The current study was designed to investigate risk factors related to the survival of cirrhosis patients and assessed the possibility of using miR-9a-5p predictability to prevent post-treatment portal hypertension. MATERIAL AND METHODS: Patients with portal hypertension due to liver cirrhosis treated from January 2015 to September 2016 were included in this study. Patients without relapse after treatment were selected as the success group while patients with relapse after treatment were selected as the recurrence group. Serum samples from healthy people were also collected. The blood indexes of the 2 groups of patients before and after treatment were compared and the miR-9a-5p serum level in each group was determined. The Kaplan-Meier method was applied to analyze three-year survival, Cox univariate regression was used to analyze the risk factors for recurrence of cirrhotic portal hypertension, and the receiver operating characteristic curve (ROC) was used to evaluate the diagnostic value of serum miR-9a-5p, total bilirubin (TBIL) and platelet (PLT) levels in patients with recurrence. RESULTS: The miR-9a-5p level in the recurrence group was higher than that in the success group after treatment. In patients with recurrence, the miR-9a-5p level was negatively correlated with red blood cell count, TBIL, white blood cell count, and PLT count, and positively correlated with albumin. The miR-9a-5p, TBIL and PLT are potential markers of recurrent portal hypertension in liver cirrhosis. The miR-9a-5p had the highest area under the curve (AUC) value in patients with relapse. CONCLUSIONS: The miR-9a-5p is a risk factor for the recurrence of cirrhotic portal hypertension after treatment. It may be used as a marker of recurrence, and so has potential clinical value for the diagnosis and treatment of recurrent portal hypertension.


Assuntos
Hipertensão Portal , MicroRNAs , Área Sob a Curva , Humanos , Hipertensão Portal/etiologia , Cirrose Hepática/complicações , MicroRNAs/genética , MicroRNAs/metabolismo , Curva ROC
10.
PLoS One ; 16(8): e0254073, 2021.
Artigo em Inglês | MEDLINE | ID: mdl-34351940

RESUMO

INTRODUCTION: Coronavirus disease 2019 (COVID-19) caused by SARS-CoV-2 virus, is a major public health concern spanning from healthy carriers to patients with life-threatening conditions. Although most of COVID-19 patients have mild-to-moderate clinical symptoms, some patients have severe pneumonia leading to death. Therefore, the early prediction of disease prognosis and severity is crucial in COVID-19 patients. The main objective of this study is to evaluate the haemocytometric parameters and identify severity score associated with SARS-CoV-2 infection. METHODS: Clinical and laboratory records were retrospectively reviewed from 97 cases of COVID-19 admitted to hospitals in Istanbul, Turkey. The patient groups were subdivided into three major groups: Group 1 (Non-critical): 59 patients, Group 2 (Critical-Survivors): 23 patients and Group 3 (Critical-Non-survivors):15 patients. These data was tested for correlation, including with derived haemocytometric parameters. The blood analyses were performed the Sysmex XN-series automated hematology analyser using standard laboratory protocols. All statistical testing was undertaken using Analyse-it software. RESULTS: 97 patients with COVID-19 disease and 935 sequential complete blood count (CBC-Diff) measurements (days 0-30) were included in the final analyses. Multivariate analysis demonstrated that red cell distribution width (RDW) (>13.7), neutrophil to lymphocyte ratio (NLR) (4.4), Hemoglobin (Hgb) (<11.4 gr/dL) and monocyte to neutrophil ratio (MNR) (0.084) had the highest area under curve (AUC) values, respectively in discrimination critical patients than non-critical patients. In determining Group 3, MNR (<0.095), NLR (>5.2), Plateletcount (PLT) (>142 x103/L) and RDW (>14) were important haemocytometric parameters, and the mortality risk value created by their combination had the highest AUC value (AUC = 0.911, 95% CI, 0886-0.931). Trend analysis of CBC-Diff parameters over 30 days of hospitalization, NLR on day 2, MNR on day 4, RDW on day 6 and PLT on day 7 of admission were found to be the best time related parameters in discrimination non-critical (mild-moderate) patient group from critical (severe and non-survivor) patient group. CONCLUSION: NLR is a strong predictor for the prognosis for severe COVID-19 patients when the cut-off chosen was 4.4, the combined mortality risk factor COVID-19 disease generated from RDW-CV, NLR, MNR and PLT is best as a mortality haematocytometric index.


