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1.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-313435

ABSTRACT

Background: The coronavirus disease 2019 (COVID-19) has caused global pandemic, resulting in considerable mortality. The risk factors, clinical treatments and especially comprehensive risk models for COVID-19 death are urgently warranted. Methods In this retrospective study, 281 non-survivors and 712 survivors with propensity score matching by age, sex and comorbidities were enrolled from January 13, 2020 to March 31, 2020. Results Higher SOFA, qSOFA, APACHE II and SIRS scores, hypoxia, elevated inflammatory cytokines, multi-organ dysfunction, decreased immune cells subsets and complications were significantly associated with the higher COVID-19 death risk. In addition to traditional predictors for death risk, including APACHE II (AUC = 0.83), SIRS (AUC = 0.75), SOFA (AUC = 0.70) and qSOFA scores (AUC = 0.61), another four prediction models that included immune cells subsets (AUC = 0.90), multiple organ damage biomarkers (AUC = 0.89), complications (AUC = 0.88) and inflammatory-related indexes (AUC = 0.75) were established. Additionally, the predictive accuracy of combining these risk factors (AUC = 0.950) was also significantly higher than that of each risk group alone, outperforming previous risk models, which was significant for early clinical management for COVID-19. Conclusions The potential risk factors could help to predict the clinical prognosis of COVID-19 patients at an early stage. The combined model might be more suitable for the death risk evaluation of COVID-19.

2.
BMC Infect Dis ; 21(1): 951, 2021 Sep 14.
Article in English | MEDLINE | ID: covidwho-1412707

ABSTRACT

BACKGROUND: The coronavirus disease 2019 (COVID-19) has caused a global pandemic, resulting in considerable mortality. The risk factors, clinical treatments, especially comprehensive risk models for COVID-19 death are urgently warranted. METHODS: In this retrospective study, 281 non-survivors and 712 survivors with propensity score matching by age, sex, and comorbidities were enrolled from January 13, 2020 to March 31, 2020. RESULTS: Higher SOFA, qSOFA, APACHE II and SIRS scores, hypoxia, elevated inflammatory cytokines, multi-organ dysfunction, decreased immune cell subsets, and complications were significantly associated with the higher COVID-19 death risk. In addition to traditional predictors for death risk, including APACHE II (AUC = 0.83), SIRS (AUC = 0.75), SOFA (AUC = 0.70) and qSOFA scores (AUC = 0.61), another four prediction models that included immune cells subsets (AUC = 0.90), multiple organ damage biomarkers (AUC = 0.89), complications (AUC = 0.88) and inflammatory-related indexes (AUC = 0.75) were established. Additionally, the predictive accuracy of combining these risk factors (AUC = 0.950) was also significantly higher than that of each risk group alone, which was significant for early clinical management for COVID-19. CONCLUSIONS: The potential risk factors could help to predict the clinical prognosis of COVID-19 patients at an early stage. The combined model might be more suitable for the death risk evaluation of COVID-19.


Subject(s)
COVID-19 , Sepsis , Humans , Intensive Care Units , Organ Dysfunction Scores , Prognosis , ROC Curve , Retrospective Studies , Risk Factors , SARS-CoV-2
3.
BMC Infect Dis ; 21(1): 951, 2021 Sep 14.
Article in English | MEDLINE | ID: covidwho-1406708

