Operating Characteristics Research Articles

Energy Consumption Optimization for the Cold Source System of a Hospital in Shanghai-Part I: Analysis of Operating Characteristics and the Control Strategies of the Chillers

Background: Hospitals account for the most proportion of energy consumption in the public building sector. Chillers usually account for most of the overall energy consumption of the cold source system. Objective: To solve the problem of chillers' large energy consumption problem, novel technologies were developed, and achievements were patented. Methods: The operating characteristics influencing factors of the magnetic suspension centrifugal chiller (MSCC) and variable frequency screw chiller (VFSC) of a hospital in Shanghai were analyzed and discussed by actual measurements. Then, based on the operating characteristics of the chiller obtained from the analysis of the measured data, the cooling capacity was classified by the K-Means clustering method to obtain the startup strategy of the chillers. Results: The effects of the supply chilled water temperature, the supply cooling water temperature and variable cooling water flow rate on the maximum cooling capacity and coefficient of performance (COP) of both chillers were explored. The load distribution scheme was discussed based on the chillers' startup strategy. Conclusion: The average part load ratio operation scheme was the preferred chiller distribution scheme. A chiller's maximum allowable part load ratio should not exceed 80% during the low-load operation period and should not be less than 60% during the conventional operation period. It provided a reference for optimizing the chiller operation strategy to reduce system energy consumption.

Indonesian Patient Health Questionnaire's Clinical Utility in Psychiatric Outpatients: Ruling Out Conditions per ICD-11 Criteria

This study aimed to assess the diagnostic accuracy of the Patient Health Questionnaire (PHQ) for identifying common mental disorders in an outpatient clinical psychologist office setting in Indonesia. A total of 661 outpatients from a clinical psychology office in Jakarta, Indonesia, participated in the study. The complete PHQ was administered, and its results were compared with diagnoses made by clinical psychologists based on ICD-11 criteria, including somatoform disorder (n = 6), depression (n = 117), Generalized Anxiety Disorder (GAD, n = 50), panic disorder (n = 42), bulimia nervosa (n = 2), binge eating disorder (n = 2), and other diagnoses such as OCD and BPD (n = 442). Receiver operating characteristics were computed to examine cut-off points, and optimal cut-off points based on the Youden Index were identified for somatoform disorder (PHQ-15 ≥ 13), depression (PHQ-9 ≥ 13), GAD (GAD- 7 ≥ 10), and panic disorder (PHQ-PD ≥ 7). Cut-off points for the alcohol abuse and eating disorder modules of the PHQ could not be determined due to a lack of sample, and AUC was suboptimal for PHQ-9, GAD-7, and PHQ-ED. The Indonesian PHQ demonstrated good sensitivity but low specificity in identifying somatoform disorder, depression, GAD, and panic disorders based on ICD-11 criteria among Indonesian clinical psychologist office outpatients. In the Indonesian outpatient psychiatric context, the utility of the Indonesian PHQ appeared to be most effective in ruling out diagnoses.

Some aspects of reliability prediction of chemical industry and hydrogen energy facilities (vessels, machinery and equipment) operated in emergency situations and extreme conditions

This work is aimed at a comprehensive solution to the problem of reliable and safe operation of a transport energy system with a high energy concentration based on a universal energy carrier - cryogenic liquid hydrogen.The article discusses the possibility of using various methods and techniques to assess the reliability of machines and equipment operated in emergency situations and extreme conditions. The obtained results are analyzed.Currently, the oil and gas complex pays great attention to the development of hydrogen technologies, as well as hydrogen energy in connection with the relevance of the Climate Agenda. In this regard, hydrogen energy facilities are of the greatest interest: cryogenic hydrogen reservoirs, cryogenic hydrogen pipelines, cryogenic oxygen reservoirs and cryogenic oxygen pipelines, as well as cryogenic reservoirs and pipelines for storing process nitrogen gas. An important role for global energy exchange is played by LH2 tankers for transporting cryogenic hydrogen. For example, Australia and Japan built the first LH2 tanker to transport hydrogen from Australia to Japan. In addition, another 85 LH2 tankers are expected to be built.After transportation, cryogenic hydrogen is stored in cryogenic hydrogen storages, usually also representing cryogenic hydrogen tanks with piping in the form of cryogenic pipelines, as well as cryogenic nitrogen tanks for storing process nitrogen gas. Further, hydrogen is used in road transport, aviation, ship fleet, industry, and energy. The main elements of mobile, stationary and airborne hydrogen storage systems are under critical loads and are in the area of increased study and attention.In this regard, we considered the functions of changing the main operational characteristics, made proposals on the possibility of predicting the development of accumulated faults and proposals for ensuring safety and extending the life of objects, taking into account the determination of local and integral damage to cryogenic tanks and pipelines.

