Index Measurements Research Articles

Associations of Circulating ANGPTL3, C-Terminal Domain-Containing ANGPTL4, and ANGPTL3/8 and ANGPTL4/8 Complexes with LPL Activity, Diabetes, Inflammation, and Cardiovascular Mortality.

ANGPTL3/4/8 (angiopoietin-like proteins 3, 4, and 8) are important regulators of LPL (lipoprotein lipase). ANGPTL8 forms complexes with ANGPTL3 and ANGPTL4. ANGPTL4/8 complex formation converts ANGPTL4 from a furin substrate to a plasmin substrate, and both cleavages generate similar C-terminal domain-containing (CD)-ANGPTL4 fragments. Whereas several studies have investigated associations of free ANGPTL proteins with cardiovascular risk, there are no data describing associations of the complexes and CD-ANGPTL4 with outcomes or describing the effects of the complexes on LPL bound to GPIHBP1 (glycosylphosphatidylinositol HDL-binding protein 1). Recombinant protein assays were used to study ANGPTL protein and complex effects on GPIHBP1-LPL activity. ANGPTL3/8, ANGPTL3, ANGPTL4/8, and CD-ANGPTL4 were measured with dedicated immunoassays in 2394 LURIC (Ludwigshafen Risk and Cardiovascular Health) study participants undergoing coronary angiography and 6188 getABI study (German Epidemiological Trial on Ankle Brachial Index) participants undergoing ankle brachial index measurement. There was a follow-up for cardiovascular death with a median (interquartile range) duration of 9.80 (8.75-10.40) years in the LURIC study and 7.06 (7.00-7.14) years in the getABI study. ANGPTL3/8 potently inhibited GPIHBP1-LPL activity and showed positive associations with LDL-C (low-density lipoprotein cholesterol) and triglycerides (both P<0.001). However, in neither study did ANGPTL3/8 correlate with cardiovascular death. Free ANGPTL3 was positively associated with cardiovascular death in the getABI study but not the LURIC study. ANGPTL4/8 and especially CD-ANGPTL4 were positively associated with the prevalence of diabetes, CRP (C-reactive protein; all P<0.001), and cardiovascular death in both studies. In the LURIC and getABI studies, respective hazard ratios for cardiovascular mortality comparing the third with the first ANGPTL4/8 tertile were 1.47 (1.15-1.88) and 1.68 (1.25-2.27) when adjusted for sex, age, body mass index, and diabetes. For CD-ANGPTL4, these hazard ratios were 2.44 (1.86-3.20) and 2.76 (2.00-3.82). ANGPTL3/8 potently inhibited GPIHBP1-LPL enzymatic activity, consistent with its positive association with serum lipids. However, ANGPTL3/8, LDL-C, and triglyceride levels were not associated with cardiovascular death in the LURIC and getABI cohorts. In contrast, concentrations of ANGPTL4/8 and particularly CD-ANGPTL4 were positively associated with inflammation, the prevalence of diabetes, and cardiovascular mortality.

Real-World Evidence of Feasible Assessment and Intervention in Cardiovascular Physical Therapy for Older Patients With Heart Failure - Insight From the J-Proof HF of the Japanese Society of Cardiovascular Physical Therapy.

This study aimed to clarify the feasibility of cardiovascular physical therapy assessment and intervention in older patients with heart failure (HF) in Japan. We performed a secondary analysis of data from a nationwide multicenter registry (the J-Proof HF), and enrolled consecutive HF patients aged ≥65 years who were prescribed cardiovascular physical therapy during hospitalization from December 2020 to March 2022. Of the 9,650 enrolled patients (median age 83.0 years; 49.8% male), the availability rate of comorbidities and assessments was >95%. In the activities of daily living (ADL) assessment, the Barthel Index (BI) and Functional Independence Measure were 97.6% and 60.4%, respectively. The results of the physical therapy assessment indicated completion rates of ≥80%, with lower rates of <60% for gait speed and short-performance physical battery in the group with a BI of <85 points. In physiotherapy intervention, gait training and muscle strength training were performed by >80% of patients, whereas aerobic exercise and resistance training were performed by 35.4% and 2.6% patients, respectively. Our results in this study indicated that medical findings, such as comorbidities, echocardiography, and laboratory findings, were considered a feasible assessment that could be confirmed at all hospitals. Gait training, ADL training, and muscle strength training are much more common than exercise training in older patients with HF.

