Akaike's information criterion in generalized estimating equations

Prognostic significance of different lymph node staging systems in patients with resectable, node-positive, stage III, non-small cell lung cancer: Identifying the optimal classification for enhanced prognostic stratification

PURPOSE

The traditional N staging system fails to adequately stratify the prognostic heterogeneity in patients with resectable node-positive, stage III, non-small cell lung cancer, particularly in those undergoing postoperative radiotherapy. The purpose of this study was to determine the optimal nodal status classification strategy: the traditional N classification, the positive lymph nodes-based classification, or the lymph node ratio-based classification. Furthermore, we aimed to identify the population that would benefit the most from postoperative radiotherapy using the best classification strategy.

METHODS

We analysed data from 5028 patients with resectable node-positive, stage III, non-small cell lung cancer sourced from the Surveillance, Epidemiology, and End Results (SEER) database. Various lymph node staging systems, including traditional N staging, classification based on the number of positive lymph nodes, and classification based on the lymph node ratio, were incorporated into the prognostic prediction model. Survival outcomes were evaluated using lung cancer-specific survival and Kaplan-Meier analysis.

RESULTS

The lymph node ratio classification model demonstrated the highest prognostic prediction performance, with the highest C-index, area under the curve, and the lowest Akaike information criterion, followed by the positive lymph nodes classification model and the traditional N staging model. Prognostic stratification analysis based on different lymph node staging systems indicated that a lymph node ratio greater than 0.28 and more than three positive lymph nodes were associated with a high-risk prognosis. Furthermore, postoperative radiotherapy significantly improved lung cancer-specific survival in overall resectable node-positive, stage III, non-small cell lung cancer (P<0.05). Notably, survival curve analysis revealed the most pronounced differences in lung cancer-specific survival between the groups receiving postoperative radiotherapy or not in the high-risk prognosis group, particularly among those with a lymph node ratio greater than 0.28, and more than three positive lymph nodes, and lastly the traditional N staging model.

CONCLUSION

In patients with resectable node-positive, stage III, non-small cell lung cancer, classification according to the lymph node ratio, followed by the positive lymph nodes, may offer superior prognostic prediction capabilities compared to the traditional N staging in addressing prognostic heterogeneity. Additionally, identifying a high-risk prognosis with a lymph node ratio greater than 0.28 appears to be the most effective criterion for selecting candidates who would benefit from postoperative radiotherapy.

Household tobacco expenditure and associated characteristics during substantial regular tobacco tax increases: analysis from a nationally representative longitudinal study in Australia from 2006 to 2022

OBJECTIVE

We investigated household tobacco expenditure by socioeconomic status and examined the associated factors in Australia from 2006 to 2022, incorporating a period of substantial regular tobacco tax increases (2010-2020).  METHODS: We conducted a repeated cross-sectional analysis of household data from the Household, Income, and Labour Dynamics in Australia survey to examine differences in household tobacco expenditure by Socio-Economic Indexes for Areas (SEIFA). Descriptive analyses were performed for all households and those with any tobacco expenditure, with dollar values adjusted for inflation to 2022. Linear regression with generalised estimating equations (GEE) assessed associations between different individual-level factors and household tobacco expenditure.

RESULTS

Between 2006 and 2022, smoking prevalence decreased by 5.6% points. Overall average annual household tobacco expenditure decreased by $7.8 ($980.5 to $972.7), while households that purchased tobacco increased spending by $1092.2 ($3839.5 to $4931.7). In 2022, households in the most disadvantaged areas allocated more than double the proportion of their disposable income to tobacco (6.3%) compared with households in the most advantaged areas (2.7%). GEE analysis showed a dose-response relationship between SEIFA category and household tobacco expenditure, with the most disadvantaged households spending an additional $245.5 (95% CI: $193.7-$297.2) compared with the most advantaged households. The additional tobacco-related expenditure for people who currently smoked compared with those who never smoked was $1500.5 (95% CI: $1424-$1577).

CONCLUSION

Disadvantaged households allocated more of their income to tobacco and spent more on tobacco overall than advantaged households, reflecting higher smoking prevalence. Additional non-price-related measures are needed to address these inequities.

Transition to retirement impact on food consumption frequency: results from a longitudinal analysis within the Survey of Health, Ageing and Retirement in Europe (SHARE)

OBJECTIVES

It has been suggested that major life course transitions, such as retirement, can greatly impact lifestyles. However, the evidence is scant and inconclusive, especially with reference to the effects on dietary habits. We investigated the long-term effects of retirement on the frequency of food consumption using data from the Survey of Health, Ageing, and Retirement in Europe (SHARE).