Comprehensive strain assessment and mortality after acute myocardial infarction: a retrospective observational study based on the Essen Coronary Artery Disease registry

Background and aimsCurrent ESC guidelines on the management of patients after acute myocardial infarction only include the evaluation of left ventricular (LV) function by assessment of the ejection fraction in...

Prediction of preterm birth in multiparous women using logistic regression and machine learning approaches

To predict preterm birth (PTB) in multiparous women, comparing machine learning approaches with traditional logistic regression. A population-based cohort study was conducted using data from the Ontario Better Outcomes Registry and Network (BORN). The cohort included all multiparous women who delivered a singleton birth at 20–42 weeks’ gestation in an Ontario hospital between April 1, 2012 and March 31, 2014. The primary outcome was PTB < 37 weeks, with spontaneous PTB analyzed as a secondary outcome. Stepwise logistic regression and the Boruta machine learning were used to select the important variables during the first and second trimester. For building prediction models, the whole data set were divided for the two independent parts: two-third for training the classifiers (Logistic regression, random forests, decision trees, and artificial neural networks) and one-third for model validation. Then, the training data set were balanced by random over sampling technique. The best hyper parameters were obtained by the tenfold cross validation. The performance of all models was evaluated by sensitivity, specificity, positive predictive value, negative predictive value, and the area under the receiver operating characteristics (AUC). The cohort included 145,846 births, of which 8125 (5.57%) were preterm. In first-trimester models, the strongest predictors of PTB were previous PTB, preexisting diabetes, and abnormal pregnancy‐associated plasma protein-A. In the testing data set, the highest predictive ability was seen for artificial neural networks, with an area under the receiver operating characteristic curve (AUC) of 68.8% (95% CI 67.6–70.1%). In second-trimester models, addition of infant sex, attendance at first-trimester appointment, medication exposure, and abnormal alpha-fetoprotein concentrations increased the AUC to 72.1% (95% CI 71.1–73.1%) with logistic regression. With the inclusion of the variable complications during pregnancy, the AUC increased to 80.5% (95% CI 79.6–81.5%) using logistic regression. For both overall and spontaneous PTB, during both the first and second trimesters, models yielded negative predictive values of 97%. Overall, machine learning and logistic regression produced similar performance for prediction of PTB. For overall and spontaneous PTB, both first- and second-trimester models provided negative predictive values of ~ 97%, higher than that of fetal fibronectin.

Utility of the Neutrophil to Lymphocyte Ratio for Predicting Mortality in Pleural Empyema - A Retrospective Study

Purpose: The prognostic qualities of the hematological biomarker neutrophil to lymphocyte ratio (NLR) have not yet been evaluated in pleural empyema. Therefore, we aimed to find if NLR can predict adverse outcome in such clinical setting. Methods: Retrospectively we studied 84 patients with pleural empyema who were operated in emergency setting in a clinic of thoracic surgery of an academic hospital over a 34-month period (01.2021- 10.2023). To assess the prognostic performance of NLR we used the area under the receiver operating characteristics (AUROC) curves. Results: Of a total of 84 patients, nine (10.7%) died. Using ROC Curve analysis we found that NLR has an excellent prognostic ability and outperformed systemic immune inflammation index (SII), platelet to lymphocyte ratio (PLR), quick- sequential organ failure (qSOFA) score and systemic inflammation response syndrome (SIRS) (AUROC = 0.904 vs 0.782 vs 0.749 vs 0.747 vs 0.676, respectively) in outcome prediction. An optimal threshold NLR &gt; 9.88 x 109 /L for prognostication of death was identified with a sensitivity of 85.7% and a specificity of 83.6%. Conclusion: In pleural empyema the neutrophil to lymphocyte ratio demonstrates excellent ability to predict the unfavorable outcome.

