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Objective To investigate the value of coronary computed tomography angiography(CCTA)for the non-invasive discrimination of chronic total occlusion(CTO)and subtotal occlu-sion(SO).Methods A total of 134 elderly patients undergoing CCTA and invasive coronary angio-graphy in our hospital from January 2019 to December 2021 were enrolled,and assigned into CTO group(62 cases)and SO(72 cases)according to the results of the examinations.Occlusion length,shape of proximal stump(blunt/conical),and collateral vessels were measured as anatomical find-ings.Transluminal attenuation gradient was obtained by a post-processing software.Univariate and multivariate logistic regression analyses were performed to explore factors related to CTO.Re-stricted cubic splines with three knots at the 10th,50th,and 90th percentiles were used to flexibly model the association of the factors with CTO,and ROC curve was plotted to evaluate the per-formance.Results Diabetes(OR=0.423,95％CI:0.186-0.963),occlusion length(OR=1.088,95％CI:1.031-1.148)and blunt-shaped stump(OR=2.453,95％CI:1.042-5.773)were inde-pendent predictors for discriminating CTO and SO(P＜0.05,P＜0.01).ROC curve analysis showed that the AUC value of occlusion length in the discrimination was 0.718(95％CI:0.634-0.792,P=0.001).Conclusion CCTA can be used to discriminate CTO and SO in elderly patients.
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Objective To construct a nomogram prediction model for major adverse cardiovascular events(MACE)within 1 year after percutaneous coronary intervention(PCI)in elderly patients with acute coronary syndrome(ACS).Methods A retrospective analysis was conducted on 551 patients with diagnosed ACS and undergoing PCI in Department of Cardiovascular Medicine of Air Force Medical Center from 1 January 2020 to 1 April 2022.According to the occurrence of MACE during 1 year of follow-up,they were classified into MACE group(n=176)and non-MACE group(n=375).Risk factors for the occurrence of MACE in elderly ACS patients within 1 year after PCI were analysed using univariate and multivariate logistic regression,a nomogram prediction model was constructed,and the predictive power of the model was assessed using the area under the ROC curve(AUC).Results The MACE group had significantly higher Gensini score,systemic immune-inflammation index,and GRACE score,but obviously lower prognostic nutritional index than the non-MACE group(P＜0.01).Multivariate logistic regression analysis showed that recent smoking(OR=2.222,95％CI:1.361-3.628,P=0.010),hyperlipidaemia(OR=1.881,95％CI:1.145-3.089,P=0.013),prognostic nutritional index(OR=4.645,95％CI:2.788-7.739,P=0.001),LVEF(OR=5.177,95％CI:3.160-8.483,P=0.001),systemic immune-inflammation index(OR=5.396,95％CI:3.179-9.159,P=0.001),and preoperative di-agnosis of non-STEMI(OR=2.829,95％CI:1.356-5.901,P=0.006)or STEMI(OR=3.451,95％CI:1.596-7.463,P=0.002)were independent influencing factors for occurrence of MACE after PCI in elderly ACS patients.ROC curve analysis showed that the AUC value of the nomo-gram model for predicting MACE within 1 year after PCI in elderly ACS patients was 0.888.Con-clusion Our developed nomogram model is simple and practical,and can effectively predict the occurrence of MACE within 1 year after PCI in elderly ACS patients.And external validation should be carried out to ensure its generality.
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Objective To investigate the changes in serum HP and ADMA levels in patients with ACI and the correlation of their levels with recanalization after venous thrombolysis and poor prognosis.Methods A total of 260 ACI patients undergoing venous thrombolysis in our hospital from January 2020 to March 2023 were retrospectively recruited,and were categorized into reper-fusion group(n=196)and non-reperfusion group(n=64)based on the efficacy of thrombolysis.After a 90-day follow-up,they were further divided into good prognosis group(n=159)and poor prognosis group(n=101)according to the results of a modified Rankin scale.Serum levels of HP and ADMA at admission were compared between the two groups.Logistic regression analysis was used to analyze the risk factors for non-reperfusion and poor prognosis in ACI patients.ROC curve analysis was performed to evaluate the predictive value of serum HP and ADMA levels for non-reperfusion and the diagnostic efficiency for poor prognosis in ACI patients.Results The non-reperfusion group exhibited notably elevated serum HP and ADMA levels than the reperfusion group(2.10±0.21 g/Lvs1.29±0.31 g/L,1.68±0.19 μmol/L vs 0.69±0.11 μmol/L,P＜0.01).HP and ADMA were identified as significant risk factors for uncanalization after treatment(P＜0.01).The AUC value of their combination in diagnosing uncanalization after venous thrombolys-is was 0.869(95％CI:0.830-0.908).Furthermore,significantly higher serum levels of HP and ADMA were observed in the poor prognosis group than the good prognosis group(2.27±0.19 g/L vs 1.15±0.34 g/L,1.72±0.21 μmol/L vs 0.64±0.10 μmol/L,P＜0.01).HP and ADMA were also recognized as influencing factors for poor prognosis in 90 d after treatment(P＜0.01).The AUC value was 0.816(95％CI:0.768-0.865)when their combination was used to predict poor prognosis in 90 d after treatment.Conclusion HP and ADMA are highly expressed in the se-rum of ACI patients with failed venous thrombolysis and poor prognosis.Their combined detec-tion can effectively predict both uncanalization and poor prognosis.
