Additional Predictors Research Articles

Pathways to resilience: The parallel change in children's emotional difficulties and family context during the COVID-19 lockdown in Italy.

The study analyses which pathways to adjustment emerged at the family level during the COVID-19 containment period in Italy, during which children were locked down with their families for 56 days from March 11 to May 6. Using a longitudinal design, with data pre- and postevent, a bivariate latent change score model analyzed the covariance of the change in family well-being (FW) and in emotional difficulties (ED), testing if the longitudinal change in ED is a function of the starting level of FW, and vice-versa. Children's stress reactions to the pandemic and other related experiences were included as additional predictors. A total of 166 middle school students (86 females) with a mean age of 11.14 (SD = .47) completed two online questionnaires, in January 2020 (T0) and in June 2020 (T1). Results showed that children's ED decreased significantly, on average, during the lockdown period, and FW remained constant. ED and FW change scores had a significant and negative covariation (β = - .46; p = .01). When family well-being increased emotional difficulties decreased, and vice versa. FW at T0 predicted no change in FW, nor did T0 scores of ED predict any change in FW. The strong intercorrelated change between children's ED and FW during the lockdown does not seem influenced by preexisting levels of individual and family functioning. Findings supported the view that for some families, the COVID-19 lockdown was also an opportunity to experience deeper emotional connections, contributing to a decrease in ED. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Predicting Skeletal-related Events Using SINS.

Predictive study utilized retrospectively collected data. The primary objective was to evaluate the predictive association between the Spine Instability Neoplastic Score (SINS) and Skeletal-related events (SREs). Secondary objectives included examining characteristics of cases with SINS < 6 among those who developed SRE, and evaluating the impact of additional predictors on prediction accuracy. Advances in cancer treatment have prolonged the lives of cancer patients, emphasizing the importance of maintaining quality of life. Skeletal-related events from metastatic spinal tumors significantly impact quality of life. However, currently, there is no scientifically established method to predict the occurrence of SRE. SINS, developed by the Spine Oncology Study Group, assesses spinal instability using six categories. Therefore, the predictive performance of SINS for SRE occurrence is of considerable interest to clinicians. This predictive study utilized retrospectively collected data from a single-center registry comprising over 1,000 patients with metastatic spinal tumors. SINS and clinical data were collected. Logistic regression was used to create a prediction equation for SRE using SINS. Additional analyses explored factors associated with SRE in patients with SINS < 6. The study included 1,041 patients with metastatic spinal tumors. SRE occurred in 121 cases (12%). The prediction model for SRE using SINS demonstrated an area under the curve (AUC) of 0.832. Characteristics associated with SRE included lower female prevalence, surgeries to primary sites, bone metastases to non-spinal sites, and metastases to other organs. A post hoc analysis incorporating additional predictors improved the AUC to 0.865. The SINS demonstrated reasonable predictive performance for SRE within one month of the initial visit. Incorporating additional factors improved prediction accuracy. The study emphasizes the need for a comprehensive clinical prediction model for SRE in metastatic spinal tumors.

Too much of a good thing? Hand hygiene and the long-term course of contamination-related obsessive-compulsive symptoms.

Increased hygiene behavior may be a factor in the development of contamination-related obsessive-compulsive symptoms (C-OCS). We aimed at investigating (1) the course of C-OCS over 1 year after the start of the COVID-19 pandemic and (2) the effects of changes in hand hygiene (i.e., duration and frequency of handwashing) and related distress regulation on the long-term course of C-OCS. In a longitudinal study, we assessed 1,220 individuals from the German general population at the start of the COVID-19 pandemic (t1), 3 months later (t2), and 12 months later (t3). Pre-pandemic data were available in a subsample from 2014 (n = 430). A decrease in C-OCS over the first year of the pandemic emerged with a small effect size. Thirty-six percent of the participants scored above the clinical cut-off score at t1, 31% at t2, and 27% at t3. In 2014, only 11% scored above the clinical cut-off score. Hierarchical regression showed that C-OCS at t1 was the strongest predictor of a long-term increase in C-OCS. With small effect sizes, change in the duration (not frequency) of handwashing from t1 to t2, as well as the distress-reducing effect of handwashing served as additional predictors. Implications for information on hand hygiene guidelines are discussed.