THE LYON SCORE: A NOVEL REFLUX SCORING SYSTEM BASED ON THE LYON CONSENSUS 2.0 THAT ASSOCIATES WITH TREATMENT OUTCOME FROM ANTI-REFLUX THERAPY

Background: We explored if a score derived from parameters from esophageal testing could increase confidence in diagnosing conclusive gastroesophageal reflux disease and in predicting outcome. Methods: A prediction score was developed using metrics based on Lyon Consensus 2.0 thresholds extracted from endoscopy and pH-impedance monitoring. The Lyon score was the sum of weighted scores derived from a logistic regression model. The outcome was response to anti-reflux therapy, defined as 50% reduction in global symptoms on validated questionnaires. An existing database of endoscopy-negative patients with typical reflux symptoms undergoing esophageal testing from two centers (Europe and US) constituted the developmental cohort, while two separate cohorts (Europe and Asia) served as validation cohorts. Receiver operating characteristics (ROC) analysis determined performance of the Lyon score in predicting treatment response. Results: In 281 developmental cohort patients (median age 53 years, 57.7% female), the Lyon score demonstrated an AUC of 0.819 in predicting 50% symptom improvement (p&lt;0.001) on ROC, with an optimal threshold of 6.25 (sensitivity 81.2%, specificity 73.4%). Of the individual components, only acid exposure time (AUC 0.799, p&lt;0.001), mean nocturnal baseline impedance (AUC 0.785, p&lt;0.001) and reflux episodes (AUC 0.764, p&lt;0.001) approached the Lyon score performance. The Lyon score segregated treatment response in both the European (AUC 0.908, p&lt;0.001) and Asian validation cohorts (AUC 0.637, p&lt;0.001), and outperformed the DeMeester score in sensitivity for predicting outcome in the developmental and Asian validation cohorts. Conclusion: The novel Lyon score segregates reflux phenotypes, and identifies likelihood of symptom response from antireflux therapy.

Research on Comprehensive Evaluation Indicators and Methods of World-Class Open-Pit Coal Mines

Since the 20th century, with the rapid development of the global economy, human demand for fossil energy such as coal has been increasing. In the face of fierce competition, the state and various ministries and commissions have put forward the goals and requirements of building a world-class enterprise, and how to become a world-class open-pit coal mine and establish the corresponding evaluation standards has become an urgent scientific problem to be solved. According to the characteristics of open-pit coal mine production and operation, from the perspective of benchmarking world class, the key factors affecting the construction of world-class open-pit coal mines are extracted by using the fuzzy DEMATEL method, and the comprehensive evaluation index system, evaluation standards, and methods of open-pit coal mines are established, which provides benchmarks and guidelines for the construction of world-class open-pit coal mines and improves the construction level of world-class open-pit coal mines.

Discrimination Between Benign and Malignant Lesions With Restriction Spectrum Imaging MRI in an Enriched Breast Cancer Screening Cohort.