DESIGN AND PARTICIPANTS

We used data from a SHARE-based cohort, including European individuals from 28 countries aged 50 and older who were employed at baseline and retired during follow-up time (2004-2020).

MEASUREMENTS

Dietary habits were assessed through self-reported frequencies of consumption for fruit and vegetables, dairy products, meat and fish, legumes and eggs. A dietary score (dichotomised as ≥5 or <5) was also estimated. Generalised estimating equation models calculated relative risks (RR) of daily (for fruit, vegetables and dairy products) and 3-6 times per week (for meat, fish, legumes and eggs) consumptions before and after retirement, adjusting for selected variables.

RESULTS

The cohort included 8,998 individuals with a mean follow-up time of 9 years. Baseline daily consumption frequencies were 73.7% for fruit and vegetables and 65.9% for dairy products, while 3-6 times per week frequencies were 39.8% for meat and fish and 26.1% for legumes and eggs. An increase in 3-6 times a week consumption of meat and fish (RR 1.07, 95% CI 1.01-1.13) and legumes and eggs (RR 1.09, 95% CI 1.01-1.17) was observed 10 or more years post-retirement. Daily consumption of fruit and vegetables, and dairy products remained stable. The RR of a dietary score ≥5 post-retirement was 1.11 (95% CI 1.06-1.16, 10 or more years after).

CONCLUSIONS

Retirement positively appears to influence overall dietary habits, particularly by improving the consumption frequency of protein-rich foods, while the stability in fruit, vegetables, and dairy consumption suggests that well-established habits persist despite life transitions.

DCE-MRI radiomics of primary breast lesions combined with ipsilateral axillary lymph nodes for predicting efficacy of NAT

BACKGROUND

This study aimed to assess the predictive value of radiomic analysis derived from primary lesions and ipsilateral axillary suspicious lymph nodes (SLN) on dynamic contrast-enhanced MRI (DCE-MRI) for evaluating the response to neoadjuvant therapy (NAT) in early high-risk and advanced breast cancer (BC) patients.

METHODS

A retrospective analysis was conducted on 222 BC patients (192 from Center I and 30 from Center II) who underwent NAT. Radiomic features were extracted from the primary lesion (intra- and peritumoral regions) and ipsilateral axillary SLN to develop radiomic signatures (RS-primary, RS-SLN). An integrated signature (RS-Com) combined features from both regions. Feature selection was performed using correlation analysis, the Mann-Whitney U test, and least absolute shrinkage and selection operator (LASSO) regression. A diagnostic nomogram was constructed by integrating RS-Com with key clinical factors. Model performance was evaluated using receiver operating characteristic (ROC) and decision curve analysis (DCA).

RESULTS

RS-Com demonstrated superior predictive performance compared to RS-primary and RS-SLN alone. The DeLong test confirmed that axillary SLNs provide supplementary information to the primary lesion. Among clinical factors, N staging and HER2 status were significant contributors. The nomogram, integrating RS-Com, N staging, and HER2 status, achieved the highest performance in the training (AUC: 0.926), validation (AUC: 0.868), and test (AUC: 0.839) cohorts, outperforming both the clinical models and RS-Com alone.

CONCLUSION

Radiomic features from axillary SLNs offer valuable supplementary information for predicting NAT response in BC patients. The proposed nomogram, incorporating radiomics and clinical factors, provides a robust tool for individualized treatment planning.

Does inclusion of neighborhood variables improve clinical risk prediction for advanced prostate cancer in Black and White men?

INTRODUCTION

Black men are diagnosed with high-grade prostate cancer (PCa; Gleason sum ≥7) at greater rates than White men. This persistent disparity has led to mortality rates among Black men that are twice the rate of White men. Risk prediction tools can aid clinical decision making for PCa screening, biopsy, and treatment. However, research has not integrated neighborhood-level risk factors that are associated with rates of high-grade PCa. This study sought to determine whether inclusion of neighborhood-level variables can improve prediction of high-grade PCa over the existing Prostate Cancer Prevention Trial (PCPT) calculator.

METHODS

Existing PCa cases from 2005 to 2017 were ascertained from urology, radiation, and medical oncology clinics at Fox Chase Cancer Center/Temple University Health System (FCCC/TUHS). Existing databases from patient medical records, biosamples, pathology, and neighborhood data from the U.S. census were linked via geocodes. Informed by prior studies that selected social environmental variables, a series of logistic regression models were completed to predict the probability of high-grade PCa on prespecified sets of variables from the PCPT.

RESULTS

Our best fitting, multilevel model included PCPT variables (i.e., PSA, digital rectal exam, age, race, prior biopsy, family history) as well as insurance status, neighborhood-level poverty, residence in a high risk PCa cluster, and % of Employed Men in Protective Service Occupations. However, the AUC for this model (0.673) was only marginally improved from the initial model of only PCPT variables (0.671). Further, in separate analyses by race (White, Black) the % of Employed Men in Protective Service Occupations was only significant among White men.