Assuntos
COVID-19/sangue , COVID-19/mortalidade , Adulto , Idoso , Área Sob a Curva , Contagem de Células Sanguíneas/métodos , Feminino , Hemoglobinas , Humanos , Laboratórios , Linfócitos , Masculino , Pessoa de Meia-Idade , Monócitos , Neutrófilos , Contagem de Plaquetas , Prognóstico , Curva ROC , Estudos Retrospectivos , Fatores de Risco , SARS-CoV-2/patogenicidade , Índice de Gravidade de Doença , Turquia
11.
PLoS One ; 16(8): e0255402, 2021.
Artigo em Inglês | MEDLINE | ID: mdl-34379666

RESUMO

Epidemiological and genetic studies on COVID-19 are currently hindered by inconsistent and limited testing policies to confirm SARS-CoV-2 infection. Recently, it was shown that it is possible to predict COVID-19 cases using cross-sectional self-reported disease-related symptoms. Here, we demonstrate that this COVID-19 prediction model has reasonable and consistent performance across multiple independent cohorts and that our attempt to improve upon this model did not result in improved predictions. Using the existing COVID-19 prediction model, we then conducted a GWAS on the predicted phenotype using a total of 1,865 predicted cases and 29,174 controls. While we did not find any common, large-effect variants that reached genome-wide significance, we do observe suggestive genetic associations at two SNPs (rs11844522, p = 1.9x10-7; rs5798227, p = 2.2x10-7). Explorative analyses furthermore suggest that genetic variants associated with other viral infectious diseases do not overlap with COVID-19 susceptibility and that severity of COVID-19 may have a different genetic architecture compared to COVID-19 susceptibility. This study represents a first effort that uses a symptom-based predicted phenotype as a proxy for COVID-19 in our pursuit of understanding the genetic susceptibility of the disease. We conclude that the inclusion of symptom-based predicted cases could be a useful strategy in a scenario of limited testing, either during the current COVID-19 pandemic or any future viral outbreak.


Assuntos
COVID-19/patologia , Predisposição Genética para Doença , Área Sob a Curva , COVID-19/genética , COVID-19/virologia , Estudos Transversais , Estudo de Associação Genômica Ampla , Humanos , Fenótipo , Polimorfismo de Nucleotídeo Único , Curva ROC , SARS-CoV-2/isolamento & purificação
12.
PLoS One ; 16(8): e0256022, 2021.
Artigo em Inglês | MEDLINE | ID: mdl-34379684

RESUMO

BACKGROUND: The coronavirus disease 2019 (COVID-19) pandemic rapidly increases the use of mechanical ventilation (MV). Such cases further require extracorporeal membrane oxygenation (ECMO) and have a high mortality. OBJECTIVE: We aimed to identify prognostic biomarkers pathophysiologically reflecting future deterioration of COVID-19. METHODS: Clinical, laboratory, and outcome data were collected from 102 patients with moderate to severe COVID-19. Interleukin (IL)-6 level and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA copy number in plasma were assessed with ELISA kit and quantitative PCR. RESULTS: Twelve patients died or required ECMO owing to acute respiratory distress syndrome despite the use of MV. Among various variables, a ratio of oxygen saturation to fraction of inspired oxygen (SpO2/FiO2), IL-6, and SARS-CoV-2 RNA on admission before intubation were strongly predictive of fatal outcomes after the MV use. Moreover, among these variables, combining SpO2/FiO2, IL-6, and SARS-CoV-2 RNA showed the highest accuracy (area under the curve: 0.934). In patients with low SpO2/FiO2 (< 261), fatal event-rate after the MV use at the 30-day was significantly higher in patients with high IL-6 (> 49 pg/mL) and SARS-CoV-2 RNAaemia (> 1.5 copies/µL) compared to those with high IL-6 or RNAaemia or without high IL-6 and RNAaemia (88% vs. 22% or 8%, log-rank test P = 0.0097 or P < 0.0001, respectively). CONCLUSIONS: Combining SpO2/FiO2 with high IL-6 and SARS-CoV-2 RNAaemia which reflect hyperinflammation and viral overload allows accurately and before intubation identifying COVID-19 patients at high risk for ECMO use or in-hospital death despite the use of MV.


