Background /Objectives: The fetal thymus is increasingly assessed as a marker of fetal wellbeing, yet reliable gestational-age-specific reference data remain limited. We aimed to establish reference ranges, centile charts, and internally validated Z-score equations for the thymus transverse diameter at 18 + 0-25 + 6 weeks of gestation. Methods: This retrospective cross-sectional study was conducted at a single tertiary fetal medicine centre between January 2023 and December 2025. Structurally normal singleton pregnancies with a reliable gestational age were eligible. The maximum transverse diameter of the fetal thymus was measured in the three-vessel trachea view. The mean was modelled by polynomial regression and, after heteroscedasticity was confirmed, a gestational-age-specific standard deviation was modelled using the Royston-Wright approach. Z-score equations and smoothed centiles were derived, and performance was assessed by bootstrap, cross-validation, and split-sample validation. Results: A total of 2103 pregnancies were included. A cubic mean model was selected, and variance increased significantly with gestation (Breusch-Pagan p = 1.34 & times; 10-18). The predicted median increased from 9.7 mm at 18 weeks to 18.3 mm at 25 weeks. Fetal sex was statistically associated with thymus transverse diameter, but the effect was negligible (adjusted mean difference 0.247 mm; p = 0.011; Cohen's d = 0.051; interaction p = 0.949), so a single reference was retained. Excluding maternal comorbidities changed the median by at most 0.24 mm. Bootstrap optimism was 0.006 mm and the 10-fold cross-validated root-mean-square error 1.863 mm. Conclusions: We provide contemporary gestational-age-specific reference ranges and internally validated Z-score equations for the thymus transverse diameter between 18 + 0 and 25 + 6 weeks, which may support clinical assessment and future research, pending external validation.
Background/Objectives: Fetal ventriculomegaly is a heterogeneous prenatal finding with variable severity, evolution, and risk of associated cerebral abnormalities. Prenatal ultrasound is the primary diagnostic and follow-up modality, while fetal magnetic resonance imaging (MRI) may provide additional anatomical information. This study evaluated ultrasound features and longitudinal evolution across the ventriculomegaly severity spectrum and investigated prenatal features associated with additional MRI abnormalities. Methods: This single-center observational cohort included 62 fetuses who underwent detailed prenatal ultrasound, fetal MRI, and serial ultrasound follow-up. Ventriculomegaly was classified as mild (10–12 mm), moderate (>12–15 mm), or severe (>15 mm). Multivariable logistic regression assessed prenatal features associated with additional MRI abnormalities, and receiver operating characteristic analysis evaluated its discriminatory performance. Results: Mild, moderate, and severe ventriculomegaly were present in 12 (19.4%), 22 (35.5%), and 28 (45.2%) fetuses. Additional MRI abnormalities increased with severity (16.7%, 40.9%, and 71.4%; p = 0.004). Longitudinal evolution differed across severity groups (Fisher’s exact test, p = 0.013), with progression observed in 25.0%, 45.5%, and 71.4% of mild, moderate, and severe cases, respectively. Greater ultrasound ventricular diameter (OR 1.19 per 1 mm increase, 95% CI 1.03–1.37; p = 0.021) and bilateral asymmetric ventriculomegaly (OR 3.82, 95% CI 1.04–13.96; p = 0.043) were independently associated with additional MRI abnormalities. Ventricular diameter showed moderate discriminatory performance (AUC 0.768, 95% CI 0.651–0.886); an exploratory, data-derived 13.5 mm threshold yielded 83.9% sensitivity and 54.8% specificity. Conclusions: Increasing ventricular severity was associated with more frequent progression and additional MRI abnormalities. The associations of ventricular diameter and bilateral asymmetric ventriculomegaly with additional MRI abnormalities should be considered exploratory and require further validation. The identification of additional abnormalities even in mild cases supports the complementary role of fetal MRI alongside longitudinal ultrasound assessment.