Self-perceived stigma in Parkinson’s Disease in an online sample: Comparison with in-person sample, role of anxiety, and relative utility of four measures of stigma perception

Objective Persons with Parkinson’s disease (PwPD) experience motor and non-motor symptoms that may elicit stigmatization. We investigated whether online assessment would replicate in-person findings of younger age and depression as predictors of stigma perception. We further assessed the predictive value of anxiety, and compared predictors across four stigma measures. Methods The online study (n = 347), like the earlier in-person study (n = 362), used the Parkinson’s Disease Questionnaire stigma subscale (PDQ-39stigma). It also assessed anxiety and added the Stigma Scale for Chronic Illness (SSCI), Stigmatization Scale, and Mental Health Consumers’ Experience of Stigma Scale. We correlated stigma perception scores with demographic/clinical characteristics and conducted hierarchical regression and mediation analyses. Results Online and in-person predictors of stigma perception with the PDQ-39stigma included younger age (men) and depression (men, women). Depression mediated the relation between stigma perception and motor experiences of daily living (EDLs). In the online sample, when anxiety was added, it predicted stigma perception (PDQ-39stigma, SSCI) and mediated the relation between stigma and both motor and non-motor EDLs (PDQ-39stigma). For all four stigma-perception scales, younger age predicted scores. Multiple additional predictors of PDQ-39stigma and SSCI scores suggest their utility relative to the other two scales. Conclusions: Younger age and depression predicted self-perceived stigma in online and in-person samples, indicating the cross-modal utility of the measure, PDQ-39stigma. In the online sample, anxiety also predicted stigma perception per the PDQ-39stigma and SSCI. We recommend both measures and note that treating depression and anxiety may be important especially in younger PwPD to reduce self-perceived stigma.

Exploring predictors of STEM aspirations from a STEM capital perspective

ABSTRACT Background The concept of science, technology, engineering, and mathematics (STEM) capital can serve as a framework for understanding how various resources contribute to aspiration formation in STEM fields. However, to date, it remains unclear what factors should be included in STEM capital and how they may help explain why students do or do not aspire to STEM careers. Purpose This study aimed to validate the instruments and explore the predictive effect of various factors, including STEM capital and other non-STEM specific cultural capital factors, on students’ STEM aspirations while comparing these variables among primary, junior secondary, and senior secondary levels. Sample A stratified sample of students (N = 3,991) from the upper-primary to senior-secondary level in Hong Kong participated in the study. Design and methods An online survey investigation was conducted for data collection. Exploratory and confirmatory factor analyses were performed to validate the instruments before ANOVA, correlation analysis, and regression analysis were performed. Results The elementary students had significantly greater scores on the STEM capital variables than did the students at the junior and senior secondary levels. Gender, age, parental school involvement and expectations, informal STEM participation, positive views of professionals, and self-concept in mathematics positively predicted STEM aspirations, while having a parent/guardian with a STEM career negatively predicted students’ aspirations. In addition, the results showed that having STEM books at home and self-concept in information technology were additional predictors at some educational levels. The explored factors can explain approximately 30% of the variance in students’ STEM aspirations. Conclusion Senior students’ STEM capital factors exhibit lower levels compared to their younger peers. The developed, adapted, and translated instruments are valid for measuring the factors composing STEM capital, where some cultural and STEM capital factors significantly explain variations in students’ STEM aspirations. The mechanism of the negative effect of parental STEM occupations and the implications of the current study are also discussed.

Predicting Burnout, Well-Being, and Posttraumatic Growth in Correctional Officers

Correctional officers work in a stressful environment and are exposed to elevated levels of critical incidents. Such exposure can lead to negative psychological outcomes like burnout. However, positive psychological experiences including well-being and posttraumatic growth are also possible under such adverse conditions. Therefore, the purpose of this study was to explore predictors of burnout, well-being, and posttraumatic growth in a sample of correctional officers ( N = 142). The results of multiple regression analyses indicated that age, workplace adversity, and resilience were significant predictors of correctional officer burnout. A sense of workplace belongingness and the use of adaptive coping strategies were significant positive predictors of well-being and posttraumatic growth. Trait resilience and the receipt of social support were additional significant positive predictors of well-being. These results highlight the importance of individual, interpersonal, and organizational factors in promoting positive health outcomes, preventing negative health outcomes, and providing avenues for staff support.

