Background: The statistical methods to analyze and predict the related dangerous factors of deep fungal infection in lung cancer patients were several, such as logic regression analysis, meta-analysis, multivariate Cox proportional hazards model analysis, retrospective analysis, and so on, but the results are inconsistent. Materials and Methods: A total of 696 patients with lung cancer were enrolled. The factors were compared employing Student's t-test or the Mann-Whitney test or the Chi-square test and variables that were significantly related to the presence of deep fungal infection selected as candidates for input into the final artificial neural network analysis (ANN) model. The receiver operating characteristic (ROC) and area under curve (AUC) were used to evaluate the performance of the artificial neural network (ANN) model and logistic regression (LR) model. Results: The prevalence of deep fungal infection from lung cancer in this entire study population was 32.04%(223/696), deep fungal infections occur in sputum specimens 44.05%(200/454). The ratio of candida albicans was 86.99% (194/223) in the total fungi. It was demonstrated that older (${\geq}65$ years), use of antibiotics, low serum albumin concentrations (${\leq}37.18g/L$), radiotherapy, surgery, low hemoglobin hyperlipidemia (${\leq}93.67g/L$), long time of hospitalization (${\geq}14$days) were apt to deep fungal infection and the ANN model consisted of the seven factors. The AUC of ANN model($0.829{\pm}0.019$)was higher than that of LR model ($0.756{\pm}0.021$). Conclusions: The artificial neural network model with variables consisting of age, use of antibiotics, serum albumin concentrations, received radiotherapy, received surgery, hemoglobin, time of hospitalization should be useful for predicting the deep fungal infection in lung cancer.
Background: Prior studies showed a relationship between serum albumin and the albumin to globulin ratio with different types of cancer. We aimed to evaluate the predictive value of the albumin-globulin ratio (AGR) for survival of patients with lung adenocarcinoma. Materials and Methods: This retrospective study included 240 lung adenocarcinoma patients. Biochemical parameters before chemotherapy were collected and survival status was obtained from the hospital registry. The AGR was calculated using the equation AGR=albumin/(total protein-albumin) and ranked from lowest to highest, the total number of patients being divided into three equal tertiles according to the AGR values. Furthermore, AGR was divided into two groups (low and high tertiles) for ROC curve analysis. Cox model analysis was used to evaluate the prognostic value of AGR and AGR tertiles. Results: The mean survival time for each tertile was: for the $1^{st}$ 9.8 months (95%CI:7.765-11.848), $2^{nd}$ 15.4 months (95%CI:12.685-18.186), and $3^{rd}$ 19.9 months (95%CI:16.495-23.455) (p<0.001). Kaplan-Meier curves showed significantly higher survival rates with the third and high tertiles of AGR in comparison with the first and low tertiles, respectively. At multivariate analysis low levels of albumin and AGR, low tertile of AGR and high performance status remained an independent predictors of mortality. Conclusions: Low AGR was a significant predictor of long-term mortality in patients with lung adenocarcinoma. Serum albumin measurement and calculation of AGR are easily accessible and cheap to use for predicting mortality in patients with lung adenocarcinoma.
