AIMTo compare the results of bladder tumor associated antigen (BTA TRAK), nuclear matrix protein 22 (NMP 22) and voided urine cytology (VUC) in detecting bladder cancer.

METHODSA total of 135 elderly male and 50 healthy volunteers enrolled in this study were classified into three groups: (i) 93 patients with bladder cancer; (ii) 42 patients with urinary benign conditions; and (iii) 50 healthy volunteers. BTA TRAK and NMP 22 kits were used to detect bladder cancer. Voided urine cytology was used to compare the sensitivity and specificity of the screening tests.

RESULTSThe sensitivity and specificity of cytology, BTA TRAK and NMP 22 were 24% and 97%, 51% and 73%, 78% and 73%, respectively. The level of NMP 22 increased with tumor grading. The BTA TRAK kit has the lowest sensitivity among the screening tests. The NMP 22 with the best sensitivity can be an adjunct to cytology for evaluating bladder cancer.

CONCLUSIONThe NMP 22 test has a better correlation with the grading of the bladder cancer than BTA TRAK. As cytology units are typically not available in hospitals or in outpatient clinics, NMP 22 might be a promising tool for screening bladder cancer.

Aged ; Humans ; Male ; Nuclear Proteins ; urine ; Taiwan ; Urinary Bladder Neoplasms ; diagnosis ; urine ; Urine ; cytology

OBJECTIVEThe pathogenesis of minimal change nephrotic syndrome (MCNS) remains unclear. This study aimed to investigate the expression of interleukin-6 (IL-6) in rats with doxorubicin-induced nephropathy and its possible roles in the pathogenesis of MCNS.

METHODSEighty-three male Wistar rats were randomly assigned into a control group (n=32) and a nephropathy group (n=51). Nephropathy was induced by a single tail vein injection of doxorubicin (5 mg/kg). The control group was injected with normal saline. Twenty-four-hour urinary protein excretion was measured 7, 14, 28 and 42 days after doxorubicin injection. IL-6 expression in urine and renal tissues was determined using ELISA 7, 14, 28 and 42 days after doxorubicin injection.

RESULTSThe urinary protein excretion increased significantly in the nephropathy group 7, 14, 28 and 42 days after doxorubicin injection compared with that in the control group (P<0.01). IL-6 expression in urine and renal tissues increased significantly 7, 14, 28 and 42 days after doxorubicin injection compared with that in the control group (P<0.01). IL-6 expression in urine and renal tissues was positively correlated with 24-hour urinary protein excretion in the nephropathy group (r=0.794, P<0.01; r= 0.870, P<0.01). IL-6 expression in urine was positively correlated with that in renal tissues (r=0.739, P<0.01).

CONCLUSIONSIL-6 expression in the urine and renal tissues is increased in MCNS rats. IL-6 might play an important role in the pathogenesis of MCNS.

Animals ; Antibiotics, Antineoplastic ; toxicity ; Disease Models, Animal ; Doxorubicin ; toxicity ; Interleukin-6 ; analysis ; Kidney ; chemistry ; Male ; Nephrosis, Lipoid ; chemically induced ; immunology ; Rats ; Rats, Wistar

Objective To assess whether strain parameters derived from three-dimensional speckle tracking imaging ( 3D-STI) could identify improvement of cardiac function and predict response of patients with immunoglobulin light-chain cardiac amyloidosis ( AL-CA) following chemotherapy . Methods Totally 13 patients with AL-CA [aged (58 .5 ± 8 .9)years;69％ males] were treated with melphalan or bortezomib-based regimens and by regular chemotherapy for 6 months .The clinical data was collected . Maximal left ventricular wall thickness (MLVWT) ,left ventricular mass index (LVMI) ,left ventricular ejection fraction ( LVEF) ,systolic mitral annular velocity ( s′) ,early diastolic mitral annular velocity echocardiography ( e′) , 3D-STI global longitudinal ,circumferential ,radial and area strain (GLS ,GCS ,GRS ,and GAS) ,the standard deviation of time to peak longitudinal strain among 16 left ventricular segments ( TS-SD_GLS ) were obtained by conventional echocardiography and 3D-STI . In addition ,serologic biomarkers including N-terminal pro-brain natriuretic peptide ( NT-proBNP) and free light chains ( FLC) were acquired at baseline and 6 months after chemotherapy . These patients were divided into two groups according to difference of FLC :complete response (CR) group and Non-CR group . The clinical data ,cardiac ultrasound parameters and serological parameters were compared between groups ,each group parameters at baseline and 6 months after chemotherapy were compared within the group.Results ①There were no significant differencein conventional echocardiographic parameters ,GCS ,GRS and GAS ,as well as TS-SD_GLS in either group between before and after chemotherapy . But GLS was improved only in CR group ( P = 0 .036) ,and its improvement was correlated with the decrease in NT-proBNP ( r = -0 .738 , P = 0 .037) . ② In baseline evaluation ,patients in Non-CR group had increased LVMI ,deteriorated e′ and GLS ,and longer Ts-SD as compared to those in CR group ( all P < 0 .05 ) . ③ ROC analysis revealed that these parameters had discriminative ability to forecast those with better therapeutic effectiveness ,esecially for AL-CA patients with baseline LVMI<96 .55 g/m2 ,e′>4 .7 cm/s ,absolute value of GLS>16 .6％ ,and TS-SD_GLS<35 .2 ms ,which may have better hematologic response to chemotherapy . Conclusions GLS can identify early improvement of cardiac function in AL-CA patients after chemotherapy . Moreover ,LVMI ,e′,GLS and TS-SD_GLS are sensitive measurements of pre-treatment ventricular impairment ,and may predict better response to chemotherapy .