Interplay between preclinical indices of obesity and neural signatures of fluid intelligence in youth.

Pediatric obesity rates have quadrupled in the United States, and deficits in higher-order cognition have been linked to obesity, though it remains poorly understood how deviations from normal body mass are related to the neural dynamics serving cognition in youth. Herein, we determine how age- and sex-adjusted measures of body mass index (zBMI) scale with neural activity in brain regions underlying fluid intelligence. Seventy-two youth aged 9-16 years underwent high-density magnetoencephalography while performing an abstract reasoning task. The resulting data were transformed into the time-frequency domain and significant oscillatory responses were imaged using a beamformer. Whole-brain correlations with zBMI were subsequently conducted to quantify relationships between zBMI and neural activity serving abstract reasoning. Our results reveal that participants with higher zBMI exhibit attenuated theta (4-8 Hz) responses in both the left dorsolateral prefrontal cortex and left temporoparietal junction, and that weaker temporoparietal responses scale with slower reaction times. These findings suggest that higher zBMI values are associated with weaker theta oscillations in key brain regions and altered performance during an abstract reasoning task. Thus, future investigations should evaluate neurobehavioral function during abstract reasoning in youth with more severe obesity to identify the potential impact.

Thermodynamic properties of binary, ternary and quaternary mixtures: N‑butyl acetate- n-hexanol - n,n-dimethylacetamide-water. Modeling using regression algorithms and optimization using socially-inspired evolutionary algorithms

BackgroundThe design of chemical plants requires knowledge of the thermodynamic properties of the fluids involved. MethodsIn our research, we performed experimental measurements of the refractive index and density of binary, ternary and quaternary systems containing n‑butyl acetate, n-hexanol, n,n-dimethylacetamide and water, at atmospheric pressure and the following temperatures: 293.15 K, 303.15 K, 313.15 K and 323.15 K. They were used to determine the excess molar volume, which was correlated with mole fractions, normalized temperature and refractive index, using artificial neural networks and other models obtained with regression algorithms, optimized with different socially-inspired evolutionary algorithms. Significant FindingsThe best results were achieved with decision tree regression and the queuing search optimization algorithm. The present approach is based on the fact that there are few similar studies in the literature; in addition, the models obtained can complement/supplement the experimental data through predictions.

Baseline Neck Disability Index and Patient-Reported Outcomes Measurement Information System Physical Function Predict Postoperative Return to Normal in Cervical Spine Surgery.

Recent studies assessing the importance of various preoperative factors on postoperative outcomes following spine surgery have uncovered several important variables that influence subjective and objective outcomes following cervical spine surgery, but it is still unclear which patients are most likely to benefit from operative management. The objective of this study was to assess whether preoperative patient-reported outcome measures (PROMs) can be used to predict which patients achieve "normal" levels of pain and function after surgery. This was a prospective cohort study. This study included all adult patients undergoing cervical spine surgery by 1 of 7 senior spine surgeons at our institution between 2016 and 2018. Of the 164 patients who were eligible for 6-month follow-up at the time that study data were collected, 139 had available follow-up data and were included in our analysis. Patients completed the Neck Disability Index (NDI) as well as the Patient-Reported Outcomes Measurement Information System (PROMIS) Physical Function (PF) and Pain Interference computer adaptive tests preoperatively and at 6 months postoperatively. Patients who achieved postoperative patient-acceptable symptom state (PASS) for NDI (≤17) and the normative mean (50) for PROMIS were identified. The relationship between preoperative PROMs and the probability of achieving PASS and the normative mean was assessed. One hundred thirty-nine patients met inclusion criteria with diagnoses of myelopathy (n = 36), radiculopathy (n = 48), and myeloradiculopathy (n = 49). For NDI, a 1-point worsening in the preoperative score resulted in an OR of achieving PASS of 0.96 (P < 0.001) in the overall population. This association held true for patients with radiculopathy (OR 0.96; P = 0.022) but not myelopathy (OR 0.98; P = 0.35). For PROMIS PF, a 1-point improvement in the preoperative score resulted in an OR of achieving the normative mean of 1.10 (P < 0.001). This association held true for patients with radiculopathy (OR 1.14; P = 0.033) but did not reach statistical significance for patients with myelopathy (OR 1.03; P = 0.515). Preoperative PROMs can predict postoperative benefit for patients undergoing cervical spine surgery, with worse baseline function associated with a lower likelihood of attaining PASS for NDI and the normative mean for PROMIS PF, especially for patients with radiculopathy. Baseline symptoms and function, including myelopathy or radiculopathy-dominant symptoms and preoperative PROMs, may predict postoperative outcomes.