Assuntos
COVID-19/mortalidade , Interleucina-6/sangue , RNA Viral/metabolismo , SARS-CoV-2/genética , Adulto , Idoso , Idoso de 80 Anos ou mais , Área Sob a Curva , COVID-19/patologia , COVID-19/virologia , Feminino , Mortalidade Hospitalar , Humanos , Masculino , Pessoa de Meia-Idade , Consumo de Oxigênio , Prognóstico , Estudos Prospectivos , Curva ROC , Respiração Artificial , SARS-CoV-2/isolamento & purificação , Carga Viral
13.
PLoS One ; 16(8): e0255748, 2021.
Artigo em Inglês | MEDLINE | ID: mdl-34432797

RESUMO

BACKGROUND: Prediction models should be externally validated to assess their performance before implementation. Several prediction models for coronavirus disease-19 (COVID-19) have been published. This observational cohort study aimed to validate published models of severity for hospitalized patients with COVID-19 using clinical and laboratory predictors. METHODS: Prediction models fitting relevant inclusion criteria were chosen for validation. The outcome was either mortality or a composite outcome of mortality and ICU admission (severe disease). 1295 patients admitted with symptoms of COVID-19 at Kings Cross Hospital (KCH) in London, United Kingdom, and 307 patients at Oslo University Hospital (OUH) in Oslo, Norway were included. The performance of the models was assessed in terms of discrimination and calibration. RESULTS: We identified two models for prediction of mortality (referred to as Xie and Zhang1) and two models for prediction of severe disease (Allenbach and Zhang2). The performance of the models was variable. For prediction of mortality Xie had good discrimination at OUH with an area under the receiver-operating characteristic (AUROC) 0.87 [95% confidence interval (CI) 0.79-0.95] and acceptable discrimination at KCH, AUROC 0.79 [0.76-0.82]. In prediction of severe disease, Allenbach had acceptable discrimination (OUH AUROC 0.81 [0.74-0.88] and KCH AUROC 0.72 [0.68-0.75]). The Zhang models had moderate to poor discrimination. Initial calibration was poor for all models but improved with recalibration. CONCLUSIONS: The performance of the four prediction models was variable. The Xie model had the best discrimination for mortality, while the Allenbach model had acceptable results for prediction of severe disease.


Assuntos
COVID-19/patologia , Modelos Estatísticos , Idoso , Área Sob a Curva , COVID-19/mortalidade , COVID-19/virologia , Estudos de Coortes , Feminino , Mortalidade Hospitalar , Hospitalização , Humanos , Unidades de Terapia Intensiva , Masculino , Pessoa de Meia-Idade , Noruega , Prognóstico , Curva ROC , SARS-CoV-2/isolamento & purificação , Índice de Gravidade de Doença , Reino Unido
14.
Medicine (Baltimore) ; 100(31): e26189, 2021 Aug 06.
Artigo em Inglês | MEDLINE | ID: mdl-34397790

RESUMO

BACKGROUND AND OBJECTIVES: Postoperative major complications after esophageal cancer resection vary and may significantly impact long-term outcomes. This study aimed to build an individualized nomogram to predict post-esophagectomy major morbidity. METHODS: This retrospective study included 599 consecutive patients treated at a single center between January 2017 and April 2019. Of them, 420 and 179 were assigned to the model development and validation cohorts, respectively. Major morbidity predictors were identified using multiple logistic regression. Model discrimination and calibration were evaluated by validation. Regarding clinical usefulness, we examined the net benefit using decision curve analysis. RESULTS: The mean age was 64 years; 79% of the patients were male. The most common comorbidities were hypertension, diabetes mellitus, and stroke history. The 30-day postoperative major morbidity rate was 24%. Multivariate logistic regression analysis showed that age, smoking history, coronary heart disease, dysphagia, body mass index, operation time, and tumor size were independent risk factors for surgery-associated major morbidity. Areas under the receiver-operating characteristic curves of the development and validation groups were 0.775 (95% confidence interval, 0.721-0.829) and 0.792 (95% confidence interval, 0.709-0.874), respectively. In the validation cohort, the nomogram showed good calibration. Decision curve analysis demonstrated that the prediction nomogram was clinically useful. CONCLUSION: Morbidity models and nomograms incorporating clinical and surgical data can be used to predict operative risk for esophagectomy and provide appropriate resources for the postoperative management of high-risk patients.