Breast cancer screening with dynamic contrast-enhanced MRI (DCE-MRI) is recommended for high-risk women but has limitations, including variable specificity and difficulty in distinguishing cancerous (CL) and high-risk benign lesions (HRBL) from average-risk benign lesions (ARBL). Complementary non-invasive imaging techniques would be useful to improve specificity. To evaluate the performance of a previously-developed breast-specific diffusion-weighted MRI (DW-MRI) model (BS-RSI3C) to improve discrimination between CL, HRBL, and ARBL in an enriched screening population. Prospective. Exactly 187 women, either with mammography screening recommending additional imaging (N = 49) or high-risk individuals undergoing routine breast MRI (N = 138), before the biopsy. Multishell DW-MRI echo planar imaging sequence with a reduced field of view at 3.0 T. A total of 72 women had at least one biopsied lesion, with 89 lesions categorized into ARBL, HRBL, CL, and combined CLs and HRBLs (CHRLs). DW-MRI data were processed to produce apparent diffusion coefficient (ADC) maps, and estimate signal contributions (C1, C2, and C3-restricted, hindered, and free diffusion, respectively) from the BS-RSI3C model. Lesion regions of interest (ROIs) were delineated on DW images based on suspicious DCE-MRI findings by two radiologists; control ROIs were drawn in the contralateral breast. One-way ANOVA and two-sided t-tests were used to assess differences in signal contributions and ADC values among groups. P-values were adjusted using the Bonferroni method for multiple testing, P = 0.05 was used for the significance level. Receiver operating characteristics (ROC) curves and intra-class correlations (ICC) were also evaluated. C1, √C1C2, and were significantly different in HRBLs compared with ARBLs (P-values < 0.05). The had the highest AUC (0.821) in differentiating CHRLs from ARBLs, performing better than ADC (0.696), especially in non-mass enhancement (0.776 vs. 0.517). This study demonstrated the BS-RSI3C could differentiate HRBLs from ARBLs in a screening population, and separate CHRLs from ARBLs better than ADC. 2.

Diagnostic performance of pupil perimetry in detecting hemianopia under standard and virtual reality viewing conditions.

To determine the diagnostic performance and reliability of two pupil perimetry (PP) methods in homonymous hemianopia. This cross-sectional monocenter cohort study performed gaze-contingent flicker PP (gcFPP) and a virtual reality version of gcFPP (VRgcFPP) twice on separate occasions in all patients suffering from homonymous hemianopia due to neurological impairment. The main outcomes were (1) test accuracy and (2) test-retest reliability: (1) was measured through area under the receiver operating characteristics curve (AUC) calculation of (VR)gcFPP results with comparators being SAP and healthy controls, respectively; (2) was evaluated by comparing tests 1 and 2 of both methods within patients. Both gcFPP and VRgcFPP were performed in 15 patients (12 males, MAge = 57, SDAge = 15) and 17 controls (6 males, MAge = 53, SDAge = 12). Mean test accuracy was good in separating damaged from intact visual field regions (gcFPP: Mauc = 0.83, SDauc = 0.09; VRgcFPP: Mauc = 0.69,SDauc = 0.13) and in separating patients from controls (gcFPP: Mauc = 0.92,SDauc = 0.13; VRgcFPP: Mauc = 0.96,SDauc = 0.15). A high test-retest reliability was found for the proportion intact versus damaged visual field (gcFPP: r = 0.95, P < .001, VRgcFPP: r = 1.00, P < .001). Overall, these results can be summarized as follows: (1) the comparison of pupil response amplitudes between intact versus damaged regions per patient indicate that gcFPP allows for cleaner imaging of intact versus damaged visual field regions than VRgcFPP, (2) the comparisons of average differences in intact versus damaged amplitudes between patients and controls demonstrate high diagnostic performance of both gcFPP and VRgcFPP, and (3) the test-retest reliabilities confirm that both gcFPP and VRgcFPP reliably and consistently measure defects in homonymous hemianopia. KEY MESSAGES: What is known Standard automated perimetry is the current gold standard for visual field examination, but not always suited for the evaluation of the VF in neurologically impaired patients. Pupil perimetry consists of the measurement of pupillary responses to light stimuli as a measure of visual sensitivity. What is new This study reports the highest diagnostic accuracy of pupil perimetry so far in patients with homonymous hemianopia. Gaze-contingent flicker pupil perimetry reliably and consistently measures defects in homonymous hemianopia under standard and virtual reality viewing conditions.

Predicting post-lung transplant survival in systemic sclerosis using CT-derived features from preoperative chest CT scans.