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Objective To detect the content of intestinal Escherichia coli(E.coli)in patients with acute ischemic stroke(AIS)and to analyze the relationship between the bacteria and short-term prognosis of patients with cerebral stroke.Methods A total of 75 elderly AIS patients admitted to our department from March to December 2022 were enrolled,and divided into good prognosis group(47 cases)and poor prognosis group(28 cases)according to the results of modified Rankin scale 3 months after discharge.Multivariate logistic regression analysis was used to analyze the factors affecting the prognosis of the patients,and ROC curve analysis was employed to analyze the predictive value of the intestinal bacterial content for the short-term prognosis of stroke pa-tients.Results The NIHSS score at admission and E.coli content were significantly higher in the poor prognosis group than the good prognosis group(P＜0.01).Multivariate logistic regression analysis showed that NIHSS score at admission(OR=1.302,95％CI:1.077-1.573,P=0.006)and E.coli content(OR=2.803,95％CI:1.454-5.404,P=0.002)were independent risk factors for short-term poor prognosis in the AIS patients.ROC curve analysis indicated that the AUC value was 0.758 for E.coli content,0.718 for NIHSS score,and 0.818 when the 2 indicators combined together.Conclusion Intestinal E.coli content and NIHSS score may be related to the poor prog-nosis of elderly AIS patients.The higher the content of E.coli is,the worse the recovery of neuro-logical function,which affects the short-term prognosis of the patients.
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Objective:To explore the variables associated with the severity of coronavirus disease 2019 (COVID-19) caused by the SARS-CoV-2 omicron variant during the epidemic in patients with myeloproliferative neoplasms (MPN).Methods:A cross-sectional study. During the SARS-CoV-2 omicron variant pandemic from December 15, 2022, to March 15, 2023, COVID-19 related data for patients with MPN who were treated at Peking University People′s Hospital were collected through an online questionnaire-based survey. All questionnaires and clinical data were checked by medical assistants. Logistic multivariate analysis was used to explore the prevalence and variables associated with the severity of COVID-19 in patients with MPN.Results:A total of 239 patients with MPN, including 90 (37.7%) presenting with essential thrombocythemia (ET), 50 (20.9%) with polycythemia vera (PV), and 99 (41.4%) with myelofibrosis (MF), were enrolled in the study. The 99 patients with MF included 87 (87.9%) with primary MF, 5 (5.1%) with post-PV MF, and 7 (7.1%) with post-ET MF. Overall, 239 (100%) patients reported that they experienced COVID-19 during the pandemic. Of these, 226 (94.6%) had mild disease, 4 (1.7%) had moderate disease, 7 (2.9%) had severe disease, and 2 (0.8%) had critical disease. Two (0.8%) patients with severe COVID-19 died, one of which suffered from MT and the other from PV. Multivariate analysis showed that older age ( OR=2.36, 95% CI 1.24-4.49), MF ( OR=10.22, 95% CI 1.13-92.80), or comorbidity ( OR=5.25, 95% CI 1.25-22.03) were associated with a significantly higher risk of developing moderate, severe, or critical COVID-19. Among patients with MF, higher risk stratification reflected an increased risk of developing moderate, severe, or critical COVID-19 ( P=0.034). Conclusion:During the omicron pandemic, older age, MF (especially higher-risk categories), and comorbidity were associated with a higher risk of developing moderate, severe, or critical COVID-19.
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Objective:To establish a prediction model of risk factors for early Q-T interval prolongation after acute myocardial infarction (AMI), which helps prevent and reduce the occurrence of acute malignant events.Methods:This is a case-control study. A total of 100 patients with Q-T interval prolongation after AMI who received treatment at Heilongjiang Provincial Hospital from January 2018 to December 2022 were included in this study. An additional 100 patients without Q-T interval prolongation after AMI who concurrently received treatment in the same hospital were also included in this study. Two model groups, including model group 1 (with Q-T interval prolongation, n = 50) and model group 2 (without Q-T interval prolongation, n = 50), and two test groups, including test group 1 (with Q-T interval prolongation, n = 50) and test group 2 (without Q-T interval prolongation, n = 50), were designated. Logistic regression analysis was performed to construct a prediction model of risk factors for Q-T interval prolongation. The area under the receiver operating characteristic curve was determined to evaluate the prediction model. The value of the prediction model was validated in the test groups. Results:Multivariate logistic regression showed that female gender ( OR = 2.307, 95% CI: 0.09-0.91, P = 0.041) and heart failure ( OR = 3.087, 95% CI: 1.15-8.27, P = 0.025) were independent risk factors for early Q-T interval prolongation after AMI. The area under the receiver operating characteristic curve of the prediction model was 0.770, with a sensitivity of 84.0%, a specificity of 66.0%, the Jordan index of 0.44, and the corresponding optimal critical value of 0.43. This indicates good fit of the model. Conclusion:Female gender and heart failure are independent risk factors for early Q-T interval prolongation after AMI. The model constructed based on the above-mentioned risk factors fits well and has a high predictive value, which helps reduce the occurrence of early Q-T interval prolongation after AMI.
