Small Mean Difference Research Articles

Improved ground truth annotation by multimodal image registration from 3D ultrasound to histopathology for resected tongue carcinoma.

This study's objectives are (1) to investigate the registration accuracy from intraoperative ultrasound (US) to histopathological images, (2) to assess the agreement and correlation between measurements in registered 3D US and histopathology, and (3) to train a nnUNet model for automatic segmentation of 3D US volumes of resected tongue specimens. Ten 3D US volumes were acquired, including the corresponding digitalized histopathological images (n = 29). Based on corresponding landmarks, the registrations between 3D US and histopathology images were calculated and evaluated using the target registration error (TRE). Tumor thickness and resection margins were measured based on three annotations: (1) manual histopathological tumor annotation (HTA), manual 3D US tumor annotation, and (2) the HTA registered in the 3D US. The agreement and correlation were computed between the measurements based on the HTA and those based on the manual US and registered HTA in US. A deep-learning model with nnUNet was trained on 151 3D US volumes. Segmentation metrics quantified the model's performance. The median TRE was 0.42mm. The smallest mean difference was between registered HTA in US and histopathology with 2.16mm (95% CI - 1.31; 5.63) and a correlation of 0.924 (p < 0.001). The nnUNet predicted the tumor with a Dice similarity coefficient of 0.621, an average surface distance of 1.15mm, and a Hausdorff distance of 3.70mm. Multimodal image registration enabled the HTA's registration in the US images and improved the agreement and correlation between the modalities. In the future, this could be used to annotate ground truth labels accurately.

Development and evaluation of a novel user-operated slider-based audiometry method.

To evaluate a novel user-operated audiometry method allowing users full control in determining their pure-tone hearing thresholds. Comparative study. Participants were recruited from a hearing clinic after undergoing manual audiometry (six frequencies). They then performed test-retests of a new test (slider audiometry, eight frequencies) and completed the System Usability Scale questionnaire. 37 adult participants, including 30 hearing-impaired and seven normal-hearing individuals. Mean (SD) threshold differences for octave frequencies between 250 to 2000 Hz between manual and slider audiometry ranged from -7.8 (6.6) to -5.7 (6.5) dB and were significant. For 4000 and 8000 Hz mean differences were -0.3 (8.4) and 0.0 (9.7) dB and insignificant. Standard deviations ranged from 6.5 to 9.7 dB across six tested frequencies. Slider test-retest mean threshold differences ranged from -1.4 (4.7) to 0.3 (6.0) dB across eight tested frequencies, with standard deviations ranging from 4.1 to 8.5 dB. The average usability score for the slider audiometry was 88.3. When compared to manual audiometry, the slider audiometry demonstrated validity at 4000 and 8000 Hz but found significantly lower thresholds for octave frequencies between 250 to 2000 Hz. Test-retests of the new method revealed small mean differences and acceptable SDs.

Comparing Device-Generated and Calculated Bioimpedance Variables in Community-Dwelling Older Adults.

Despite BIA emerging as a clinical tool for assessing older adults, it remains unclear how to calculate whole-body impedance (Z), reactance (Xc), resistance (R), and phase angle (PhA) from segmental values using modern BIA devices that place electrodes on both sides of the body. This investigation aimed to compare both the whole-body and segmental device-generated phase angle (PhADG) with the phase angle calculated using summed Z, Xc, and R from the left, right, and combined sides of the body (PhACalc) and to compare bioelectric variables between sides of the body. A sample of 103 community-dwelling older adults was assessed using a 50 kHz direct segmental multifrequency BIA device. Whole-body PhACalc values were assessed for agreement with PhADG using 2.5th and 97.5th quantile nonparametric limits of agreement and Spearman's rho. Bioelectrical values between sides of the body were compared using Wilcoxon rank and Spearman's rho. A smaller mean difference was observed between PhADG and right PhACalc (-0.004°, p = 0.26) than between PhACalc on the left (0.107°, p = 0.01) and on the combined sides (0.107°, p < 0.001). The sum of Z, R, and PhACalc was significantly different (p < 0.01) between the left (559.66 ± 99.55 Ω, 556.80 ± 99.52 Ω, 5.51 ± 1.5°, respectively) and the right sides (554.60 ± 94.52 Ω, 552.02 ± 94.23 Ω, 5.41 ± 0.8°, respectively). Bilateral BIA values do not appear to be interchangeable when determining whole-body measurements. Present data suggest that using right-sided segmental values would be the most appropriate choice for calculating whole-body bioelectrical variables.