Denoising astronomical images using an enhanced Pix2Pix model

Astronomical images are frequently affected by sensor noise, which can negatively impact the accuracy of subsequent data analysis. To address this issue, this study proposes an enhanced Pix2Pix generative adversarial network model that incorporates Residual Blocks and Self-Attention mechanisms to improve denoising performance. The effectiveness of the proposed model is evaluated by comparing it with traditional denoising methods, standard Pix2Pix, Pix2Pix with Residual Blocks, and Pix2Pix with Self-Attention using Peak Signal-to-Noise Ratio (PSNR) and Structural Similarity Index Measure (SSIM) metrics. The findings demonstrate that the Pix2Pix model, when combined with both Residual Blocks and Self-Attention, significantly outperforms other models in noise reduction and detail preservation. This improved approach offers a robust solution for high-quality processing of astronomical images, providing clearer and more reliable data for scientific analysis. The results highlight the potential of advanced deep learning techniques in overcoming the challenges posed by sensor noise in astronomical imaging.

A Novel Approach to Image Classification for Detecting Abnormalities in Neuroimages based on the Structural Similarity Index Measure

A Novel Approach to Image Classification for Detecting Abnormalities in Neuroimages based on the Structural Similarity Index Measure

Refractive index sensing characteristics of PCF-SPR based on dual-plasmon materials

Abstract In this paper, a photonic crystal fiber (PCF) refractive index sensor based on surface plasmon resonance (SPR) with dual plasmonic materials (indium tin oxide and gold) is proposed. We innovatively designed a dual-core PCF structure and pore arrangement effectively enhancing the coupling effect. Using two different plasma materials, phase matching is achieved at two different wavelengths for the evanescent and surface plasmon waves, resulting in dual resonance peaks. The refractive index sensing is accomplished by measuring the dual-peak resonance shift, which expands the detection wavelength and RI detection ranges. The sensor can detect analytes with refractive indices ranging from 1.32 to 1.43 at wavelengths between 0.4 um and 1.4 um. We optimized the photonic crystal fiber structure and studied the sensing performance of the sensor, improving its sensitivity. Simulation results indicate that the designed PCF sensor exhibits outstanding maximum dual-peak shift sensitivity (DPSS), reaching up to 28,000 RIU-1, along with maximum amplitude sensitivity (AS) and wavelength sensitivity (WS) of 18,500 RIU-1 and 34,500 RIU-1, respectively, in the direction of y-polarization. Furthermore, the sensor achieves high resolution, and the figure of merit (FOM) values can reach up to 5.134×10-7 and 2758. Consequently, the proposed sensor can provide high-precision and extensive-range measurements of solution refractive indices within the visible and infrared light spectrum, and it holds potential application prospects in numerous fields, such as food safety testing and chemical substance detection.&amp;#xD;