The current understanding of survival prediction of lung transplant (LTx) patients with systemic sclerosis (SSc) is limited. This study aims to identify novel image features from preoperative chest CT scans associated with post-LTx survival in SSc patients and integrate them into comprehensive prediction models. We conducted a retrospective study based on a cohort of SSc patients with demographic information, clinical data, and preoperative chest CT scans who underwent LTx between 2004 and 2020. This cohort consists of 102 patients (mean age, 50 years ± 10, 61% (62/102) females). Five CT-derived body composition features (bone, skeletal muscle, visceral, subcutaneous, and intramuscular adipose tissues) and three CT-derived cardiopulmonary features (heart, arteries, and veins) were automatically computed using 3-D convolutional neural networks. Cox regression was used to identify post-LTx survival factors, generate composite prediction models, and stratify patients based on mortality risk. Model performance was assessed using the area under the receiver operating characteristics curve (ROC-AUC). Muscle mass ratio, bone density, artery-vein volume ratio, muscle volume, and heart volume ratio computed from CT images were significantly associated with post-LTx survival. Models using only CT-derived features outperformed all state-of-the-art clinical models in predicting post-LTx survival. The addition of CT-derived features improved the performance of traditional models at 1-year, 3-year, and 5-year survival prediction with maximum AUC scores of 0.77 (0.67-0.86), 0.85 (0.77-0.93), and 0.90 (95% CI: 0.83-0.97), respectively. The integration of CT-derived features with demographic and clinical features can significantly improve t post-LTx survival prediction and identify high-risk SSc patients. Question What CT features can predict post-lung-transplant survival for SSc patients? Finding CT body composition features such as muscle mass, bone density, and cardiopulmonary volumes significantly predict survival. Clinical relevance Our individualized risk assessment tool can better guide clinicians in choosing and managing patients requiring lung transplant for systemic sclerosis.

Determinants of decision-making in biopsy of PI-RADS 3 transition zone lesions.

Cancer rates for Prostate Imaging-Reporting and Data System (PI-RADS) 3 lesions are low. We aimed to determine the clinical and magnetic resonance imaging (MRI) parameters that can provide risk stratification for PI-RADS 3 transition zone (TZ) lesions to guide decision for biopsy, which can improve the cost-effectiveness of resource utilisation. The MRI scans of all patients who underwent MRI-ultrasound fusion targeted biopsy from 1 May 2016 to 31 December 2022 were retrospectively assessed by two board-certified abdominal radiologists. The following data were collected and analysed serum prostate-specific antigen, Prostatic Health Index (PHI), prostate volume, histological results, lesion size, location, diffusion-weighted imaging (DWI) parameter scores and overall PI-RADS score. Two hundred and fourteen TZ lesions were included. Among 131 PI-RADS 3 lesions, those with marked restricted diffusion (DWI score ≥4), diameter ≥1 cm, prostrate-specific antigen density (PSAD) ≥0.11 and PHI ≥34 were more likely to contain clinically significant prostate cancer (csPCa; P = 0.04, 0.02, 0.049 and 0.05, respectively), with areas under the receiver operating characteristics curve of 0.9, 0.76, 0.84 and 0.80, respectively. Apical lesions were more likely to contain csPCa compared to midgland or basal lesions (P = 0.01). Clinical parameters (PSAD and PHI) and MRI features (lesion size, DWI score, lesion location) can be used to risk stratify PI-RADS 3 TZ lesions and guide decision for targeted biopsy.

Modeling serum M-protein response for early detection of biochemical relapse in myeloma patients treated with bortezomib, lenalidomide and dexamethasone.

Multiple myeloma (MM) treatment guidelines recommend waiting for formal progression criteria (FPC) to be met before proceeding to the next line of therapy. As predicting progression may allow early switching to next-line therapy while the disease burden is relatively low, we evaluated the predictive accuracy of a mathematical model to anticipate relapse 180 days before the FPC is met. A subset of 470/1143 patients from the IA16 dataset who were initially treated with VRd (Velcade (bortezomib), Revlimid (lenalidomide), and dexamethasone) in the CoMMpass study (NCT01454297) were randomly split 2:1 into training and testing sets. A model of M-protein dynamics was developed using the training set and used to predict relapse probability in patients in the testing set given their response histories up to 12 or more months of treatment. The predictive accuracy of this model and M-protein "velocity" were assessed via receiver operating characteristics (ROC) analysis. The final model was a two-population tumor growth inhibition model with additive drug effect and transit delay compartments for cell killing. The ROC area under the curve value of relapse prediction 180 days ahead of observed relapse by FPC was 0.828 using at least 360 days of response data, which was superior to the M-protein velocity ROC score of 0.706 under the same conditions. The model can predict future relapse from early M-protein responses and can be used in a future clinical trial to test whether early switching to second-line therapy results in better outcomes in MM.