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Objective:To investigate the predictive value of preoperative aspartate aminotransferase to alanine aminotransferase ratio (AAR) for early recurrence after radical resection of single small hepatocellular carcinoma.Methods:A retrospective cohort study was conducted to analyze the clinical data of 137 patients who underwent radical resection of liver cancer at the General Hospital of Ningxia Medical University from January 2017 to July 2021. These patients were categorized into a recurrence group ( n = 72) and a non-recurrence group ( n = 65) based on early postoperative recurrence. Univariate and multivariate logistic regression analyses were conducted in the training cohort to identify independent risk factors for early recurrence of small hepatocellular carcinomas. Subsequently, the AARs were grouped, and patients with similar propensity scores estimated by the logistic model were matched 1:1 using the Propensity Score Match method with a caliper value of 0.02 to eliminate confounders. Logistic regression analysis was then repeated to assess the predictive value of the matched AAR for postoperative recurrence in patients with single small hepatocellular carcinoma. Results:Univariate analysis revealed that age ( χ2 = 4.22, P = 0.040), the ratio of fibrinogen to albumin ( χ2 = 8.26, P = 0.004), and the AAR ( χ2 = 5.83, P = 0.016) were significantly associated with early recurrence of small liver cancer after radical resection. Multivariate logistic regression analysis further identified age ( P = 0.042), the ratio of fibrinogen to albumin ( P = 0.024), and the AAR ( P = 0.018) as independent risk factors for early recurrence of single small hepatocellular carcinoma following radical surgery. After excluding confounding factors using the Propensity Score Match method, 25 patient pairs were successfully matched. Post-matching logistic regression analysis revealed that an AAR > 0.74 ( P = 0.005) and age > 60 years ( P = 0.024) were independent risk factors for early recurrence in patients with single small hepatocellular carcinoma following radical resection. Conclusion:Preoperative AAR is an independent risk factor for early recurrence in patients with single small hepatocellular carcinoma following surgery, demonstrating excellent predictive value.
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ABSTRACT Introduction: The aim of this study was to assess the impact of aortic angulation (AA) on periprocedural and in-hospital complications as well as mortality of patients undergoing Evolut™ R valve implantation. Methods: A retrospective study was conducted on 264 patients who underwent transfemoral-approach transcatheter aortic valve replacement with self-expandable valve at our hospital between August 2015 and August 2022. These patients underwent multislice computer tomography scans to evaluate AA. Transcatheter aortic valve replacement endpoints, device success, and clinical events were assessed according to the definitions provided by the Valve Academic Research Consortium-3. Cumulative events included paravalvular leak, permanent pacemaker implantation, new-onset stroke, and in-hospital mortality. Patients were divided into two groups, AA ≤ 48° and AA > 48°, based on the mean AA measurement (48.3±8.8) on multislice computer tomography. Results: Multivariable logistic regression analysis was performed to identify predictors of cumulative events, utilizing variables with a P-value < 0.2 obtained from univariable logistic regression analysis, including AA, age, hypertension, chronic renal failure, and heart failure. AA (odds ratio [OR]: 1.73, 95% confidence interval [CI]: 0.89-3.38, P=0.104), age (OR: 1.04, 95% CI: 0.99-1.10, P=0.099), hypertension (OR: 1.66, 95% CI: 0.82-3.33, P=0.155), chronic renal failure (OR: 1.82, 95% CI: 0.92-3.61, P=0.084), and heart failure (OR: 0.57, 95% CI: 0.27-1.21, P=0.145) were not found to be significantly associated with cumulative events in the multivariable logistic regression analysis. Conclusion: This study demonstrated that increased AA does not have a significant impact on intraprocedural and periprocedural complications of patients with new generation self-expandable valves implanted.
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ABSTRACT Objective To identify factors associated with hospitalization in the intensive care unit in children and adolescents with COVID-19. Methods This was a retrospective cohort study using secondary data of hospitalized children and adolescents (zero to 18 years old) with COVID-19 reported in Paraíba from April 2020 to July 2021, totaling 486 records. Descriptive analysis, logistic regression and multilevel regression were performed, utilizing a significance level of 5%. Results According to logistic regression without hierarchical levels, there was an increased chance of admission to the intensive care unit for male patients (OR = 1.98; 95%CI 1.18 - 3.32), patients with respiratory distress (OR = 2.43; 95%CI 1.29 - 4.56), patients with dyspnea (OR = 3.57; 95%CI 1.77 - 7.18) and patients living in large cities (OR = 2.70; 95%CI 1.07 - 6.77). The likelihood of requiring intensive care was observed to decrease with increasing age (OR = 0.94; 95%CI = 0.90 - 0.97), the presence of cough (OR = 0.32; 95%CI 0.18 - 0.59) or fever (OR = 0.42; 95%CI 0.23 - 0.74) and increasing Gini index (OR = 0.003; 95%CI 0.000 - 0.243). According to the multilevel analysis, the odds of admission to the intensive care unit increased in male patients (OR = 1.70; 95%CI = 1.68-1.71) and with increasing population size of the municipality per 100,000 inhabitants (OR = 1.01; 95%CI 1.01-1.03); additionally, the odds of admission to the intensive care unit decreased for mixed-race versus non-brown-skinned patients (OR = 0.981; 95%CI 0.97 - 0.99) and increasing Gini index (OR = 0.02; 95%CI 0.02 - 0.02). Conclusion The effects of patient characteristics and social context on the need for intensive care in children and adolescents with SARS-CoV-2 infection were better estimated with the inclusion of a multilevel regression model.