Incidence of mental disorders in soldiers deployed to Afghanistan who have or have not experienced a life-threatening military incident-a quasi-experimental cohort study.

There is very good international research on deployment-related mental disorders in military personnel. The incidence rates show a very wide range. A new strategy is therefore proposed in order to achieve better standardization and thus better comparability of the studies. In addition to a non-deployed comparison group, we propose to compare deployed soldiers with and without critical military incidents during the deployment. This additional distinction makes it possible to differentiate between the influencing variables of actual threat and general deployment stress. N = 358 male combat soldiers deployed to Afghanistan were included in the study. Clinical interviews were conducted several days before deployment and after deployment. Of them, n = 80 soldiers suffered a life-threatening military incident during deployment, whereas 278 soldiers did not. Odds ratios (OR) were calculated for the groups with and without critical military incidents and the new onset for PTSD, anxiety disorders and depressive disorders. When comparing both groups, we found significantly higher 1-year incidence rates in the group with critical military incidents: 6.4% vs. 1.1% (OR 6.2) for post-traumatic stress disorder (PTSD); 7.0% vs. 1.1% (OR 6.5) for depression; and 15.9% vs. 2.8% (OR 6.6) for anxiety disorders. The 1-year incidence rate of mental multimorbidity (PTSD with anxiety or depression) was 4.8% vs. 0.4% (OR 12.0). These results indicate that life-threatening military incidents during military deployment are important to mental health. As the different threat levels of the various missions are taken into account, additional predictors could be determined more precisely in further research.

Financial toxicity among patients undergoing resectional surgery for inflammatory bowel disease in the United States.

Financial toxicity describes the financial burden and distress that patients experience due to medical treatment. Financial toxicity has yet to be characterized among patients with inflammatory bowel disease (IBD) undergoing surgical management of their disease. This study investigated the risk of financial toxicity associated with undergoing surgery for IBD. This study used a retrospective analysis using the National Inpatient Sample from 2015 to 2019. Adult patients who underwent IBD-related surgery were identified using the International Classification of Diseases (10th Revision) diagnostic and procedure codes and stratified into privately insured and uninsured groups. The primary outcome was risk of financial toxicity, defined as hospital admission charges that constituted 40% or more of patient's post-subsistence income. Secondary outcomes included total hospital admission cost and predictors of financial toxicity. The analytical cohort consisted of 6412 privately insured and 3694 uninsured patients. Overall median hospital charges were $21 628 (interquartile range $14 758-$35 386). Risk of financial toxicity was 86.5% among uninsured patients and 0% among insured patients. Predictors of financial toxicity included emergency admission, being in the lowest residential income quartile and having ulcerative colitis (compared to Crohn's disease). Additional predictors were being of Black race or male sex. Financial toxicity is a serious consequence of IBD-related surgery among uninsured patients. Given the pervasive nature of this consequence, future steps to support uninsured patients receiving surgery, in particular emergency surgery, related to their IBD are needed to protect this group from financial risk.

Mapping Potential Malaria Vector Larval Habitats for Larval Source Management in Western Kenya: Introduction to Multimodel Ensembling Approaches.

Identification and mapping of larval sources are a prerequisite for effective planning and implementing mosquito larval source management (LSM). Ensemble modeling is increasingly used for prediction modeling, but it lacks standard procedures. We proposed a detailed framework to predict potential malaria vector larval habitats by using multimodel ensemble modeling, which includes selection of models, ensembling method, and predictors, evaluation of variable importance, prediction of potential larval habitats, and assessment of prediction uncertainty. The models were built and validated based on multisite, multiyear field observations and climatic/environmental variables. Model performance was tested using independent field observations. Overall, we found that the ensembled model predicted larval habitats with about 20% more accuracy than the average of the individual models ensembled. Key larval habitat predictors in western Kenya were elevation, geomorphon class, and precipitation for the 2 months prior. Additional predictors may be required to increase the predictive accuracy of the larva-positive habitats. This is the first study to provide a detailed framework for the process of multimodel ensemble modeling for malaria vector habitats. Mapping of potential habitats will be helpful in LSM planning.