DISCUSSION

Study findings demonstrate the potential for neighborhood variables to enhance current risk prediction models and identify interaction effects revealing differences across subgroups, such as race. The lack of significant associations between neighborhood variables and Black men highlight the complexity of systemic racism and neighborhood-level variables on PCa outcomes.

A path forward on online misinformation mitigation based on current user behavior

Social media misinformation has become a serious societal problem, and recent research has focused on developing effective ways to counter its harmful impacts. This work investigates user-level countermeasures, or how individuals who see the misinformation respond to it directly, possibly to help stop its spread in their online communities. Using a registered report design, we conducted an online survey of 1010 American social media users who use social media at least once weekly. Participants were asked how they respond and think others should respond to misinformation they unintentionally post or see posted by others, and how their responses differ depending on their relationship with the person who posted that misinformation. Overall, the results revealed a difference between respondents' beliefs and actions: participants reported expecting others to exert more effort when responding to misinformation than the level of effort they themselves reported. Additionally, on average, participants were more likely to say they intervened when misinformation was posted by someone close to them rather than by an acquaintance or a stranger. Understanding current behavioral patterns and public opinion can inform efforts to elicit public participation in countering misinformation and increase the effectiveness of platform-level countermeasures.Protocol registration: The stage 1 protocol for this Registered Report was accepted in principle on March 13th, 2024. The protocol, as accepted by the journal, can be found at: https://figshare.com/s/683b1e7c2f2bad96f604 .

Conventional Cardiopulmonary Resuscitation Versus Extracorporeal Membrane Oxygenation-Assisted CPR in Children: A Retrospective Analysis of Outcomes and Factors Associated with Conversion from the Former to the Latter

BACKGROUND/OBJECTIVES

Conventional cardiopulmonary resuscitation (CCPR) has been the foundational resuscitation approach for decades. Where CCPR is unsuccessful, extracorporeal membrane oxygenation-assisted CPR (ECPR) may improve outcomes. Predicting failure of CCPR and immediate need for ECPR is difficult, and data are lacking. In this retrospective analysis, we analysed both factors that are associated with conversion from CCPR to ECPR and survival outcomes for each event.

METHODS

Patients having a CPR event that occurred in the PICU between 2016 and 2022 were included. Pre-CPR-event clinical and laboratory data were collected. We recorded whether CPR was converted to ECPR and documented patient outcomes.

RESULTS

201 CPR events occurred in 164 children, with 45 events converted from CCPR to ECPR. Time to ROSC or time to ECMO flow was (median [IQR]) 2 (1.5) min for CCPR events and 37 (21.60) min for ECPR events. The maximum pre-CPR-event lactate values were 1.8 mmol/L for CCPR and 4.5 mmol/L for ECPR events. Respiratory arrest preceded 35.3% of CCPR and 4.4% of ECPR events. PICU mortality was 27.8% for CCPR and 50% for ECPR events. Most deaths occurred because of withdrawal of life-sustaining treatments. In a multivariable analysis, cardiac surgical diagnosis, pre-CPR-event lactate, as well as duration of CPR were associated with conversion from CCPR to ECPR.

CONCLUSIONS

Our study demonstrates that pre-CPR-event lactate concentrations and duration of arrest should alert clinicians to a high likelihood of needing ECPR, while a preceding respiratory arrest may indicate a low likelihood. Mortality post CCPR is significant, mainly due to overall illness severity rather than the consequences of the CPR event.

Continuity of care in a pandemic: an observational study in GP-centred healthcare in Germany

BACKGROUND

Continuity of care (COC) refers to the sustained quality of healthcare over time and is a central element of effective general practice. High levels of COC have been associated with improved health outcomes, including reduced risks of hospitalisation. Previous research demonstrated that participation in Germany's "general practitioner-centred healthcare" (GPCHC) programme, designed to strengthen general practice care, led to higher COC. Furthermore, higher COC was independently linked to decreased risks of hospitalisations, including rehospitalisations and avoidable admissions. This study aimed to investigate whether the benefits of COC for GPCHC patients persisted in 2020, the first year of the COVID-19 pandemic, compared with 2019, the year preceding the pandemic.

METHODS

An observational study was conducted in Germany using data from a health insurance database. The study included two patient cohorts: those enrolled in the GPCHC programme (n=1 049 910) and those not enrolled in GPCHC (n=537 759) for both 2019 and 2020. The analysis compared three measures of COC-Usual Provider Index, Herfindahl Index and Sequential Continuity Index-adjusted for patient characteristics. Longitudinal multivariable regression models were employed to evaluate differences between the cohorts and assess the impact of the COVID-19 pandemic on COC outcomes.