RESUMO Objetivo Identificar fatores associados ao internamento na unidade de terapia intensiva de crianças e adolescentes com COVID-19. Método Estudo de coorte retrospectiva, com dados secundários, de crianças e adolescentes hospitalizados (zero a 18 anos), notificados com COVID-19 na Paraíba, de abril de 2020 a julho de 2021, totalizando 486 registros. Foram realizadas análise descritiva, regressão logística e regressão multinível, considerando o nível de significância de 5%. Resultados Na regressão logística sem níveis hierárquicos, ocorreu aumento da chance de internamento na unidade de terapia intensiva em pacientes do sexo masculino (RC = 1,98; IC95% 1,18 - 3,32), com desconforto respiratório (RC = 2,43; IC95% 1,29 - 4,56), dispneia (RC = 3,57; IC95% 1,77 - 7,18) e residentes em cidades com grande porte populacional (RC = 2,70; IC95% 1,07 - 6,77). Foi observada diminuição da chance de cuidados intensivos com aumento da idade em anos (RC = 0,94; IC95%=0,90 - 0,97), presença de tosse (RC = 0,32; IC95% 0,18 - 0,59), febre (RC = 0,42; IC95% 0,23 - 0,74) e aumento no Índice de Gini (RC = 0,003; IC95% 0,000 - 0,243). Na análise multinível, a chance de internamento na unidade de terapia intensiva aumentou no sexo masculino (RC = 1,70; IC95%=1,68-1,71) e por conta do aumento no porte populacional do município a cada 100 mil habitantes (RC = 1,01; IC95% 1,01 - 1,03); a chance de internamento na unidade de terapia intensiva diminuiu em pacientes pardos versus não pardos (RC = 0,981; IC95% 0,97 - 0,99) e por conta do aumento a cada pontuação do Índice de Gini (RC = 0,02; IC95% 0,02 - 0,02). Conclusão Os efeitos das condições próprias do paciente e do contexto social na necessidade de cuidados intensivos em crianças e adolescentes com infecção pelo SARS-CoV-2 são mais bem estimados com a inclusão de um modelo de regressão multinível nas análises.
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Response surface methodology (RSM) consists of mathematical and statistical techniques to develop models which help to understand the influence of various factors on a dependent variable of interest. The feasibility of RSM use to detect cases of periodontitis and its correlated factors has not yet been evaluated. This study developed mathematical models for periodontitis diagnosis independent of periodontal probing using the RSM. Demographic, socioeconomic, behavioral, systemic, local factors, and periodontitis were assessed in 176 volunteers. Periodontitis case was defined according to three different definitions: 1) ≥3 sites with clinical attachment level (CAL) ≥4 mm; 2) at least one site with CAL ≥4 mm and bleeding on probing; 3) ≥2 proximal sites with CAL ≥3 mm and ≥2 proximal sites with probing depth (PD) ≥4 mm (not on the same tooth) OR 1 site with PD ≥5 mm. 4th-degree polynomial equations showed high coefficients of determination (R²= 1) and were used to represent the mathematical models of periodontitis cases. According to definition 1, the diagnosis of periodontitis was accurate by including in the model: age, sex, education level, plaque index (PI), number of missing teeth, previous hygiene instructions, and body mass index (BMI). According to definition 2, the diagnosis of periodontitis was accurate by including in the model: age, sex, education level, income, PI, previous oral hygiene instructions, frequency of brushing and type of toothbrush, and use of mouthwash in the model. For an accurate diagnosis of periodontitis according to definition 3, the model included: age, education level, IP, number of missing teeth, previous oral hygiene instruction, BMI, and diabetes. The multifactorial mathematical models were able to diagnosis periodontitis according to different periodontitis case definitions using only variables of easy evaluation and non-invasive. (AU)
A metodologia de superfície de resposta (MSR) consiste em técnicas matemáticas e estatísticas para desenvolver modelos que ajudam a entender a influência de vários fatores em uma variável dependente de interesse. A viabilidade do uso da MSR para detectar casos de periodontite e seus fatores correlacionados ainda não foi avaliada. Este estudo desenvolveu modelos matemáticos para diagnóstico de periodontite independente da sondagem periodontal usando a MSR. Fatores demográficos, socioeconômicos, comportamentais, sistêmicos, locais e periodontite foram avaliados em 176 voluntários. O caso de periodontite foi definido de acordo com três definições diferentes: 1) ≥3 locais com nível de inserção clínica (NIC) ≥4 mm; 2) Um local com NIC ≥4 mm e sangramento à sondagem; 3) ≥2 locais proximais com NIC ≥3 mm e ≥2 locais proximais com profundidade de sondagem (PS) ≥4 mm (não no mesmo dente) OU 1 local com PS ≥5 mm. Equações polinomiais de 4º grau apresentaram altos coeficientes de determinação (R²= 1) e foram utilizadas para representar os modelos matemáticos dos casos de periodontite. De acordo com a definição 1, o diagnóstico de periodontite foi preciso ao incluir no modelo: idade, sexo, escolaridade, índice de placa (IP), número de dentes perdidos, instruções de higiene anteriores e índice de massa corporal (IMC). De acordo com a definição 2, o diagnóstico de periodontite foi preciso ao incluir no modelo: idade, sexo, escolaridade, renda, IP, instruções prévias de higiene bucal, frequência de escovação e tipo de escova dental e uso de enxaguatório bucal no modelo. Para um diagnóstico preciso de periodontite de acordo com a definição 3, o modelo incluiu: idade, escolaridade, IP, número de dentes perdidos, instrução prévia de higiene oral, IMC e diabetes. Os modelos matemáticos multifatoriais foram capazes de diagnosticar a periodontite de acordo com diferentes definições de casos de periodontite usando apenas variáveis de fácil avaliação e não invasivas. (AU)
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Estimar a prevalência de diabetes mellitus e os fatores associados em adultos. Trata-se de um inquérito realizado com 1.637 indivíduos nas zonas urbana e rural do município de Rio Branco, Acre. Diabetes foi definido pela presença de glicemia no plasma em jejum ≥ 126 mg/dl ou utilização de hipoglicemiante oral ou insulina. Medidas de associação foram estimadas por regressão logística hierarquizada. A prevalência de diabetes foi de 6,5% (n = 202). Após análise, a chance de ser diabético esteve independente e positivamente associada a idade ≥ 60 anos (OR: 6,67; IC95%: 1,83-24,30); história familiar de diabetes mellitus (OR: 2,88; IC95%: 1,43-5,81); circunferência da cintura aumentada (OR: 1,83; IC95%:1,01-3,33); dislipidemia (OR: 2,95; IC95%: 1,34-6,49); anemia (OR: 3,15; IC95%: 1,30-7,60); e doença renal crônica (DRC) (OR: 4,00; IC95%: 1,70-9,33). Foi detectada uma prevalência de 6,5%, estando o diabetes associado com idade, história familiar, anemia e DRC. Indica-se a necessidade do adequado rastreio de comorbidades nesses pacientes.