Operational characteristics and controlling strategies of a novel dual-return-air dehumidification evaporative cooling system (DDEC)

Dehumidification evaporative cooling (DEC) systems exhibit superior environmental adaptability compared to conventional evaporative cooling systems. However, the dehumidification process in DEC is coupled with its cooling process, presenting challenges in adapting to varying environmental conditions. To address this issue, this study proposes a novel dual-return-air dehumidification evaporative cooling system (DDEC) that utilizes two return airflows to control both dehumidification and cooling efficiency. A thermodynamic model based on COMSOL LiveLink with MATLAB for the DDEC has been established and validated, enabling an analysis of the impact of operational parameters on its performance and the identification of key parameters. The results show that there are an optimum inlet flow rate (1100 m3/h) and a third flow rate control factor (0.2) that maximize the coefficient of performance (COP), giving the maximum COP of 0.87 and 0.35 respectively. Moreover, the first and second air flow rate control factors only have a significant influence on the supply air humidity of the DDEC. A higher regenerative temperature can reduce both the temperature and humidity ratio of the supply air but tends to decrease COP. Finally, a single-directional controlling strategy is proposed and analyzed for the DDEC application in different environments.

Improvement of Single Event Transient Effects for a Novel AlGaN/GaN High Electron-Mobility Transistor with a P-GaN Buried Layer and a Locally Doped Barrier Layer

In this paper, a novel AlGaN/GaN HEMT structure with a P-GaN buried layer in the buffer layer and a locally doped barrier layer under the gate (PN-HEMT) is proposed to enhance its resistance to single event transient (SET) effects while also overcoming the degradation of other characteristics. The device operation mechanism and characteristics are investigated by TCAD simulation. The results show that the peak electric field and impact ionization at the gate edges are reduced in the PN-HEMT due to the introduced P-GaN buried layer in the buffer layer. This leads to a decrease in the peak drain current (Ipeak) induced by the SET effect and an improvement in the breakdown voltage (BV). Additionally, the locally doped barrier layer provides extra electrons to the channel, resulting in higher saturated drain current (ID,sat) and maximum transconductance (gmax). The Ipeak of the PN-HEMT (1.37 A/mm) is 71.8% lower than that of the conventional AlGaN/GaN HEMT (C-HEMT) (4.85 A/mm) at 0.6 pC/µm. Simultaneously, ID,sat and BV are increased by 21.2% and 63.9%, respectively. Therefore, the PN-HEMT enhances the hardened SET effect of the device without sacrificing other key characteristics of the AlGaN/GaN HEMT.

Comparative Study Between Variable Flip Angle and Modified Look-Locker Inversion Recovery for Evaluating Renal Interstitial Fibrosis.