Objective approach in the assessment of speech quality in patients with tongue cancer after hemiglossectomy

Introduction. Surgery is the leading treatment for tongue cancer, performance which leads to impaired speech function. Because speech is one of the most important tools of social interaction, its disorder can significantly affect patients’ quality of life. To date, there is no generally accepted objective approach to assessing the quality of speech that would make it possible to analyze speech changes at different stages of therapy and help in development of treatment strategy.Aim. To compare the sound reproduction of patients with tongue cancer after hemiglossectomy with and without reconstruction using an objective assessment method, namely – a special software.Materials and methods. The study included 29 patients who received surgical treatment in the volume of hemiglossectomy with ipsilateral cervical lymphodissection. The patients were divided into 2 groups: the group 1 included 14 patients who underwent reconstruction with submental, radial and buccal flaps, the group 2 – 15 patients who did not underwent it. Sound reproduction by each patient was recorded before the operation, no earlier than 10–12 days after it (session of type 1) and after the end of specialized treatment: radiation therapy, chemoradiation therapy (session of type 2). If adjuvant therapy was not prescribed, the type 2 session was performed 3–6 months after surgery. The records made during sessions of the types 1 and 2 were compared with records of preoperative session. During each session, the pronunciation of 30 syllables containing 3 problematic sounds was recorded: [k], [s] and [t] (10 syllables with each of the sounds). The differences in the data obtained during the sessions types 1 and 2 were analyzed according both the syllable set and separately for each sound studied.Results. The reconstruction performed improves sound pronunciation [t] after hemiglossectomy both after surgery and 3–6 months after the end of specialized treatment (p &lt;0.01). After completion of specialized treatment, the pronunciation of the sound [s] significantly improved in both groups. However, in the reconstruction group, the variations in pronunciation values of this sound before the operation and after it obtained in the groups 1 and 2 were significantly reduced. During the assessment of the pronunciation of sound [k], the similar data were obtained. When comparing the quality of speech of patients during the type 2 session, the best results were obtained in group 1: in patients of this group, there were smaller mean differences in the sounds pronunciation as compared to the initial recording (p &lt;0.001) than in patients of group 2.Conclusion. Resection of the tongue most negatively affects pronunciation of the dental-alveolar sounds than the whistling or palatine-dental sounds. The time factor has a positive effect on the speech quality of patients, therefore, the assessment of sound reproduction in patients after hemiglossectomy should be performed no earlier than 3–6 months after the end of specialized treatment.

Reliability and agreement of manual and automated morphological radiographic hip measurements

ObjectiveTo determine the reliability and agreement of manual and automated morphological measurements, and agreement in morphological diagnoses. MethodsThirty pelvic radiographs were randomly selected from the World COACH consortium. Manual and automated measurements of acetabular depth-width ratio (ADR), modified acetabular index (mAI), alpha angle (AA), Wiberg center edge angle (WCEA), lateral center edge angle (LCEA), extrusion index (EI), neck-shaft angle (NSA), and triangular index ratio (TIR) were performed. Bland-Altman plots and intraclass correlation coefficients (ICCs) were used to test reliability. Agreement in diagnosing acetabular dysplasia, pincer and cam morphology by manual and automated measurements was assessed using percentage agreement. Visualizations of all measurements were scored by a radiologist. ResultsThe Bland-Altman plots showed no to small mean differences between automated and manual measurements for all measurements except for ADR. Intraobserver ICCs of manual measurements ranged from 0.26 (95%-CI 0–0.57) for TIR to 0.95 (95%-CI 0.87–0.98) for LCEA. Interobserver ICCs of manual measurements ranged from 0.43 (95%-CI 0.10–0.68) for AA to 0.95 (95%-CI 0.86–0.98) for LCEA. Intermethod ICCs ranged from 0.46 (95%-CI 0.12–0.70) for AA to 0.89 (95%-CI 0.78–0.94) for LCEA. Radiographic diagnostic agreement ranged from 47% to 100% for the manual observers and 63%–96% for the automated method as assessed by the radiologist. ConclusionThe automated algorithm performed equally well compared to manual measurement by trained observers, attesting to its reliability and efficiency in rapidly computing morphological measurements. This validated method can aid clinical practice and accelerate hip osteoarthritis research.

Validation of an web-based dietary assessment tool (RiksmatenFlex) against doubly labelled water and 24 h dietary recalls in pregnant women

IntroductionDigital technologies have enabled new possibilities to assess dietary intake and have shown promise in terms of decreased participant burden, improved accuracy and lower costs. However, their potential and validity in pregnant populations are scarcely explored.ObjectivesThis study aimed to (a) validate energy intakes obtained from a web-based dietary recall method developed for national surveys (RiksmatenFlex) against total energy expenditure (TEE) by means of the doubly labelled water (DLW) method, and (b) to compare intakes of macronutrients, key unhealthy and healthy foods as well as adherence to food-based dietary guidelines between RiksmatenFlex and repeated 24 h telephone dietary recalls in healthy Swedish pregnant women.MethodsThis study was conducted as a nested validation within the HealthyMoms trial. Intakes of foods, macronutrients and energy were assessed during three days through RiksmatenFlex and 24 h telephone dietary recalls, and Swedish Healthy Eating Index (SHEI) scores were also calculated for both methods (n = 52). For 24 women, TEE was also assessed through the DLW method. Paired Samples T-tests and Wilcoxon Signed Ranks Tests were used to identify differences between means for foods, macronutrients, energy and SHEI scores. Pearson correlation coefficient or Spearman’s rho were performed to identify relationships between variables. To compare energy intake (RiksmatenFlex) with TEE (DLW method) and 24 h telephone dietary recalls, Bland and Altman plots were constructed.ResultsAverage energy intake from RiksmatenFlex (10,015 [SD 2004] kJ) was not statistically different from TEE (10,252 [SD 1197] kJ) (p = 0.596) (mean difference: -237 kJ/24 h). Correspondingly, there were small mean differences between average intakes of key unhealthy and healthy foods and average SHEI scores between RiksmatenFlex and 24 h telephone dietary recalls. However, the Bland and Altman plots showed wide limits of agreement for all dietary variables (e.g., for energy intake using RiksmatenFlex versus TEE: ±4239 kJ/24 h). High correlations between the investigated dietary variables for the two dietary methods were observed (r = 0.751 to 0.931; all p < 0.001).ConclusionRiksmatenFlex captured average intakes of energy, unhealthy and healthy food groups and adherence to food-based dietary guidelines in a comparable way to 24 h telephone dietary recalls and the DLW method. Our results support the validity of RiksmatenFlex as a web-based dietary assessment method for future use in pregnancy for intervention studies and national dietary surveys.