To estimate the prevalence of diabetes mellitus and associated factors in adults.Survey carried out with 1,637 individuals in urban and rural areas of the municipality of Rio Branco, state of Acre. Diabetes was defined by the presence of fasting plasma glucose ≥ 126 mg/dl or the use of oral hypoglycemic agents or insulin. Association measures were estimated by hierarchical logistic regression.The prevalence of diabetes was 6.5% (n = 202). After analysis, the chance of being diabetic was independently and positively associated with age ≥ 60 years (OR: 6.67; 95%CI: 1.83-24.30); family history of diabetes mellitus (OR: 2.88; 95%CI: 1.43-5.81); increased waist circumference (OR: 1.83; 95%CI: 1.01-3.33); dyslipidemia (OR: 2.95; 95%CI: 1.34-6.49); anemia (OR: 3.15; 95%CI: 1.30-7.60); and chronic kidney disease (CKD) (OR: 4.00; 95%CI: 1.70-9.33). A prevalence of 6.5% was detected, with diabetes associated with age, family history, anemia, and CKD. The need for adequate screening of comorbidities in these patients is indicated.
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Objective:To construct a simple model of arteriovenous fistula classification,and to achieve the classification of arteriovenous fistula in hemodialysis patients.Methods:The study was a retrospective analysis, a total of 304 hemodialysis patients with internal fistula in People′s Hospital of Deyang City from January 2016 to January 2021 were selected by convenience sampling method,depending on whether the internal fistula was dysfunctional, patients were divided into 64 in the internal fistula failure group and 240 in the internal fistula patency group. Independent influence factors and their regression coefficient were obtained by single-factor analysis and logistic regression analysis, The risk score formula was established based on the regression coefficient to form a simple model of internal fistula classification.The model was evaluated by receiver operating characteristic curve and the scoring criteria for internal fistula classification was determined.Results:Logistic regression analysis showed that diabetes mellitus, hypotension, age≥60 years old, compression time≥30 min, blood phosphorus>1.78 mmol/L, triglyceride>1.71 mmol/L and fibrinogen>4 g/L were independent influencing factors of internal fistula failure (all P<0.05).The area under the receiver operating characteristic curve was 0.858(95% CI 0.789-0.928, P<0.01), and the best critical value of the internal fistula classification was 7.5, the sensitivity was 80.4% and the specificity was 84.8%. Conclusions:By obtaining the predictors of internal fistula failure, conducted the risk score, and constructed a simple model of internal fistula classification, which can effectively predicted the risk of internal fistula failure. It is conducive to the implementation of internal fistula classification management and the puncture of corresponding grade, to ensure the pathway safety of patients.
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Objective:To analyze the influencing factors of delayed nausea and vomiting in patients with primary liver cancer after transarterial chemoembolization based on Logistic regression model and decision tree model.Methods:This was a cross-sectional study. A total of 236 patients with primary liver cancer after transarterial chemoembolization in The Second Affiliated Hospital of Air Force Military Medical University from March 2021 to June 2022 were conveniently selected as the research subjects. The factors related to delayed nausea and vomiting were collected, and Logistic regression and decision tree models were established, respectively, and the differences between the two models were compared.Results:The incidence of delayed nausea and vomiting of patients with primary liver cancer after transarterial chemoembolization was 45.34% (107/236). Logistic regression model showed that age, anxiety, sleep disorder, emetic risk level of chemotherapeutic drugs, embolic agent type, and pain 24 hours after surgery were the influencing factors of delayed nausea and vomiting in patients with primary liver cancer after transarterial chemoembolization(all P<0.05). Decision tree model showed that age, sleep disorder, emetic risk level of chemotherapeutic drugs, embolic agent type, and pain 24 hours after surgery were the influencing factors of delayed nausea and vomiting in patients with primary liver cancer after transarterial chemoembolization (all P<0.05). The classification accuracy rates of Logistic regression, decision tree model and combined diagnosis of two models were 72.9%, 71.2% and 72.0% respectively; the areas under the ROC curve were 0.778, 0.781 and 0.806 respectively, with no significant difference (all P>0.05). Conclusions:The analysis results of Logistic regression and decision tree model on the influencing factors of delayed nausea and vomiting in patients with primary liver cancer after transarterial chemoembolization are highly consistent, which can be combined to provide a more comprehensive reference for the evaluation and intervention of medical staff.
