Receiver operating characteristic curve: overview and practical use for clinicians

Differential gene expression analysis pipelines and bioinformatic tools for the identification of specific biomarkers: A review

In recent years, the role of bioinformatics and computational biology together with omics techniques and transcriptomics has gained tremendous importance in biomedicine and healthcare, particularly for the identification of biomarkers for precision medicine and drug discovery. Differential gene expression (DGE) analysis is one of the most used techniques for RNA-sequencing (RNA-seq) data analysis. This tool, which is typically used in various RNA-seq data processing applications, allows the identification of differentially expressed genes across two or more sample sets. Functional enrichment analyses can then be performed to annotate and contextualize the resulting gene lists. These studies provide valuable information about disease-causing biological processes and can help in identifying molecular targets for novel therapies. This review focuses on differential gene expression (DGE) analysis pipelines and bioinformatic techniques commonly used to identify specific biomarkers and discuss the advantages and disadvantages of these techniques.

Value of modified qSOFA, glucose and lactate in predicting prognosis in children with sepsis in the PICU

The purpose was to investigate how well age-adjusted modified quick Sequential Organ Failure Assessment (qSOFA) scores paired with blood glucose and lactate levels predict the outcomes of septicemic children in the pediatric intensive care unit (PICU). One hundred children who were diagnosed with sepsis and septic shock in the PICU of Henan Children's Hospital were eligible, and other 20 patients in the same hospital at different times were selected as a validation set. Respiratory rate (RR), heart rate (HR), capillary refill time (CRT), and Alert, Voice, Pain, Unresponsive (AVPU) scale were included in the age-adjusted modified qSOFA scoring criteria for scoring. The primary outcome was 28-day all-cause mortality. The predictive values were evaluated by the ROC curve. In the sepsis group, 50 patients were male, and 50 patients were female. The 28-day all-cause mortality rate was 52%. Fifty-one patients with age-adjusted modified qSOFA scores >1. The serum lactate level was 2.4 mmol/L, and the blood glucose level was 9.3 mmol/L. The AUCs for the age-adjusted modified qSOFA score, serum lactate and blood glucose levels for the prediction of 28-day all-cause mortality in children with sepsis were 0.719, 0.719 and 0.737, respectively. The cut-off values were one point, 3.8 mmol/L and 10 mmol/L, respectively. The AUC of the age-adjusted modified qSOFA score for the validation set of was 0.925. When the three indices were combined, the AUC was 0.817, the Hosmer-Lemeshow goodness-of-fit test showed χ2 = 2.428 and p = .965. When children with sepsis are admitted to the ICU, we recommend performing rapid scoring and rapid bedside lactate and glucose testing to determine the early prognosis.

Non-invasive detection of systemic lupus erythematosus using SERS serum detection technology and deep learning algorithms

Systemic lupus erythematosus (SLE) is an autoimmune disease with multiple symptoms, and its rapid screening is the research focus of surface-enhanced Raman scattering (SERS) technology. In this study, gold@silver-porous silicon (Au@Ag-PSi) composite substrates were synthesized by electrochemical etching and in-situ reduction methods, which showed excellent sensitivity and accuracy in the detection of rhodamine 6G (R6G) and serum from SLE patients. SERS technology was combined with deep learning algorithms to model serum features using selected CNN, AlexNet, and RF models. 92 % accuracy was achieved in classifying SLE patients by CNN models, and the reliability of these models in accurately identifying sera was verified by ROC curve analysis. This study highlights the great potential of Au@Ag-PSi substrate in SERS detection and introduces a novel deep learning approach for SERS for accurate screening of SLE. The proposed method and composite substrate provide significant value for rapid, accurate, and noninvasive SLE screening and provide insights into SERS-based diagnostic techniques.

Discriminative validity and interpretability of the mood and feelings questionnaire

BACKGROUND

Using the Mood and Feelings Questionnaire (MFQ) to differentiate between depression severity levels remains unexplored. We explored the discriminative validity of the MFQ to identify an optimal cut-off MFQ score to distinguish between subthreshold-to-mild and moderate-to-severe depression severity levels.

METHODS

An observational cross-sectional design was used in a sample (N = 67) of help-seeking youth (ages 13 to 18, inclusive) experiencing depressive symptoms. The MFQ was administered verbatim to youth by a research analyst over the phone. Youth were then grouped into subthreshold-to-mild or moderate-to-severe depression severity categories based on scores received on the Kiddie Schedule for Affective Disorders and Schizophrenia-Depression Rating Scale. Receiver Operating Characteristic curve analyses were conducted, with area under the curve (AUC) and Youden Index (J) as primary indices. We hypothesized that the lower limit of the 95 % confidence interval for the area under the curve would be ≥0.70.

RESULTS

The primary analysis yielded an AUC of 0.85 (95 % CI: 0.763-0.947) and an optimal cut-off of ≥43 (J = 0.60, positive predictive value = 91.4 %, negative predictive value = 62.5 %, sensitivity = 72.7 %, specificity = 87.0 %).

LIMITATIONS

Our study collected a small sample, and as such cannot identify how subgroup classification (e.g., based on race or gender) may moderate outcomes. Further, unknown measurement error of the predictor and reference variable measures can bias the estimates.

CONCLUSIONS

Our preliminary findings highlight the potential for the MFQ to support clinical decision-making relevant to adolescents experiencing varying severities of depressive symptoms in secondary care settings.

Analysis of risk factors and construction of a prediction model for posttraumatic stress disorder among Chinese college students during the COVID-19 pandemic

BACKGROUND

To explore the risk factors of post-traumatic stress disorder (PTSD) among Chinese college students during the COVID-19 pandemic and the construction and validation of risk prediction models.

METHODS

A total of 10,705 university students were selected for the study. The questionnaire included the Generalized Anxiety Disorder 7 (GAD-7), Patient Health Questionnaire 9 (PHQ-9), PTSD Checklist for DSM-5 (PCL-5), and self-designed questionnaire. These assessments were conducted to facilitate the survey, construct the predictive model and validate the model's validity.

RESULTS

Sex, left-behind experience, poverty status, anxiety score, and depression score were identified as independent risk factors influencing psychological trauma among Chinese college students during the COVID-19 pandemic, while COVID-19 infection emerged as a protective factor against psychological trauma. A column chart was constructed to visualize the six independent risk factors derived from logistic regression analysis. The Hosmer-Lemeshow test results (χ2 = 13.021, P = 0.111) indicated that the risk prediction model fitted well. The receiver operating characteristic (ROC) curve showed an area under the curve (AUC) of 0.864 in the model group and 0.855 in the validation group. The calibration curves of the model closely resembled the ideal curve. Decision curve analysis (DCA) revealed that the model provided net benefit and demonstrated good clinical utility.

LIMITATIONS

The validation of the model is currently restricted to internal assessments. However, further confirmation through larger sample sizes, multicenter investigations, and prospective studies is necessary.

CONCLUSIONS

The model effectively predicted PTSD risk among Chinese college students during the COVID-19 pandemic, indicating strong clinical applicability.

Establishing the Predictive Validity of the Assessment of Motor and Process Skills for Driving Performance Outcomes

IMPORTANCE

Although the Assessment of Motor and Process Skills (AMPS) is an excellent tool for evaluating the functional performance of instrumental activities of daily living (IADLs), a limited number of studies have used the AMPS for decisions regarding the IADL of fitness to drive and community mobility.

OBJECTIVE

To determine the specificity and sensitivity of the AMPS as a tool for determining a person's fitness to drive.

DESIGN

Cross-sectional observational design.

SETTING

Three driving rehabilitation programs in three states.

PARTICIPANTS

Participants were 388 community-living adults (M age = 68.74 yr, SD = 11.53); 196 adults were recruited before completing a comprehensive driving evaluation, and 192 were recruited in two other studies of older drivers.

OUTCOME AND MEASURES

AMPS and results of comprehensive driving evaluation or on-road assessment.

RESULTS

Using a logistical regression, AMPS Motor and Process Skills scores yielded a sensitivity of 84.6% and a specificity of 88.8%. The odds ratio of the AMPS Motor Skills score was .347; for the AMPS Process Skills score, it was .014. Using cross-validations, the model with AMPS Motor and Process scores produced a cross-validation area under the curve of .918, with sensitivity and specificity of 84.6% and 88.4%, respectively, and a probability greater than .334 was used for predicting a fail or drive-with-restriction evaluation.

CONCLUSIONS AND RELEVANCE

The AMPS Motor and Process Skills scores revealed significant differences between those who failed or had driving restrictions and with those who passed the driving evaluation, which supported the AMPS as an effective tool for predicting fitness to drive. Plain-Language Summary: This study demonstrates how the Assessment of Motor and Process Skills (AMPS), as a top-down occupational therapy assessment tool, can be used to differentiate between medically at-risk drivers who are likely to pass a comprehensive driving evaluation and those who are likely to fail or need restrictions. AMPS will assist occupational therapy practitioners in determining who is most appropriate to receive driving rehabilitation services and/or when to refer a person for a comprehensive driving evaluation.

Plasma cell-free DNA as a monitoring tool for high-risk pregnancies associated with antiphospholipid syndrome

INTRODUCTION

Despite thromboprophylaxis, women with antiphospholipid syndrome (APS) face high-risk pregnancies due to proinflammatory and prothrombotic states. This highlights the need for new monitoring and prognostic tools. Recent insights into the pathophysiological role of neutrophil activation and extracellular trap (NET) formation in this syndrome led to the exploration of plasma cell-free DNA (cfDNA), a derivative of NETosis, as a promising biomarker.

MATERIALS AND METHODS

cfDNA was isolated and quantified from plasma samples of healthy pregnant women (control group, HC) and women with APS (APS group). We assessed the physiological variability of cfDNA across the three trimesters in HC. Levels of cfDNA were compared between APS and HC by gestational trimester. ROC curve analysis was performed to evaluate the efficacy of cfDNA levels for classifying APS patients. Furthermore, cfDNA levels in pregnant women with APS with obstetric complications were compared to those from uncomplicated pregnancies.

RESULTS

Among HC, cfDNA significantly increased in the third trimester compared to the first and second. Elevated cfDNA levels in APS compared to HC were observed in the first and second trimesters. First-trimester cfDNA levels demonstrated the highest classification ability to discriminate between APS and HC patients (AUC: 0.906). Among APS, those with complicated pregnancies (fetal growth restriction, preeclampsia, placenta accreta) exhibited significantly elevated cfDNA levels in the second trimester.