SMOS-derived Antarctic thin sea ice thickness: data description and validation in the Weddell Sea

Abstract. Accurate satellite measurements of the thickness of Antarctic sea ice are urgently needed but pose a particular challenge. The Antarctic data presented here were produced using a method to derive the sea ice thickness from 1.4 GHz brightness temperatures previously developed for the Arctic, with only modified auxiliary data. The ability to observe the thickness of thin sea ice using this method is limited to cold conditions, meaning it is only reasonable during the freezing period, typically March to October. The Soil Moisture and Ocean Salinity (SMOS) level-3 sea ice thickness product contains estimates of the sea ice thickness and its uncertainty up to a thickness of about 1 m. The sea ice thickness is provided as a daily average on a polar stereographic projection grid with a sample resolution of 12.5 km, while the SMOS brightness temperature data used have a footprint size of about 35–40 km in diameter. Data from SMOS have been available since 2010, and the mission's operation has been extended to continue until at least the end of 2025. Here we compare two versions of the SMOS Antarctic sea ice thickness product which are based on different level-1 input data (v3.2 based on SMOS L1C v620 and v3.3 based on SMOS L1C 724). A validation is performed to generate a first baseline reference for future improvements of the retrieval algorithm and synergies with other sensors. Sea ice thickness measurements to validate the SMOS product are particularly rare in Antarctica, especially during the winter season and for the valid range of thicknesses. From the available validation measurements, we selected datasets from the Weddell Sea that have varying degrees of representativeness: Helicopter-based EM Bird (HEM), Surface and Under-Ice Trawl (SUIT), and stationary Upward-Looking Sonars (ULS). While the helicopter can measure hundreds of kilometres, SUIT's use is limited to distances of a few kilometres and thus only captures a small fraction of an SMOS footprint. Compared to SMOS, the ULS are point measurements and multi-year time series are necessary to enable a statistically representative comparison. Only four of the ULS moorings have a temporal overlap with SMOS in the year 2010. Based on selected averaged HEM flights and monthly ULS climatologies, we find a small mean difference (bias) of less than 10 cm and a root mean square deviation of about 20 cm with a correlation coefficient R &gt; 0.9 for the valid sea ice thickness range between 0 and about 1 m. The SMOS sea ice thickness showed an underestimate of about 40 cm with respect to the less representative SUIT validation data in the marginal ice zone. Compared with sea ice thickness outside the valid range, we find that SMOS strongly underestimates the real values, which underlines the need for combination with other sensors such as altimeters. In summary, the overall validity of the SMOS sea ice thickness for thin sea ice up to a thickness of about 1 m has been demonstrated through validation with multiple datasets. To ensure the quality of the SMOS product, an independent regional sea ice extent index was used for control. We found that the new version, v3.3, is slightly improved in terms of completeness, indicating fewer missing data. However, it is worth noting that the general characteristics of both datasets are very similar, also with the same limitations. Archived data are available in the PANGAEA repository at https://doi.org/10.1594/PANGAEA.934732 (Tian-Kunze and Kaleschke, 2021) and operationally at https://doi.org/10.57780/sm1-5ebe10b (European Space Agency, 2023).

Estimating Surgical Urethral Length on Intraoperative Robot-Assisted Prostatectomy Images Using Artificial Intelligence Anatomy Recognition.