RESULTS

For GPCHC patients, COC in general practice was relevantly and significantly higher with respect to the three COC measures in 2019. We could observe the same advantage for GPCHC patients in 2020. Interestingly, for the SCI index, indicating the fraction of sequential encounter pairs at which the same provider is seen, we could observe that COC was even more advantageous for GPCHC patients in 2020 in comparison to 2019. Finally, we could observe that higher COC in 2019 was independently associated with decreased healthcare utilisation of the inpatient care sector in 2020.

CONCLUSIONS

In a pandemic period in which healthcare is faced with new challenges, both for patients and healthcare providers, GPCHC was still associated with higher COC. The GPCHC programme and its contents are obviously better up to the requirements of the COC even in such a situation of pandemic-induced discontinuity.

A Novel Method to Predict Carbohydrate and Energy Expenditure During Endurance Exercise Using Measures of Training Load

BACKGROUND

Sports nutrition guidelines recommend carbohydrate (CHO) intake be individualized to the athlete and modulated according to changes in training load. However, there are limited methods to assess CHO utilization during training sessions.

OBJECTIVES

We aimed to (1) quantify bivariate relationships between both CHO and overall energy expenditure (EE) during exercise and commonly used, non-invasive measures of training load across sessions of varying duration and intensity and (2) build and evaluate prediction models to estimate CHO utilization and EE with the same training load measures and easily quantified individual factors.

METHODS

This study was undertaken in two parts: a primary study, where participants performed four different laboratory-based cycle training sessions, and a validation study where different participants performed a single laboratory-based training session using one of three exercise modalities (cycling, running, or kayaking). The primary study included 15 cyclists (five female; maximal oxygen consumption [ V ˙ O2max], 51.9 ± 7.2 mL/kg/min), the validation study included 21 cyclists (seven female; V ˙ O2max 53.5 ± 11.0 mL/kg/min), 20 runners (six female; V ˙ O2max 57.5 ± 7.2 mL/kg/min), and 18 kayakers (five female; V ˙ O2max 45.6 ± 4.8 mL/kg/min). Training sessions were quantified using six training load metrics: two using heart rate, three using power, and one using perceived exertion. Carbohydrate use and EE were determined separately for aerobic (gas exchange) and anaerobic (net lactate accumulation, body mass, and O2 lactate equivalent method) energy systems and summed. Repeated-measures correlations were used to examine relationships between training load and both CHO utilization and EE. General estimating equations were used to model CHO utilization and EE, using training load alongside measures of fitness and sex. Models were built in the primary study and tested in the validation study. Model performance is reported as the coefficient of determination (R2) and mean absolute error, with measures of calibration used for model evaluation and for sport-specific model re-calibration.

RESULTS

Very-large to near-perfect within-subject correlations (r = 0.76-0.96) were evident between all training load metrics and both CHO utilization and EE. In the primary study, all models explained a large amount of variance (R2 = 0.77-0.96) and displayed good accuracy (mean absolute error; CHO = 16-21 g [10-14%], EE = 53-82 kcal [7-11%]). In the validation study, the mean absolute error ranged from 16-50 g [15-45%] for CHO models to 53-182 kcal [9-31%] for EE models. The calibrated mean absolute error ranged from 9-20 g [8-18%] for CHO models to 36-72 kcal [6-12%] for EE models.

CONCLUSIONS

At the individual level, there are strong linear relationships between all measures of training load and both CHO utilization and EE during cycling. When combined with other measures of fitness, EE and CHO utilization during cycling can be estimated accurately. These models can be applied in running and kayaking when used with a calibration adjustment.

Alternative Formulations of Job Strain and Sleep Disturbances: A Longitudinal Study in the United States

BACKGROUND

Sleep disturbances are a major public health concern in the United States, leading to adverse health outcomes. In the working population, job strain has been identified as an important risk factor for sleep disturbances, but evidence from the United States remained limited. This study aimed to examine longitudinal associations between job strain and sleep disturbances in the United States, with a focus on the alternative formulations of job strain.

METHODS

A total of 1721 participants were drawn from two waves of the Midlife in the United States (MIDUS) study, with an average 9-year follow-up period. Job strain was measured using Karasek's Job-Demand-Control model and operationalized in six formulations: standard quadrant, simplified quadrant, linear, quotient, logarithm quotient, and quartile based on quotient. Generalized Estimating Equations were used to estimate longitudinal associations of alternative formulations of job strain at baseline with sleep disturbances across follow-up. Corrected Quasi-likelihood Information Criterion (QICu) was used to assess the goodness of fit.