Assuntos
Neoplasias Esofágicas/cirurgia , Carcinoma de Células Escamosas do Esôfago/cirurgia , Esofagectomia/efeitos adversos , Nomogramas , Complicações Pós-Operatórias/etiologia , Fatores Etários , Idoso , Área Sob a Curva , Índice de Massa Corporal , Comorbidade , Doença das Coronárias/epidemiologia , Transtornos de Deglutição/etiologia , Neoplasias Esofágicas/complicações , Neoplasias Esofágicas/epidemiologia , Neoplasias Esofágicas/patologia , Carcinoma de Células Escamosas do Esôfago/complicações , Carcinoma de Células Escamosas do Esôfago/epidemiologia , Carcinoma de Células Escamosas do Esôfago/patologia , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Duração da Cirurgia , Curva ROC , Estudos Retrospectivos , Fatores de Risco , Fumar/epidemiologia , Carga Tumoral
15.
PLoS One ; 16(8): e0256744, 2021.
Artigo em Inglês | MEDLINE | ID: mdl-34437642

RESUMO

INTRODUCTION: Coronavirus Disease 2019 is a primarily respiratory illness that can cause thrombotic disorders. Elevation of D-dimer is a potential biomarker for poor prognosis in COVID-19, though optimal cutoff value for D-dimer to predict mortality has not yet been established. This study aims to assess the accuracy of admission D-dimer in the prognosis of COVID-19 and to establish the optimal cutoff D-dimer value to predict hospital mortality. METHODS: Clinical and laboratory parameters and outcomes of confirmed COVID-19 cases admitted to four hospitals in Kathmandu were retrospectively analyzed. Admitted COVID-19 cases with recorded D-dimer and definitive outcomes were included consecutively. D-dimer was measured using immunofluorescence assay and reported in Fibrinogen Equivalent Unit (µg/ml). The receiver operating characteristic curve was used to determine the accuracy of D-dimer in predicting mortality, and to calculate the optimal cutoff value, based on which patients were divided into two groups and predictive value of D-dimer for mortality was measured. RESULTS: 182 patients were included in the study out of which 34(18.7%) died during the hospital stay. The mean admission D-dimer among surviving patients was 1.067 µg/ml (±1.705 µg/ml), whereas that among patients who died was 3.208 µg/ml (±2.613 µg/ml). ROC curve for D-dimer and mortality gave an area under the curve of 0.807 (95% CI 0.728-0.886, p<0.001). Optimal cutoff value for D-dimer was 1.5 µg/ml (sensitivity 70.6%, specificity 78.4%). On Cox proportional hazards regression analysis, the unadjusted hazard ratio for high D-dimer was 6.809 (95% CI 3.249-14.268, p<0.001), and 5.862 (95% CI 2.751-12.489, p<0.001) when adjusted for age. CONCLUSION: D-dimer value on admission is an accurate biomarker for predicting mortality in patients with COVID-19. 1.5 µg/ml is the optimal cutoff value of admission D-dimer for predicting mortality in COVID-19 patients.