Objective: To construct a convolutional neural network (CNN) model that can recognize and delineate anatomic structures on intraoperative video frames of robot-assisted radical prostatectomy (RARP) and to use these annotations to predict the surgical urethral length (SUL). Background: Urethral dissection during RARP impacts patient urinary incontinence (UI) outcomes, and requires extensive training. Large differences exist between incontinence outcomes of different urologists and hospitals. Also, surgeon experience and education are critical toward optimal outcomes. Therefore, new approaches are warranted. SUL is associated with UI. Artificial intelligence (AI) surgical image segmentation using a CNN could automate SUL estimation and contribute toward future AI-assisted RARP and surgeon guidance. Methods: Eighty-eight intraoperative RARP videos between June 2009 and September 2014 were collected from a single center. Two hundred sixty-four frames were annotated according to prostate, urethra, ligated plexus, and catheter. Thirty annotated images from different RARP videos were used as a test data set. The dice (similarity) coefficient (DSC) and 95th percentile Hausdorff distance (Hd95) were used to determine model performance. SUL was calculated using the catheter as a reference. Results: The DSC of the best performing model were 0.735 and 0.755 for the catheter and urethra classes, respectively, with a Hd95 of 29.27 and 72.62, respectively. The model performed moderately on the ligated plexus and prostate. The predicted SUL showed a mean difference of 0.64 to 1.86 mm difference vs human annotators, but with significant deviation (standard deviation = 3.28-3.56). Conclusion: This study shows that an AI image segmentation model can predict vital structures during RARP urethral dissection with moderate to fair accuracy. SUL estimation derived from it showed large deviations and outliers when compared with human annotators, but with a small mean difference (<2 mm). This is a promising development for further research on AI-assisted RARP.

Clinical validation of the accuracy of an intra-operative assessment tool using 3D ultrasound compared to histopathology in patients with squamous cell carcinoma of the tongue

BackgroundHistopathological analysis often shows close resection margins after surgical removal of tongue squamous cell carcinoma (TSCC). This study aimed to investigate the agreement between intraoperative 3D ultrasound (US) margin assessment and postoperative histopathology of resected TSCC.MethodsIn this study, ten patients were prospectively included. Three fiducial cannulas were inserted into the specimen. To acquire a motorized 3D US volume, the resected specimen was submerged in saline, after which images were acquired while the probe moved over the specimen. The US volumes were annotated twice: (1) automatically and (2) manually, with the automatic segmentation as initialization. After standardized histopathological processing, all hematoxylin-eosin whole slide images (WSI) were included for analysis. Corresponding US images were found based on the known WSI spacing and fiducials. Blinded observers measured the tumor thickness and the margin in the caudal, deep, and cranial directions on every slide. The anterior and posterior margin was measured per specimen.ResultsThe mean difference in all measurements between manually segmented US and histopathology was 2.34 (SD: ±3.34) mm, and Spearman’s rank correlation coefficient was 0.733 (p < 0.001). The smallest mean difference was in the tumor thickness with 0.80 (SD: ±2.44) mm and a correlation of 0.836 (p < 0.001). Limitations were observed in the caudal region, where no correlation was found.ConclusionThis study shows that 3D US and histopathology have a moderate to strong statistically significant correlation (r = 0.733; p < 0.001) and a mean difference between the modalities of 2.3 mm (95%CI: -4.2; 8.9). Future research should focus on patient outcomes regarding resection margins.

A Pilot Comparative Study between Creatinine- and Cystatin-C-Based Equations to Estimate GFR and Kidney Ultrasound Percentiles in Children with Congenital Anomalies of the Kidney and Urinary Tract.

Congenital anomalies affecting the kidneys present significant challenges in pediatric nephrology, needing precise methods for assessing renal function and guiding therapeutic intervention. Bedside Schwartz formula with the cystatin-C-based Full Age Spectrum formula and Chronic Kidney Disease in Children (CKiD) U 25 formula used in estimating glomerular filtration rate (eGFR) and also to assess if the eGFR in association with kidney length percentiles can be a monitoring parameter for the progression of chronic kidney disease in children with congenital anomalies of the kidney and urinary tract (CAKUT). A total of 64 pediatric patients (median age at diagnostic was 12 months with an interquartile range of 2 to 60) were diagnosed with congenital anomalies in the kidney and urinary tract between June 2018 and May 2023 at "Louis Turcanu" Emergency Hospital for Children in Timisoara, Romania. Baseline characteristics, CAKUT types, associated pathologies, CKD staging, and eGFR using creatinine and cystatin C were analyzed. The mean age at the moment of examination was 116.50 months; (65, 180). Chronic kidney disease staging revealed a predominance of patients in CKD stages G1 and A1. Analysis of eGFR methods revealed a small mean difference between eGFR estimated by creatinine and cystatin C, with a moderate-strong positive correlation observed between the eGFR and ultrasound parameters. Using cystatin-C-based formulas for eGFR, in conjunction with ultrasound measurements, may offer reliable insights into renal function in pediatric patients with congenital anomalies affecting the kidney and urinary tract. However, the economic aspect must be taken into consideration because cystatin C determination is approximately eight times more expensive than that of creatinine. An interdisciplinary approach is crucial for managing patients with CAKUT.

Comparison of Sysmex XN-V body fluid mode and deep-learning-based quantification with manual techniques for total nucleated cell count and differential count for equine bronchoalveolar lavage samples.