RESULTS

All approaches showed that higher job strain at baseline was significantly associated with an increase in sleep disturbances across follow-up. QICu scores indicated that continuous Demand-Control formulations (linear, quotient, logarithm quotient) had better model performance of 4602.66, 4604.28, and 4601.99, respectively. The logarithm quotient showed the best fit.

CONCLUSIONS

Our findings imply the importance of early workplace interventions in reducing job strain to improve sleep hygiene. They further show that the continuous formulations quantifying job strain were more consistent and robust, which provides suggestions for future workplace health research in the United States.

Incentivizing adherence to pre-exposure prophylaxis for HIV prevention: a randomized pilot trial among male sex workers in Mexico

Low adherence to preventative medications against life-long health conditions is a major contributor to global morbidity and mortality. We implemented a pilot randomized controlled trial in Mexico to measure the extent to which conditional economic incentives help male sex workers increase their adherence to pre-exposure prophylaxis (PrEP) for HIV prevention. We followed n = 110 male sex workers over 6 months. At each quarterly visit (at months 0, 3, and 6), all workers received a $10 transport reimbursement, a free 3-month PrEP supply, and completed socio-behavioral surveys. The primary outcome was an objective biomarker of medication adherence based on tenofovir (TFV) drug concentration levels in hair collected at each visit. Individuals randomized to the intervention received incentives based on a grading system as a function of PrEP adherence: those with high (> 0.043 ng/mg TFV concentration), medium (0.011 to 0.042 ng/mg), or low (< 0.011 ng/mg) adherence received $20, $10, or $0, respectively. Six-month pooled effects of incentives on PrEP adherence were analyzed using population-averaged gamma generalized estimating equation models. We estimated heterogeneous treatment effects by sex worker characteristics. The incentive intervention led to a 28.7% increase in hair antiretroviral concentration levels over 6 months consistent with increased PrEP adherence (p = 0.05). The effect of incentives on PrEP adherence was greater for male sex workers who were street-based (vs. internet) workers (p < 0.10). These pilot findings suggest that modest conditional economic incentives could be effective, at scale, for improving PrEP adherence among male sex workers, and should be tested in larger implementation trials. ClinicalTrials.gov Identifier: NCT03674983.

Variable selection in modelling clustered data via within-cluster resampling

In many biomedical applications, there is a need to build risk-adjustment models based on clustered data. However, methods for variable selection that are applicable to clustered discrete data settings with a large number of candidate variables and potentially large cluster sizes are lacking. We develop a new variable selection approach that combines within-cluster resampling techniques with penalized likelihood methods to select variables for high-dimensional clustered data. We derive an upper bound on the expected number of falsely selected variables, demonstrate the oracle properties of the proposed method, and evaluate the finite sample performance of the method through extensive simulations. We illustrate the proposed approach using a colon surgical site infection data set consisting of 39,468 individuals from 149 hospitals to build risk-adjustment models that account for both the main effects of various risk factors and their two-way interactions.

Traumatic Encephalopathy Syndrome: Head Impact Exposure and Blood Biomarkers in Professional Combat Athletes

OBJECTIVE

This study aimed to (1) determine whether there was an association between a diagnosis of traumatic encephalopathy syndrome (TES) and changes in three specific serum biomarkers, and (2) determine head impact exposure thresholds among both TES+ and TES- groups.

SETTING

Data were collected from Cleveland Clinic's Professional Athletes Brain Health Study (PABHS).

PARTICIPANTS

This study included 192 professional combat athletes, 35 years of age and older. Athletes must be actively fighting or retired with a minimum of 10 professional fights over their careers.

DESIGN/INTERVENTION

This was a retrospective observational study of the PABHS longitudinal cohort.

MAIN MEASURES

The generalized linear model with the generalized estimating equation for repeated measurements was used to compare various biomarkers between both active and retired TES- and TES+ groups.

RESULTS

The odds ratio for TES diagnosis was 5.44 (95% CI = 2.48, 11.94; P < .0001) among active fighters and 10.75 (95% CI = 3.52, 32.85; P < .0001) among retired fighters, indicating the odds for a TES diagnosis were over 5 times greater for active fighters with every fight completed at or beyond 30 professional fights. Retired fighters had 10 times greater odds of TES diagnosis with every fight completed at or beyond 15 professional fights. Likewise, the odds of a TES diagnosis were 2.0% (95% CI = 0.3, 3.1; P = 0.0039) greater with each pg/mL increase of glial fibrillary acidic protein (GFAP). No relationship was observed between a TES diagnosis and neurofilament light chain or P-tau231.