Assuntos
Biomarcadores/análise , COVID-19/diagnóstico , Produtos de Degradação da Fibrina e do Fibrinogênio/análise , Adulto , Idoso , Área Sob a Curva , COVID-19/mortalidade , COVID-19/virologia , Feminino , Mortalidade Hospitalar , Humanos , Estimativa de Kaplan-Meier , Masculino , Pessoa de Meia-Idade , Prognóstico , Modelos de Riscos Proporcionais , Curva ROC , Estudos Retrospectivos , SARS-CoV-2/isolamento & purificação
16.
Medicine (Baltimore) ; 100(32): e26900, 2021 Aug 13.
Artigo em Inglês | MEDLINE | ID: mdl-34397917

RESUMO

ABSTRACT: Coronavirus disease 2019 (COVID-19) can lead to serious illness and death, and thus, it is particularly important to predict the severity and prognosis of COVID-19. The Sequential Organ Failure Assessment (SOFA) score has been used to predict the clinical outcomes of patients with multiple organ failure requiring intensive care. Therefore, we retrospectively analyzed the clinical characteristics, risk factors, and relationship between the SOFA score and the prognosis of COVID-19 patients.We retrospectively included all patients ≥18 years old who were diagnosed with COVID-19 in the laboratory continuously admitted to Jingzhou Central Hospital from January 16, 2020 to March 23, 2020. The demographic, clinical manifestations, complications, laboratory results, and clinical outcomes of patients infected with the severe acute respiratory syndrome coronavirus-2 were collected and analyzed. Clinical variables were compared between patients with mild and severe COVID-19. Univariate and multivariate logistic regression analyses were performed to identify the risk factors for severe COVID-19. The Cox proportional hazards model was used to analyze risk factors for hospital-related death. Survival analysis was performed by the Kaplan-Meier method, and survival differences were assessed by the log-rank test. Receiver operating characteristic (ROC) curves of the SOFA score in different situations were drawn, and the area under the ROC curve was calculated.A total of 117 patients with confirmed diagnoses of COVID-19 were retrospectively analyzed, of which 108 patients were discharged and 9 patients died. The median age of the patients was 50.0 years old (interquartile range [IQR], 35.5-62.0). 63 patients had comorbidities, of which hypertension (27.4%) was the most frequent comorbidities, followed by diabetes (8.5%), stroke (4.3%), coronary heart disease (3.4%), and chronic liver disease (3.4%). The most common symptoms upon admission were fever (82.9%) and dry cough (70.1%). Regression analysis showed that high SOFA scores, advanced age, and hypertension were associated with severe COVID-19. The median SOFA score of all patients was 2 (IQR, 1-3). Patients with severe COVID-19 exhibited a significantly higher SOFA score than patients with mild COVID-19 (3 [IQR, 2-4] vs 1 [IQR, 0-1]; P  < .001). The SOFA score can better identify severe COVID-19, with an odds ratio of 5.851 (95% CI: 3.044-11.245; P < .001). The area under the ROC curve (AUC) was used to evaluate the diagnostic accuracy of the SOFA score in predicting severe COVID-19 (cutoff value = 2; AUC = 0.908 [95% CI: 0.857-0.960]; sensitivity: 85.20%; specificity: 80.40%) and the risk of death in COVID-19 patients (cutoff value = 5; AUC = 0.995 [95% CI: 0.985-1.000]; sensitivity: 100.00%; specificity: 95.40%). Regarding the 60-day mortality rates of patients in the 2 groups classified by the optimal cutoff value of the SOFA score (5), patients in the high SOFA score group (SOFA score ≥5) had a significantly greater risk of death than those in the low SOFA score group (SOFA score < 5).The SOFA score could be used to evaluate the severity and 60-day mortality of COVID-19. The SOFA score may be an independent risk factor for in-hospital death.


Assuntos
COVID-19/complicações , Escores de Disfunção Orgânica , Adulto , Área Sob a Curva , COVID-19/epidemiologia , COVID-19/mortalidade , Feminino , Humanos , Modelos Logísticos , Masculino , Pessoa de Meia-Idade , Prognóstico , Modelos de Riscos Proporcionais , Curva ROC , Estudos Retrospectivos , Fatores de Risco , Índice de Gravidade de Doença , Estatísticas não Paramétricas
17.
Expert Opin Drug Metab Toxicol ; 17(9): 1149-1156, 2021 Sep.
Artigo em Inglês | MEDLINE | ID: mdl-34372746