CONCLUSIONS

Elevated levels of cfDNA in pregnant women with APS, particularly among those with obstetric complications, supports further investigation into the potential of cfDNA as a valuable tool in the obstetric management of women with APS.

The Value of Amide Proton Transfer MRI in the Diagnosis of Malignant and Benign Urinary Bladder Lesions: Comparison With Diffusion-Weighted Imaging

BACKGROUND

Conventional magnetic resonance imaging (MRI) has certain limitations in distinguishing between malignant and benign urinary bladder (UB) lesions. Amide proton transfer (APT) imaging may provide more diagnostic information than diffusion-weighted imaging (DWI) to distinguish between malignant and benign UB.

PURPOSE

To investigate the potential of APT imaging in the diagnosis of malignant and benign UB lesions and to compare its diagnostic efficacy with that of conventional DWI.

STUDY TYPE

Prospective.

SUBJECTS

Eighty patients with UB lesions.

FIELD STRENGTH/SEQUENCE

A 3.0 T/turbo spin echo (TSE) T1-weighted and T2-weighted imaging, single-shot echo planar DWI, and three-dimensional TSE APT imaging.

ASSESSMENT

Patients underwent radical cystectomy or transurethral resection of the bladder lesions within 2 weeks after CT urography and MRI examination. APT signal intensity in UB lesions was quantified by the asymmetric magnetization transfer ratio (MTRasym). MTRasym and apparent diffusion coefficient (ADC) values were measured and compared between malignant and benign UB lesions.

STATISTICAL TESTS

Kolmogorov-Smirnov test, Student's t test or Mann-Whitney U test, Spearman rank correlation coefficient, area under the receiver operating characteristic (ROC) curve (AUC), Delong test, and intraclass correlation coefficient (ICC). The significance threshold was set at P < 0.05.

RESULTS

Thirty-two patients had pathologically confirmed benign UB lesions, including 2 bladder leiomyomas, 1 submucosal amyloidosis, 1 inflammatory myofibroblastic tumor, and 28 inflammatory lesions, and 48 patients had pathologically confirmed urothelial carcinoma. Urothelial carcinomas showed significantly higher MTRasym values (1.53% [0.74%] vs. 0.85% [0.23%]) and significantly lower ADC values (1.24 ± 0.34 × 10-3 mm2/s vs. 1.43 ± 0.22 × 10-3 mm2/s) than benign UB lesions. The MTRasym value (AUC = 0.928) was significantly better in differentiating urothelial carcinoma from benign UB lesions than the ADC value (AUC = 0.722).

DATA CONCLUSION

APT imaging may have value in discriminating malignant from benign UB lesions and has better diagnostic performance than DWI.

LEVEL OF EVIDENCE

3 TECHNICAL EFFICACY: Stage 2.

Localization of epileptogenic zone based on time-varying effective networks

Surgical resection of the epileptogenic zone (EZ) is an effective method for treating drug-resistant epilepsy. At present, the accuracy of EZ localization needs to be further improved. The characteristics of graph theory based on partial directed coherence networks have been applied to the localization of EZ, but the application of network control theory to effective networks to locate EZ is rarely reported. In this study, the method of partial directed coherence analysis was utilized to construct the time-varying effective brain networks of stereo-electroencephalography (SEEG) signals from 20 seizures in 12 patients. Combined with graph theory and network control theory, the differences in network characteristics between epileptogenic and non-epileptogenic zones during seizures were analyzed. We also used dung beetle optimized support vector machine classification model to evaluate the localization effect of EZ based on brain network characteristics of graph theory and controllability. The results showed that the classification of the average controllability feature was the best, and the area under the receiver operating characteristic (ROC) curve (AUC) was 0.9505, which is 1.32 % and 1.97 % higher than the traditional methods. The AUC value increased to 0.9607 after integrating the average controllability with other features. This study proved the effectiveness of controllability characteristic in identifying the EZ and provided a theoretical basis for the clinical application of network controllability in the EZ.

Systematic review and meta-analysis of observational studies evaluating glial fibrillary acidic protein (GFAP) and ubiquitin C-terminal hydrolase L1 (UCHL1) as blood biomarkers of mild acute traumatic brain injury (mTBI) or sport-related concussion (SRC) in adult subjects

INTRODUCTION

Neurotrauma is the leading cause of death in individuals <45 years old. Many of the published articles on UCHL1 and GFAP lack rigorous methods and reporting.

CONTENT

Due to the high heterogeneity between studies, we evaluated blood GFAP and UCHL1 levels in the same subjects. We determined the biomarker congruence among areas under the ROC curves (AUCs), sensitivities, specificities, and laboratory values in ng/L to avoid spurious results. The definitive meta-analysis included 1,880 subjects in eight studies. The items with the highest risk of bias were as follows: cut-off not prespecified and case-control design not avoided. The AUC of GFAP was greater than the AUC of UCHL1, with a lower prediction interval (PI) limit of 50.1 % for GFAP and 37.3 % for UCHL1, and a significantly greater percentage of GFAP Sp. The PI of laboratory results for GFAP and UCHL1 were 0.517-7,518 ng/L (diseased), 1.2-255 ng/L (nondiseased), and 3-4,180 vs. 3.2-1,297 ng/L, respectively.

SUMMARY

Only the GFAP positive cut-off (255 ng/L) appears to be reliable. The negative COs appear unreliable.

OUTLOOK

GFAP needs better standardization. However, the AUCs of the phospho-Tau and phospho-Tau/Tau proteins resulted not significantly lower than AUC of GFAP, but this result needs further verifications.

Predicting extubation failure in preterm infants using lung ultrasound: a diagnostic accuracy study

OBJECTIVE

To determine the accuracy of pre-extubation lung ultrasound (LUS) to predict reintubation in preterm infants born <32 weeks' gestation.

DESIGN

Prospective diagnostic accuracy study.

SETTING

Two neonatal intensive care units.

METHODS

Anterior and lateral LUS was performed pre-extubation. The primary outcome was the accuracy of LUS scores (range 0-24) to predict reintubation within 72 hours. Secondary outcomes were accuracy in predicting (1) reintubation within 7 days, (2) reintubation stratified by postnatal age and (3) accuracy of lateral imaging only (range 0-12). Pre-specified subgroup analyses were performed in extremely preterm infants born <28 weeks' gestation. Cut-off scores, sensitivities and specificities were calculated using receiver operating characteristic analysis and reported as area under the curves (AUCs).

RESULTS

One hundred preterm infants with a mean (SD) gestational age of 27.4 (2.2) weeks and birth weight of 1059 (354) g were studied. Thirteen were subsequently reintubated. The AUC (95% CI) of the pre-extubation LUS score for predicting reintubation was 0.63 (0.45-0.80). Accuracy was greater in extremely preterm infants: AUC 0.70 (0.52-0.87) and excellent in infants who were <72 hours of age at the time of extubation: AUC 0.90 (0.77-1.00). Accuracy was poor in infants who were >7 days of age. Lateral imaging alone demonstrated similar accuracy to scanning anterior and lateral regions.

CONCLUSIONS

In contrast to previous studies, LUS was not a strong predictor of reintubation in preterm infants. Accuracy is increased in extremely preterm infants. Future research should focus on infants at highest risk of extubation failure and consider simpler imaging protocols.

TRIAL REGISTRATION NUMBER

Australian New Zealand Clinical Trials Registry: ACTRN12621001356853.

Factors affecting peripheral neuropathy induced by nanoparticle albumin-bound paclitaxel in patients with pancreatic cancer

AIM

Chemotherapy-induced peripheral neuropathy (CIPN) is a major toxicity limiting the use of nab-paclitaxel (Nab-P) in treating patients with pancreatic cancer. The aim of this study was to identify the factors affecting CIPN using patient-reported outcome measures and the minimally invasive volumetric absorptive microsampling (VAMS) technique.

METHODS

The maximum concentrations of paclitaxel (Cmax) were measured from 81 VAMS samples collected from 44 participants with pancreatic cancer. The association between CIPN development and demographic, clinical and pharmacokinetic factors was determined using univariable and multivariable logistic regression. The association between CIPN severity and the factors was evaluated using Spearman's rank correlation. The impact of Cmax and the number of treatment cycles on the severity was assessed using multivariable linear regression.

RESULTS

The development of CIPN was significantly associated with cumulative dose (odds ratio 1.005, 95% confidence interval [CI] 1.003-1.007), treatment cycles (3.47, 2.25-5.85), alkaline phosphate (0.992, 0.985-0.998) and age (1.092, 1.020-1.179), with an area under the receiver operating characteristic curve of 0.89 (95% CI 0.83-0.95). The severity of CIPN significantly worsened with increasing cumulative dose (coefficient 0.58, 95% CI 0.44-0.69), treatment cycles (0.57, 0.44-0.68) and age (0.18, 0.00-0.35). The severity of CIPN was predictable from treatment cycles (P = .0002) and Cmax (P = .01).

CONCLUSION

The higher the cumulative dose of Nab-P, treatment cycles and age, the more frequently and severely do the patients experience CIPN. In predicting the severity of CIPN using Cmax, minimally invasive VAMS is a feasible alternative to venous blood sampling.

The associations between dietary flavonoids intake and risk of depressive symptom in diabetic patients: Data from NHANES 2007-2008, 2009-2010, and 2017-2018

BACKGROUND

The increasing incidence of depressive symptoms in diabetic patients contributes to the global burden of disease, but few epidemiological studies have evaluated the relationship between dietary flavonoids intake and depressive symptoms in diabetic patients in American adults.

OBJECTIVE

This study intended to evaluate the associations of dietary flavonoids intake and depressive symptoms in diabetic patients in American adults.

METHODS

We conducted a cross-sectional analysis of 1993 adults aged ≥20 years old who participated in the 2007-2008, 2009-2010, and 2017-2018 National Health and Nutrition Examination Surveys (NHANES). Chi-square test and independent-sample t-test were used to compare subjects' characteristics. Logistic regression model was further used to analyze the relationship between dietary flavonoid intake and depressive symptoms in diabetic patients. Restricted cubic spline (RCS) analysis was used to investigate the non-linear relationship between dietary flavonoid intake and the prevalence of depressive symptoms in diabetic patients. The weighted quartile sum (WQS) regression was used to analyze the effect of 29 flavonoids monomers.