Bronchoalveolar lavage (BAL) is a diagnostic method for the assessment of the lower respiratory airway health status in horses. Differential cell count and sometimes also total nucleated cell count (TNCC) are routinely measured by time-consuming manual methods, while faster automated methods exist. The aims of this study were to compare: 1) the Sysmex XN-V body fluid (BF) mode with the manual techniques for TNCC and two-part differential into mononuclear and polymorphonuclear cells; 2) the Olympus VS200 slide scanner and software generated deep-learning-based algorithm with manual techniques for four-part differential cell count into alveolar macrophages, lymphocytes, neutrophils, and mast cells. The methods were compared in 69 clinical BAL samples. Incorrect gating by the Sysmex BF mode was observed on many scattergrams, therefore all samples were reanalyzed with manually set gates. For the TNCC, a proportional and systematic bias with a correlation of r = 0.79 was seen when comparing the Sysmex BF mode with manual methods. For the two-part differential count, a mild constant and proportional bias and a very small mean difference with moderate limits of agreement with a correlation of r = 0.84 and 0.83 were seen when comparing the Sysmex BF mode with manual methods. The Sysmex BF mode classified significantly more samples as abnormal based on the TNCC and the two-part differential compared to the manual method. When comparing the Olympus VS200 deep-learning-based algorithm with manual methods for the four-part differential cell count, a very small bias in the regression analysis and a very small mean difference in the difference plot, as well as a correlation of r = 0.85 to 0.92 were observed for all four cell categories. The Olympus VS200 deep-learning-based algorithm also showed better precision than manual methods for the four-part differential cell count, especially with an increasing number of analyzed cells. The Sysmex XN-V BF mode can be used for TNCC and two-part differential count measurements after reanalyzing the samples with manually set gates. The Olympus VS200 deep-learning-based algorithm correlates well with the manual methods, while showing better precision and can be used for a four-part differential cell count.

Rectal and axillary admission temperature in preterm infants less than 32 weeks' gestation, a prospective study.

The purpose of this research was to evaluate the differences between rectal and axillary temperature measurements in preterm infants who were born less than 32 weeks' gestation using digital thermometers upon their admission to the Neonatal Intensive Care Unit (NICU). Prospective, observational, single centre study. Rectal and axillary temperatures measurements were performed using a digital thermometer. The study examined various maternal and neonatal factors to describe the study group, including the use of prenatal corticosteroids, the occurrence of maternal diabetes and hypertension, a history of maternal prolonged rupture of membranes (PROM), maternal chorioamnionitis, the mode of delivery, along with the neonate's gender, birth weight, and gestational age. The Pearson correlation coefficient (R) was calculated to ascertain the linear relationship between the temperatures taken at the rectal and axillary sites. The concordance between the two sets of temperature data was analyzed using the Bland-Altman method. Eighty infants with a mean gestational age of 28.4 weeks (SD = 2.9) and a mean birth weight of 1,229 g (SD = 456) were included in the study. The mean axillary temperature was 36.4 °C (SD = 0.7), which was lower than the mean rectal temperature of 36.6 °C (SD = 0.6) (p = 0.012). Rectal temperatures surpassed axillary measurements in 59% of instances, while the reverse was observed in 21% of cases. Rectal and axillary temperatures had a strong correlation (Pearson correlation coefficient of 0.915, p < 0.001). Bland-Altman plot showed a small mean difference of 0.1C between the two temperatures measurements but the limits of agreement were wide (+0.7 to -0.6 °C). For hypothermic infants, the mean difference between rectal and axillary temperatures was 0.27 °C, with a wide limit of agreement ranging from -0.5 °C to +1 °C. Conversely, for normothermic infants, the mean difference was smaller at 0.1 °C, with a narrower limit of agreement from -0.4 °C to +0.6 °C. While there is a good correlation between axillary and rectal temperatures, the wider limits of agreement indicate variability, particularly in hypothermic infants. For a more accurate assessment of core body temperature in hypothermic infants, clinicians should consider using rectal measurements to ensure effective thermal regulation and better clinical outcomes.

Comparison of post-auricular and frontal bispectral index values obtained during renal surgeries

BackgroundThe bispectral index (BIS) monitor is one of the EEG-derived monitoring techniques and well-established devices used to measure the depth of anesthesia. This study aimed to assess the agreement of BIS values based on the positions of either post-auricular or frontal sensors in individual patients undergoing renal surgeries while lateral positions at various stages of anesthesia.Patients and methods12 patients older than 18 years, ASA I-III patients scheduled for elective renal operations, two BIS were placed on each patient, one on each side of the post-auricular region and one across the forehead, and each sensor was connected to a different BIS monitor. We gathered three pieces of data at each of the six-time points: BIS score, signal quality index (SQI) score calculating the signal’s strength and electromyography (EMG) score: before the onset of anesthesia (awake) when the eyelash reflex is lost (LOC), after intubation (intubation), following the initial surgical incision, each 30 min throughout the procedure (maintenance), and at the moment the patient’s eyes open naturally after waking up from anesthesia (emergence).ResultsThe overall BIS value at the frontal position was significantly higher than the post-auricular position (52.5 ± 22.2 and 52.1 ± 22.1, respectively, P = 0.010). On the other hand, the BIS value was comparable between the frontal and post-auricular positions at LOC, intubation, 60, 120, and 80 min and at emergence. A strong link between the two sensor positions, as indicated by the correlation coefficient (r = 0.607, P < 0.001), and the Bland-Altman analysis revealed a small mean difference (-1.8) and a low (9.0/- 12.5) limit of agreement, with just 4.3% of the readings falling outside of it during the anesthetic maintenance period.ConclusionAcceptable variation in BIS data was observed when obtained from the two different sensor positions for clinical usage. The post-auricular BIS sensor system may be a suitable substitute for an impractical frontal setup.Protocol RegistrationThe study was registered in clinicaltrials.gov on 11/07/2022 (trial registration number: NCT05451823).