RESUMO

PURPOSE: To compare the pharmacokinetics, pharmacodynamics and safety of the new prolonged-release leuprorelin acetate microspheres for injection (3.75 mg) with the reference product Enantone® (3.75 mg). METHOD: 48 healthy male volunteers were enrolled and randomly received a single 3.75 mg dose of the test drug or Enantone®. RESULTS: There were no significant differences in Cmax, AUC0-t and AUC0-48 between the test group and reference group (P > 0.05). The 90% confidence intervals of the two groups were 87.49%~112.74%, 97.15%~154.25%, and 80.85%~109.01%, respectively. Twenty-eight days after administration, both groups reached 100.0% castration level; there was no difference in the time from administration to reaching castration level between the two groups (P > 0.05); However, the difference between the two groups in the duration of castration level was statistically significant (P < 0.05). There were no major or serious adverse events, and the severity was mild to moderate. CONCLUSION: The pharmacokinetic characteristics of leuprorelin in two groups were consistent. The two groups exhibited similar inhibitory effects on testosterone and more subjects in the test group maintained a longer castration time than those in the reference group.


Assuntos
Antineoplásicos Hormonais/administração & dosagem , Leuprolida/administração & dosagem , Testosterona/sangue , Adulto , Antineoplásicos Hormonais/farmacocinética , Antineoplásicos Hormonais/farmacologia , Área Sob a Curva , Preparações de Ação Retardada , Humanos , Injeções , Leuprolida/farmacocinética , Leuprolida/farmacologia , Masculino , Microesferas , Método Simples-Cego , Fatores de Tempo , Adulto Jovem
18.
Medicine (Baltimore) ; 100(29): e26491, 2021 Jul 23.
Artigo em Inglês | MEDLINE | ID: mdl-34398005

RESUMO

ABSTRACT: Hepatocellular carcinoma (HCC) is 1 of the deadliest malignancies worldwide. Despite significant advances in diagnosis and treatment, the mortality rate from HCC persists at a substantial level. Construction of a prognostic model that can reliably predict HCC patients' overall survival is urgently needed.Two RNA-seq dataset (the Cancer Genome Atlas and International Cancer Genome Consortium) and 1 microarray dataset (GSE14520) were included in our study. RNA-binding proteins (RBPs) in HCC patients was examined by differentially expressed genes analysis, functional enrichment analysis and protein-protein interaction network analysis. Subsequently, the Cancer Genome Atlas dataset was randomly divided into training and testing cohort with a prognostic model developed in the training cohort. In order to evaluate the prognostic value of the model, a comprehensive survival assessment was conducted.Five RBPs (ribosomal protein L10-like, enhancer of zeste homolog 2 (EZH2), peroxisome proliferator-activated receptor gamma coactivator 1 alpha (PPARGC1A), zinc finger protein 239, interferon-induced protein with tetratricopeptide repeats 1) were used to construct the model. The model accurately predicted the prognosis of liver cancer patients in both the training cohort and validation cohort. HCC patients could be assigned into a high-risk group and a low-risk group by this model, and the overall survival of these 2 groups was significantly different (P  < .05). Furthermore, the risk scores obtained by this model were highly correlated with immune cell infiltration.The prognostic model helps to identify HCC patients at high risk of mortality, which optimizes decision-making for individualized treatment.


Assuntos
Carcinoma Hepatocelular/complicações , Prognóstico , Proteínas com Motivo de Reconhecimento de RNA/análise , Área Sob a Curva , Carcinoma Hepatocelular/epidemiologia , Carcinoma Hepatocelular/mortalidade , Estudos de Coortes , Humanos , Neoplasias Hepáticas/complicações , Neoplasias Hepáticas/epidemiologia , Neoplasias Hepáticas/mortalidade , Modelos de Riscos Proporcionais , Curva ROC , Medição de Risco/métodos , Medição de Risco/normas , Medição de Risco/estatística & dados numéricos , Análise de Sobrevida
19.
Medicine (Baltimore) ; 100(29): e26627, 2021 Jul 23.
Artigo em Inglês | MEDLINE | ID: mdl-34398018