RESULTS

The results showed that the total flavonoid intake in the third quartile (OR, 0.635; 95 % CI,0.419-0.962; P, 0.032) was significantly associated with a reduced risk of depressive symptoms in diabetic patients compared with the lowest quartile. And there was a U-shaped association between dietary flavonoid intake and risk of depressive symptoms in diabetic patients. Top contributors of flavonoid monomers were eriodictyol, naringenin, and theaflavin-3'-gallate, accounting for a percentage of 30.83 %, 22.17 %, and 6.92 %, respectively.

CONCLUSION

Moderate (56.07-207.12 mg/day) dietary flavonoid intake was associated with a reduced risk of depressive symptoms in diabetic patients. The important flavonoid monomers were eriodictyol, naringenin, and theaflavin-3'-gallate.

Diagnostic performance of ultrasound elastography in differentiating hepatocellular carcinoma and intrahepatic cholangiocarcinoma: a systematic review and meta-analysis

PURPOSE

To evaluate the diagnostic value of ultrasound elastography (USE) for characterizing hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (ICC).

METHODS

The protocol was pre-registered a priori at ( https://osf.io/namvk/ ). Using PubMed, Web of Science, Embase, and Cochrane Library, we found studies up to April 20, 2024 by searching HCC, ICC, and USE as keywords. Parameters of USE were directly compared between HCC and ICC patients using random-effects bivariate model on STATA 17.0, MedCalc 20.0, and Psychometrica. Trim & fill method and sensitivity analysis were also performed.

RESULTS

Eighteen studies were included with 1057 patients, consisting of 863 HCC lesions, 188 ICC lesions, and 6 mixed lesions. The pooled Emean values of HCC and ICC were 28.3 (CI = 19.8 to 36.8) and 44.0 (CI = 20.9 to 67.2). HCC tumors were 34.3% softer than ICC while peritumoral tissue in HCC lesions was 75% stiffer than ICC lesions based on Emean. The strain value index (tumoral-to-peritumoral ratio) in HCC patients was 49.4% less than that of ICC patients. USE demonstrated a pool sensitivity of 87% (CI = 73-95%), specificity of 82% (CI = 65-92%), positive likelihood ratio of 4.8 (CI = 2.2 to 10.3), negative likelihood ratio of 0.16 (CI = 0.07 to 0.37), and diagnostic odds ratio of 31 (CI = 7 to 127) in differentiation of ICC from HCC.

CONCLUSION

By evaluating tumoral and pre-tumoral stiffness, along with strain value index, USE may provide a valuable quantitative diagnostic tool for accurately differentiating HCC and ICC.

UnTWISTing the BALS: A study of predictive accuracy of clinical scoring tools for testicular torsion identification in adults

OBJECTIVE

Testicular torsion is an uncommon but time-critical condition in EDs. If the diagnosis is missed or delayed, there are significant medicolegal and patient fertility implications. Scoring tools are advocated for use in children but have limited validation in adults. The aim of the present study was to explore the predictive accuracy of the testicular torsion scoring tools, Testicular Workup for Ischemia and Suspected Torsion (TWIST) and Boettcher Alert Score (BALS), in adult patients with a final ED diagnosis of torsion.

METHODS

All patients with an ED working diagnosis of testicular torsion were identified retrospectively. Data collected from digital medical records included demographics, processes of care and clinical information. The outcome of interest was the predictive performance of the scores for a confirmed diagnosis of testicular torsion as adjudicated by an urologist or a surgeon.

RESULTS

Fifty-four patients had complete clinical data, of whom 13 had confirmed torsion. The TWIST score had a high area under the receiver operating characteristics curve (AUROC) of 0.89 (95% confidence interval [CI] = 0.78-0.999) with a score of 6-7 corresponding to a positive predictive value (PPV) of 80% (95% CI = 38-96%). The BAL score had an AUROC of 0.79 (95% CI = 0.69-0.92). PPV for a score ≥2 was 38% (95% CI = 22-56%).

CONCLUSION

A high TWIST score correlates to a high likelihood of torsion and can inform surgical decision-making in the absence of US.

Performance of machine learning algorithms for lung cancer prediction: a comparative approach

Due to the excessive growth of PM 2.5 in aerosol, the cases of lung cancer are increasing rapidly and are most severe among other types as the highest mortality rate. In most of the cases, lung cancer is detected with least symptoms at its later stage. Hence, clinical records may play a vital role to diagnose this disease at the correct stage for suitable medication to cure it. To detect lung cancer an accurate prediction method is needed which is significantly reliable. In the digital clinical record era with advancement in computing algorithms including machine learning techniques opens an opportunity to ease the process. Various machine learning algorithms may be applied over realistic clinical data but the predictive power is yet to be comprehended for accurate results. This paper envisages to compare twelve potential machine learning algorithms over clinical data with eleven symptoms of lung cancer along with two major habits of patients to predict a positive case accurately. The result has been found based on classification and heat map correlation. K-Nearest Neighbor Model and Bernoulli Naive Bayes Model are found most significant methods for early lung cancer prediction.

Discordant performance of mpox serological assays

BACKGROUND

Since July 23, 2022, global mpox cases reached 92,546, with over 31,000 in the United States. Asymptomatic carriage is a critical mechanism influencing the global dissemination of mpox. Seroprevalence studies are crucial for determining the epidemic's true burden, but uncertainties persist in serologic assay performance and how smallpox vaccination may influence assay interpretation.

OBJECTIVES

Our study aimed to assess the performance of several diagnostic assays among mpox-positive, vaccinated, and pre-outbreak negative control samples. This investigation sought to enhance our understanding and management of future mpox outbreaks.

STUDY DESIGN

Serum samples from 10 mpox-positive, five vaccinated uninfected, and 137 pre-outbreak controls were obtained for serological testing. The mpox-positive samples were obtained around 100 days post symptom onset, and vaccinated patients were sampled approximately 90 days post-vaccination. Multiple diagnostic assays were employed, including four commercial ELISAs (Abbexa, RayBioTech, FineTest, ProteoGenix) and a multiplex assay (MesoScale Diagnostics (MSD)) measuring five mpox and five smallpox antigens.

RESULTS

Three commercial ELISA kits had low specificity (<50 %). The Proteogenix ELISA targeting the E8L antigen had a 94 % sensitivity and 87 % specificity. The E8L antigen on the MSD assay exhibited the greatest distinction between exposure groups, with 98 % sensitivity and 93 % specificity.

CONCLUSIONS

None of the assays could distinguish between mpox-positive and vaccinated samples. The MSD assay targeting the MPXV E8L antigen demonstrated the greatest differentiation between mpox-positive and pre-outbreak negative samples. Our findings underscore the imperative to identify sensitive and specific assays to monitor population-level mpox exposure and infection.

Assessment of exercise-induced dehydration in underhydrated athletes: Which method shows the most promise?

BACKGROUND & AIMS

Athletes are commonly exposed to exercise-induced dehydration. However, the best method to detect dehydration under this circumstance is not clear. This study aimed to analyze pre- and post-dehydration measurements of biomarkers, including saliva osmolality (SOsm), urine osmolality (UOsm), urine-specific gravity (USG), urine color (Ucolor), serum osmolality (SeOsm), serum arginine vasopressin (AVP), serum sodium (Na+), and thirst sensation in underhydrated athletes, using the body mass loss (BML) as the reference method.

METHODS

In this clinical trial (NCT05380089), a total of 38 athletes (17 females) with a regular low water intake (<35 mL/kg/day) were submitted to exercise-induced dehydration with a heat index of 29.8 ± 3.1 °C and an individualized running intensity (80-90% of first ventilatory threshold).

RESULTS

ROC curve analysis revealed significant discriminative abilities of SOsm, with AUC values of 0.76 at 1.5% BML, 0.75 at 1.75% BML, and 0.87 at 2% BML, while Na+ and SeOsm showed the highest AUC of 0.87 and 0.91 at 2% BML, respectively. SOsm showed high sensitivity at 1.5% of BML, while SeOsm and Na+ demonstrated high sensitivity at 2% of BML.

CONCLUSION

This study highlights SOsm as a potential indicator of hydration status across different levels of BML. Additionally, Na+ and SeOsm emerged as accurate dehydration predictors at 1.75% and 2% of BML. Notably, the accuracy of urinary indices and thirst sensation for detecting hydration may be limited.

Evaluating deep learning techniques for identifying tongue features in subthreshold depression: a prospective observational study

Objective

This study aims to evaluate the potential of using tongue image features as non-invasive biomarkers for diagnosing subthreshold depression and to assess the correlation between these features and acupuncture treatment outcomes using advanced deep learning models.

Methods

We employed five advanced deep learning models-DenseNet169, MobileNetV3Small, SEResNet101, SqueezeNet, and VGG19_bn-to analyze tongue image features in individuals with subthreshold depression. These models were assessed based on accuracy, precision, recall, and F1 score. Additionally, we investigated the relationship between the best-performing model's predictions and the success of acupuncture treatment using Pearson's correlation coefficient.

Results

Among the models, SEResNet101 emerged as the most effective, achieving an impressive 98.5% accuracy and an F1 score of 0.97. A significant positive correlation was found between its predictions and the alleviation of depressive symptoms following acupuncture (Pearson's correlation coefficient = 0.72, p<0.001).

Conclusion

The findings suggest that the SEResNet101 model is highly accurate and reliable for identifying tongue image features in subthreshold depression. It also appears promising for assessing the impact of acupuncture treatment. This study contributes novel insights and approaches to the auxiliary diagnosis and treatment evaluation of subthreshold depression.