Factors Associated with Intention to Use Telerehabilitation for Children with Special Needs: A Cross-Sectional Study.

Background: Children with special health care needs (CSHCN) require long-term and ongoing rehabilitation interventions supporting their development. Telerehabilitation can provide continuous rehabilitation services for CSHCN. However, few studies have explored the intention of CSHCN and their caregivers to use telerehabilitation and its impact on them. Objective: The objective of this study was to identify factors that influence the intention to use telerehabilitation among CSHCN and their caregivers. Methods: This study was a cross-sectional study. Based on the unified theory of acceptance and use of technology, extended with additional predictors (trust and perceived risk [PR]), this study developed a research model and proposed 10 hypotheses. A structured questionnaire was distributed to 176 caregivers. Data were analyzed and research hypotheses were tested using partial least squares structural equation modeling to better understand the factors influencing the use of telerehabilitation. Results: A total of 164 valid questionnaires were collected. CSHCN and their caregivers were overall satisfied with this telerehabilitation medical service. The results of the structural model analysis indicated that social influence (SI), facilitating conditions (FC), and trust had significant effects on behavioral intention (BI) to use telerehabilitation, while the paths between performance expectancy (PE), effort expectancy (EE), and PR and BI were not significant. PE, EE, and SI had a significant effect on trust. Moreover, EE and SI had indirect effects on BI, with trust as the mediator. Conclusions: The results indicated that SI, FC, and trust are significant factors influencing CSHCN and their caregivers' use of telerehabilitation. Trust is also an important mediator for the intention and highly influenced by PE, EE, and SI.

Gender differences in pain perception among burning mouth syndrome patients: a cross-sectional study of 242 men and 242 women

Several orofacial painful conditions are influenced by gender-related factors, but no studies are available with regard to Burning Mouth Syndrome (BMS). The present study aimed at investigating gender differences among BMS patients and their influence on pain perception. 242 BMS males (BMSm) and 242 BMS females (BMSf) matched for age were consecutively enrolled. Sociodemographic and clinical characteristics were recorded and the numeric rating scale (NRS), the Total Pain Rating Index (T-PRI), the Hamilton rating scale for anxiety and depression (HAM-A, HAM-D), the Pittsburgh sleep quality index (PSQI) and the Epworth sleepiness scale (ESS) were administered. The BMSm presented statistically significant higher levels of education and rate of employment compared to the BMSf (p-values: 0.001**). Moreover, the BMSm were greater consumers of alcohol and had a higher BMI than the BMSf (p-values: < 0.001**, 0.034*). With respect to systemic comorbidities, cardiovascular diseases were statistically more prevalent among the BMSm, while hypothyroidism was more frequent in the BMSf (p-vales: < 0.001**). No differences were noted between the two groups in terms of oral symptoms and in the median scores of NRS, T-PRI, HAM-A, HAM-D, PSQI and ESS. Interestingly, the multivariate regression analysis revealed that, while anxiety, high BMI, poor sleep and high level of T-PRI were correlated to the intensity of pain (NRS) in both groups, low education was additional predictor of pain in BMSf. Further, depression, alcohol and intensity of pain were factors positively associated to the quality of pain (T-PRI) in the BMSm, whereas low education, non-married status and NRS were correlated to the T-PRI, in the BMSf. Surprisingly, smoking was inversely correlated to the intensity of pain and quality of pain respectively in BMSf and BMSm. Sociodemographic and risk factors were found to differently influence pain perception in BMSm and BMSf. Therefore, clinicians should take into account gender differences in the assessment of BMS patients to better tailor the overall pain management.