Background/Objectives: Febrile neutropenia (FN) in hematologic malignancies carries a high risk of sepsis. We developed a regression model and a simplified nurse-led sepsis risk score using artificial intelligence (AI)-enabled remote patient monitoring (RPM) measurements and routine clinical and laboratory variables. Methods: A nested case–control study included 120 adult FN episodes (40 Sepsis-3-defined cases within 14 days of FN onset; 80 matched controls) in a hematology/bone marrow transplantation unit (BMT) in India (December 2021–December 2024). Heart rate and respiratory rate were obtained by ballistocardiography; blood pressure (BP), peripheral oxygen saturation (SpO2), and temperature were obtained using connected probes. Only a single set of FN-onset measurements was analyzed; longitudinal RPM trends and platform-generated alerts were excluded. Conditional logistic regression identified independent predictors and supplied coefficients for an integer-weighted score. Regression-model validation used two 1000-resample bootstrap analyses: one holding cut-offs and predictors fixed, the other repeating cut-off determination and backward selection. Integer-score discrimination was assessed separately. Results: Six predictors—tachycardia, hypotension, ≥2 comorbidities, absolute neutrophil count <99.5 cells/μL, chills, and elevated procalcitonin—formed an 8-point score. The regression model area under the receiver operating characteristic curve (AUC) was 0.847, with fixed-specification optimism of 0.028 and a corrected AUC of 0.819. Repeating cut-off determination and predictor selection yielded an apparent AUC of 0.855, optimism of 0.036, and corrected AUC of 0.819. The integer-score apparent AUC was 0.654 (95% CI 0.567–0.740), without optimism correction. Conclusions: Regression-model discrimination remained similar after accounting for cut-off determination and predictor selection. Integer-score performance remains uncorrected for optimism and requires independent temporal validation before clinical use. RPM’s AI functions and continuous-monitoring benefits were not evaluated. Temporal validation is planned in Phase II. Trial registration: Clinical Trials Registry of India (CTRI/2025/06/088290).
Background/Objectives: Smart devices estimate blood pressure (BP) from photoplethysmography (PPG), but models trained on other people generalize poorly, and device constraints limit model size. This study compared calibration strategies and model sizes for PPG-based BP estimation. Methods: We used 65 hand-crafted PPG features with MIMIC-BP (1295 training and 229 subject-disjoint test subjects, ten repeats) and 17 external VitalDB surgical cases. We compared calibration-free regressors, calibration with one to five cuffs, recalibration policies and calibration models of decreasing size. Results: Without calibration, six regressors reached a systolic BP (SBP) mean absolute error (MAE) of 13.0–13.3 mmHg on unseen subjects, close to a constant predictor (14.2 mmHg). A delta model that predicts the change from the cuff reading reduced the SBP MAE to 11.8 mmHg with one cuff and 10.8 mmHg with five, but followed only 30–50% of large changes. With five calibration readings, the model achieved a pooled area under the curve (AUC) of 0.94 for new-onset SBP ≥160 mmHg on MIMIC-BP, but sensitivity was zero at an estimated-SBP threshold of 160 mmHg. Accuracy was governed by the recalibration interval: recalibration nominally every 15 min gave 10.3 mmHg on VitalDB, and event-triggered cuffs were not better than periodic ones. A 47 KB tree model lost 0.2 mmHg against a 1.5 MB reference. Conclusions: For these data, calibration was required, the recalibration interval mattered more than model complexity, and a compact tree model was sufficient; on-device use requires further validation. Accuracy remained poor at blood-pressure extremes, and external validation in only 17 VitalDB cases remains preliminary.
Background/Objectives: Gut microbiota dysbiosis is increasingly implicated in colorectal carcinogenesis, and microbial signatures are emerging as non-invasive diagnostic tools. This systematic review synthesised human studies that evaluated gut microbiota composition, microbiota-derived metabolites and microbial biomarkers for the detection of colorectal cancer (CRC) and colorectal adenoma. Methods: Following the PRISMA 2020 statement, PubMed/MEDLINE, Scopus and the Cochrane Library were searched for studies published between 2015 and 2025, supplemented by Google Scholar and reference-list screening. Human observational and interventional studies reporting microbiota-based diagnostic or associative endpoints were eligible. Data were synthesised narratively, and risk of bias was appraised with QUADAS-2; the protocol was not prospectively registered. Results: Ten studies (5318 participants; nine from East Asia, one from Europe) were included. Four used targeted quantitative PCR, three 16S rRNA sequencing and three shotgun metagenomics, all three combined with metabolomics. Fusobacterium nucleatum and Parvimonas micra were the taxa most frequently enriched in neoplasia (five studies each), together with Peptostreptococcus species, whereas butyrate-producing commensals (Faecalibacterium prausnitzii, Roseburia spp.) were depleted. Multi-omics panels achieved the highest discrimination for CRC (area under the curve [AUC] 0.92–0.994), while performance for adenoma was lower (AUC 0.64–0.91). Adding bacterial markers to the faecal immunochemical test (FIT) increased sensitivity for CRC and advanced adenoma at the cost of specificity. Most studies had a high or unclear risk of bias in the patient-selection and index-test domains, and only two evaluated a screening or mixed symptomatic population. No study reported microbial markers separately for the right colon, left colon and rectum, or for early-onset (<50 years) CRC, and age was often unbalanced between cases and controls. Conclusions: Microbiota-derived biomarkers show reproducible associations with colorectal neoplasia and promising diagnostic accuracy, particularly as adjuncts to FIT, but the evidence derives mainly from small, hospital-based case–control studies in East Asian populations, and accuracy for adenomas remains limited. Site-specific and early-onset data are lacking. Standardised, prospective, multi-ethnic validation studies are required before clinical implementation.