Using Dried Blood Spots to Quantitatively Detect Anti-SARS-CoV-2 IgG Antibodies by ELISA: A Validation Study

SARS-CoV-2 serological testing is useful to determine seroprevalence, epidemiological trends, and the extent of transmission. The collection and transport of serum samples can be logistically challenging, especially in remote underserved areas. Dried blood spots (DBSs) would allow easier sample collection and logistical handling compared with standard serum collection, particularly for extensive and repeated SARS-CoV-2 serosurveys. We evaluated the sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of the IgG ELISA (Wantai, Beijing, China) using DBSs against sera for the quantitative detection of SARS-CoV-2 IgG antibody. The IgG ELISA was used to test paired sera and DBSs obtained from individuals with recent virologically confirmed COVID-19 illness and banked paired sera and DBSs collected before the COVID-19 pandemic. We found that 100/100 (100%) seropositive samples were positive using DBSs, and 193/194 (99%) seronegative samples were negative using DBSs. Compared with sera, the DBS method had a 100% sensitivity, 99% specificity, 99% PPV, and 100% NPV. Use of DBSs for SARS-CoV-2 household or population serosurveys may be considered in situations with limitations in sample collection, shipment, and storage.

Relationship between Countermovement Jump and Sprint Performance in Professional Football Players

Objectives: The aim of this study was to assess the relationship between the countermovement jump (CMJ) and sprint performance of professional football players, and to determine which strength and speed elements assessed by the CMJ translate into effective running. Methods: The research sample comprised 87 male professional football players (age 23.7 ± 4.20 years; body mass 82.33 ± 6.56 kg; body height 1.86 ± 0.05 m) who performed the CMJ on a dual-force platform, as well as the 30 m sprint test. The time and velocity of the run were recorded by photocells at 0, 5, 10, and 30 m of the distance. Results: No significant differences were noted in the time or velocity of the sprint over the initial 5 m between the groups of football players with a higher and lower braking rate of force development (RFD) in the CMJ (p > 0.05). However, at subsequent intervals (5-10 m and 10-30 m), players with a higher braking RFD achieved significantly better time and velocity than those with a lower RFD. Significant correlations in the group with a lower braking RFD between the CMJ and sprint variables occurred in the propulsion phase of the CMJ and most of them were in the first interval (0-5 m). In the group with a higher braking RFD, significant relationships were visible in both the propulsion (concentric) and braking (eccentric) phases of the CMJ, mainly during the second and third intervals of the sprint test. Conclusions: The noted observations may suggest that the relationship between strength and running performance is more complex than previously indicated, and that higher strength in the CMJ does not fully correlate with better sprinting. Therefore, it has been hypothesized that training aimed at generally increasing strength may not always be fully beneficial for running performance in football players and hence specific training guidelines are suggested for targeted strengthening of the required muscle performance characteristics. This may possibly contribute to reducing the unnecessary muscle overload during both training and matches, thereby preventing sports-related injuries.

Early detection of altered cold perception in elderly with type 2 diabetes using a novel Quantitative Sensory Testing method

AIM

To compare the effectiveness of two methods for measuring cold detection thresholds in screening for temperature-perception deficits in elderly individuals with type 2 diabetes (T2 diabetes).

METHODS

Cold threshold measurements were performed on seven body regions of participants with diabetes without neuropathy (n = 30; mean age, 70.9 ± 6.5 years) and healthy participants (n = 73; mean age, 68 ± 5 years). Two protocols applying the Levels Method were used: the first used skin temperature as the starting point; the second used 40 °C.

RESULTS

Cold detection thresholds were significantly higher in subjects with diabetes, particularly on the foot. For CDT TSk, values were -2.22 ± 1.91 °C in non-diabetic and -3.27 ± 3.33 °C in diabetic groups (p = 0.023); for CDT 40, values were -9.82 ± 3.5 °C and -12.18 ± 4.5 °C (p = 0.003). However, after adjusting for age, the group effect on cold threshold with skin temperature as baseline disappeared. Sensory screens showed that the Area Under Curve of the method using a 40 °C baseline was 0.69 (p = 0.002).

CONCLUSION

Measuring the cold detection threshold on the foot with a 40 °C baseline is more effective than using skin temperature as a baseline for screening sensory alterations in elderly subjects with type 2 diabetes before neuropathy onset.

SIGNIFICANCE

These findings highlight the importance of selecting the appropriate cold detection threshold method for elderly individuals with type 2 diabetes. The optimal method can facilitate early identification of sensory changes, minimizing complications and improving overall well-being.

Autistic Characteristics, Cognitive Impairment, and Sex as Predictors of Anxiety and Depression among Autistic Youth

Although it is well established that autistic youth are at high risk for anxiety and depression, factors associated with heightened risk within this population are poorly understood. The purpose of this study was to evaluate whether autistic characteristics and cognitive impairment interact to predict anxiety and depression symptoms, and whether the impacts of autistic characteristics and cognitive impairment on anxiety and depression differ for male and female children. Participants comprised 7989 youth (M = 11.23 years) enrolled in SPARK, a national cohort of autistic individuals. Autistic characteristics were assessed via the Social Communication Questionnaire. Anxiety and depression were assessed via the Child Behavior Checklist. Linear regressions were conducted to examine associations between autistic characteristics, cognitive impairment, and symptoms and to test for interactions. The effect of parent-reported autistic characteristics on anxiety was stronger for males than for females, while the effect of cognitive impairment on anxiety was stronger for females than for males. A different pattern was observed for depression. The effect of autistic characteristics on depression was the same for males and females, while cognitive impairment was not associated with depression per parent report. Findings indicate that both male and female children with high levels of autistic characteristics are susceptible to experiencing anxiety and depression, and that autistic female children with intact cognitive abilities are uniquely vulnerable to experiencing anxiety based on parent report. Results have implications for the prevention of internalizing problems in autistic youth, and highlight future directions for longitudinal work examining mechanisms of comorbidity.

Investigation of biomarkers to predict outcomes in allogeneic hematopoietic stem cell transplantation

BACKGROUND

Various biomarkers have been developed and evaluated to predict the prognosis and complications of allogeneic hematopoietic cell transplantation (HCT). Most previous studies conducted on different biomarkers evaluated single effects such as those associated with inflammation, immunology, iron metabolism, and nutrition, and only a few studies have comprehensively analyzed markers.

OBJECTIVE

The study aimed to survey comprehensive multiple markers prior to HCT and extract those that significantly predict the outcomes.

STUDY DESIGN

A prospective multicenter observational study was performed. (UMIN000013506) Patients undergoing HCT for hematologic diseases were consecutively enrolled. Besides the usual clinical biomarkers, serum samples for extra-clinical biomarkers were collected and cryopreserved before starting the conditioning regimen. A total of 32 candidate biomarkers were selected, 23 from hematology, biochemistry, immunology, nutrition, and iron metabolism, and 9 from composite markers. Based on the area under the curve (AUC) values for survival, promising biomarkers was extracted. Internal validation for these markers was applied based on bootstrap methods. Setting the cut-off values for them, log-rank test was applied and outcomes including overall survival (OS), relapse, and non-relapse mortality (NRM) were evaluated using multivariate analyses. Furthermore, detailed analysis including transplant-related complications and external validation were conducted focusing on C-reactive protein (CRP) to platelet (Plt) ratio.

RESULTS

A total of 152 patients with hematologic malignancies were enrolled from April 2014 to March 2017. CRP, soluble interleukin-2 receptor (IL2R), CRP to albumin (Alb) ratio, CRP to Plt ratio, Plt to IL2R ratio, and IL2R to Alb ratio were identified as promising markers. Internal validation successfully confirmed their reliability of AUC and multivariate analysis demonstrated the statistical significance between the higher and the lower markers. Above all, a higher CRP to Plt ratio was significantly associated with a lower OS (hazard ratio [HR] 2.77; 95% confidence interval [CI] 1.30-5.91; P = 0.008) and higher non-relapse mortality rates (HR 2.79; 95%CI 1.14-6.80; P = 0.024) at 180 days. Furthermore, univariate analysis showed that a higher CRP to Plt ratio was significantly associated with a higher incidence of sinusoidal obstructive syndrome (P < 0.001) and bloodstream infection (P = 0.027). An external validation test confirmed the significance of the CRP to Plt ratio for these outcomes.

CONCLUSION

The multicenter prospective observational study successfully identified significant biomarkers in patients with hematologic malignancies who received HCT. In particular, CRP to Plt ratio was identified as a novel and useful biomarker for predicting transplant outcomes. Further investigations are needed to validate the novel markers, analysis of the pathophysiology, and application to treatment settings other than HCT.

Exercise capacity prior to major cancer surgery: A cross-sectional observational study of the validity of the 6-minute walk and 30-second sit-to-stand tests

INTRODUCTION

Cardiopulmonary exercise testing (CPET) is the gold standard for measuring exercise capacity, however, it is resource intensive and has limited availability. This study aimed to determine: 1) the association between the 6-min walk test (6MWT) and the 30-s sit-to-stand test (30STS) with CPET peak oxygen uptake (VO2peak) and anaerobic threshold (AT) and 2) 6MWT and 30STS cut points associated with a higher risk of postoperative complications.

METHODS

A cross-sectional study, retrospectively analyzing data collected from a tertiary cancer center over a 23-month period. Measures included CPET VO2peak and AT, 6MWT and 30STS test. Correlations were used to characterize relationships between variables. Receiver operating characteristic curve analyses determined 6MWT and 30STS cut points that aligned with CPET variable cut points.

RESULTS

Note that, 156 participants were included. The 6MWT and 30STS displayed moderate correlations with VO2peak, rho = 0.65, p = 0.01 and rho = 0.52, p < 0.005 respectively. Fair correlations were observed between AT and 6MWT (rho = 0.36, p = 0.01) and 30STS (rho = 0.41, p < 0.005). The optimal cut points to identify VO2peak < 15 mL/kg/min were 493.5 m on the 6MWT and 12.5 stands on the 30STS test and for AT < 11 mL/kg/min were 506.5 m on the 6MWT and 12.5 stands on the 30STS test.

CONCLUSION

Both the 6MWT and 30STS test could be used as alternative tools for measuring exercise capacity preoperatively in the cancer setting where CPET is not available. A range of 6MWT and 30STS cut points, according to sensitivity and specificity levels, may be used to evaluate risk of postoperative outcomes.

Neutrophil-to-lymphocyte ratio at diagnosis as a biomarker for survival of amyotrophic lateral sclerosis

INTRODUCTION

The neutrophil-to-lymphocyte ratio (NLR) has previously been reported to be associated with survival in ALS. To provide further information about the role of NLR as a biomarker in ALS, we performed a systematic review, analyzed data from our local cohort of ALS subjects and performed a meta-analysis.