CONCLUSION

This study provides preliminary evidence that progressively elevated levels of the GFAP blood biomarker increase the odds of a TES diagnosis among retired professional fighters. Further evaluation is required to improve clarity and understanding of the relationship between progressive changes in the GFAP blood biomarker and a TES diagnosis, specifically evaluating the duration of chronicity and exposure thresholds.

A rapid decline in gender bias relates to changes in subsistence practices over demographic changes in a formerly matrilineal community

This research examines dynamics of kinship systems, emphasizing changes in gender-biased inheritance and social interaction within a formerly matrilineal community. Using demographic data over 70-year of lifespan from 17 Tibetan villages, we observe a significant shift within the predominantly matrilineal inheritance structure: a once-prevalent preference for females in older cohorts has now gone in recent generations. We explore two possible explanations: that this is driven by changes in subsistence system or by changes in sibling configuration. Our investigation reveals that a change from agriculture to non-traditional economy with more market integration marks a pivot from matrilineal to non-unilineal inheritance systems. Moreover, results from economic games conducted in two distinct survey periods (2015 and 2021) indicate that high donations for females in 2015 have become unbiased in 2021. These findings provide concrete evidence of shifts in gender preference both at the level of familial resource allocation and broader societal interactions.

Comparative Feeding and Defecation Behaviors of Trypanosoma cruzi-Infected and Uninfected Triatomines (Hemiptera: Reduviidae) from the Americas

Triatomines are vectors of Trypanosoma cruzi (Kinetoplastida: Trypanosomatidae), the agent of Chagas disease. Stercorarian transmission occurs when infectious parasites are passed in insect feces to vertebrates through the biting wound or mucosa. Defecating on hosts during or shortly after blood feeding is, therefore, critical for transmission, and delayed triatomine defecation behavior has been posited to contribute to a low incidence of human Chagas disease in the U.S. We allowed nymphal T. cruzi-infected and uninfected Triatoma gerstaeckeri (Stål, 1859) and Triatoma sanguisuga (LeConte, 1855) to interact with restrained guinea pigs and measured insect feeding and defecation events; South American Rhodnius prolixus (Stål, 1859; Latin America) served as a comparison group. In 148 trials, 40.0% of insects fed, of which 71.2% defecated. Compared to R. prolixus, T. gerstaeckeri had >9 times higher odds of feeding, and T. sanguisuga fed longer. Observations of defecation while feeding occurred across all three species. The post-feeding defecation interval (PFDI) of R. prolixus was significantly shorter (4.54 ± 2.46 min) than that of T. gerstaeckeri (9.75 ± 2.52 min) and T. sanguisuga (20.69 ± 8.98 min). Furthermore, the PFDI was shorter for TcI-infected insects compared to uninfected insects. Triatoma gerstaeckeri and T. sanguisuga are capable of stercorarian transmission, although the calculated metrics suggest they are less efficient vectors than R. prolixus.

Full title: prevalence and risk factors of overweight in Beijing infants basing generalized estimating equation: a longitudinal study

BACKGROUND

The prevalence of childhood overweight and obesity in China has been rapidly increasing in recent years. The purposes of this study were to investigate the prevalence of infant overweight in Beijing and to explore the influencing factors using a generalized estimating equation (GEE) model.

METHODS

This is a birth cohort study from January 2022 to December 2022 in Beijing, involving 2,008 newborns from local residents. Four times of follow-up visits were conducted at 2, 5, 8, and 12 months of age for physical measurements and health information collection. Multiple exposures were considered, including demographic characteristics of infants, maternal pregnancy information, feeding pattern and outdoor activities of infants. The GEE model was utilized to identify influencing factors for infant overweight while adjusting for potential confounders.

RESULTS

The prevalence of overweight for 2-, 5-, 8-, and 12-month-old infants were 14.4%, 21.6%, 24.4%, and 24.2%, respectively. Among the influencing factors, irregular exercise during pregnancy (OR = 1.190, P = 0.045), mixed feeding or artificial feeding (non-exclusive breastfeeding) (OR = 1.233, P = 0.025), high birth weight (OR = 1.468, P < 0.001), and high pre-pregnancy body mass index (BMI) (OR = 2.113, P = 0.005) were positively correlated with infant overweight. Conversely, weight gain ≤ 15.0 kg during pregnancy (OR = 0.778, P = 0.016), high birth length (OR = 0.990, P = 0.003), and longer duration of outdoor activity for infants (OR = 0.764, P < 0.001) were negatively correlated with infant overweight.

CONCLUSIONS

Our findings suggest certain factors are associated with infant overweight risk. Further research is required before making causal inferences and formulating preventive strategies for infant overweight.