Individualised cortical gyrification in neonates with congenital heart disease

Abstract Congenital heart disease (CHD) is associated with impaired early brain development and adverse neurodevelopmental outcomes. This study investigated how individualised measures of preoperative cortical gyrification index (GI) differ in 142 infants with CHD, using a normative modelling approach with reference data from 320 typically developing infants. GI Z-scores for the whole brain and six major cortical areas were generated using two different normative models: one accounting for postmenstrual age at scan, postnatal age at scan and sex, and another additionally accounting for supratentorial brain volume (STBV). These Z-scores were compared between CHD and control groups to test the hypothesis that cortical folding in infants with CHD deviates from the normal developmental trajectory. The relationships between whole-brain GI Z-scores from the two normative models and both cerebral oxygen delivery (CDO2) and neurodevelopmental outcomes were also investigated. Global and regional brain gyrification was significantly reduced in neonates with CHD, but not when STBV was accounted for. This finding suggests that whilst cortical folding is reduced in CHD, it is primarily driven by a reduction in brain size. There was a significant positive correlation between CDO2 and whole-brain GI Z-scores in CHD, but not when STBV was accounted for. CDO2 is therefore likely to play a more important role in the biological processes underlying volumetric brain growth than cortical folding. No significant associations between whole-brain GI Z-scores and motor/cognitive outcomes or autism traits were identified in the 70 infants with CHD who underwent neurodevelopmental assessment at 22-months. Our results suggest that chronic in-utero and early postnatal hypoxia in CHD is associated with reductions in cortical folding that are proportional to reductions in supratentorial brain volume.

Double Tseng’s Algorithm with Inertial Terms for Inclusion Problems and Applications in Image Deblurring

In this research paper, we present a novel theoretical technique, referred to as the double Tseng’s algorithm with inertial terms, for finding a common solution to two monotone inclusion problems. Developing the double Tseng’s algorithm in this manner not only comprehensively expands theoretical knowledge in this field but also provides advantages in terms of step-size parameters, which are beneficial for tuning applications and positively impact the numerical results. This new technique can be effectively applied to solve the problem of image deblurring and offers numerical advantages compared to some previously related results. By utilizing certain properties of a Lipschitz monotone operator and a maximally monotone operator, along with the identity associated with the convexity of the quadratic norm in the framework of Hilbert spaces, and by imposing some constraints on the scalar control conditions, we can achieve weak convergence to a common zero point of the sum of two monotone operators. To demonstrate the benefits and advantages of this newly proposed algorithm, we performed numerical experiments to measure the improvement in the signal–to–noise ratio (ISNR) and the structural similarity index measure (SSIM). The results of both numerical experiments (ISNR and SSIM) demonstrate that our new algorithm is more efficient and has a significant advantage over the relevant preceding algorithms.

Conditional probabilistic diffusion model driven synthetic radiogenomic applications in breast cancer.

This study addresses the heterogeneity of breast cancer (BC) by employing a Conditional Probabilistic Diffusion Model (CPDM) to synthesize Magnetic Resonance Images (MRIs) based on multi-omic data, including gene expression, copy number variation, and DNA methylation. The lack of paired medical images and genomics data in previous studies presented a challenge, which the CPDM aims to overcome. The well-trained CPDM successfully generated synthetic MRIs for 726 TCGA-BRCA patients, who lacked actual MRIs, using their multi-omic profiles. Evaluation metrics such as Frechet's Inception Distance (FID), Mean Square Error (MSE), and Structural Similarity Index Measure (SSIM) demonstrated the CPDM's effectiveness, with an FID of 2.02, MSE of 0.02, and SSIM of 0.59 based on the 15-fold cross-validation. The synthetic MRIs were used to predict clinical attributes, achieving an Area Under the Receiver-Operating-Characteristic curve (AUROC) of 0.82 and an Area Under the Precision-Recall Curve (AUPRC) of 0.84 for predicting ER+/HER2+ subtypes. Additionally, the MRIs accurately predicted BC patient survival with a Concordance-index (C-index) score of 0.88, outperforming other baseline models. This research demonstrates the potential of CPDMs in generating MRIs based on BC patients' genomic profiles, offering valuable insights for radiogenomic research and advancements in precision medicine. The study provides a novel approach to understanding BC heterogeneity for early detection and personalized treatment.