ABSTRACT

BACKGROUND: The coronavirus disease 2019 (COVID-19) has caused a global pandemic, resulting in considerable mortality. The risk factors, clinical treatments, especially comprehensive risk models for COVID-19 death are urgently warranted. METHODS: In this retrospective study, 281 non-survivors and 712 survivors with propensity score matching by age, sex, and comorbidities were enrolled from January 13, 2020 to March 31, 2020. RESULTS: Higher SOFA, qSOFA, APACHE II and SIRS scores, hypoxia, elevated inflammatory cytokines, multi-organ dysfunction, decreased immune cell subsets, and complications were significantly associated with the higher COVID-19 death risk. In addition to traditional predictors for death risk, including APACHE II (AUC = 0.83), SIRS (AUC = 0.75), SOFA (AUC = 0.70) and qSOFA scores (AUC = 0.61), another four prediction models that included immune cells subsets (AUC = 0.90), multiple organ damage biomarkers (AUC = 0.89), complications (AUC = 0.88) and inflammatory-related indexes (AUC = 0.75) were established. Additionally, the predictive accuracy of combining these risk factors (AUC = 0.950) was also significantly higher than that of each risk group alone, which was significant for early clinical management for COVID-19. CONCLUSIONS: The potential risk factors could help to predict the clinical prognosis of COVID-19 patients at an early stage. The combined model might be more suitable for the death risk evaluation of COVID-19.


Subject(s)
COVID-19 , Sepsis , Humans , Intensive Care Units , Organ Dysfunction Scores , Prognosis , ROC Curve , Retrospective Studies , Risk Factors , SARS-CoV-2
4.
Med Clin (Engl Ed) ; 155(8): 327-334, 2020 Oct 23.
Article in English | MEDLINE | ID: covidwho-1057042

ABSTRACT

BACKGROUND: Novel coronavirus disease 2019 (COVID-19) is an emerging infectious disease caused by SARS-CoV-2. At the peak of the outbreak in Wuhan (January and February), there are two types of COVID-19 patients: laboratory confirmation and clinical diagnosis. This study aims to compare and analyze the clinical outcomes and characteristics of confirmed and clinically diagnosed COVID-19 patients to determine whether they are of the same type and require equal treatment. More importantly, the prognostic factors of COVID-19 patients are explored. METHODS: A total of 194 hospitalized patients with COVID-19 pneumonia were retrospectively studied. Demographic data, clinical characteristcs, laboratory results and prognostic information were collected by electronic medical record system and analyzed. RESULTS: Among 194 subjects included, 173 were confirmed and 21 were clinically diagnosed. There were no significant differences in clinical outcomes (mortality rate 39[22.54%] vs 7[33.33%], P = 0.272) and hospital stay (19.00 vs 16.90 days, P = 0.411) between the confirmed and clinically diagnosed group, and prognostic factors were similar between them. Older age, lower albumin levels, higher serum Lactate dehydrogenase (LDH) levels, higher D-D levels, longer prothrombin time (PT), higher IL-6 levels, lower T cells indicated poor prognosis in patients with COVID-19 pneumonia. NK cell has the highest AUC among all measured indicators (NK AUC = 0.926, P < 0.001). CONCLUSION: Laboratory-confirmed and clinically diagnosed COVID-19 patients are similar in clinical outcomes and most clinical characteristics. They are of the same type and require equal treatment. Age, AST, LDH, BUN, PT, D-D, IL6, white blood cell and neutrophil counts, T cell and T cell subset counts can efficiently predict clinical outcomes.


