OBJECTIVE: To analyze risk factors associated with bladder dysfunction in patients with type 2 diabetes mellitus (T2DM) and to construct a prediction model for early prediction of diabetic bladder dysfunction (DBD).
METHODS: We included hospitalized patients with T2DM from the endocrinology department of Shenzhen Hospital, Southern Medical University, Shenzhen, China, from January 2019 to 2022. Factors associated with DBD in bivariate analysis with a p < 0.05 were included in a multivariate logistic regression analysis. Multivariate logistic regression analysis was used to determine independent risk factors and to construct a prediction model. The prediction model was presented as the model formula. The receiver operating characteristic (ROC) curve was used to evaluate the predictive value of the above risk factors and the prediction model for DBD. The model was internally verified by Boostrap resampling 1000 times.
RESULTS: Two hundred and eleven patients were included in this study, and they were divided into the DBD group (n = 101) and the non-DBD group (n = 110). Eight variables showed significant significance in the bivariate analysis, including age, diabetic peripheral neuropathy (DPN), glycated hemoglobin (HbA1c), urinary microalbumin (mALB), red blood cell count (RBC), white blood cell count (WBC), absolute neutrophil count (ANC), percentage of monocyte (Mono%). Furthermore, multivariate logistic regression analysis revealed that age (OR [95% CI]: 1.077 [1.042-1.112]), p < 0.001; DPN (OR [95% CI]: 2.373 [1.013-5.561]), p = 0.047; HbA1c (OR [95% CI]: 1.170 [1.029-1.330]), p = 0.017 and ANC (OR [95% CI]: 1.234 [1.059-1.438]), p = 0.007 were independent risk factors for the DBD. The prediction model formula was Logit (p) = -6.611 + 0.074 age + 0.864 DPN + 0.157 HbA 1 c + 0.078 ANC. The area under the ROC curve (AUC) for the four risk factors were 0.676, 0.582, 0.618, and 0.674, respectively. The prediction model predicted DBD with higher accuracy than the individual risk factors, AUC = 0.817 (95% CI: 0.757-0.877), and the sensitivity and specificity were 88.1% and 50.0%, respectively. The model internal validation results showed that the AUC = 0.804 (95% CI: 0.707-0.901), and the calibration curve is close to the ideal diagonal line.
CONCLUSIONS: Age, DPN, HbA1c, and ANC were risk factors for DBD. The prediction model constructed based on the four risk factors had a good predictive value for predicting the occurrence of DBD.

BACKGROUND: The systemic inflammation score (SIS), based on serum albumin (Alb) and lymphocyte-to-monocyte ratio (LMR), is a novel prognostic tool for some tumours. Studies indicate that the SIS can be used as a postoperative prognostic marker. However, its predictive value in elderly oesophageal squamous cell carcinoma (ESCC) patients treated with radiotherapy is unclear.
METHODS: In total, 166 elderly ESCC patients who received radiotherapy with or without chemotherapy were included. Based on different combinations of Alb and LMR levels, the SIS was divided into 3 groups, SIS = 0 (n = 79), SIS = 1 (n = 71) and SIS = 2 (n = 16). The Kaplan-Meier method was used for survival analysis. Univariate and multivariate analyses were performed to assess prognosis. Time-dependent receiver operating characteristic (t-ROC) curves were used to compare the prognostic accuracy of the SIS with that of Alb, LMR, neutrophil-to lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and systemic immune-inflammatory index (SII).
RESULTS: Decreased Alb and LMR were both associated with shorter OS, whereas a lower SIS was significantly associated with better outcomes. The OS of SIS = 0, SIS = 1 and SIS = 2 was 28.0 ± 2.9, 16.0 ± 2.8 and 10.0 ± 7.0 months, respectively (p = 0.000). Similar results were also observed for PFS. Multivariate analysis of the model with SIS revealed that the SIS was a significant independent biomarker for predicting OS and PFS. The nomogram showed that the C-index was improved to 0.677 when the SIS factor was incorporated. Furthermore, the 3-year OS rates for patients in the SIS-high group (SIS = 1 and SIS = 2) undergoing concurrent radiotherapy with a single agent (CCRT-1) and concurrent radiotherapy with two agents (CCRT-2) were 42% and 15%, respectively (p = 0.039). The t-ROC curve showed that the SIS was more sensitive than other prognostic factors for predicting overall survival.
CONCLUSIONS: The SIS may be a useful prognostic marker in elderly patients with ESCC receiving radiotherapy alone or chemoradiotherapy. The SIS showed a better predictive ability for OS than the continuous variable Alb and could stratify patient prognosis in different therapeutic regimens. CCRT-1 may be the best treatment for SIS-high patients.