A Cubical Persistent Homology-Based Technique for Image Denoising with Topological Feature Preservation

Image denoising is a fundamental challenge in image processing, where the objective is to remove noise while preserving critical image features. Traditional denoising methods, such as Wavelet, Total Variation (TV) minimization, and Non-Local Means (NLM), often struggle to maintain the topological integrity of image features, leading to the loss of essential structures. This study proposes a Cubical Persistent Homology-Based Technique (CPHBT) that leverages persistence barcodes to identify significant topological features and reduce noise. The method selects filtration levels that preserve important features like loops and connected components. Applied to digit images, our method demonstrates superior performance, achieving a Peak Signal-to-Noise Ratio (PSNR) of 46.88 and a Structural Similarity Index Measure (SSIM) of 0.99, outperforming TV (PSNR: 21.52, SSIM: 0.9812) and NLM (PSNR: 22.09, SSIM: 0.9822). These results confirm that cubical persistent homology offers an effective solution for image denoising by balancing noise reduction and preserving critical topological features, thus enhancing overall image quality.

SSIM-Based Autoencoder Modeling to Defeat Adversarial Patch Attacks

Object detection systems are used in various fields such as autonomous vehicles and facial recognition. In particular, object detection using deep learning networks enables real-time processing in low-performance edge devices and can maintain high detection rates. However, edge devices that operate far from administrators are vulnerable to various physical attacks by malicious adversaries. In this paper, we implement a function for detecting traffic signs by using You Only Look Once (YOLO) as well as Faster-RCNN, which can be adopted by edge devices of autonomous vehicles. Then, assuming the role of a malicious attacker, we executed adversarial patch attacks with Adv-Patch and Dpatch. Trying to cause misdetection of traffic stop signs by using Adv-Patch and Dpatch, we confirmed the attacks can succeed with a high probability. To defeat these attacks, we propose an image reconstruction method using an autoencoder and the Structural Similarity Index Measure (SSIM). We confirm that the proposed method can sufficiently defend against an attack, attaining a mean Average Precision (mAP) of 91.46% even when two adversarial attacks are launched.

Combining Fusion-Based Thresholding and Non-Linear Diffusion for Improved Speckle Noise Mitigation in SAR Images

The primary concern of synthetic aperture radar (SAR) images is speckle noise, an inherent property. The creation of speckle noise is in a granular form and its nature is multiplicative. To reduce such noise from the radar images, the researchers’ primary motive is to suppress granular pattern while preserving the quality of the obtained images, thereby facilitating easier feature extraction and classification. Existing speckle-noise reduction methods often fail to preserve fine details such as edges and textures. This study proposes a fusion-based method that integrates non-linear transform-based thresholding with advanced noise reduction techniques. The proposed method is implemented on two simulated SAR images at noise variance levels of σ = from 5 to 40. The fundamental and most significant step is to analyze the effect of granular patterns in radar images before despeckling. Different performance metrics, classified into with-reference and without-reference indexes, are considered to investigate the effectiveness of the proposed despeckle method. The Signal-to-Noise Ratio (SNR) for SAR-1 at σ = 20 was observed at 16.22 dB, outperforming the next best result of 12.89 dB from the Log Compression filter. The Universal Image Quality Index (UIQI) reached 0.6987, indicating high visual quality retention across various noise levels. The proposed despeckling method demonstrated superior performance in comparison to different filters, achieving a Peak Signal-to-Noise Ratio (PSNR) improvement of up to 29.37 dB on SAR-2 at a noise variance of σ = 5, significantly higher than the best filter method’s 26.70 dB. Additionally, the method achieved a Structural Similarity Index Measure (SSIM) of 0.6538, indicating superior image quality preservation.