Persistent organic pollutant exposure as a risk factor of gestational diabetes mellitus: A systematic review and meta-analysis.

Findings related to the association between persistent organic pollutants (POPs) and gestational diabetes mellitus (GDM) are inconclusive. To estimate the strength of the association between POP exposure and GDM in a systematic review with meta-analysis. MEDLINE, Scopus and Web of Science were searched until July 2023. Cohort and case-control studies analysing the association between POPs and GDM. We assessed the risk of bias using the Quality in Prognosis Studies scale (QUIPS). Standardised mean differences were pooled using random-effect models. Sixteen articles including 12 216 participants were selected. The risk of bias was high in four articles (25%), moderate in 11 (68.75%) and low in one (6.25%). Small mean difference between GDM cases and controls was observed for PFHpA (0.26, 95% confidence interval [CI] 0.1-0.35, I2 = 0.0%), PCB180 (0.37, 95% CI 0.19-0.56; I2 = 25.3%), BDE47 (0.23, 95% CI 0.0-0.45, I2 = 0%), BDE99 (0.36, 95% CI 0.14-0.59; I2 = 0%), BDE100 (0.42, 95% CI 0.19-0.64; I2 = 0%) and HCB (0.22, 95% CI 0.01-0.42, I2 = 39.6%). No considerable difference was observed for the rest of POPs. Small mean differences between GDM cases and controls were observed for some POPs. However, evidence shows mostly moderate quality and results were heterogeneous. Improved research methodology is needed to assess POPs and GDM risk.

Dynamic Contrast-enhanced CT Lymphangiography to Quantify Thoracic Duct Lymphatic Flow.

Background CT lymphangiography has been used to image the lymphatic anatomy and assess lymphatic abnormalities. There is, however, a need to develop a method for quantification of lymphatic flow rate in the thoracic duct (TD). Purpose To develop and validate a TD lymphatic flow measurement technique using dynamic contrast-enhanced CT lymphangiography. Materials and Methods Lymphatic flow rate was measured with two techniques: a first-pass analysis technique based on a single compartment model and a thresholding technique distinguishing between opacified and nonopacified voxels within the TD. The measurements were validated in a swine animal model between November 2021 and September 2022. CT images were acquired at 100 kV and 200 mA using a fast-pitched helical scan mode covering the entire TD following contrast material injection into the bilateral inguinal lymph nodes. Two helical CT scans, acquired at the base and peak contrast enhancement of the TD, were used to measure lymphatic flow rate. A US flow probe surgically placed around the TD provided the reference standard measurement. CT lymphatic flow measurements were compared with the reference US flow probe measurements using regression and Bland-Altman analysis. Repeatability was determined using repeated flow measurements within approximately 10 minutes of each other. Results Eleven swine (10 male; mean weight, 43.6 kg ± 2.6 [SD]) were evaluated with 71 dynamic CT acquisitions. The lymphatic flow rates measured using the first-pass analysis and thresholding techniques were highly correlated with the reference US flow probe measurements (r = 0.99 and 0.91, respectively) and showed good agreement with the reference standard, with Bland-Altman analysis showing small mean differences of 0.04 and 0.05 mL/min, respectively. The first-pass analysis and thresholding techniques also showed good agreement for repeated flow measurements (r = 0.94 and 0.90, respectively), with small mean differences of 0.09 and 0.03 mL/min, respectively. Conclusion The first-pass analysis and thresholding techniques could be used to accurately and noninvasively quantify TD lymphatic flow using dynamic contrast-enhanced CT lymphangiography. © RSNA, 2023 See also the editorial by Choyke in this issue.