Complexity of Arctic Ocean water isotope (δ18O, δ2H) spatial and temporal patterns revealed with machine learning

The stable isotope compositions of water (δ18O, δ2H, deuterium-excess) are important tracers that help illuminate the changing Arctic water cycle and how Arctic-sourced water can influence lower latitudes. We present simultaneous boundary layer water vapor and ocean water isotope data that were measured continuously in the western Arctic Ocean. Sea surface water isotopes varied between the shallower continental Chukchi Shelf and the deeper Chukchi Borderlands to the north. The Chukchi Borderlands surface waters were less saline than the offshore Chukchi Shelf, as the Borderlands are influenced by greater sea ice cover and contribution of sea ice melt to surface freshwater. This greater contribution of sea ice melt resulted in lower deuterium-excess (δ2H − 8*δ18O) in surface water values in the deeper Chukchi Borderlands than on the shallower Chukchi Shelf. Additionally, the sea ice melt contributions to freshwater were less prominent than river runoff, but freshwater from both sources decreased substantially below 70 m depth in the Chukchi Borderlands. Our observed water isotope values provided the foundation for producing water isotope maps (isoscapes) based on remote sensing and machine learning which incorporate parameters that can influence ocean circulation and thus water isotopes (e.g., salinity, sea surface temperature, water depth). These isoscapes suggest spatial complexity in the distribution of stable water isotopes in the Arctic, including sharp gradients in the distribution of the isotopes in seawater that were studied. These isoscapes can be improved in future iterations, for example, with the availability of more spatially continuous, remotely sensed oceanic variables or continuous ship-based measurements to use as additional predictors. As a result, the generation of these isoscapes could become a useful tool for understanding the past, present, and future Arctic water cycle in the context of the global hydrologic cycle.

The relationship between sales growth, profitability, and tax avoidance

The study aims to examine the intricate interplay between sales growth, profitability, and tax avoidance strategies adopted by firms. Through an analysis of a diverse dataset spanning multiple industries and regions, this study investigates how sales growth influences a firm’s marketing approach to tax avoidance and its subsequent impact on profitability. The sample is Jordanian industrial firms listed on the Amman Stock Exchange for the study period between 2010 and 2020. Four critical variables used in the dataset are tax avoidance, return on assets, sales, and size. It employs a mixed-methods approach, including quantitative regression analysis and qualitative assessments of corporate tax strategies. The study results reveal a strong negative relationship between ROA and tax avoidance; for every unit increase in ROA, tax avoidance decreases by 0.198 units. Sales, however, do not exhibit a statistically significant association with tax avoidance. Firm size is an additional predictor with a marginally significant direct link with tax avoidance (β = 0.042, p = 0.049). This study highlights the central role of profitability in shaping tax avoidance strategies, with larger firms marginally more inclined toward tax planning.

PM2.5 Is Insufficient to Explain Personal PAH Exposure.

To understand how chemical exposure can impact health, researchers need tools that capture the complexities of personal chemical exposure. In practice, fine particulate matter (PM2.5) air quality index (AQI) data from outdoor stationary monitors and Hazard Mapping System (HMS) smoke density data from satellites are often used as proxies for personal chemical exposure, but do not capture total chemical exposure. Silicone wristbands can quantify more individualized exposure data than stationary air monitors or smoke satellites. However, it is not understood how these proxy measurements compare to chemical data measured from wristbands. In this study, participants wore daily wristbands, carried a phone that recorded locations, and answered daily questionnaires for a 7-day period in multiple seasons. We gathered publicly available daily PM2.5 AQI data and HMS data. We analyzed wristbands for 94 organic chemicals, including 53 polycyclic aromatic hydrocarbons. Wristband chemical detections and concentrations, behavioral variables (e.g., time spent indoors), and environmental conditions (e.g., PM2.5 AQI) significantly differed between seasons. Machine learning models were fit to predict personal chemical exposure using PM2.5 AQI only, HMS only, and a multivariate feature set including PM2.5 AQI, HMS, and other environmental and behavioral information. On average, the multivariate models increased predictive accuracy by approximately 70% compared to either the AQI model or the HMS model for all chemicals modeled. This study provides evidence that PM2.5 AQI data alone or HMS data alone is insufficient to explain personal chemical exposures. Our results identify additional key predictors of personal chemical exposure.