Background: The DR-$70^{TM}$ immunoassay is a newly developed cancer diagnostic test which quantifies the serum fibrin degradation products (FDP), produced during fibrinolysis, by antibody reaction. The purpose of this study was to evaluate the potential of DR-$70^{TM}$ Immunoassay in screening malignant tumor. Methods: Sample subjects were 4,169 adults, both male and female, who visited the health promotion center of a general hospital from March 2004 to April 2005 and underwent the DR-$70^{TM}$ immunoassay test and other tests for cancer diagnosis. The patient group was defined as 42 adults out of the sample subjects who were newly diagnosed with cancer during the same time period when the DR-$70^{TM}$ immunoassay test was performed. Final confirmation of a malignant tumor was made by pathological analysis. Results: The mean DR-$70^{TM}$ level was $0.83{\pm}0.65{\mu}g/ml$ (range: 0.00 (0.0001)${\sim}7.42{\mu}g/ml)$ in the control group (n=4,127) as opposed to $2.70{\pm}2.33{\mu}g/ml$ (range: $0.12{\sim}9.30{\mu}g/ml)$ in the cancer group (n=42), and statistical significance was established (p<0.0001, Student t-test). When categorized by the type of malignant tumor, all cancer patients with the exception of the subgroups of colon and rectal cancer showed significantly higher mean DR-$70^{TM}$ levels compared with the control group (p<0.0001, Kruscal-Wallis test). The receiver operating characteristic (ROC) curve analysis revealed ${\geq}1.091{\mu}g/ml$ as the best cut-off value. Using this cut-off value, the DR-$70^{TM}$ immunoassay produced a sensitivity of 71.4%, a specificity of 70.1%, a positive predictability of 69.4%, and a negative predictability of 69.2% (1). Conclusion: A significant increase in the mean DR-$70^{TM}$ value was observed in the cancer group (thyroidal, gastric, breast, hepatic and ovarian) com pared with the control group. In particular, the specificity and sensitivity of the DR-$70^{TM}$ immunoassay was relatively high in the subgroups of breast, gastric, and thyroidal cancer patients. There is need for further studies on a large number of malignant tumor patients to see how the DR-$70^{TM}$ level might be changed according to the differentiation grade and postoperative prognosis of the malignant tumor.
Species distribution modeling is one of the most effective habitat analysis methods for wildlife conservation. This study was for evaluating the suitability of species distribution to distance between forest patches in Seoul city using tits. We analyzed the distribution of the four species of tits: varied tit (Parus varius), marsh tit (P. palustris), great tit (P. major) and coal tit (P. ater), using the landscape indexes and connectivity indexes, and compared the resulting suitability indexes from 100m to 1,000m. As factors affecting to the distribution of tits, we calculated landscape indices by separating them into intra-patch indices (i.e. logged patch area (PA), area-weighted mean patch shape index (PSI), tree rate (TR)) and inter-patch indices (i.e. patch degree (PD), patch betweenness (PB), difference probability of connectivity (DPC)), to analyze the internal properties of the patches and their connectivity by tits occurrence data using logistic regression modeling. The models were evaluated by AICc (Akaike Information Criteria with a correction for finite sample sizes) and AUC (Area Under Curve of ROC). The results of AICc and AUC showed DPC, PA, PSI, and TR were important factors of the habitat models for great tit and marsh tit at the level of distance 500~800m. In contrast, habitat models for coal tit and varied tit, which are known as forest interior species, reflected PA, PSI, and TR as intra-patch indices rather than connectivity. These mean that coal tit and varied tit are more likely to find a large circular forest patch than a small and long-shaped forest patch, which are higher rate of forest. Therefore, different strategies are required in order to enhance the habitats of the forest birds, tits, in a region that has fragmented forest patches such as Seoul city. It is important to manage forest interior areas for coal tit and varied tit, which are known as forest interior species and to manage not only forest interior areas but also connectivity of the forest patches in the threshold distance for great tit and marsh tit as adapted species to the urban ecosystem for sustainable ecosystem management.
Atrial fibrillation(AF). chronic or paroxysmal is the most frequent arrhythmia in human subjects Duration of P wave in signal-averaged electrocardiography(SAECG) reflects intra-atrial conduction time and therefore. could be used as an electrophysiological marker for atrial conduction chance at the earthy stave. So we apply the analysis method using SAECG to diagnose Paroxysmal atrial fibrillation(PAF) . Subjects Participated for the study consisted of two groups: a control group(n=34) of normal healthy volunteers and a group of AF Patients(n=38) with a documented history of PAF but no other history of cardiac disease. We evaluated the effect of several filtering and determination methods to find the starting and ending feints of the P wavy on its duration. To increase the measurement reliability of P wave duration. the automatic detection method was proposed. Also. to increase the detection rate for PAF risk, the decision threshold value was optimized using receiver operation characteristics(ROC) curve. Results showed that the highest statistical difference (p〈0.001) of the P wane duration between controls and subjects was obtained at the Processing condition, using absolute threshold vague(8.75 $\mu N$) , a least mean square(LMS) high pass filter and 30 Hz cutoff frequency. The most outstanding difference(sensitivity 88 % specificity 64.4 %) between controls and subjects was obtained at the decision threshold value of 112 ms.