METHODS

(1) The systematic review used established methods. (2) Using data from our cohort of subjects, we analyzed the association of NLR with survival. (3) Meta-analysis was performed using previous studies and our local data.

RESULTS

(1) In the systematic review, higher NLR was associated with shorter survival in all studies. (2) In our subjects, survival was significantly shorter in patients in the highest NLR groups. (3) Meta-analysis showed subjects with highest NLR tertile or with NLR >3 had significantly shorter survival than other subjects.

DISCUSSION

This study supports NLR as a biomarker in ALS; high NLR is associated with poor survival.

Using the Moral Injury and Distress Scale to identify clinically meaningful moral injury

Despite the proliferation of moral injury studies, a remaining gap is distinguishing moral injury from normative distress following exposure to potentially morally injurious events (PMIEs). Our goal was to leverage mental health and functional measures to identify clinically meaningful and functionally impairing moral injury using the Moral Injury and Distress Scale (MIDS). Participants who endorsed PMIE exposure (N = 645) were drawn from a population-based sample of military veterans, health care workers, and first responders. Using signal detection methods, we identified the optimally efficient MIDS score for detecting clinically significant posttraumatic stress and depressive symptom severity, trauma-related guilt, and functional impairment. The most efficient cut scores across outcomes converged between 24 and 27. We recommend a cut score of 27 given that roughly 70% of participants who screened positive on the MIDS at this threshold reported clinically significant mental health symptoms, and approximately 50% reported severe trauma-related guilt and/or functional impairment. Overall, 10.2% of respondents exposed to a PMIE screened positive for moral injury at this threshold, particularly those who identified as a member of a minoritized racial or ethnic group (17.9%) relative to those who identified as White, non-Hispanic (8.0%), aOR = 2.52, 95% CI [1.45, 4.42]. This is the first known study to establish a cut score indicative of clinically meaningful and impairing moral injury. Such scores may enhance clinicians' abilities to conduct measurement-based moral injury care by enabling them to identify individuals at risk of negative outcomes and better understand risk and protective factors for moral injury.

Remote assessment of cognition and quality of life following radiotherapy for nasopharyngeal carcinoma: deep-learning-based predictive models and MRI correlates

PURPOSE

Irradiation of the brain regions from nasopharyngeal carcinoma (NPC) radiotherapy (RT) is frequently unavoidable, which may result in radiation-induced cognitive deficit. Using deep learning (DL), the study aims to develop prediction models in predicting compromised cognition in patients following NPC RT using remote assessments and determine their relation to the quality of life (QoL) and MRI changes.

METHODS

Seventy patients (20-76 aged) with MRI imaging (pre- and post-RT (6 months-1 year)) and complete cognitive assessments were recruited. Hippocampus, temporal lobes (TLs), and cerebellum were delineated and dosimetry parameters were extracted. Assessments were given post-RT via telephone (Telephone Interview Cognitive Status (TICS), Telephone Montreal Cognitive Assessment (T-MoCA), Telephone Mini Addenbrooke's Cognitive Examination (Tele-MACE), and QLQ-H&N 43). Regression and deep neural network (DNN) models were used to predict post-RT cognition using anatomical and treatment dose features.

RESULTS

Remote cognitive assessments were inter-correlated (r > 0.9). TLs showed significance in pre- and post-RT volume differences and cognitive deficits, that are correlated with RT-associated volume atrophy and dose distribution. Good classification accuracy based on DNN area under receiver operating curve (AUROC) for cognitive prediction (T-MoCA AUROC = 0.878, TICS AUROC = 0.89, Tele-MACE AUROC = 0.919).

CONCLUSION

DL-based prediction models assessed using remote assessments can assist in predicting cognitive deficit following NPC RT. Comparable results of remote assessments in assessing cognition suggest its possibility in replacing standard assessments.

IMPLICATIONS FOR CANCER SURVIVORS

Application of prediction models in individual patient enables tailored interventions to be provided in managing cognitive changes following NPC RT.

PFAS and their association with the increased risk of cardiovascular disease in postmenopausal women

Cardiovascular diseases (CVDs) are one of the major causes of death globally. In addition to traditional risk factors such as unhealthy lifestyles (smoking, obesity, sedentary) and genetics, common environmental exposures, including persistent environmental contaminants, may also influence CVD risk. Per- and polyfluoroalkyl substances (PFASs) are a class of highly fluorinated chemicals used in household consumer and industrial products known to persist in our environment for years, causing health concerns that are now linked to endocrine disruptions and related outcomes in women, including interference of the cardiovascular and reproductive systems. In postmenopausal women, higher levels of PFAS are observed than in premenopausal women due to the cessation of menstruation, which is crucial for PFAS excretion. Because of these findings, we explored the association between perfluorooctanoic acid (PFOA), perfluorooctane sulfonate (PFOS), and perfluorobutanesulfonic acid in postmenopausal women from our previously established CVD study. We used liquid chromatography with tandem mass spectrometry, supported by machine learning approaches, and the detection and quantification of serum metabolites and proteins. Here, we show that PFOS can be a good predictor of coronary artery disease, whereas PFOA can be an intermediate predictor of coronary microvascular disease. We also found that the PFAS levels in our study are significantly associated with inflammation-related proteins. Our findings may provide new insight into the potential mechanisms underlying the PFAS-induced risk of CVDs in this population. This study shows that exposure to PFOA and PFOS is associated with an increased risk of cardiovascular disease in postmenopausal women. PFOS and PFOA levels correlate with amino acids and proteins related to inflammation. These circulating biomarkers contribute to the etiology of CVD and potentially implicate a mechanistic relationship between PFAS exposure and increased risk of cardiovascular events in this population.

Are visual analogue scales valid instruments to measure psychological pain in psychiatric patients?

OBJECTIVE

The Psychological-Physical-Pain Visual Analogue Scale (PPP-VAS) was thought to probably help in identifying patients at risk of suicide. However, no data on its validity to measure psychological pain was available. Our main aim was to investigate the convergent validity of the PPP-VAS using two well-validated scales of psychological pain, the Orbach and Mikulincer Mental Pain scale (OMMP) and the Holden et al. Psychache Scale.

METHODS

This multicentre study recruited a total of 1618 adult psychiatric inpatients and outpatients in Italy. Psychological pain was evaluated using the OMMP, Holden et al., and PPP-VAS scales. Psychiatric status, suicidal status, physical pain, depression, and hopelessness were also assessed.

RESULTS

A structural equation model (SEM) using the items of psychological pain from the PPP-VAS showed that items loaded significantly on the psychological pain factor and showed good fit. Similarly, a second SEM model using the three scales of psychological pain showed acceptable fit and converged into a psychological pain construct. Correlations between the PPP-VAS and depression, hopelessness, and physical pain showed moderate correlations (r = 0.43 to r = 0.67). Finally, psychological pain evaluated with the PPP-VAS was significantly related with recent suicidal ideation in all patients (OR [95 % CI] = 1.07 [1.05, 1.09]) and recent suicide attempts in moderately to severely depressed patients, OR [95 % CI] = 1.01 [1.02, 1.03].

CONCLUSION

The PPP-VAS showed good psychometric properties in evaluating psychological pain. The characteristics of the PPP-VAS makes this scale a great option for its use in clinical practice to detect patients at risk of suicide.

Clinical toxicology of acute glyphosate self-poisoning: impact of plasma concentrations of glyphosate, its metabolite and polyethoxylated tallow amine surfactants on the toxicity

INTRODUCTION

Common major co-formulants in glyphosate-based herbicides, polyethoxylated tallow amine surfactants, are suspected of being more toxic than glyphosate, contributing to the toxicity in humans. However, limited information exists on using polyethoxylated tallow amine concentrations to predict clinical outcomes. We investigated if plasma concentrations of glyphosate, its metabolite and polyethoxylated tallow amines can predict acute kidney injury and case fatality in glyphosate poisoning.

METHODS

We enrolled 151 patients with acute glyphosate poisoning between 2010 and 2013. Plasma concentrations of glyphosate, its metabolite, aminomethylphosphonic acid, and polyethoxylated tallow amines were determined in 2020 using liquid chromatography-tandem mass spectrometry. Associations between exposure and poisoning severity were assessed.

RESULTS

Plasma concentrations of glyphosate and aminomethylphosphonic acid demonstrated good and moderate performances in predicting acute kidney injury (≥2), with an area under the receiver operating characteristic curve of 0.83 (95% CI 0.69-0.97) and 0.76 (95% CI 0.59-0.94), respectively. Polyethoxylated tallow amines were detected in one-fifth of symptomatic patients, including one of four fatalities and those with unsaturated tallow moieties being good indicators of acute kidney injury (area under the receiver operating characteristic curve ≥0.7). As the number of repeating ethoxylate units in tallow moieties decreased, the odds of acute kidney injury increased. Glyphosate and aminomethylphosphonic acid concentrations were excellent predictors of case fatality (area under the receiver operating characteristic curve >0.9).

DISCUSSION

The 2.7% case fatality rate with 49% acute, albeit mild, acute kidney injury following glyphosate poisoning is consistent with previously published data. A population approach using model-based metrics might better explore the relationship of exposure to severity of poisoning.

CONCLUSIONS

Plasma concentrations of glyphosate and its metabolite predicted the severity of clinical toxicity in glyphosate poisoning. The co-formulated polyethoxylated tallow amine surfactants were even more strongly predictive of acute kidney injury but were only detected in a minority of patients.

Which is Better in Predicting CT Scores in Patients with Chronic Rhinosinusitis after Medical treatment-Baseline Rhinosinusitis Disability Index (RSDI) or Endoscopic Score?

Introduction

Rhinosinusitis disability index (RSDI) questionnaire is used to assess the severity of chronic rhinosinusitis (CRS) from the patient's perspective. The severity of CRS can be measured objectively with the endoscope and computed tomogram (CT) using the Lund-Kennedy endoscopic score and Mackay-Lund scores respectively. The objective of the study is to evaluate whether baseline RSDI and Lund-Kennedy (LK) endoscopy scoring can help predict the Mackay-Lund CT (MKLCT) scores after medical treatment in patients with CRS.