The influence of the stimulus level used to prescribe nonlinear frequency compression on speech perception.

Nonlinear frequency compression (NFC) is a signal processing technique designed to lower high frequency inaudible sounds for a listener to a lower frequency that is audible. Because the maximum frequency that is audible to a listener with hearing loss will vary with the input speech level, the input level used to set nonlinear frequency compression could impact speech recognition. The purpose of this study was to determine the influence of the input level used to set nonlinear frequency compression on nonsense syllable recognition. Nonsense syllable recognition was measured for three NFC fitting condition (i.e., with nonlinear frequency compression set based on speech input levels of 50-, 60-, and 70-dB SPL, respectively), as well as without nonlinear frequency compression (restricted bandwidth condition). Twenty-three adults (ages 42-80 years old) with hearing loss. Data were collected, monaurally, using a hearing aid simulator. The start frequency and frequency compression ratios were set based on the SoundRecover Fitting Assistant. Speech stimuli were 657 consonant-vowel-consonant nonwords presented at 50, 60, and 70 dB SPL and mixed with steady noise (6 dB SNR) and scored based on entire word, initial consonant, vowel, and final consonant. Linear mixed effects examined the effects of NFC fitting condition , presentation level, and scoring method on percent correct recognition. Additional predictor variables of start frequency and frequency-compression ratio were examined. Nonsense syllable recognition increased as presentation level increased. Nonsense syllable recognition for all presentation levels was highest when nonlinear frequency compression was set based on the 70 dB SPL input level and decreased significantly when set based on the 60- and 50-dB SPL inputs. Relative to consonant recognition, there was a greater reduction in vowel recognition. Nonsense syllable recognition between NFC fitting conditions improved with increases in the start frequency, where higher start frequencies led to better nonsense word recognition. Nonsense syllable recognition was highest when setting nonlinear frequency compression based on a 70 dB SPL presentation level and suggest that a high presentation level should be used to determine nonlinear frequency compression parameters for an individual patient.

Strengthening Quality Measurement to Predict Success for Total Knee Arthroplasty: Results from a Nationally Representative Total Knee Arthroplasty Cohort.

When performed well on appropriate patients, total knee arthroplasty (TKA) can dramatically improve quality of life. Patient-reported outcome measures (PROMs) are increasingly used to measure outcome following TKA. Accurate prediction of improvement in PROMs after TKA potentially plays an important role in judging the surgical quality of the health-care institutions as well as informing preoperative shared decision-making. Starting in 2027, the U.S. Centers for Medicare & Medicaid Services (CMS) will begin mandating PROM reporting to assess the quality of TKAs. Using data from a national cohort of patients undergoing primary unilateral TKA, we developed an original model that closely followed a CMS-proposed measure to predict success, defined as achieving substantial clinical benefit, specifically at least a 20-point improvement on the Knee injury and Osteoarthritis Outcome Score, Joint Arthroplasty (KOOS, JR) at 1 year, and an enhanced model with just 1 additional predictor: the baseline KOOS, JR. We evaluated each model's performance using the area under the receiver operator characteristic curve (AUC) and the ratio of observed to expected (model-predicted) outcomes (O:E ratio). We studied 5,958 patients with a mean age of 67 years; 63% were women, 93% were White, and 87% were overweight or obese. Adding the baseline KOOS, JR improved the AUC from 0.58 to 0.73. Ninety-four percent of those in the top decile of predicted probability of success under the enhanced model achieved success, compared with 34% in its bottom decile. Analogous numbers for the original model were less discriminating: 77% compared with 57%. Only the enhanced model predicted success accurately across the spectrum of baseline scores. The findings were virtually identical when we replicated these analyses on only patients ≥65 years of age. Adding a baseline knee-specific PROM score to a quality measurement model in a nationally representative cohort dramatically improved its predictive power, eliminating ceiling and floor effects and mispredictions for readily identifiable patient subgroups. The enhanced model neither favors nor discourages care for those with greater knee dysfunction and requires no new data collection. Prognostic Level II . See Instructions for Authors for a complete description of levels of evidence.

