OBJECTIVE: To identify which non-invasive infection indicators could better predict post-cervical cerclage (CC) infections, and on which days after CC infection indicators should be closely monitored.
METHODS: The retrospective, single-center study included 619 single-pregnancy patients from January 2021 to December 2022. Patients were categorized into infected and uninfected groups based on physicians\' judgments of post-CC infections. Registered information included patient characteristics, cervical insufficiency history, gestational age at CC, surgical method (McDonald/Shirodkar), purpose of CC, mid-pregnancy miscarriage/preterm birth, infection history or risk factors, and infection indices on days 1, 3, 5, and 7 after CC. Propensity score matching (PSM) was applied to reduce patient characteristic bias. Statistical analysis of C-reactive protein (CRP), white blood cell (WBC), neutrophil count (NEU), percentage of neutrophil count (NEU_P), interleukin-6 (IL-6), and procalcitonin (PCT) in the infected group compared with the uninfected group was performed using chi-square tests and t-tests. Receiver operating characteristic (ROC) curves were used to further assess the diagnostic value of CRP, PCT, and CRP-PCT in combination.
RESULTS: Among the 619 included patients, 206 patients were matched using PSM and subsequently assessed. PCT values on day 1 and day 3 after CC exhibited significant differences between the two groups in two statistical ways (P < 0.01, P < 0.05). The CRP levels on day 1 were significantly higher in the infected group compared to the uninfected group in two statistical ways (P < 0.05). On day 3, the mean CRP value was significantly elevated in the infected group compared to the uninfected group (P < 0.05). Analyses of IL-6, WBC, NEU, and NEU_P did not yield clinically significant results. The area under the ROC curves for CRP, PCT, and CRP-PCT on day 1 and day 3 were all below 0.7. In the preventive CC group, the AUC values of CRP and CRP-PCT obtained on d1 were found to be higher than 0.7, indicating moderate diagnostic accuracy.
CONCLUSIONS: For women after CC surgery, especially of preventive aim, increased serum CRP and PCT levels from post-CC day 1 to day 3 may signal a potential postoperative infection, warranting close monitoring.

OBJECTIVE: To study the correlation between achilles tendon rupture (ATR) and hyperuricemia, also verify the known risk factors for ATR.
METHODS: A retrospective review of 488 subjects was performed (182 with Achilles tendon rupture, 306 controls with ankle sprains). Demographic variables and risk factors for rupture were tabulated and compared. The baseline data and related indicators were compared, and the risk factors of ATR were analyzed by constructing a binary logistic regression model.
RESULTS: Univariate logistic analysis showed that BMI, smoking, and hyperuricemia were risk factors for the development of ATR (OR = 1.65, 95%CI 1.13-2.42, P = 0.01; OR = 1.47, 95%CI 1.00-2.24, P < 0.05; OR = 2.85, 95%CI 1.84-4.42, P < 0.01). Multifactorial analysis showed that BMI ≥ 25 kg/m2, smoking, and hyperuricemia were independent risk factors for the development of ATR (OR = 1.66, 95%CI 1.11-2.49, P = 0.01; OR = 2.15, 95%CI 1.28-3.60, P < 0.01; OR = 3.06, 95%CI 1.92-4.89, P < 0.01). Among the blood biochemical indicators, total cholesterol (TC) and uric acid (UA) were independent risk factors for the occurrence of ATR (OR = 1.54, 95% CI 1.12-2.12, P = 0.01; OR = 1.01, 95% CI 1.01-1.01, P < 0.01).
CONCLUSIONS: Our study confirmed that, as in previous results, higher BMI, smoking, and total cholesterol are risk factors for ATR, Hyperuricemia may contribute to the development of ATR, and adjunctive tests for TC and UA in the blood biochemistry may be helpful in predicting the risk of ATR.

The aim of the study was to investigate the land use change dynamics under CMIP6 projections using Land Change Modeler (LCM). The Global Sensitivity Analysis (GSA) techniques was applied to quantify the sensitivity of single parameter and combination of parameters. Land use and land cover (LULC) transitions of the baseline period (2006-2016) was assessed with a model performance accuracy of 80%. Receiver operating characteristic (ROC) analysis shows that the model has performed well for all the LULC classes except builtup land. Prediction under the SSP245 scenario depicts that areal extent of agricultural, forest, and snow, and glacier will decrease by the mid-century (2045). However, the grassland and barren land area will increase from the baseline period. A similar change pattern with a higher magnitude has also been predicted under SSP585 scenario. The CMIP6 forcing index considers socio-economic effects and LCM predicted an expansion in barren land which may be attributed to changes in cryosphere in the studied area.

OBJECTIVE: In comparative systematic reviews of diagnostic accuracy, inconsistencies between direct and indirect comparisons may lead to bias. We investigated whether using individual patient data (IPD) can adjust for this form of bias.
METHODS: We included IPD of 3 ovarian reserve tests from 32 studies. Inconsistency was defined as a statistically significant difference in relative accuracy or different comparative results between the direct and indirect evidence. We adjusted for the effect of threshold and reference standard, as well as for patient-specific variables.
RESULTS: Anti-Müllerian hormone (AMH) and follicle stimulation hormone (FSH) differed significantly in sensitivity (-0.1563, P = 0.04). AMH and antral follicle count (AFC) differed significantly in sensitivity (0.1465, P < 0.01). AMH and AFC differed significantly in specificity (-0.0607, P = 0.02). The area under the curve (AUC) differed significantly between AFC and FSH (0.0948, P < 0.01) in the direct comparison but not (0.0678, P = 0.09) in the indirect comparison. The AUCs of AFC and AMH differed significantly (-0.0830, P < 0.01) in the indirect comparison but not (-0.0176, P = 0.29) in the direct comparison. These differences remained after adjusting for indirectness.
CONCLUSIONS: Estimates of comparative accuracy obtained through indirect comparisons are not always consistent with those obtained through direct comparisons. Using IPD to adjust for indirectness did not successfully remove the bias in this case study.