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Objective:To explore the construction of a Logistic prediction model and countermeasures for type 2 diabetic nephropathy based on clinical data.Methods:The patients with type 2 diabetic nephropathy admitted to Shijiazhuang Second Hospital from September 2019 to September 2021 (study group) were selected and the patients were selected according to a 1∶1 ratio using individual matching (control group), each group with 200 patients. Single and multiple factors analysis were used to analyze the factors influencing type 2 diabetic nephropathy, and Logistic regression equation models were developed to verify their predictive value.Results:Logistic regression equation model showed that the course of type 2 diabetes, glycosylated hemoglobin (HbA 1c), fasting plasma glucose (FPG), homocysteine (Hcy), urinary microalbumin, and serum creatinine (Scr) were high risk factors for type 2 diabetic nephropathy ( P<0.05). The results of Logistic regression model evaluation showed that the model was established with statistical significance, and the coefficients of the regression equations had statistically significant differences. The Hosmer-Lemeshow goodness-of-fit test showed that the model fitting effect was good. Logistic regression model was used to statistically analyzed the data set, and the receiver operating characteristic (ROC) curve of type 2 diabetic nephropathy was drawn, the area under the curve was 0.949(95% CI 0.922 - 0.968), the prediction sensitivity was 81.50%, the specificity was 95.50%, the calibration curve showed that the predicted results was in good agreement with the observed results. Conclusions:The independent predictors of type 2 diabetic nephropathy involve HbA 1c, FPG, Hcy, urinary microalbumin. The Logistic prediction model based on these predictors has reliable predictive value and can help guide clinical diagnosis and treatment.
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Objective:To investigate the risk factors of moderate to severe pain in patients with non-small cell lung cancer within 3 days after lobectomy.Methods:The clinical data of 297 patients with non-small cell lung cancer who underwent lobectomy in the Department of Thoracic Surgery, Sun Yat-sen University Cancer Center from December 2020 to June 2021 were retrospectively analyzed. A numerical rating scale was used to score the most severe pain within 3 days after surgery. Pain score ≥ 4 was defined as moderate to severe pain. The risk factors for moderate to severe pain were analyzed by binary Logistic regression. General linear model repeated measures and linear mixed models were used to analyze the trend of risk factors influencing postoperative pain with time.Results:The incidence of moderate to severe pain was 34.2% (102/297), 59.8% (178/297), 66.4% (198/297), and 28.2% (84/297) on days 0, 1, 2, and 3 after surgery respectively. The risk for moderate to severe pain was significantly higher in patients undergoing thoracotomy than patients undergoing thoracoscopic surgery on days 1 ( OR = 1.99, P = 0.009), 2 ( OR = 3.08, P < 0.001), and 3 ( OR = 3.88, P < 0.001) after surgery. However, the risk for moderate to severe pain in patients undergoing thoracotomy was slightly, but not significantly, higher than that in patients undergoing thoracoscopic surgery ( OR = 1.53, P = 0.087). The risk for moderate to severe pain was higher in female patients than male patients on day 2 ( OR = 1.62, P = 0.077), and in particular on day 3 after surgery ( OR = 2.39, P = 0.002). Prophylactic use of parecoxib significantly reduced the risk of moderate to severe pain on day 0 ( OR = 0.32, P = 0.004), 1 ( OR = 0.20, P < 0.001), 2 ( OR = 0.36, P < 0.001) and 3 ( OR = 0.56, P = 0.047). Conclusion:The incidence of moderate to severe pain on days 1 and 2 after lobectomy was relatively high in patients with non-small cell lung cancer. Patients undergoing thoracotomy have a higher risk of moderate to severe pain than those who underwent thoracoscopic surgery. Female patients have a higher risk for moderate to severe pain on days 2 and 3 after surgery than male patients. Prophylactic use of parecoxib can decrease the risk for moderate to severe pain in patients with non-small cell lung cancer.