Integrating Deep Learning and Homomorphic Encryption for Secure Image Transmission

This paper introduces a novel approach to securing medical image transmission through the integration of deep learning techniques into cryptographic processes. Leveraging the capabilities of Backpropagation (BP), Convolutional Neural Networks (CNN), Residual Networks (ResNet), and Generative Adversarial Network (GAN), our method aims to enhance the privacy and security of medical images in real-time applications like telemedicine. The proposed system focuses on optimizing performance metrics including Peak Signal-to-Noise Ratio (PSNR), Root Mean Square Error (RMSE), Structural Similarity Index Measure (SSIM), Mean Average Precision (MAP), and encryption speed. Through experimental evaluation, our approach demonstrates promising results in terms of encryption efficiency and preservation of image quality. By addressing the critical need for secure transmission methods in healthcare, this research contributes to advancing the field of medical image cryptography and lays the groundwork for further exploration in deep learning-based security solutions for healthcare data.

Characterization of the acoustic attenuation index of perforated plasterboard ceilings and lining wall and comparison with an empirical model

Perforated plasterboards are known for their absorption performance. Measurements of the sound reduction index R is realized with these boards. Two configurations is tested in laboratory, one configuration of a perforated plasterboard ceiling suspended on concrete floor and a second configuration of perforated plasterboard lining wall fixed on 16cm concrete wall. Following this characterization, a semi-empirical model to estimate the attenuation index is proposed. The perforated board is simulated by considering an heterogeneous board of gypsum and holes related by the perforation rate. The prediction model is compared with the measurement with a good accuracy. Finally, after extrapolations of sound reduction index is proposed for other perforation rates.

Distribution of Fibrosis-4 index and vibration-controlled transient elastography-derived liver stiffness measurement for patients with metabolic dysfunction-associated steatotic liver disease in health check-up.

The multisociety consensus nomenclature has introduced steatotic liver disease (SLD) with diverse subclassifications, which are metabolic dysfunction-associated steatotic liver disease (MASLD), metabolic dysfunction and alcohol-associated steatotic liver disease (MetALD), alcohol-associated liver disease (ALD), specific etiology, and cryptogenic. We investigated their prevalence, as per the new definition, in individuals undergoing health check-ups. Additionally, we analyzed the distribution of Fibrosis-4 (FIB-4) index and vibration-controlled transient elastography (VCTE)-derived liver stiffness measurement (LSM) for MASLD. In this cross-sectional study, 6530 subjects undergoing a health check-up in Japan were included. Conventional B-mode ultrasound was carried out on all 6530 subjects, and those with MASLD underwent VCTE. The prevalence of SLD was 39.5%, comprising MASLD 28.7%, MetALD 8.6%, ALD 1.2%, specific etiology SLD 0.3%, and cryptogenic SLD 0.7%. Subjects with VCTE-derived LSM ≥8kPa constituted 2.1% of MASLD. FIB-4 ≥1.3 showed that the sensitivity, specificity, positive predictive value (PPV), and negative predictive value for diagnosing VCTE-derived LSM ≥8kPa were 60.6%, 77.0%, 5.3%, and 98.9%, respectively. The referral rate to specialists was 23.8% using FIB-4 ≥1.30. "FIB-4 ≥1.3 in subjects <65years and FIB-4 ≥2.0 in subjects ≥65years" showed higher PPV (6.7%) and lower referral rate (17.1%) compared with FIB-4 ≥1.3, but the sensitivity (54.5%) did not show adequate diagnostic capability as a noninvasive test for diagnosing VCTE-derived LSM ≥8kPa. Acknowledging the selection bias in hepatology centers, we undertook this prospective health check-up study. Although the FIB-4 index proves to be a convenient marker, it might not perform well as a primary screening tool for liver fibrosis in the general population (UMIN Clinical Trials Registry No. UMIN000035188).