Noninvasive Radiomics Approach Predicts Dopamine Agonists Treatment Response in Patients with Prolactinoma: A Multicenter Study

RATIONALE AND OBJECTIVES

The first-line treatment for prolactinoma is drug therapy with dopamine agonists (DAs). However, some patients with resistance to DA treatment should prioritize surgical treatment. Therefore, it is crucial to accurately identify the drug treatment response of prolactinoma before treatment. The present study was performed to determine the DA treatment response of prolactinoma using a clinical radiomic model that incorporated radiomic and clinical features before treatment.

MATERIALS AND METHODS

In total, 255 patients diagnosed with prolactinoma were retrospectively divided to training and validation sets. An elastic net algorithm was used to screen the radiomic features, and a fusion radiomic model was established. A clinical radiomic model was then constructed to integrate the fusion radiomic model and the most important clinical features through multivariate logistic regression analysis for individual prediction. The calibration, discrimination, and clinical applicability of the established models were evaluated. 60 patients with prolactinoma from other centers were used to validate the performance of the constructed model.

RESULTS

The fusion radiomic model was constructed from three significant radiomic features, and the area under the curve in the training set and validation set was 0.930 and 0.910, respectively. The clinical radiomic model was constructed using the radiomic model and three clinical features. The model exhibited good recognition and calibration abilities as evidenced by its area under the curve of 0.96, 0.92, and 0.92 in the training, validation, and external multicenter validation set, respectively. Analysis of the decision curve showed that the fusion radiomic model and clinical radiomic model had good clinical application value for DA treatment response prediction in patients with prolactinoma.

CONCLUSION

Our clinical radiomic model demonstrated high sensitivity and excellent performance in predicting DA treatment response in prolactinoma. This model holds promise for the noninvasive development of individualized diagnosis and treatment strategies for patients with prolactinoma.

Wellbeing and quality of life among parents of individuals with Fontan physiology

PURPOSE

To examine global and health-related quality of life (QOL) among parents of individuals with Fontan physiology and determine associations with sociodemographic, parent and child-related health, psychological, and relational factors.

METHODS

Parents participating in the Australian and New Zealand Fontan Registry (ANZFR) QOL Study (N = 151, Parent Mean age = 47.9 ± 10.2 years, age range: 31.6-79.6 years, 66% women; child Mean age = 16.3 ± 8.8, age range: 6.9-48.7 years, 40% female) completed a series of validated measures. Health-related QOL was assessed using the PedsQL 4.0 Core Generic Scales for adults and global QOL was assessed using a visual analogue scale (0-10).

RESULTS

Most parents (81%) reported good global QOL (≥ 6), consistent with broader population trends. Nearly one-third of parents (28%) reported at-risk health-related QOL (based on total PedsQL scores) with physical functioning most affected (44%). Psychological factors, including psychological stress and sense of coherence, emerged as the strongest correlates of global and health-related QOL, explaining an additional 16 to 30% of the variance (using marginal R2). Final models explained 35 and 57% and of the variance in global and health-related QOL, respectively (marginal R2). Relational factors, including perceived social support and family functioning contributed minimally when analyzed alongside psychological variables.

CONCLUSION

While parents of individuals with Fontan physiology report good global QOL, challenges in health-related QOL exist. We identified key psychological, sociodemographic, and health-related factors associated with parental QOL outcomes. These data may aid early identification of physical and psychosocial difficulties and guide targeted health resource allocation for this population.

On GEE for Mean-Variance-Correlation Models: Variance Estimation and Model Selection

Generalized estimating equations (GEE) are of great importance in analyzing clustered data without full specification of multivariate distributions. A recent approach by Luo and Pan jointly models the mean, variance, and correlation coefficients of clustered data through three sets of regressions. We note that it represents a specific case of the more general estimating equations proposed by Yan and Fine which further allow the variance to depend on the mean through a variance function. In certain scenarios, the proposed variance estimators for the variance and correlation parameters in Luo and Pan may face challenges due to the subtle dependence induced by the nested structure of the estimating equations. We characterize specific model settings where their variance estimation approach may encounter limitations and illustrate how the variance estimators in Yan and Fine can correctly account for such dependencies. In addition, we introduce a novel model selection criterion that enables the simultaneous selection of the mean-scale-correlation model. The sandwich variance estimator and the proposed model selection criterion are tested by several simulation studies and real data analysis, which validate its effectiveness in variance estimation and model selection. Our work also extends the R package geepack with the flexibility to apply different working covariance matrices for the variance and correlation structures.