RESUMO

OBJECTIVE: Previous investigations yielded inconsistent results for diagnostic and prognostic predictive values of MicroRNAs (miRNAs) for acute myocardial infarction (AMI). METHODS AND RESULTS: We systematically searched on PubMed and Web of Science for articles explored association of miRNAs and AMI published from January 1989 to March 2019. For diagnostic studies, a summary of sensitivity, specificity, positive likelihood ratios (PLR), negative likelihood ratios (NLR), and diagnostic odds ratio (DOR), which indicated the accuracy of microRNAs in the differentiation of AMI and no AMI, were calculated from the true positive (TP), true negative (TN), false positive (FP), and false negative (FN) of each study. In addition, the summary receive-operating characteristics (SROC) curve was constructed to summarize the TP and FP rates. For follow-up study, we computed hazard ratios (HRs) and 95% confidence intervals (CIs) for individual clinical outcomes. The meta-analysis showed a sensitivity [0.72 (95% CI: 0.61--0.81)] and specificity [0.88 (95% CI: 0.79--0.94)] of miR-1 for AMI. In addition, miR-133 showed a sensitivity [0.73 (95% CI: 0.55--0.85)] and specificity [0.88 (95% CI: 0.74--0.95)] for AMI. Moreover, the present study showed a sensitivity [0.83 (95% CI: 0.74--0.89)] and specificity [0.96 (95% CI: 0.82--0.99)] of miR-208 for AMI. A significant association was found between miR-208 and mortality after AMI (HR 1.09, 95% CI 1.01--1.18). It also indicated a sensitivity [0.84 (95% CI: 0.70--0.92)] and specificity [0.97 (95% CI: 0.87--0.99)] of miR-499 for AMI. CONCLUSIONS: Circulating miR-1, miR-133, miR-208, and miR-499 showed diagnostic values in AMI.


Assuntos
MicroRNAs/análise , Infarto do Miocárdio/sangue , Valor Preditivo dos Testes , Área Sob a Curva , Biomarcadores/análise , Biomarcadores/sangue , Humanos , MicroRNAs/sangue , Infarto do Miocárdio/fisiopatologia , Razão de Chances , Prognóstico , Curva ROC
20.
Artif Intell Med ; 118: 102115, 2021 08.
Artigo em Inglês | MEDLINE | ID: mdl-34412838

RESUMO

Predicting the associations between microRNAs (miRNAs) and diseases is of great significance for identifying miRNAs related to human diseases. Since it is time-consuming and costly to identify the association between miRNA and disease through biological experiments, computational methods are currently used as an effective supplement to identify the potential association between disease and miRNA. This paper presents a Multi-view Kernel Fusion Network (MvKFN) based prediction method (MvKFN-MDA) to address the problem of miRNA-disease associations prediction. A novel multiple kernel fusion framework Multi-view Kernel Fusion Network (MvKFN) is first proposed to effectively fuse different views similarity kernels constructed from different data sources in a highly nonlinear way. Using MvKFNs, both different base similarity kernels for miRNA, such as sequence, functional, semantic, Gaussian profile kernels and different base similarity kernels for diseases, such as semantic, Gaussian profile kernel are nonlinearly fused into two integrated similarity kernels, one for miRNA, another for disease. Then, miRNA and disease feature representations are extracted from the miRNA and disease integrated similarity kernels respectively. These features are then fed into a neural matrix completion framework which finally outputs the association prediction scores. The parameters of MvKFN-MDA are learned based on the known miRNA-disease association matrix in a supervised end-to-end way. We compare the proposed method with other state-of-the-art methods. The AUCs of our proposed method were superior to the existing methods in both 5-FCV and LOOCV on two open experimental datasets. Furthermore, 49, 48, and 47 of the top 50 predicted miRNAs for three high-risk human diseases, namely, colon cancer, lymphoma, and kidney cancer, are verified respectively using experimental literature. Finally, 100% accuracy from the top 50 predicted miRNAs is achieved when breast cancer is used as a case study to evaluate the ability of MvKFN-MDA for predicting a new disease without any known related miRNAs.


Assuntos
Neoplasias do Colo , Neoplasias Renais , Linfoma , MicroRNAs , Algoritmos , Área Sob a Curva , Neoplasias do Colo/diagnóstico , Biologia Computacional , Humanos , Neoplasias Renais/diagnóstico , Linfoma/diagnóstico , MicroRNAs/genética
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