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Objective:To investigate the role of a simple Nomogram model in evaluating the severity of mycoplasma pneumoniae pneumonia (MPP) in adults.Methods:The clinical data of 162 patients with MPP who received treatment in Wenzhou Central Hospital from March 2015 to October 2022 were retrospectively analyzed. These patients were divided into a severe group ( n = 67) and a common group ( n = 95) according to whether they were diagnosed with severe MPP. The clinical data of patients were recorded. Fourteen clinical variables were screened, including age, sex, onset season, fever, heat peak, fever duration, cough duration, white blood cell count, percentage of neutrophils, percentage of lymphocytes, hemoglobin, platelet count, C-reactive protein, and procalcitonin. Multivariate logistic regression analysis of statistically significant variables in univariate analysis was performed. The Nomogram model was constructed with the R language software package (version 3.6.2). The model was verified with a calibration curve and receiver operating characteristic curve. Results:Univariate analysis results showed that in the severe group, the fever peak ( Z = 5.03, P < 0.001) was higher, fever duration ( χ2 = 27.55, P < 0.001), and cough duration ( χ2 = 28.72, P < 0.001) were longer, white cell count ( t = 2.93, P = 0.004), percentage of neutrophils ( t = 9.08, P < 0.001), C-reactive protein ( t = 35.05, P < 0.001), and procalcitonin level ( t = 15.09, P < 0.001) were greater compared with the common group. The percentage of lymphocytes ( t = 1.16, P < 0.001), hemoglobin level ( t = 1.22, P < 0.001), and platelet count ( t = 2.82, P < 0.001) in the severe group were significantly lower than those in the common group. Multivariate logistic regression analysis results showed that heat peak, cough duration, and C-reactive protein were positively correlated with the severity of MPP (all P < 0.05). The percentage of lymphocytes, hemoglobin concentration, and platelet count were negatively correlated with the severity of MPP (all P < 0.05). The establishment and validation results of the Nomogram model showed that the accuracy of the model was good, with a sensitivity of 88.73%, a specificity of 77.61%, and a C-index of 0.904. Conclusion:Heat peak, cough duration, percentage of lymphocytes, platelet count, and C-reactive protein are closely related to the severity of early MPP. A simple Nomogram model can be one of the tools for early assessment of the severity of MPP.
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Objective:To analyze risk factors for prognosis of adult patients with traumatic brain injury (TBI), construct the prognostic model of TBI and evaluate its predictive value.Methods:A case-control study was used to analyze the clinical data of 522 patients with TBI admitted to Xijing Hospital of Air Force Medical University from March 2011 to September 2019, including 438 males and 84 females; aged 18-75 years [(44.9±15.0)years]. According to the Glasgow outcome score (GOS) at discharge, the patients were divided into good prognosis group (GOS 4-5 points, n=165) and poor prognosis group (GOS 1-3 points, n=357). The two groups were compared with regards to qualitative data such as sex, underlying diseases, causes of injury, multiple injuries, open injuries, intracranial foreign bodies, cerebral herniation, consciousness status on admission and at discharge, surgery, lung infection on admission, tracheostomy, ventilator-assisted ventilation, hospital-acquired pneumonia/pathogenic bacteria and intracranial infection, and quantitative data such as Glasgow coma score (GCS) on admission and at discharge, age, measurements on admission [systolic blood pressure, diastolic blood pressure, mean arterial pressure, temperature, heart rate, creatinine, urea nitrogen, blood sodium, blood potassium, blood glucose, prothrombin time (PT), activated partial thromboplastin time (APTT), platelets, international normalized ratio (INR), pupil size of both eyes] and length of hospital stay. Univariate analysis and Lasso regression analysis were used to screen the risk factors affecting the prognosis of TBI patients, and the selected influencing factors were included in multivariate Logistic regression analysis to identify independent risk factors and construct regression equations. R was used to draw a visual nomogram based on regression equation for predicting the prognosis of TBI patients. The prognostic predictive value of the nomogram was evaluated by using the receiver operating characteristic (ROC) curve, and the area under the curve (AUC), Youden index, sensitivity, specificity and consistency index (C index) were calculated. Results:Univariate analysis showed that there were significant differences between the two groups in underlying diseases, open injuries, cerebral herniation, consciousness status on admission and at discharge, lung infection on admission, tracheostomy, ventilator-assisted ventilation, hospital-acquired pneumonia/pathogenic bacteria, GCS on admission and at discharge, age, and measurements on admission (systolic blood pressure, mean arterial pressure, body temperature, heart rate, creatinine, urea nitrogen, blood potassium, blood glucose, PT, INR, pupil size of right eye) (all P<0.05 or 0.01). There were no significant differences between the two groups in gender, causes of injury, multiple injuries, intracranial foreign bodies, surgery, intracranial infection, measurements on admission (diastolic blood pressure, blood sodium, APTT, platelets, pupil size of left eye) and length of hospital stay (all P>0.05). After screening by Lasso regression model, the results of multivariate Logistic regression analysis showed that GCS on admission ( OR=0.67, 95% CI 0.62, 0.73, P<0.01), age ( OR=1.03, 95% CI 1.01, 1.04, P<0.01), blood glucose on admission ( OR=1.17, 95% CI 1.06, 1.30, P<0.01) and INR on admission ( OR=17.08, 95% CI 2.12, 137.89, P<0.01) could be used as the main risk factors to construct the prediction model, and the regression equation was constructed: Logit [ P/(1- P)]=-0.398× "GCS on admission"+0.024× "age"+0.158×"blood glucose on admission"+2.838×"INR on admission"-1.693. The AUC for the prognosis prediction in adult patients with TBI using R based on a visual nomogram model was 0.87 (95% CI 0.83, 0.89, P<0.01). The Youden index for the predicted probability was 0.60 (sensitivity of 85.2% and specificity of 75.2%), with the C index of 0.87. Conclusion:Age, GCS on admission, blood glucose on admission and INR on admission are the main risk factors affecting the prognosis of TBI in adults, and the nomogram drawn by these parameters can better predict their clinical outcome.