Comparison of Outcomes of Hematopoietic Cell Transplantation (HCT) for Asymptomatic Patients with Sickle Cell Disease (SCD) and That of Propensity Matched Symptomatic Patients Undergoing HCT

Introduction Hematopoietic cell transplantation (HCT), a potential curative option for sickle cell disease (SCD) has typically been offered to patients with severe disease manifestations. With improved outcomes, especially in young children receiving HCT from HLA identical donors, some clinicians are performing HCT for patients without severe manifestations. HCT is associated with risk of substantial short-term morbidity, death, and long-term sequelae. Performance of HCT in patients who have not yet suffered from complications of SCD, raises unique issues of cost-benefit tradeoff, ethics, and healthcare equity. Further, it is unknown whether patients who have not suffered complications of SCD would have better outcomes following HCT. The objective of this study was to compare the outcomes for asymptomatic patients in patients undergoing HCT for SCD and propensity matched symptomatic SCD patients undergoing HCT. Methods: We queried the HCT for SCD dataset of patients undergoing HCT between 1990-2022 and reported to the Center for International Bone Marrow Research (CIBMTR) registry. Transplant essential data had been submitted for all patients while a subset of patients was assigned to the comprehensive research form (CRF) track. On these patients HCT centers submitted detailed SCD specific baseline data, as well as outcomes relevant to SCD and organ specific complications. The main reason for HCT is one of the variables collected in the CRF. Thus, we selected patients in the CRF track for further study. We describe demographics, baseline characteristics, transplant essential outcomes including overall survival (OS) and event free survival (EFS), graft failure (GF), Acute graft versus host disease (aGVHD) and chronic GVHD (cGVHD), venocclusive disease of the liver (VOD), post-transplant pneumonia/acute chest syndrome or other pulmonary complications(ACS), nephropathy, stroke, avascular necrosis (AVN), vasocclusive crises (VOC). We created a propensity score model, adding baseline variables. For each categorical outcome variable, frequency tables and tests of difference in proportions were derived. Descriptive statistics and tests of difference in means were derived for the two numeric outcome variables. In addition, survival analysis (Cox regression modeling) was conducted to determine the time until an individual experienced graft failure or death and whether event rates were associated with group classification adjusting for age and donor type. Results: For the entire cohort of 1718 patients undergoing HCT from 1990 to 2022 patients were followed for a median 47.8 months (0.3-312.9), 73.4% of patients with age at HCT &amp;lt;18 years and 74.7% with Karnofsky-Lansky score ≥ 90. The 3-year OS was 91.2%, 3-year EFS 75.5%, and GF rate was 17.9%, aGVHD grades II-IV occurred in 18.3%, and cGVHD developed in 22.3%. A total of 763 patients were assigned to the CRF track. The main reason for HCT was reported for these patients, and 49 patients were reported to be asymptomatic at baseline. In the asymptomatic patients majority of the HCT were performed for patients under the age of 10 years (n = 33) in patients with Hemoglobin SS (n = 45) and most occurred between 2013-2018 (n = 24). Average follow up period was 48 months. The most common graft source and conditioning regimens utilized were bone marrow (n = 35) HLA identical sibling donor type (63.2%, n = 31), and reduced intensity conditioning (n = 25) respectively. Other donor types included HLA mismatched relative (n = 9), mismatched unrelated donor and cord blood (n = 5), and matched unrelated was used in 4 patients. There was one death, at 16.5 months with cGvHD. GF occurred in 14.3%, OS was 97.9%, EFS 83.67%, 20.4% developed aGvHD and 28.5% developed cGvHD and none developed secondary malignancies or post-transplant lymphoproliferative disorders. Propensity matched control group (Figure 1) was constructed based on age at HCT, donor type, graft type, HCT comorbidity index, SCD type. There was good variable balance with a small standardized mean difference for matched observations. There were no statistically significant differences in least mean squares for EFS, death, OS, GF, AGVHD, CGVHD, VOD, VOC, AVN, stroke or ACS between the propensity matched groups ( Figure 1). Discussion: Complications and outcomes of HCT in asymptomatic patients with SCD patients is similar to that in propensity matched symptomatic SCD patients undergoing HCT.

Are parent-reported sleep logs essential? A comparison of three approaches to guide open source accelerometry-based nocturnal sleep processing in children.

We examined the comparability of children's nocturnal sleep estimates using accelerometry data, processed with and without a sleep log. In a secondary analysis, we evaluated factors associated with disagreement between processing approaches. Children (n = 722, age 5-12 years) wore a wrist-based accelerometer for 14 days during Autumn 2020, Spring 2021, and/or Summer 2021. Outcomes included sleep period, duration, wake after sleep onset (WASO), and timing (onset, midpoint, waketime). Parents completed surveys including children's nightly bed/wake time. Data were processed with parent-reported bed/wake time (sleep log), the Heuristic algorithm looking at Distribution of Change in Z-Angle (HDCZA) algorithm (no log), and an 8 p.m.-8 a.m. window (generic log) using the R-package 'GGIR' (version 2.6-4). Mean/absolute bias and limits of agreement were calculated and visualised with Bland-Altman plots. Associations between child, home, and survey characteristics and disagreement were examined with tobit regression. Just over half of nights demonstrated no difference in sleep period between sleep log and no log approaches. Among all nights, the sleep log approach produced longer sleep periods (9.3 min; absolute mean bias [AMB] = 28.0 min), shorter duration (1.4 min; AMB = 14.0 min), greater WASO (11.0 min; AMB = 15.4 min), and earlier onset (13.4 min; AMB = 17.4 min), midpoint (8.8 min; AMB = 15.3 min), and waketime (3.9 min; AMB = 14.8 min) than no log. Factors associated with discrepancies included smartphone ownership, bedroom screens, nontraditional parent work schedule, and completion on weekend/summer nights (range = 0.4-10.2 min). The generic log resulted in greater AMB among sleep outcomes. Small mean differences were observed between nights with and without a sleep log. Discrepancies existed on weekends, in summer, and for children with smartphones and screens in the bedroom.