Methodology

This is a prospective, observational study, carried out from 1st October 2017 to 30th September 2019 in the ENT out- patient department at a tertiary hospital in Northern India. 90 patients diagnosed with CRS were enrolled consecutively in the study. RSDI questionnaire was filled out for all the participants. They all underwent a diagnostic endoscopy and CRS was graded according to the Lund-Kennedy endoscopic scores. All participants were given medical treatment. Patients underwent CT of the paranasal sinuses after medical treatment and the MLKCT scores were calculated. The baseline RSDI and Lund-Kennedy scores were correlated with the MKLCT scores using Spearman's Rank correlation tests. The diagnostic ability of the RSDI and LK endoscopy scores to predict the least MKLCT scores was compared using the receiver operator characteristics curves (ROC).

Results

A statistically significant correlation was seen with LK endoscopy scores and MKLCT scores (r = 0.396, p < 0.001) Among the individual parameters of the LK endoscopy scores only the polyp score had a statistically significant correlation with MKLCT scores (r = 0.593, p < 0.001). A weak negative correlation (r = - 0.058, p = 0.586) was seen between the RSDI scores and MKLCT scores. AUC in ROC curves for a LK endoscopy scores and RSDI scores were 0.690 and 0.462 respectively. Cut-off for predicting a MKLCT score of one or more for RSDI score was 25, with a sensitivity of 61% and specificity of 38.5%. Similarly, the cut-off for LK endoscopic score was 4.5, with a sensitivity of 68.8% and specificity of 61.5%.

Conclusion

Statistically significant (p < 0.001) association was found between baseline Lund-Kennedy endoscopic scores and Mackay-Lund CT scores post medical treatment. No significant association was found between RSDI scores and Mackay-Lund CT scores. ROC analysis indicated that Lund- Kennedy endoscopy score is a more accurate tool than RSDI score to predict a Mackay-Lund CT scores after medical treatment.

Supplementary Information

The online version contains supplementary material available at 10.1007/s12070-024-04708-6.

Validation of the ND-PAE Diagnosis in Children with Heavy Prenatal Alcohol Exposure

This study evaluated criteria for neurobehavioral disorder associated with prenatal alcohol exposure (ND-PAE). Kable et al. (Child Psychiatry Hum Dev 55:426, 2022) assessed the validity of this diagnosis in a sample with low exposure to alcohol. The current study expanded this assessment to a sample with a wider age range and heavier alcohol exposure. Data were collected from participants (5-17 years) with prenatal alcohol exposure (PAE) and typically developing controls at six Collaborative Initiative on Fetal Alcohol Spectrum Disorders sites using neuropsychological assessment and caregiver reports. Impairment was tested at 1SD, 1.5SD, and 2SD below the normative average and a modification of the adaptive functioning requirement was tested. Testing impairment at 1SD resulted in the highest endorsement rates in both groups. Our findings replicated the study by Kable et al. and show that current criteria captured a high rate of those with PAE and that requiring fewer adaptive functioning criteria resulted in higher sensitivity to PAE.

The Neck-Persistency-Net: a three-dimensional, convolution, deep neural network aids in distinguishing vital from non-vital persistent cervical lymph nodes in advanced head and neck squamous cell carcinoma after primary concurrent radiochemotherapy

PURPOSE

To evaluate the diagnostic performance (DP) of the high-resolution contrast computed tomography (HR-contrast-CT) based Neck-Persistency-Net in distinguishing vital from non-vital persistent cervical lymph nodes (pcLNs) in patients with advanced head and neck squamous cell carcinoma (HNSCC) following primary concurrent chemoradiotherapy (CRT) with [18F]-fluorodeoxyglucose positron emission tomography and high-resolution contrast-enhanced computed tomography ([18F]FDG-PET-CT). Furthermore, the Neck-Persistency-Net's potential to justify omitting post-CRT neck dissection (ND) without risking treatment delays or preventing unnecessary surgery was explored.

METHODS

All HNSCC patients undergoing primary CRT followed by post-CRT-ND for pcLNs recorded in the institutional HNSCC registry were analyzed. The Neck-Persistency-Net DP was explored for three scenarios: balanced performance (BalPerf), optimized sensitivity (OptSens), and optimized specificity (OptSpec). Histopathology of post-CRT-ND served as a reference.

RESULTS

Among 68 included patients, 11 were female and 32 had vital pcLNs. The Neck-Persistency-Net demonstrated good DP with an area under the curve of 0.82. For BalPerf, both sensitivity and specificity were 78%; for OptSens (90%), specificity was 62%; for OptSpec (95%), sensitivity was 54%. Limiting post-CRT-ND to negative results would have delayed treatment in 27%, 40%, and 7% for BalPerf, OptSens and OptSpec, respectively, versus 23% for [18F]FDG-PET-CT. Conversely, restricting post-CRT-ND to positive results would have prevented unnecessary post-CRT-ND in 78%, 60%, and 95% for BalPerf, OptSens and OptSpec, respectively, versus 55% for [18F]FDG-PET-CT.

CONCLUSION

The DP of the Neck-Persistency-Net was comparable to [18F]-FDG-PET-CT. Depending on the chosen decision boundary, the potential to justify the omission of post-CRT-ND without risking treatment delays in false negative findings or reliably prevent unnecessary surgery in false positive findings outperforms the [18F]-FDG-PET-CT.

Study of microRNAs in Gingival Crevicular Fluid as Periodontal Diseases Biomarkers: Systematic Review

AIM

The aim of this review was to identify the microRNAs (miRNAs) present in gingival crevicular fluid (GCF) that can be used as biomarkers for the diagnosis of periodontal diseases, and to determine which of them has a higher diagnostic yield for periodontitis.

METHODS

The review was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines (reference number CRD42024544648). The Pubmed, Scopus, Cochrane Library, Embase, Web of Science, and Google Scholar databases were searched for clinical studies conducted in humans investigating periodontal diseases and miRNAs in GCF. The methodological quality of the articles was measured with the Newcastle-Ottawa Scale.

RESULTS

A total of 3222 references were identified in the initial literature search, and 16 articles were finally included in the review. The design of the studies was heterogeneous, which prevented a meta-analysis of the data. Most of the studies compared miRNA expression levels between patients with periodontitis and healthy controls. The most widely researched miRNA in periodontal diseases was miR-200b-3p and miR-146a.

CONCLUSIONS

the miRNAs most studied are miR-146a, miR-200b, miR-223, miR-23a, and miR-203, and all of them except miR-203 have an acceptable diagnostic plausibility for periodontitis.

Association of preoperative antiviral treatment with incidences of post-hepatectomy liver failure in hepatitis B virus-related hepatocellular carcinoma

BACKGROUND

Post-hepatectomy liver failure (PHLF) is a common consequence of radical partial hepatectomy in hepatocellular carcinoma (HCC).

AIMS

To investigate the relationship between preoperative antiviral therapy and PHLF, as well as assess the potential efficacy of hepatitis B virus (HBV) DNA level in predicting PHLF.

METHODS

A retrospective study was performed involving 1301 HCC patients with HBV who underwent radical hepatectomy. Receiver operating characteristic (ROC) analysis was used to assess the capacity of HBV DNA to predict PHLF and establish the optimal cutoff value for subsequent analyses. Logistic regression analyses were performed to assess the independent risk factors of PHLF. The increase in the area under the ROC curve, categorical net reclassification improvement (NRI), and integrated discrimination improvement (IDI) were used to quantify the efficacy of HBV DNA level for predicting PHLF. The P < 0.05 was considered statistically significant.

RESULTS

Logistic regression analyses showed that preoperative antiviral therapy was independently associated with a reduced risk of PHLF (P < 0.05). HBV DNA level with an optimal cutoff value of 269 IU/mL (P < 0.001) was an independent risk factor of PHLF. All the reference models by adding the variable of HBV DNA level had an improvement in area under the curve, categorical NRI, and IDI, particularly for the fibrosis-4 model, with values of 0.729 (95%CI: 0.705-0.754), 1.382 (95%CI: 1.341-1.423), and 0.112 (95%CI: 0.110-0.114), respectively. All the above findings were statistically significant.

CONCLUSION

In summary, preoperative antiviral treatment can reduce the incidence of PHLF, whereas an increased preoperative HBV DNA level has a correlative relationship with an increased susceptibility to PHLF.

Bilirubin Molecular Species Play an Important Role in the Pathophysiology of Acute-on-Chronic Liver Failure

Bilirubin plays a key role in early diagnosis, prognosis, and prevention of liver diseases. Unconjugated bilirubin (UCB) requires conversion to a water-soluble form through liver glucuronidation, producing monoglucuronide (BMG) or diglucuronide bilirubin (BDG) for bile excretion. This study aimed to assess the roles of bilirubin's molecular species-UCB, BMG, and BDG-in diagnosing and understanding the pathogenesis of liver cirrhosis in patients with acute-on-chronic liver failure (ACLF), compensated liver cirrhosis (LC) patients, and healthy individuals. The study included patients with ACLF and compensated LC of diverse etiologies, along with healthy controls. We collected laboratory and clinical data to determine the severity and assess mortality. We extracted bilirubin from serum samples to measure UCB, BMG, and BDG using liquid chromatography-mass spectrometry (LC-MS). The quantification of bilirubin was performed by monitoring the mass charge (m/z) ratio. Of the 74 patients assessed, 45 had ACLF, 11 had LC, and 18 were healthy individuals. Among ACLF patients, the levels of molecular species of bilirubin were UCB 19.69 μmol/L, BMG 47.71 μmol/L, and BDG 2.120 μmol/L. For compensated cirrhosis patients, the levels were UCB 11.29 μmol/L, BMG 1.49 μmol/L, and BDG 0.055 μmol/L, and in healthy individuals, the levels were UCB 6.42 μmol/L, BMG 0.52 μmol/L, and BDG 0.028 μmol/L. The study revealed marked elevations in the bilirubin species in individuals with ACLF compared to those with compensated cirrhosis and healthy controls, underscoring the progression of liver dysfunction. The correlation of BMG and BDG levels with commonly used inflammatory markers suggests a relationship between bilirubin metabolism and systemic inflammation in ACLF.