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Objective:To investigate the clinical outcome after surgery and first 131I treatment in patients with moderate-risk papillary thyroid cancer (PTC), and analyze the relevant factors that affect the therapeutic effect. Methods:From January 2018 to April 2019, 135 patients (48 males, 87 females; age (42.7±11.1) years) with moderate-risk PTC in the Second Affiliated Hospital of Chongqing Medical University were retrospectively analyzed. According to the 2015 American Thyroid Association (ATA) guidelines, patients were divided into excellent response (ER) group, inderteriminate response (IDR) group, biochemical incomplete response (BIR) group and structural incomplete response (SIR) group, of which IDR, BIR, SIR were collectively referred to as the non-ER group. χ2 test and Mann-Whitney U test were used to compare the general clinical features between the ER and non-ER groups, and then multivariate logistic regression analysis was performed. The predicted value of pre-ablation stimulated thyroglobulin (ps-Tg) to ER was assessed by ROC curve analysis. Results:The treatment responses of 94 patients were ER, and those of 41 were non-ER. The differences in tumor size (0.80(0.50, 1.10) vs 1.00(0.55, 1.50) cm; U=1 491.50, P=0.036), the number of metastatic lymph nodes (3(2, 5) vs 4(2, 12); U=1 422.00, P=0.015), metastatic lymph node size (0.50(0.30, 0.65) vs 0.50(0.30, 1.45) cm; U=1 396.50, P=0.013), metastatic lymph node involvement rate (50%(30%, 70%) vs 60%(50%, 85%); U=1 441.50, P=0.024), metastatic lymph node location (central/lateral: 76/18 vs 24/17; χ2=7.40, P=0.007) and ps-Tg level (2.1(0.8, 5.3) vs 14.0(3.2, 35.2) μg/L; U=680.00, P<0.001) were statistically significant between the ER and non-ER groups. Multivariate logistic regression analysis showed that ps-Tg (odds ratio ( OR)=1.200, 95% CI: 1.107-1.302, P<0.001) was an independent factor influencing ER. The cut-off value of ps-Tg for predicting ER was 7.38 μg/L, with the sensitivity and specificity of 68.3%(28/41) and 87.2%(82/94) respectively. Conclusion:Moderate-risk PTC patients with smaller tumor size, fewer metastatic lymph nodes, lower metastatic lymph node involvement rate, metastatic lymph nodes in central area, smaller metastatic lymph node size, and ps-Tg<7.38 μg/L have better therapeutic effect after initial 131I treatment.
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Objective:To construct a prediction model for difficult tracheal intubation in the patients with obstructive sleep apnea-hypopnea syndrome (OSAHS).Methods:A total of 324 patients with OSAHS undergoing surgery with general anesthesia, admitted to our hospital from June 2019 to June 2021, were included in model group, and 175 patients with OSAHS undergoing surgery with general anesthesia, admitted from July 2021 to July 2022, were selected and served as validation group. The patients in model group were divided into occurrence group and non-occurrence group according to whether difficult tracheal intubation occurred. Logistic regression was used to construct the prediction model, and R4.2.1 software was used to draw the risk nomogram and calibration curve. The predictive accuracy of the model was evaluated by the area under the receiver operating characteristic curve.Results:Body mass index (BMI), sagittal minimum cross-sectional area, horizontal minimum cross-sectional area and mandibular distance were risk factors for difficult tracheal intubation in OSAHS patients ( P<0.05). A prediction model was developed using the above factors: Logit P=33.726+ 1.411×BMI score-0.014×sagittal airway minimum cross-sectional area-0.013×airway horizontal minimum cross-sectional area-0.312× mandibular distance. The area under the receiver operating characteristic curve was 0.846, Youden index 0.585, sensitivity 0.831, specificity 0.755, and the accuracy 0.889 (Hosmer-Lemeshow test χ2=9.24, P=0.322) in model group. The area under the external validation curve was 0.802, Youden index 0.545, sensitivity 0.636, specificity 0.908, and the accuracy 0.893 (Hosmer-Lemeshow test χ2=10.24, P=0.287) in validation group. Conclusions:The prediction model based on BMI, sagittal minimum cross-sectional area of airway, horizontal minimum cross-sectional area of airway and mandibular distance has a high value in predicting the risk of difficult tracheal intubation in patients with OSAHS.
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Objective To investigate the efficacy and safety of bivalirudin versus unfractionated heparin during perioperative primary percutaneous coronary intervention(PCI)in elderly patients with acute ST-segment elevation myocardial infarction(STEMI).Methods A total of 423 elderly patients with acute STEMI who underwent primary PCI in our hospital were consecutively en-rolled in this study.According to different perioperative anticoagulant regimens,they were divided into bivalirudin group(187 cases)and unfractionated heparin group(236 cases).Baseline data,characteristics of interventional procedures and complications during hospitalization were ana-lyzed.Primary endpoint was major adverse cardiac or cerebral events(MACCE).Secondary end-points were net adverse clinical events.Other observational indicators included stent thrombosis,acquired thrombocytopenia,BARC types 1-2 bleeding and total bleeding events.Results In-hospital MACCE and all-cause mortality were significantly lower in the bivalirudin group than unfractionated heparin group(3.7％vs 9.7％,P=0.021;3.7％vs 8.9％,P=0.039).Univariate logistic regression analysis showed that perioperative application of bivalirudin significantly reduced all-cause mortality in the patients with Killip grade Ⅰ and creatinine clearance ≥60 ml/min when compared with unfractionated heparin(P＜0.05).Conclusion In elderly patients with acute STEMI,perioperative use of bivalirudin significantly reduces the incidences of MACCE and all-cause death during hospitalization,especially in the patients with Killip grade Ⅰ and creatinine clearance ≥60 ml/min.