Variable flip angle (VFA) and modified Look-Locker inversion recovery (MOLLI) are frequently used for noninvasive evaluation of renal interstitial fibrosis (IF) in chronic kidney disease (CKD). However, controversy remains over which method is preferred. To compare the diagnostic efficacy of VFA and MOLLI for T1 mapping in evaluating renal IF. Prospective. Fifty-one participants with CKD (CKD stage 1-5, 35 males) and 18 healthy volunteers (eight males). 3.0 T, three-dimensional gradient echo sequence for B1+ VFA, and two-dimensional gradient echo sequence for MOLLI. Image quality was assessed on a five-point scale. Cortex and medulla T1 values (cT1 and mT1), corticomedullary T1 value difference (ΔT1, medulla - cortex), and corticomedullary T1 value ratio (ratio T1, cortex:medulla) were compared between VFA and MOLLI as well as between IF grade (0-4) based on biopsy. Intraclass correlation coefficient, Bland-Altman analysis, analysis of variance, Kruskal-Wallis test, correlation analysis, and receiver operating characteristics analysis with the area under the curve (AUC). P-value <0.05 was considered significant. MOLLI provided significantly better image quality compared to VFA. cT1 and mT1 values significantly differed between VFA and MOLLI (cT1-VFA: 1771.4 ± 139.4 msec vs. cT1-MOLLI: 1729.9 ± 132.1 msec; mT1-VFA: 2076.0 [interquartile range (IQR): 2045.9-2129.9] msec vs. mT1-MOLLI: 2039.2 [IQR: 1997.8-2071.6] msec). ΔT1 and ratio T1 values were not different between VFA and MOLLI (ΔT1: 300.8 ± 71.4 vs. 306.0 ± 78.4, respectively, P = 0.33 and ratio T1: 0.85 ± 0.038 vs. 0.85 ± 0.041, respectively, P = 0.064). No difference was observed between T1 variables and T1 mapping methods in diagnosing IF. ΔT1 and ratio T1 were not different between VFA and MOLLI. Both VFA and MOLLI are effective for noninvasive assessment of renal IF. 2 TECHNICAL EFFICACY: Stage 2.

Combined levothyroxine and propylthiouracil treatment in children with MCT8 deficiency: A multi-center case series of 12 patients.

To evaluate the combined administration of propylthiouracil (PTU) and levothyroxine (LT4) in managing MCT8 deficiency and identify optimal therapeutic dosages. This multi-center case series involved 12 male patients with MCT8 deficiency whose parents/guardians consented to PTU and LT4 treatment. Data were collected from January 2008 to June 24, 2024. The study focused on treatment safety and outcomes, analyzing baseline and last encounter biochemical, metabolic, and anthropometric parameters. Statistical analyses included Wilcoxon Signed Ranks tests and Generalized Estimated Equations to assess effects on thyroid and metabolic markers, and Receiver Operating Characteristics curves to predict optimal dose. Patients showed a significant reduction in serum total T3 (TT3) concentration and TT3/TT4 ratio, with increased serum TT4 and FT4 concentrations. The use of PTU effectively reduced TT3 concentration by 25% at an average dose of 6.8 mg/Kg/day, while LT4 increased FT4 concentration by 40% from baseline at an average dose of 4.3 μg/Kg/day. TSH concentration was undetectable on treatment. No statistical differences were observed in metabolic and physical parameters between baseline and last encounter overall for the group but 6 of 8 patients for whom this data was available had an increase in weight (z score). There were no adverse effects on liver function or granulocyte numbers noted throughout the period of observation. Combined treatment with PTU and LT4 normalized serum T3, FT4, TT4 in patients with MCT8 deficiency. Individualized dose adjustments were crucial for achieving therapeutic goals, indicating the need for personalized treatment plans.

Echocardiographic markers at diagnosis of persistent pulmonary hypertension of the newborn.

Clinical parameters along with echocardiographic markers are used to interrogate the haemodynamics in persistent pulmonary hypertension of the newborn (PPHN). The aim of this study was to compare different echocardiographic markers in recent cohort of newborn infants with and without PPHN. In this retrospective study, common echocardiographic markers were examined in infants>34weeks' gestation with PPHN (cases) and without PPHN (controls). Infants with congenital heart disease were excluded. Binary regression testing was used to evaluate echocardiographic markers predicting PPHN and death. In addition, diagnostic accuracy testing of echocardiographic markers using ROC was also performed. Intra-observer reliability for echocardiographic markers was examined using coefficient of variation (CoV) and intraclass correlation. Fifty-two infants were studied; 22 (42 %) infants with PPHN had significantly higher oxygen requirement, oxygenation index and ventilation days when compared with controls. Echocardiographic markers such as TR Vmax, S/D TR, PAAT, TAPSE and eccentricity index (EI) were significantly different between cases and controls. Receiver operator characteristics analysis of echocardiographic markers revealed TR Vmax 0.96 (0.9-1.0), S/D TR 0.95 (0.87-1.0) and end systolic EI 0.94 (0.87-1.0). These markers were found to predict death in this cohort of infants. CoV and Intra-observer reliability was good for various echocardiographic markers. Among the various echocardiographic markers studied, TR Vmax when present along with S/D TR and end systolic EI had good intra-observer reliability and were diagnostic of PPHN and predicted death in this cohort. Future trials could use these markers in studies examining PPHN.