P702 Long term outcomes following de-escalation of dose-intensified ustekinumab in patients with Crohn’s disease

Abstract Background Data on outcomes following de-escalation of dose-intensified ustekinumab (UST) in Crohn’s disease (CD) have not been reported. This retrospective cohort study aimed to evaluate the failure rates 6, 12, and 24 months after de-escalation from dose-intensified UST to standard dose UST and identify predictors of failure. Methods Single centre, retrospective study of consecutive CD patients undergoing de-escalation of dose-intensified UST (90mg 4-weekly) to standard dosing (90mg 8-weekly). De-escalation and post de-escalation decisions were informed by protocolised 6-monthly assessment using Harvey-Bradshaw Index, C-reactive protein (CRP), faecal calprotectin (FCP), drug level and intestinal ultrasound. Failure was defined by re-escalation of UST, corticosteroids, switch out of class, or IBD-related hospitalisation or surgery. Success was defined by continued standard UST dosing. Categorical variables were compared using Fisher-exact and continuous variables using Mann-Whitney U tests between groups. Results 14 patients underwent de-escalation from April 2020 to March 2023. The median age was 41 years, disease duration 15 years, and duration on dose-intensified UST 34 months. 43% received IV reinduction at time of escalation, 86% had previous exposure to advanced therapies, of which 43% were dose-intensified. 36% were on an immunomodulator (IMM) at de-escalation. In the 6 months prior to de-escalation, the median CRP was 3.5mg/L, FCP 96mg/g, and 91% were in sonographic remission. 5/14 (36%) failed de-escalation at 6 months and 9/14 (64%) failed by 12 months. Of those with 24 months follow up, 9/12 (75%) failed de-escalation. Median time to failure was 8 months (IQR 4.5-13). All patients who failed underwent re-escalation and 2 required surgery. UST drug levels reduced from 3.6 to 1.9mg/mL 6 months post de-escalation. Re-escalation successfully recaptured response in 7/9 (78%). A greater proportion of patients with successful de-escalation at 12 months received concomitant IMM compared to those that failed (80% vs. 11%, respectively; p = 0.02). There were no other significant differences in clinical or disease characteristics between those with failure vs. success at 6, 12, or 24 months, although numbers were small (Table 1). Conclusion One-third of patients failed de-escalation of dose-intensified UST at 6 months, two-thirds failed at 12 months and three-quarters by 24 months. Patients considered for a trial of de-escalation need close, objective monitoring as most failure occurs early, and re-escalation is successful in the majority. Concomitant IMM may reduce failure rates and should be considered. Further studies are required to confirm these findings and identify additional predictors of de-escalation failure.

Clinical and Genomic Predictors of Adverse Events in Newly Diagnosed Glioblastoma.

Adverse clinical events cause significant morbidity in patients with GBM (GBM). We examined whether genomic alterations were associated with AE (AE) in patients with GBM. We identified adults with histologically confirmed IDH-wild-type GBM with targeted next-generation sequencing (OncoPanel) at Dana Farber Cancer Institute from 2013 to 2019. Seizure at presentation, lymphopenia, thromboembolic events, pseudoprogression, and early progression (within 6 months of diagnosis) were identified as AE. The biologic function of genetic variants was categorized as loss-of-function (LoF), no change in function, or gain-of-function (GoF) using a somatic tumor mutation knowledge base (OncoKB) and consensus protein function predictions. Associations between functional genomic alterations and AE were examined using univariate logistic regressions and multivariable regressions adjusted for additional clinical predictors. Our study included 470 patients diagnosed with GBM who met the study criteria. We focused on 105 genes that had sequencing data available for ≥ 90% of the patients and were altered in ≥10% of the cohort. Following false-discovery rate (FDR) correction and multivariable adjustment, the TP53, RB1, IGF1R, and DIS3 LoF alterations were associated with lower odds of seizures, while EGFR, SMARCA4, GNA11, BRD4, and TCF3 GoF and SETD2 LoF alterations were associated with higher odds of seizures. For all other AE of interest, no significant associations were found with genomic alterations following FDR correction. Genomic biomarkers based on functional variant analysis of a routine clinical panel may help identify AE in GBM, particularly seizures. Identifying these risk factors could improve the management of patients through better supportive care and consideration of prophylactic therapies.