Wooden multistorey acoustic test facility for vibration reduction indices measurement on different junctions of floor decking used to reduce flanking transmissions

FCBA, CSTB and Cerqual joint forces together with the French acoustic wood technical commission, to create in 2020, an in-situ measurement mockup: the "Maquette Acoustique Bois". The mockup is a CLT based building of three floors construction, with four rooms on each level. Measurements from junction characterization to air-borne and impact sound insulations can be performed. In this paper the "Maquette Acoustique Bois" is used to measure vibration reductions levels indexes Kij, in different configurations, where smart building systems junctions are implemented to reduce flanking transmissions. Measurement results presented are generated from 4 types of junctions in between 2 rooms. The load bearing structure is Cross Laminated Timber (CLT). The measurement strategy is Statistical Energy Analysis (SEA). SEA involves cutting the structure into subsystems and decomposing the spectrum into third-octaves or octaves. In this way, the exchange of energy flow in the substructures can be analyzed. The parameters that govern vibrational transmission between subsystems are damping and coupling loss factors and can be identified experimentally by reversing the problem. The approach is, first, based on sub-structuring strategy of structure; second, on experimentally measured coupling and damping loss factors; third, on extracting vibration level difference one by one all flanking passes.

Maternal vascular indices and hemodynamic parameters at 36 weeks' gestation in gestational and pre-existing diabetes mellitus.

To compare maternal vascular indices and hemodynamic parameters at 35-37 weeks' gestation in pregnancies complicated by gestational diabetes mellitus (GDM), those with pre-existing diabetes mellitus (DM) and those without GDM or pre-existing DM. This was a prospective observational study in women with a singleton pregnancy attending for a routine hospital visit at 35 + 0 to 36 + 6 weeks' gestation. The visit included recording of maternal demographic characteristics and medical history, and measurement of vascular indices and hemodynamic parameters using a non-invasive operator-independent device. These included carotid-to-femoral pulse-wave velocity, augmentation index, cardiac output, stroke volume, central systolic and diastolic blood pressure, total peripheral resistance and heart rate. The values in the GDM and pre-existing DM groups were compared to those in the unaffected group. We examined 6746 women, of whom 396 were excluded because they had chronic hypertension or developed pre-eclampsia or gestational hypertension. The study population of 6350 pregnancies contained 99 (1.6%) with pre-existing Type-I or Type-II DM and 617 (9.7%) that developed GDM, including 261 (42.3%) that were treated with diet alone, 239 (38.7%) treated with metformin alone and 117 (19.0%) treated with insulin with or without metformin. Among women with GDM and those with pre-existing DM, compared to those without GDM or pre-existing DM, there was a higher median cardiac output and heart rate, central systolic and diastolic blood pressure and pulse-wave velocity, but there was no significant difference in stroke volume and total peripheral resistance. There were no significant differences within the GDM group according to treatment type, except for higher heart rate in women treated with metformin alone compared to the group treated with diet alone. Women with GDM and those with pre-existing DM have evidence of early vascular disease in the third trimester, and this may contribute to their increased long-term cardiovascular risk. © 2024 International Society of Ultrasound in Obstetrics and Gynecology.

Mapping between measurement scales in meta-analysis, with application to measures of body mass index in children.

Quantitative evidence synthesis methods aim to combine data from multiple medical trials to infer relative effects of different interventions. A challenge arises when trials report continuous outcomes on different measurement scales. To include all evidence in one coherent analysis, we require methods to "map" the outcomes onto a single scale. This is particularly challenging when trials report aggregate rather than individual data. We are motivated by a meta-analysis of interventions to prevent obesity in children. Trials report aggregate measurements of body mass index (BMI) either expressed as raw values or standardized for age and sex. We develop three methods for mapping between aggregate BMI data using known or estimated relationships between measurements on different scales at the individual level. The first is an analytical method based on the mathematical definitions of z-scores and percentiles. The other two approaches involve sampling individual participant data on which to perform the conversions. One method is a straightforward sampling routine, while the other involves optimization with respect to the reported outcomes. In contrast to the analytical approach, these methods also have wider applicability for mapping between any pair of measurement scales with known or estimable individual-level relationships. We verify and contrast our methods using simulation studies and trials from our data set which report outcomes on multiple scales. We find that all methods recreate mean values with reasonable accuracy, but for standard deviations, optimization outperforms the other methods. However, the optimization method is more likely to underestimate standard deviations and is vulnerable to non-convergence.