Objectives: . Type 2 diabetes mellitus (T2DM) is a risk factor for deep neck infection (DNI) and leads to complications and poor outcomes. Our study aimed to investigate the risk, prognosis, and complications of peritonsillar abscess (PTA) in patients with T2DM. Methods: . We extracted data of patients newly diagnosed as having T2DM between January 2000 and December 2011 from Taiwan’s National Health Insurance Research Database. These patients were matched with patients without T2DM, and PTA incidence was compared between both cohorts. Results: . In total, 67,852 patients with and 135,704 patients without T2DM were enrolled. PTA incidence was significantly higher in patients with T2DM (incidence rate ratio, 1.91; P<0.001); moreover, PTA incidence was higher at 1 to 5 years after T2DM diagnosis than at <1 and >5 years after T2DM diagnosis. Cox regression analysis showed that patients with T2DM had an approximately 2-fold higher PTA risk (adjusted hazard ratio [aHR]: 1.89, P<0.001). Patients with a higher adapted Diabetes Complications Severity Index (aDCSI) had higher PTA risk than those with a lower aDCSI (aHRs: 2.17 for aDCSI ≥1, P=0.006 and 1.81 for aDCSI=0, P=0.002). T2DM patients with a high aDCSI (≥1) had a nonsignificantly longer hospitalization duration and a higher rate of DNI complications than did those with a low aDCSI (=0). Conclusion . In patients with T2DM, PTA incidence was relatively high, and it increased with T2DM severity. Moreover, T2DM patients should be particularly careful about PTA within 1 to 5 years after the diagnosis, and physicians should keep in mind that the prognosis of PTA was correlated with T2DM severity.

Objectives: . Type 2 diabetes mellitus (T2DM) is a risk factor for deep neck infection (DNI) and leads to complications and poor outcomes. Our study aimed to investigate the risk, prognosis, and complications of peritonsillar abscess (PTA) in patients with T2DM. Methods: . We extracted data of patients newly diagnosed as having T2DM between January 2000 and December 2011 from Taiwan’s National Health Insurance Research Database. These patients were matched with patients without T2DM, and PTA incidence was compared between both cohorts. Results: . In total, 67,852 patients with and 135,704 patients without T2DM were enrolled. PTA incidence was significantly higher in patients with T2DM (incidence rate ratio, 1.91; P<0.001); moreover, PTA incidence was higher at 1 to 5 years after T2DM diagnosis than at <1 and >5 years after T2DM diagnosis. Cox regression analysis showed that patients with T2DM had an approximately 2-fold higher PTA risk (adjusted hazard ratio [aHR]: 1.89, P<0.001). Patients with a higher adapted Diabetes Complications Severity Index (aDCSI) had higher PTA risk than those with a lower aDCSI (aHRs: 2.17 for aDCSI ≥1, P=0.006 and 1.81 for aDCSI=0, P=0.002). T2DM patients with a high aDCSI (≥1) had a nonsignificantly longer hospitalization duration and a higher rate of DNI complications than did those with a low aDCSI (=0). Conclusion . In patients with T2DM, PTA incidence was relatively high, and it increased with T2DM severity. Moreover, T2DM patients should be particularly careful about PTA within 1 to 5 years after the diagnosis, and physicians should keep in mind that the prognosis of PTA was correlated with T2DM severity.

Background/Aims: Despite the high efficacy of direct-acting antivirals (DAAs), approximately 1–3% of hepatitis C virus (HCV) patients fail to achieve a sustained virological response. We conducted a nationwide study to investigate risk factors associated with DAA treatment failure. Machine-learning algorithms have been applied to discriminate subjects who may fail to respond to DAA therapy. Methods: We analyzed the Taiwan HCV Registry Program database to explore predictors of DAA failure in HCV patients. Fifty-five host and virological features were assessed using multivariate logistic regression, decision tree, random forest, eXtreme Gradient Boosting (XGBoost), and artificial neural network. The primary outcome was undetectable HCV RNA at 12 weeks after the end of treatment. Results: The training (n=23,955) and validation (n=10,346) datasets had similar baseline demographics, with an overall DAA failure rate of 1.6% (n=538). Multivariate logistic regression analysis revealed that liver cirrhosis, hepatocellular carcinoma, poor DAA adherence, and higher hemoglobin A1c were significantly associated with virological failure. XGBoost outperformed the other algorithms and logistic regression models, with an area under the receiver operating characteristic curve of 1.000 in the training dataset and 0.803 in the validation dataset. The top five predictors of treatment failure were HCV RNA, body mass index, α-fetoprotein, platelets, and FIB-4 index. The accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of the XGBoost model (cutoff value=0.5) were 99.5%, 69.7%, 99.9%, 97.4%, and 99.5%, respectively, for the entire dataset. Conclusions Machine learning algorithms effectively provide risk stratification for DAA failure and additional information on the factors associated with DAA failure.