A novel methodology for emotion recognition through 62-lead EEG signals: multilevel heterogeneous recurrence analysis

Objective

Recognizing emotions from electroencephalography (EEG) signals is a challenging task due to the complex, nonlinear, and nonstationary characteristics of brain activity. Traditional methods often fail to capture these subtle dynamics, while deep learning approaches lack explainability. In this research, we introduce a novel three-phase methodology integrating manifold embedding, multilevel heterogeneous recurrence analysis (MHRA), and ensemble learning to address these limitations in EEG-based emotion recognition.

Approach

The proposed methodology was evaluated using the SJTU-SEED IV database. We first applied uniform manifold approximation and projection (UMAP) for manifold embedding of the 62-lead EEG signals into a lower-dimensional space. We then developed MHRA to characterize the complex recurrence dynamics of brain activity across multiple transition levels. Finally, we employed tree-based ensemble learning methods to classify four emotions (neutral, sad, fear, happy) based on the extracted MHRA features.

Main results

Our approach achieved high performance, with an accuracy of 0.7885 and an AUC of 0.7552, outperforming existing methods on the same dataset. Additionally, our methodology provided the most consistent recognition performance across different emotions. Sensitivity analysis revealed specific MHRA metrics that were strongly associated with each emotion, offering valuable insights into the underlying neural dynamics.

Significance

This study presents a novel framework for EEG-based emotion recognition that effectively captures the complex nonlinear and nonstationary dynamics of brain activity while maintaining explainability. The proposed methodology offers significant potential for advancing our understanding of emotional processing and developing more reliable emotion recognition systems with broad applications in healthcare and beyond.

Clinical characteristics of pediatric patients hospitalized with community-acquired pneumonia and cytomegalovirus DNA detected in bronchoalveolar lavage fluid

Background

This study aimed to investigate the clinical characteristics of pediatric patients hospitalized with community-acquired pneumonia (CAP) and concomitant cytomegalovirus (CMV) infection.

Methods

This cross-sectional study enrolled consecutive pediatric patients admitted with CAP who tested positive for CMV DNA in bronchoalveolar lavage fluid (BALF). Flexible fiberoptic bronchoscopy was performed when routine treatment for CAP proved ineffective. The study participants were further stratified into two groups based on CMV serological test results: recent CMV infection group and CMV replication group. Clinical characteristics were compared between these two groups.

Results

Among 124 patients aged 1-11 months included in this study, 80 (64.5%) patients were categorized as having recent CMV infection, and 44 (35.5%) tested positive for CMV replication. Co-infection with other pathogens was detected more frequently in the CMV replication group (n = 29, 65.9%) than in the recent CMV infection group (n = 35, 43.7%; P = 0.018). Patients with recent CMV infection were younger and exhibited higher levels of alanine transaminase (ALT) and aspartate aminotransferase compared to those with CMV replication (all P < 0.05). Multivariable regression analysis showed age was independently associated with recent CMV infection (odds ratio [OR], 0.707; 95% confidence interval [CI], 0.586-0.853; P < 0.001). Notably, receiver operating characteristic curve analysis showed that a CMV PCR level of 3,840 copies/ml in blood samples had a sensitivity of 34.7% and specificity of 90.0% for diagnosis of recent CMV infection with an area under the curve (AUC) of 0.625 (95% CI: 0.513-0.736, P = 0.048). A CMV PCR level of 6,375 copies/ml in urine samples had a sensitivity of 77.1% and specificity of 61.5% for diagnosis of recent CMV infection with an AUC of 0.695 (95% CI: 0.531-0.858, P = 0.04). Furthermore, multivariate linear regression analysis revealed that the blood CMV DNA copy number was associated with ALT (B = 0.001; P < 0.001).

Conclusions

The CMV DNA copy numbers in blood and urine could serve as discriminatory markers between recent CMV infection and CMV replication. Measuring CMV DNA levels in blood may be an effective method for monitoring liver function impairment in pediatric patients presenting with CAP and concurrent CMV infection.

NANO.PTML model for read-across prediction of nanosystems in neurosciences. computational model and experimental case of study

Neurodegenerative diseases involve progressive neuronal death. Traditional treatments often struggle due to solubility, bioavailability, and crossing the Blood-Brain Barrier (BBB). Nanoparticles (NPs) in biomedical field are garnering growing attention as neurodegenerative disease drugs (NDDs) carrier to the central nervous system. Here, we introduced computational and experimental analysis. In the computational study, a specific IFPTML technique was used, which combined Information Fusion (IF) + Perturbation Theory (PT) + Machine Learning (ML) to select the most promising Nanoparticle Neuronal Disease Drug Delivery (N2D3) systems. For the application of IFPTML model in the nanoscience, NANO.PTML is used. IF-process was carried out between 4403 NDDs assays and 260 cytotoxicity NP assays conducting a dataset of 500,000 cases. The optimal IFPTML was the Decision Tree (DT) algorithm which shown satisfactory performance with specificity values of 96.4% and 96.2%, and sensitivity values of 79.3% and 75.7% in the training (375k/75%) and validation (125k/25%) set. Moreover, the DT model obtained Area Under Receiver Operating Characteristic (AUROC) scores of 0.97 and 0.96 in the training and validation series, highlighting its effectiveness in classification tasks. In the experimental part, two samples of NPs (Fe3O4_A and Fe3O4_B) were synthesized by thermal decomposition of an iron(III) oleate (FeOl) precursor and structurally characterized by different methods. Additionally, in order to make the as-synthesized hydrophobic NPs (Fe3O4_A and Fe3O4_B) soluble in water the amphiphilic CTAB (Cetyl Trimethyl Ammonium Bromide) molecule was employed. Therefore, to conduct a study with a wider range of NP system variants, an experimental illustrative simulation experiment was performed using the IFPTML-DT model. For this, a set of 500,000 prediction dataset was created. The outcome of this experiment highlighted certain NANO.PTML systems as promising candidates for further investigation. The NANO.PTML approach holds potential to accelerate experimental investigations and offer initial insights into various NP and NDDs compounds, serving as an efficient alternative to time-consuming trial-and-error procedures.

Minimal important difference of the Migraine Disability Assessment (MIDAS): Longitudinal data from the DMKG Headache Registry

BACKGROUND

The Migraine Disability Assessment (MIDAS) is widely used. However, there are limited data on how much a reduction in the MIDAS score indicates a change that matters to the patient.

METHODS

Data from the DMKG (i.e. German Migraine and Headache Society) Headache Registry were used to determine the minimal important difference (MID) of the MIDAS, using the Patient Global Impression of Change (PGIC) as anchor and applying average change and receiver operating characteristic curve methods.

RESULTS

In total, 1218 adult migraine patients (85.6% female, 40.2 ± 12.8 years, baseline MIDAS 44.2 ± 47.4, follow-up MIDAS 36.5 ± 45.3) were included. For patients with baseline MIDAS >20 (MIDAS grade IV, n = 757), different methods using PGIC "somewhat improved" as anchor yielded percent change MIDs of the MIDAS between -29.4% and -33.2%. For baseline MIDAS between 6 and 20 (grades II and III, n = 334), using PGIC "much improved" as anchor, difference change MIDs were between -3.5 and -4.5 points.

CONCLUSIONS

Based on the above results, we estimated the MID of the MIDAS at -30% for patients with a baseline MIDAS >20, and at -4 points for those with a baseline MIDAS of 6-20, for a tertiary headache care population.

TRIAL REGISTRATION

The DMKG Headache Registry is registered with the German Clinical Trials Register (DRKS 00021081).

Braden score predicts 30-day mortality risk in patients with ischaemic stroke in the ICU: A retrospective analysis based on the MIMIC-IV database

BACKGROUND

Ischaemic stroke remains a significant global health challenge, associated with high mortality rates. While the Braden Scale is traditionally employed to assess pressure ulcer risk, its potential to predict mortality among the intensive care unit (ICU) patients with ischaemic stroke has not been thoroughly investigated.

AIM/S

This study evaluates the predictive value of the Braden Scale for 30-day mortality among patients with ischaemic stroke admitted to ICU.

STUDY DESIGN

We conducted a retrospective analysis of 4710 adult patients with ischaemic stroke from the Medical Information Mart for Intensive Care (MIMIC)-IV database. The association between the Braden Scale scores and 30-day mortality was assessed using receiver operating characteristic (ROC) curve analysis, Cox regression models and Kaplan-Meier survival estimates.

RESULTS

Patients with Braden Scale scores ≤ 15.5 showed significantly higher 30-day mortality rates (p-value < 0.001; hazard ratio (HR): 2.08, 95% confidence interval (CI): 1.71-2.53). The area under the ROC curve (AUC) was 0.71, demonstrating good predictive performance. Multivariate analysis confirmed the Braden Scale as an independent predictor of mortality, after adjusting for age, gender and comorbidities.

CONCLUSIONS

The Braden Scale effectively identifies high-risk ischaemic stroke patients in ICU settings, endorsing its integration into routine assessments to facilitate early intervention strategies.

RELEVANCE TO CLINICAL PRACTICE

Integrating the Braden Scale into routine ICU evaluations can enhance mortality risk stratification and improve patient care tailoring.

Discriminative capacity of the Spanish version of the Inventory of Depression and Anxiety Symptoms-II (IDAS-II) for detecting DMS-5 specific disorders and poor quality of life in a clinical sample

BACKGROUND

Emotional problems can be evaluated using categorical approaches to guide treatment choices focused on targeting specific disorders, or dimensional approaches to reduce symptom severity. Moreover, recent evidence points out the need to intervene in patients' quality of life (QoL), which often remains low even after the remission of emotional problems. Thus, assessment instruments are needed to provide information on diagnosis, symptom severity, and QoL. The present study aimed to provide diagnostic and QoL cutoffs for the Inventory of Depression and Anxiety Symptoms-II (IDAS-II).

METHODS

273 patients recruited from mental health services in Huelva (Spain) completed the IDAS-II, Mini International Neuropsychiatric Interview, and Short Form-36 Health Survey. Receiver operating characteristic curve analyses were used to establish cutoff values. Diagnostic, balanced, and screening cutoffs were provided for each IDAS-II scale to detect corresponding diagnoses and poor QoL.

RESULTS

The specific IDAS-II scales Suicidality, Panic, Social Anxiety, Claustrophobia, and Traumatic Intrusions showed adequate discrimination values for their corresponding diagnoses (suicidal behavior disorder, panic disorder, social anxiety disorder, agoraphobia, and post-traumatic stress disorder, respectively). Both the General Depression and Dysphoria scales showed adequate ability to detect major depressive disorder. The IDAS-II scales showed a higher discrimination ability for Mental Health-related QoL, than for General Health-related QoL.