Park, Se-Hwan;Lee, Seung-Yup;Kang, Seung-Mo;Seon, Choon-Sik;Kim, Hyun-Kyung;Lee, Byoung-Hoon;Lee, Jae-Hyung;Kim, Sang-Hoon
Tuberculosis and Respiratory Diseases
/
v.71
no.3
/
pp.188-194
/
2011
Background: When patients with chronic respiratory symptoms have a normal spirometry result, it is not always easy to consider bronchial asthma as the preferential diagnosis. Forced expiratory flow between 25% and 75% of vital capacity ($FEF_{25{\sim}75%}$) is known as a useful diagnostic value of small airway diseases. However, it is not commonly used, because of its high individual variability. We evaluated the pattern of bronchodilator responsiveness (BDR) and the correlation between $FEF_{25{\sim}75%}$ and BDR in patients with suspicious asthma and normal spirometry. Methods: Among patients with suspicious bronchial asthma, 440 adult patients with a normal spirometry result (forced expiratory volume in one second [$FEV_1$]/forced vital capacity [FVC] ${\geq}70%$ & $FEV_1%$ predicted ${\geq}80%$) were enrolled. We divided this group into a positive BDR group (n=43) and negative BDR group (n=397), based on the result of BDR. A comparison was carried out of spirometric parameters with % change of $FEV_1$ after bronchodilator (${\Delta}FEV_1%$). Results: Among the 440 patients with normal spirometry, $FEF_{25{\sim}75%}%$ predicted were negatively correlated with ${\Delta}FEV_1%$ (r=-0.22, p<0.01), and BDR was positive in 43 patients (9.78%). The means of $FEF_{25{\sim}75%}%$ predicted were $64.0{\pm}14.5%$ in the BDR (+) group and $72.9{\pm}20.8%$ in the BDR (-) group (p<0.01). The negative correlation between $FEF_{25{\sim}75%}%$ predicted and ${\Delta}FEV_1%$ was stronger in the BDR (+) group (r=-0.38, p=0.01) than in the BDR (-) group (r=-0.17, p<0.01). In the ROC curve analysis, $FEF_{25{\sim}75%}$ at 75% of predicted value had 88.3% sensitivity and 40.3% specificity for detecting a positive BDR. Conclusion: BDR (+) was not rare in patients with suspicious asthma and normal spirometry. In these patients, $FEF_{25{\sim}75%}%$ predicted was well correlated with BDR.
Journal of rehabilitation welfare engineering & assistive technology
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v.11
no.2
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pp.91-98
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2017
Background & Object: Basic daily activity screening tool such as the Modified Barthel Index (MBI) has been used commonly in rehabilitation clinic and community based rehabilitation setting. Previous studies have shown the significant relations between the level of daily activities and driving ability on stroke or elderly people. However, there is a lack of studies to investigate the usefulness of MBI on prediction of driving ability for stroke patient. This study was to predict driving abilities of stroke survivor using Korean version Modified Barthel Index (K-MBI). Methods: A sample of 48 patients with stroke in rehabilitation hospital was recruited. All participants were tested level of basic daily activities using K-MBI. The driving ability of participants was tested using virtual reality driving simulator. The predictive validity was calculated of the K-MBI among pass or fail group of driving simulator test using receiver operating characteristics curves. Results: The cut-off score of >86.5 on the K-MBI is proper sensitivity to predict on driving performance ability. Conclusion: This pilot result offers clinical reference to therapists and caregivers for reasoning on driving recommendation period during rehabilitation stage of stroke survivors. Further studies need to identify prediction using real on-road test in a large population group.