On the development and validation of large language model-based classifiers for identifying social determinants of health

The assessment of social determinants of health (SDoH) within healthcare systems is crucial for comprehensive patient care and addressing health disparities. Current challenges arise from the limited inclusion of structured SDoH information within electronic health record (EHR) systems, often due to the lack of standardized diagnosis codes. This study delves into the transformative potential of large language models (LLM) to overcome these challenges. LLM-based classifiers-using Bidirectional Encoder Representations from Transformers (BERT) and A Robustly Optimized BERT Pretraining Approach (RoBERTa)-were developed for SDoH concepts, including homelessness, food insecurity, and domestic violence, using synthetic training datasets generated by generative pre-trained transformers combined with authentic clinical notes. Models were then validated on separate datasets: Medical Information Mart for Intensive Care-III and our institutional EHR data. When training the model with a combination of synthetic and authentic notes, validation on our institutional dataset yielded an area under the receiver operating characteristics curve of 0.78 for detecting homelessness, 0.72 for detecting food insecurity, and 0.83 for detecting domestic violence. This study underscores the potential of LLMs in extracting SDoH information from clinical text. Automated detection of SDoH may be instrumental for healthcare providers in identifying at-risk patients, guiding targeted interventions, and contributing to population health initiatives aimed at mitigating disparities.

Optimization of Basophil Activation Test in the Diagnosis and Qualification for Allergen-Specific Immunotherapy in Children with Respiratory Allergy to the House Dust Mite Dermatophagoides pteronyssinus

The aim of this study was to optimize a basophil activation test in the detection of allergy to the house dust mite Dermatophagoides pteronyssinus in children with allergic respiratory diseases. This study involved 32 cases, 13 girls and 19 boys aged 4–17 years, with perennial asthma or allergic rhinitis caused by D. pteronyssinus. The control group consisted of 13 girls and 19 boys aged 4–17 years with seasonal allergic asthma or rhinitis provoked by Timothy or birch pollen. House dust mite (HDM) allergy was excluded in the controls based on their medical history, skin prick test (SPT) results and sIgE determination. In all patients, a basophil activation test (BAT) was performed with five dilutions of D. pteronyssinus allergen (the dilution series ranged from 22.5 to 0.00225 ng/mL). The results were analyzed by using the receiver operating characteristics (ROC) to determine the optimal allergen concentrations, outcome measures and cut-off points that would differentiate most accurately between HDM-allergic and non-allergic patients. As a “gold standard”, criteria for allergen-specific immunotherapy with D. pteronyssinus or respective pollens were applied by an experienced pediatric allergist following the guidelines of the European Academy of Allergy and Clinical Immunology. The highest diagnostic efficiency was yielded by the protocol assuming a cut-off value of 9.76% activated basophils after activation with a single allergen concentration of 2.25 ng/mL (sensitivity 90.6%, specificity 100%). This protocol yielded 3 (4.7%) misclassifications, all false negative, when compared with the “gold standard”. There was a strong correlation with the BAT results at 22.5, 2.25 and 0.225 ng/mL (respectively r = 0.90 and r = 0.78, p &lt; 0.001), as well as between the BAT at 2.25 ng/mL and SPT (r = 0.82, p &lt; 0.001) and between the SPT and sIgE levels (r = 0.78, p &lt; 0.001). High cross-reactivity between D. pteronyssinus and D. farinae was confirmed based on the BAT at 22.5 ng/mL (r = 0.82, p &lt; 0.001). In conclusion, the BAT showed very good concordance with the result of a meticulous process of decision-making that combined validated allergy tests (SPT, sIgE) with expert guidelines, specialist knowledge and experience. Facing the risk of the incorrect qualification of patients for costly, long-lasting and potentially risky allergen-specific immunotherapy, the inclusion of a basophil activation test into diagnostic process seems fully justified.