CONCLUSIONS

The diagnostic and QoL cutoffs expand the clinical utility of the IDAS-II in clinical practice and research, making it a comprehensive, detailed, and versatile self-report tool. The IDAS-II allows for the assessment of emotional problems consistent with the dimensional, categorical, transdiagnostic, and QoL approaches.

Integrating clinical data mining, network analysis and experimental validation reveal the anti-inflammatory mechanism of Huangqin Qingre Chubi Capsule in rheumatoid arthritis treatment

ETHNOPHARMACOLOGICAL RELEVANCE

Huangqin Qingre Chubi Capsule (HQC) is a Chinese medicinal compound used for the treatment of damp-heat pattern rheumatism, guided by the traditional Chinese medicine syndrome differentiation practice. HQC has been used in the clinical treatment of rheumatic diseases for more than 20 years with remarkable efficacy. HQC has been experimentally shown to exert anti-arthritic effects via the Wnt signaling pathway.

AIM OF THE STUDY

This study used clinical data mining, network analysis, and in vitro and in vivo tests to investigate the anti-arthritic and possible anti-inflammatory mechanism of HQC. Specifically, emphasis was placed on the function of the hsa_circ_0091,685/EIF4A3/IL-17 axis in the anti-inflammatory process.

MATERIALS AND METHODS

A random walk model was used to evaluate the effects of HQC on clinical immune inflammatory marker function in patients with RA. Network analysis was used to predict the potential target genes and pathways of HQC. Hematoxylin & eosin, safranin O-fast green and toluidine blue staining, immunohistochemistry, and transmission electron microscopy were performed to evaluate the anti-arthritic effects of HQC in rat models. Cell Counting Kit-8 assay, quantitative real-time polymerase chain reaction, western blotting, enzyme-linked immunosorbent assay, and RNA pull-down were used to study the anti-proliferation and anti-inflammatory mechanisms of HQC.

RESULTS

Patients with RA who underwent HQC treatment showed a significant reduction in inflammatory response levels, according to retrospective clinical study. Network analysis revealed that HQC potentially targeted genes and pathways related to inflammation, especially IL-6, IL-17, TNF-α, IL-23, and IL-17 signaling pathway. Animal experiments showed that HQC inhibits inflammation through the IL-17 signaling pathway in rat models. Cellular experiments showed that HQC-containing serum inhibited the inflammatory response in patients with RA-FLS or RA by blocking hsa_circ_0091,685 and EIF4A3 expression.

CONCLUSION

In RA patients, HQC reduces the inflammatory response. The antiproliferative and anti-inflammatory qualities of HQC are responsible for its therapeutic impact. The suppression of the hsa_circ_0091,685/EIF4A3/IL-17 axis was linked to these favorable outcomes.

Comparison of Two Previously Validated Risk Assessment and Prediction Tool Models in Extended Length of Stay Patients Following total Hip Arthroplasty

INTRODUCTION

Previous studies have attempted to validate the risk assessment and prediction tool (RAPT) in primary total hip arthroplasty (THA) patients. The purpose of this study was to: (1) identify patients who had an extended length of stay (LOS) following THA; and (2) compare the accuracy of 2 previously validated RAPT models.

METHODS

We retrospectively reviewed all primary THA patients from 2014 to 2021 who had a completed RAPT score. Youden's J computational analysis was used to determine the LOS where facility discharge was statistically more likely. Based on the cut-offs proposed by Oldmeadow and Dibra, patients were separated into high- (O: 1 to 5 versus D: 1 to 3), medium- (O: 6 to 9 versus D: 4 to 7), and low- (O: 10 to 12 versus D: 8 to 12) risk groups.

RESULTS

We determined that an LOS of greater than 2 days resulted in a higher chance of facility discharge. In these patients (n = 717), the overall predictive accuracy (PA) of the RAPT was 79.8%. The Dibra model had a higher PA in the high-risk group (D: 68.2 versus O: 61.2% facility discharge). The Oldmeadow model had a higher PA in the medium-risk (O: 78.7 versus D: 61.4% home discharge) and low-risk (O: 97.0 versus D. 92.5% home discharge) groups.

CONCLUSIONS

As institutions continue to optimize LOS, the RAPT may need to be defined in the context of a patient's hospital stay. In patients requiring an LOS of greater than 2 days, the originally established RAPT cut-offs may be more accurate in predicting discharge disposition.

LEVEL OF EVIDENCE

III Retrospective Cohort Study.

The influence of nationwide COVID-19 lockdown on the functional impairment and long-term survival of dependent people for carrying out basic activities of daily living in a neighborhood of the city of Madrid, Spain: Orcasitas Cohort Longitudinal Study

Background

Prolonged confinement can lead to personal deterioration at various levels. We studied this phenomenon during the nationwide COVID-19 lockdown in a functionally dependent population of the Orcasitas neighborhood of Madrid, Spain, by measuring their ability to perform basic activities of daily living and their mortality rate.

Methods

A total of 127 patients were included in the Orcasitas cohort. Of this cohort, 78.7% were female, 21.3% were male, and their mean age was 86 years. All participants had a Barthel index of ≤ 60. Changes from pre- to post-confinement and 3 years afterward were analyzed, and the effect of these changes on survival was assessed (2020-2023).

Results

The post-confinement functional assessment showed significant improvement in independence over pre-confinement for both the Barthel score (t = -5.823; p < 0.001) and the classification level (z = -2.988; p < 0.003). This improvement progressively disappeared in the following 3 years, and 40.9% of the patients in this cohort died during this period. These outcomes were associated with the Barthel index (z = -3.646; p < 0.001) and the level of dependence (hazard ratio 2.227; CI 1.514-3.276). Higher mortality was observed among men (HR 1.745; CI 1.045-2.915) and those with severe dependence (HR 2.169; CI 1.469-3.201). Setting the cutoff point of the Barthel index at 40 provided the best detection of the risk of death associated with dependence.

Conclusions

Home confinement and the risk of death due to the COVID-19 pandemic awakened a form of resilience in the face of adversity among the population of functionally dependent adults. The Barthel index is a good predictor of medium- and long-term mortality and is a useful method for detecting populations at risk in health planning. A cutoff score of 40 is useful for this purpose. To a certain extent, the non-institutionalized dependent population is an invisible population. Future studies should analyze the causes of the high mortality observed.

Comparison of Performance Characteristics in Early Warning Scoring Tools for Diagnosis of Intubation and Mortality Among COVID-19 Patients

INTRODUCTION

Early warning scores serve as valuable tools for predicting adverse events in patients. This study aimed to compare the diagnostic performance of National Early Warning Score, Hamilton Early Warning Score, Standardized Early Warning Score, and Triage Early Warning Score in forecasting intubation and mortality among patients with coronavirus disease 2019.

METHODS

This predictive correlation study included 370 patients admitted to the emergency department of 22 Bahman Hospital in Neyshabur, Iran, from December 2021 to March 2022. The aforementioned scores were assessed daily upon patient admission and throughout a 1-month hospitalization period, alongside intubation and mortality occurrences. Data analysis used SPSS 26 and MEDCALC 20.0.13 software. We adhered to the Standards for Reporting of Diagnostic Accuracy Studies guidelines to ensure the accurate reporting of our study.

RESULTS

The patients' mean age was 65.03 ± 18.47 years, with 209 (56.5%) being male. Both Standardized Early Warning Score and Hamilton Early Warning Score demonstrated high diagnostic performance, with area under the curve values of 0.92 and 0.95, respectively. For Standardized Early Warning Score, the positive likelihood ratio was 10.81 for intubation and 17.90 for mortality, whereas for Hamilton Early Warning Score, the positive likelihood ratio was 7.88 for intubation and 10.40 for mortality. The negative likelihood ratio values were 0.23 and 0.17 for Standardized Early Warning Score and 0.21 and 0.18 for Hamilton Early Warning Score, respectively, for the 24-hour period preceding intubation events and mortality.

DISCUSSION

Findings suggest that Standardized Early Warning Score, followed by Hamilton Early Warning Score, has superior diagnostic performance in predicting intubation and mortality in patients with coronavirus disease 2019 within 24 hours before these outcomes. Therefore, serial assessments of Hamilton Early Warning Score or Standardized Early Warning Score may be valuable tools for health care providers in identifying high-risk patients with coronavirus disease 2019 who require intubation or are at increased risk of mortality.

Applying chemical shift images (in-phase/opposed phased) for differentiating low-grade from high-grade glioma and comparison with magnetic resonance spectroscopy

BACKGROUND

Grading gliomas is essential for treatment decisions and patient prognosis. In this study we evaluated the in-phase and out-of-phase sequences for distinguishing high-grade (HGG) from low-grade glioma (LGG) and the correlation with magnetic resonance spectroscopy (MRS) results.

METHODS

This observational study comprised patients with brain tumors referred to our center for brain MRS. The gold standard for diagnosis was based on the World Health Organization (WHO) glioma classification. A standard tumor protocol was accomplished using a 1.5‑T MRS scanner. Before contrast medium administration, extra in- and out-phase sequences were acquired. Three 20-30-mm2 oval regions of interest (ROIs) were placed in the solid component and the signal loss ratio (SLR) was calculated with the following formula: SLR tumor = (SI In phase - SI Opposed phase) / SI In phase Correlations and comparisons between groups were made using the Pearson, chi-square and, independent samples t tests. Receiver operating characteristic (ROC) curve analysis was performed to assess the diagnostic performance. Statistical significance was set at p < 0.05.

RESULTS

In total, 20 patients were included in the LGG and 13 were included in the HGG group. The mean SLR in the HGG and LGG groups was 3.66 ± 2.12 and 1.63 ± 1.86, respectively (p = 0.01). There was a statistically significant correlation between lipid lactate (0.48, p = 0.004) and free lipid (0.44, p = 0.009) concentrations on MRS with SLR.

CONCLUSIONS

The SLR is a simple, rapid, and noninvasive marker for differentiating between LGG and HGG. There is a significant correlation with both the concentration and presence of free lipid and lipid-lactate peaks in MRS.