Risk Factors of Non-Invasive Ventilation Failure in COPD Patients Presenting with Acute Exacerbation

Background: Non-invasive ventilation (NIV) is the first-line management for acute exacerbation of COPD (AECOPD), but some patients don’t improve and need invasive ventilation, leading to high mortality. We conducted a study to determine risk factors associated with NIV outcomes in these patients. Identifying predictive parameters of NIV failure could help timely intervention and prevent mortality. Methods: A Quasi Single Arm study was conducted at a tertiary care Hospital, in Karachi, from July to December 2022. We studied 170 COPD patients admitted to Medicine Department and Medical ICU with acute respiratory failure, among those 170 patients 80 were male and 90 were female, aged above 40 and below 80 years. Results: Among 170 AECOPD patients studied, 38% experienced NIV failure, while 61% had NIV success. In the NIV failure group, 38.46% of patients died in hospital. Most factors like quadrant infiltrate, weak cough reflex, low consciousness level, more requirements of oxygen, low pH, more respiratory rate, and positive blood cultures (p-value &lt;0.001) were significantly associated with NIV failure and mortality, while others with no significant association still contributed towards NIV failure, like co-morbidities. Out of the 66 patients with NIV failure, 56% experienced immediate failure, 33% had early NIV failure, and 11% had late NIV failure. Conclusion: Most identified risk factors significantly predicted NIV failure, suggesting they may serve as useful early indicators to guide intervention. Even non-significant factors still exhibited some association with NIV failure. Further research exploring additional predictors could optimize NIV outcomes and reduce mortality from AECOPD.

A novel sea surface pCO2-product for the global coastal ocean resolving trends over 1982–2020

Abstract. In recent years, advancements in machine learning based interpolation methods have enabled the production of high-resolution maps of sea surface partial pressure of CO2 (pCO2) derived from observations extracted from databases such as the Surface Ocean CO2 Atlas (SOCAT). These pCO2-products now allow quantifying the oceanic air–sea CO2 exchange based on observations. However, most of them do not yet explicitly include the coastal ocean. Instead, they simply extend the open ocean values onto the nearshore shallow waters, or their spatial resolution is simply so coarse that they do not accurately capture the highly heterogeneous spatiotemporal pCO2 dynamics of coastal zones. Until today, only one global pCO2-product has been specifically designed for the coastal ocean (Laruelle et al., 2017). This product, however, has shortcomings because it only provides a climatology covering a relatively short period (1998–2015), thus hindering its application to the evaluation of the interannual variability, decadal changes and the long-term trends of the coastal air–sea CO2 exchange, a temporal evolution that is still poorly understood and highly debated. Here we aim at closing this knowledge gap and update the coastal product of Laruelle et al. (2017) to investigate the longest global monthly time series available for the coastal ocean from 1982 to 2020. The method remains based on a two-step Self-Organizing Maps and Feed-Forward Network method adapted for coastal regions, but we include additional environmental predictors and use a larger pool of training and validation data with ∼18 million direct observations extracted from the latest release of the SOCAT database. Our study reveals that the coastal ocean has been acting as an atmospheric CO2 sink of −0.40 Pg C yr−1 (−0.18 Pg C yr−1 with a narrower coastal domain) on average since 1982, and the intensity of this sink has increased at a rate of 0.06 Pg C yr−1 decade−1 (0.02 Pg C yr−1 decade−1 with a narrower coastal domain) over time. Our results also show that the temporal changes in the air–sea pCO2 gradient plays a significant role in the long-term evolution of the coastal CO2 sink, along with wind speed and sea-ice coverage changes that can also play an important role in some regions, particularly at high latitudes. This new reconstructed coastal pCO2-product (https://doi.org/10.25921/4sde-p068; Roobaert et al., 2023) allows us to establish regional carbon budgets requiring high-resolution coastal flux estimates and provides new constraints for closing the global carbon cycle.