UNASSIGNED: To investigate the relationship and predictive value of first-trimester pregnancy-associated plasma protein A (PAPP-A), maternal factors, and biochemical parameters with gestational diabetes mellitus (GDM) in southern China mothers.
UNASSIGNED: This study recruited 4872 pregnant women. PAPP-A, the free beta subunit of human chorionic gonadotropin (free β-HCG), fasting plasma glucose (FPG), total cholesterol (TC), triglycerides (TG), and high- and low-density lipoproteins (HDL, LDL) were measured at 11-13+ weeks of gestation. GDM was diagnosed based on a 75 g oral glucose tolerance test at 24-28 weeks of gestation. We performed stepwise logistic regression analysis to determine the odds ratio (OR) and the 95% confidence interval (CI) of GDM. We used Receiver Operating Characteristic (ROC) curves with the area under the curve (AUC) to evaluate the predictive value of PAPP-A, maternal factors, and biochemical markers. The significance of the differences between the AUC values was assessed using the DeLong test.
UNASSIGNED: GDM was diagnosed in 750 (15.39%) women. Independent factors for GDM were age, pre-gestational BMI, GWG before a diagnosis of GDM, previous history of GDM, family history of diabetes, FPG, TG, LDL, PAPP-A, and TC. The AUC of PAPP-A was 0.56 (95% CI 0.53-0.58). The AUC of a model based on combined maternal factors, biochemical markers, and PAPP-A was 0.70 (95% CI 0.68-0.72). Differences in AUC values between PAPP-A alone and the model based on combined maternal factors, biochemical markers, and PAPP-A were statistically significant (Z= 9.983, P<0.001).
UNASSIGNED: A Low serum PAPP-A level in the first trimester is an independent risk factor for developing GDM later in pregnancy. However, it is not a good independent predictor although the predictive value of a low serum PAPP-A level increases when combined with maternal factors and biochemical markers.

There are few data on the utility of tenofovir diphosphate (TFV-DP) in dried blood spots (DBSs) to predict future viral load (VL) in postpartum women with HIV on antiretroviral therapy (ART).
We conducted a nested case-control study within a trial of postpartum ART delivery strategies. Participants started ART containing tenofovir disoproxil fumarate (TDF) in pregnancy, were <10 weeks postpartum, and had a VL <400 copies/mL. VL and TFV-DP samples were taken every 3-6 months over 24 months. Cases had ≥1 VL ≥20 copies/mL; controls were randomly sampled from women with persistent viral suppression (VS; VL <20 copies/mL). Generalized estimating equations were used to calculate likelihood odds ratios (LORs) for future VL ≥20 copies/mL by TFV-DP concentration at the preceding visit.
61 cases and 20 controls contributed 365 DBS-VL pairs (median ART duration, 16 months). Sensitivity and specificity of TFV-DP <700 fmol/punch to detect future viremia were 62.9% (95% CI, 54.7-70.6%) and 89.7% (84.9-93.4%), respectively. Adjusting for age, ART duration, previous VL, and duration between the TFV-DP and VL measures, LORs of viremia for TFV-DP concentrations 350-699 and <350 fmol/punch versus TFV-DP ≥1850 fmol/punch were 3.5 (95% CI, 1.1-10.8; P = .033) and 12.9 (3.6-46.6; P < .0001), respectively. Including only samples taken during VS, the LOR of future viremia for TFV-DP concentration <350 fmol/punch versus TFV-DP ≥1850 fmol/punch was 9.5 (1.9-47.0).
TFV-DP concentrations in DBSs were strongly associated with future viremia and appear useful to identify nonadherence and predict future elevated VL.