Background: MicroRNAs (miRNAs) have demonstrated their potential as biomarkers for lung cancer diagnosis. In recent years, miRNAs have been found in body fluids such as serum, plasma, urine and saliva. Circulating miRNAs are highly stable and resistant to RNase activity along with, extreme pH and temperatures in serum and plasma. In this study, we investigated serum miRNA profiles that can be used as a diagnostic biomarker of non-small cell lung cancer (NSCLC). Methods: We compared the expression profile of miRNAs in the plasma of patients diagnosed with lung cancer using an miRNA microarray. The data from this assay were validated by quantitative real-time PCR (qRT-PCR). Results: Six miRNAs were overexpressed and three miRNAs were underexpressed in both tissue and serum from squamous cell carcinoma (SCC) patients. Sixteen miRNAs were overexpressed and twenty two miRNAs were underexpressed in both tissue and serum from adenocarcinoma (AC) patients. Of the four miRNAs chosen for qRT-PCR analysis, the expression of miR-23a was consistent with microarray results from AC patients. Receiver operating characteristic (ROC) curve analyses were done and revealed that the level of serum miR-23a was a potential marker for discriminating AC patients from chronic obstructive pulmonary disease (COPD) patients. Conclusion: Although a small number of patients were examined, the results from our study suggest that serum miR-23a can be used in the diagnosis of AC.
Journal of the Institute of Electronics Engineers of Korea SC
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v.48
no.4
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pp.1-9
/
2011
Hemorrhagic shock is a clinically widespread syndrome characterized by inadequate oxygenation and supply. It is important to diagnose hemorrhagic shock in its early stage for improving treatment effects and survival rate. However, an accurate diagnosis and treatment could be delayed in the early stage of hemorrhagic shock by evaluating only vital signs such as heart rate and blood pressure. There have been many studies for the early diagnosis of hemorrhagic shock, reporting that lactate concentration and perfusion were useful variables for tissue hypoxia and metabolic acidosis. In this study, we measured both perfusion using a laser Doppler flowmeter and lactate concentration from the volume controlled hemorrhagic shock using rats. We also proposed a new shock index which was calculated by dividing lactate concentration by perfusion for early diagnosis. As a result of the survival prediction by the proposed index with the receiver operating characteristic curve method, the sensitivity, specificity, and accuracy of survival were 90.0, 96.7 and 94.0%, respectively. The proposed index showed the fastest significant difference among the other parameters such as blood pressure and heart rate. It could offer early diagnosis and effective treatment for human hemorrhagic shock if it is applicable to humans.
Background: The success rate of intubation under direct laryngoscopy is greatly influenced by laryngoscopic grade using the Cormack-Lehane classification. However, it is not known whether grade under direct laryngoscopy can also affects the success rate of nasotracheal intubation using a fiberoptic bronchoscpe, so this study investigated the same. In addition, we investigated other factors that influence the success rate of fiberoptic nasotracheal intubation (FNI). Methods: FNI was performed by 18 anesthesiology residents under general anesthesia in patients over 15 years of age who underwent elective oral and maxillofacial operations. In all patients, the Mallampati grade was measured. Laryngeal view grade under direct laryngoscopy, and the degree of secretion and bleeding in the oral cavity was measured and divided into 3 grades. The time required for successful FNI was measured. If the intubation time was > 5 minutes, it was evaluated as a failure and the airway was managed by another method. The failure rate was evaluated using appropriate statistical method. Receiver operating characteristic (ROC) curves and area under the curve (AUC) were also measured. Results: A total of 650 patients were included in the study, and the failure rate of FNI was 4.5%. The patient's sex, age, height, weight, Mallampati, and laryngoscopic view grade did not affect the success rate of FNI (P > 0.05). BMI, the number of FNI performed by residents (P = 0.03), secretion (P < 0.001), and bleeding (P < 0.001) grades influenced the success rate. The AUCs of bleeding and secretion were 0.864 and 0.798, respectively, but the AUC of BMI, the number of FNI performed by residents, Mallampati, and laryngoscopic view grade were 0.527, 0.616, 0.614, and 0.544, respectively. Conclusion: Unlike in intubation under direct laryngoscopy, in the case of FNI, oral secretion and nasal bleeding had a significant effect on FNI difficulty than Mallampati grade or Laryngeal view grade.
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