ANTECEDENTES: El nuevo coronavirus 2019 (COVID-19) es una nueva enfermedad infecciosa causada por el virus SARS-CoV-2. Durante el pico del brote en Wuhan (enero y febrero 2020), se detectaron dos tipos de pacientes portadores del COVID-19: pacientes confirmados a través de pruebas de laboratorio y pacientes confirmados por diagnóstico clínico. El objetivo de este estudio es comparar y analizar los resultados clínicos y las características de los pacientes con COVID-19 confirmados y clínicamente diagnosticados para determinar si son del mismo tipo y si necesitan el mismo tratamiento. El estudio es importante también para explorar los factores pronósticos de los pacientes con COVID-19. MÉTODOS: Un total de 194 pacientes hospitalizados con neumonía COVID-19 fueron estudiados retrospectivamente. Se utilizó un sistema de registro médico electrónico para recopilar los datos demográficos, las características clínicas, los resultados de laboratorio y la información pronóstica, para luego ser analizada. RESULTADOS: De los 194 pacientes incluidos, 173 dieron positivo y 21 fueron diagnosticados clínicamente. No se presentaron diferencias significativas en los resultados clínicos (tasa de mortalidad 39 [22,54%] vs. 7 [33,33%], p = 0,272) y la estancia hospitalaria (19,00 vs. 16,90 días, p = 0,411) entre el grupo de confirmados y el grupo diagnosticado clínicamente, y los factores pronósticos fueron similares entre ellos. Edad avanzada, niveles más bajos de albúmina, niveles más altos de lactato deshidrogenasa (LDH) en suero, niveles más altos de D-D, mayor tiempo de protrombina (PT), altos niveles de IL-6, células T más bajas indicaban mal pronóstico en pacientes con neumonía por COVID-19. La célula NK tiene el AUC más alto entre todos los indicadores medidos (NK AUC = 0,926, p < 0,001). CONCLUSIÓN: Los grupos de pacientes COVID-19 confirmados en laboratorio y diagnosticados clínicamente arrojan resultados clínicos similares y tienen la mayoría de las características clínicas. Son del mismo tipo y requieren el mismo tratamiento. La edad, AST, LDH, BUN, PT, D-D, IL6, los recuentos de glóbulos blancos y neutrófilos, recuentos de subgrupos de células T y células T pueden predecir los resultados clínicos de forma eficaz.

5.
SSRN; 2020.
Preprint | SSRN | ID: ppcovidwho-725

ABSTRACT

Background: Clinical characteristics evaluation and risk factors identification of the coronavirus disease 2019 (COVID-19) have been well studied, while effecti

6.
Clin Biochem ; 81: 9-12, 2020 Jul.
Article in English | MEDLINE | ID: covidwho-154983

ABSTRACT

OBJECTIVE: To analyze the diagnosis and treatment of patients with chronic renal failure complicated with novel coronavirus pneumonia, and to evaluate the effect of blood purification technology on the treatment and prognosis of such patients. METHODS: Two COVID-19 cases undergoing hemodialysis with chronic renal failure were retrospectively analysed in our hospital. RESULTS: Two COVID-19 patients were admitted to hospital due to cough, with or without fever. Laboratory tests showed decreased lymphocyte count, elevated PCT, IL-10, IL-6, TNF-α, IL-2R, high-sensitivity cardiac troponin I, NT-proBNP, creatinine, and urea nitrogen. Chest CT scan showed multiple blurred plaques and patchy shadows in both patients. Two patients received continuous venovenous hemodiafiltration (CVVHDF) every other day for 4-6 h everytime, in addition to the standard treatment. After CVVHDF, not only cytokines were reduced, but also liver function and cardiac function significantly improved. Both patients did not develop severe pneumonia. They were discharged on March 1, 2020 when meeting the discharge criteria. CONCLUSION: Two COVID-19 patients on maintenance hemodialysis discharged after a month of hospitalization. The removal of cytokines through blood purification technology may be beneficial for the recovery of COVID-19 patients.


Subject(s)
Betacoronavirus/genetics , Betacoronavirus/immunology , Coronavirus Infections/complications , Kidney Failure, Chronic/complications , Pneumonia, Viral/complications , Renal Dialysis , Adult , Aged , Anti-Bacterial Agents/therapeutic use , Antiviral Agents/therapeutic use , COVID-19 , Coronavirus Infections/blood , Coronavirus Infections/drug therapy , Coronavirus Infections/virology , Cytokines/blood , Female , Hospitalization , Humans , Kidney Failure, Chronic/blood , Length of Stay , Male , Pandemics , Pneumonia, Viral/blood , Pneumonia, Viral/drug therapy , Pneumonia, Viral/virology , Prognosis , Retrospective Studies , SARS-CoV-2 , Treatment Outcome
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