暂无摘要。

In clinical practice, abnormal biochemical changes often occur in women who eventually develop preeclampsia (PE). The study aims to investigate whether maternal serum biochemical markers in the early third trimester can predict PE and neonatal birth weight.
A retrospective case-control study was performed on 287 women who subsequently developed PE (mild = 139; severe = 148) and 143 healthy women. Fasting venous blood samples of all gravidas were drawn for routine biochemical markers screening in the early third trimester (28.49 ± 1.63 weeks). Appropriate statistical methods were selected for analysis with SPSS software.
(1) The concentrations of plasma triglyceride (TG), low-density lipoprotein cholesterol (LDL), and uric acid (UA) in the severe and mild subgroups of the PE group were significantly higher compared with the respective levels in the normal pregnancy groups (3.90 vs. 4.03 vs. 3.14 mmol/L; 3.41 vs. 3.33 vs. 2.89 mmol/L; 365.42 vs. 318.91 vs. 284.69 μmol/L; p < 0.0001). Serum calcium levels in PE group were significantly lower than those in control group (2.10 vs. 2.18 vs. 2.22 mmol/L; p < 0.0001). (2) By using the receiver operating characteristic curve to estimate the diagnosis rate of screening for PE of each marker, the highest sensitivity appeared by the combination of TG, total cholesterol (TC), LDL, high-density lipoprotein cholesterol (HDL), LDL/HDL, UA, Ca2+, and homocysteine (HCY) (79%). The area under curve (AUC) of UA was 0.70, which was the highest among these eight markers, but the AUC of an eight-marker combination model (0.85) had a better diagnostic indication. (3) In PE, the maximum systolic/diastolic blood pressure was significantly positively correlated with serum UA (r = 0.212/0.205, p < 0.0001); and negatively correlated with serum total calcium (r = -0.193/-0.196, p = 0.001). The neonatal birth weight of PE group had a positive correlation with serum TG levels (r = 0.141, p = 0.017) and serum total calcium levels (r = 0.221, p < 0.0001), and a negative correlation with UA levels (r = -0.265, p < 0.0001).
The individual marker really performs terrible in predicting PE. Joint monitoring and evaluation of these parameters may improve the screening efficiency for the prediction of PE and poor fetal growth early.

An electronic anonymized patient portal analysis using radiographic reports and admission and discharge diagnoses had sensitivity, specificity, positive predictive value, and negative predictive value of 84.7%, 78.2%, 75%, and 87%, respectively, for community-acquired pneumonia validated against a blinded expert medical review. This approach can help to track antimicrobial use and resistance.

OBJECTIVE: To investigate the relationship between pregnancy-associated plasma protein A (PAPP-A) and gestational diabetes mellitus (GDM), and to determine whether PAPP-A has improved value for predicting GDM in a Chinese population.
METHODS: Clinical data for 599 GDM patients and 986 unaffected pregnant women undergoing both antenatal examinations and delivery were retrospectively analyzed. First-trimester serum PAPP-A levels were compared between the groups. Binary logistic regression analysis was used to explore the risk factors for GDM, and the area under the receiver operating characteristic curve was used to determine the value of PAPP-A for predicting GDM.
RESULTS: GDM-affected and unaffected pregnant women were significantly different in terms of age (P < 0.001), BMI (P < 0.001), family history of diabetes (P = 0.002), α-thalassemia trait (P < 0.01), parity (P < 0.001), conception methods (P < 0.001), gestational weeks at the time of labor (P < 0.001) and corrected PAPP-A multiples of the median values (P < 0.001). Binary logistic regression analysis showed that PAPP-A levels were negatively related to the subsequent development of GDM (odds ratio 0.798, 95% confidence interval 0.647-0.984). The area under the receiver operating characteristic curve for maternal factors was 0.684 (95% CI: 0.657-0.711), and did not significantly differ from that for the combination of maternal factors and serum PAPP-A levels, which was 0.686 (95% CI: 0.660-0.713; χ2 = 0.625, P = 0.429).
CONCLUSIONS: Serum PAPP-A was an independent factor for the development of GDM in pregnant Chinese women. Serum-PAPP-A does not have improved value with respect to predicting GDM when combined with other maternal factors.