Exploring the Validity of the Work Preferences Questionnaire

Abstract: This study aimed was to develop and validate a new instrument called the Work Preferences Questionnaire (WPQ) to measure individuals’ preferences for work characteristics that are relevant to today’s work environment. A multi-step approach and two samples were used to develop and validate the WPQ across various industries. In the first study, a group of experts developed a bank of items that were then administered to 984 workers. Exploratory factor analysis revealed a nine-factor structure with good internal consistency. In the second study, an independent sample of 687 workers was used to confirm the factorial structure and highlight the distinctness of the work preference dimensions. The study found small mean differences in interindividual preference scores based on age and confirmed data equivalence between gender and education level. The WPQ addresses limitations of existing measures by focusing on a narrow set of work preferences that are highly relevant in the current work environment and includes modern aspects such as teleworking and work-life balance. The WPQ promises to be an effective tool for research and human resources practices, enabling individuals and organizations to better understand work preferences and make informed decisions about work design and personnel selection.

Automated vertebral bone mineral density measurement with phantomless internal calibration in chest LDCT scans using deep learning.

To develop and evaluate a fully automated method based on deep learning and phantomless internal calibration for bone mineral density (BMD) measurement and opportunistic low BMD (osteopenia and osteoporosis) screening using chest low-dose CT (LDCT) scans. A total of 1175 individuals were enrolled in this study, who underwent both chest LDCT and BMD examinations with quantitative computed tomography (QCT), by two different CT scanners (Siemens and GE). Two convolutional neural network (CNN) models were employed for vertebral body segmentation and labeling, respectively. A histogram technique was applied for vertebral BMD calculation using paraspinal muscle and surrounding fat as references. 195 cases (by Siemens scanner) as fitting cohort were used to build the calibration function. 698 cases as validation cohort I (VCI, by Siemens scanner) and 282 cases as validation cohort II (VCII, by GE scanner) were performed to evaluate the performance of the proposed method, with QCT as the standard for analysis. The average BMDs from the proposed method were strongly correlated with QCT (in VCI: r = 0.896, in VCII: r = 0.956, p < 0.001). Bland-Altman analysis showed a small mean difference of 1.1 mg/cm3, and large interindividual differences as seen by wide 95% limits of agreement (-29.9 to +32.0 mg/cm3) in VCI. The proposed method measured BMDs were higher than QCT measured BMDs in VCII (mean difference = 15.3 mg/cm3, p < 0.001). Osteoporosis and low BMD were diagnosed by proposed method with AUCs of 0.876 and 0.903 in VCI, 0.731 and 0.794 in VCII, respectively. The AUCs of the proposed method were increased to over 0.920 in both VCI and VCII after adjusting the cut-off. Without manual selection of the region of interest of body tissues, the proposed method based on deep learning and phantomless internal calibration has the potential for preliminary screening of patients with low BMD using chest LDCT scans. However, the agreement between the proposed method and QCT is insufficient to allow them to be used interchangeably in BMD measurement. This study proposed an automated vertebral BMD measurement method based on deep learning and phantomless internal calibration with paraspinal muscle and fat as reference.

Evaluation of Different Equations for Resting Metabolic Rate Prediction in Female Combat Sports Athletes

Only a few studies have produced equations that can estimate resting metabolic rate (RMR) in female athletes, but the accuracy of these equations for combat athletes has not yet been tested. The aim of this study was to evaluate the 12 different equations which are commonly using to determine resting metabolite rate (RMR) in the literature. Twenty-three female combat sport athletes (24.23± 3.39 years; 166.8 ± 5.3 cm; 63.13±6.53 kg; 8.78±3.19 experience years.; 56.40±3.43 VO2 mL/kg/min) were participated this study in voluntarily basis. A cross-validation approach used to compare the accuracy of 12 commonly prediction equations with measured RMR by indirect calorimetry to determine RMR in female combat sports athletes. All the predictive equation was underestimated RMR when compared with the measured RMR (p &lt; 0.05) and the smallest mean difference (92.46 ± 210.38 kcal·d-1) was observed for Altman &amp; Dittmer equation amongst the 12 predictive equations. The Altman &amp; Dittmer equation was accurately predicted 16 out of 30 subjects’ RMR value within the range ±10%. However, based on the Bland–Altman plots, the prediction equations were not accurately nor precisely predicted RMR in the current sample of female combat sport athletes. The results in the present study showed that the Altman &amp; Dittmer equation is most suitable equation to predict RMR amongst 12 equations. Although the Altman &amp; Dittmer equation was resulted with smallest mean difference, it seems that there is need to further research with longitudinal approach to understand the effects of training intensity and body mass changes on RMR in order to develop the formulas already exist used commonly.