Group cohesion and alliance predict cognitive-behavioral group treatment outcomes for youth with anxiety disorders

Knowledge about how to enhance group cognitive behavioral therapy (GCBT) outcomes is needed. In a randomized controlled effectiveness trial, we examined group cohesion (the bond between group members) and the alliance (the client-clinician bond) as predictors of GCBT outcomes. The sample was 88 youth (M age 11.7 years, SD = 2.1; 54.5% girls; 90.7% White) with anxiety disorders. Observers rated group cohesion and alliance in 32 sessions from 16 groups. We examined early group cohesion and alliance (r = .50, p < .001) and group cohesion and alliance change from early to late in treatment in relation to outcomes using generalized estimation equations accounting for nesting within groups (ICCs .31 to .55). The outcomes were diagnostic recovery, clinical severity, and parent- and youth-reported anxiety symptoms, each at post-treatment, 12-months, and 4-years follow-up. There were more significant associations with 4-years follow-up than earlier outcomes. Clinical severity and parent-reported anxiety symptoms were more frequently predicted than diagnostic recovery. Clinician- and parent-reported outcomes were far more frequently significantly predicted by cohesion and alliance than youth-rated outcomes. We conclude that group cohesion and alliance are related but distinct variables, both associated with some GCBT outcomes for as long as 4 years after treatment.

Prevalence, Determinants, and Trends in the Experience and Perpetration of Intimate Partner Violence Among a Cohort of Gay, Bisexual, and Other Men Who Have Sex with Men in Montréal, Toronto, and Vancouver, Canada (2017-2022)

Purpose: Longitudinal data on the experience and perpetration of intimate partner violence (IPV) among gay, bisexual, and other men who have sex with men (GBM) are limited. We estimated the prevalence of past 6-month (P6M) physical and/or sexual IPV (hereafter IPV) experience and perpetration, identified their determinants, and assessed temporal trends, including the impact of the coronavirus disease (COVID)-19 pandemic. Methods: We used data from the Engage Cohort Study (2017-2022) of GBM recruited using respondent-driven sampling in Montréal, Toronto, and Vancouver. Adjusted prevalence ratios (aPRs) for determinants and self-reported P6M IPV were estimated using generalized estimating equations, accounting for attrition (inverse probability of censoring weights) and relevant covariates. Longitudinal trends of IPV were also assessed. Results: Between 2017 and 2022, 1455 partnered GBM (median age 32 years, 82% gay, and 71% White) had at least one follow-up visit. At baseline, 31% of participants experienced IPV in their lifetime and 17% reported ever perpetrating IPV. During follow-up, IPV experience was more common (6%, 95% confidence interval [CI]: 5%-7%) than perpetration (4%, 95% CI: 3%-5%). Factors associated with P6M IPV experience included prior IPV experience (aPR: 2.68, 95% CI: 1.76-4.08), lower education (aPR: 2.31, 95% CI: 1.32-4.04), and substance use (injection aPR: 5.05, 95% CI: 2.54-10.05, non-injection aPR: 1.68, 95% CI: 1.00-2.82). Similar factors were associated with IPV perpetration. IPV was stable over time; periods of COVID-19 restrictions were not associated with IPV changes in this cohort. Conclusion: Prevalence of IPV was high among GBM. Determinants related to marginalization were associated with an increased risk of IPV. Interventions should address these determinants to reduce IPV and improve health.

Knowledge of Medical Interpretation Rights Among Individuals With Non-English Language Preference: A Cross-Sectional Study

OBJECTIVES

We aimed to identify demographic, acculturation, and health care factors associated with self-reported knowledge of the right to medical interpretation among individuals with non-English language preference (NELP) in California.

BACKGROUND

NELP is a significant social determinant of health contributing to adverse health outcomes through barriers in communication, limited health literacy, and biases in care delivery. The ability of patients with NELP to self-advocate for interpreter services is crucial yet hindered by various factors, including a lack of knowledge about their rights.

METHODS

This cross-sectional study used pooled data from the California Health Interview Survey from 2012 to 2021. Subjects were 12,219 adults with NELP, representing 2,516,157 individuals in California. The primary outcome was self-reported knowledge of the right to medical interpretation. Covariates included demographic, acculturation, and health care factors.

RESULTS

Of the participants, 28.6% were unaware of their rights to interpretation. Married females had higher odds of knowledge, while recent immigrants (≤5 y in the United States), those with mixed language households, no doctor visits in the past year, no insurance, and self-reported poorer health had lower odds. Sociodemographic factors like age, race, ethnicity, education, and geography showed no significant association.

CONCLUSIONS

Nearly one-third of individuals with NELP lack awareness of their right to medical interpretation. Factors such as recent immigration, poor health, and limited health care contact are significant barriers. In addition to system and policy level changes, interventions targeting these vulnerable groups are needed to improve health equity and empower patients to use interpreter services.

Association between a large change between the minimum and maximum monthly values of solar insolation and a history of suicide attempts in bipolar I disorder

BACKGROUND

The rate of suicide attempts by patients with bipolar disorder is high. In addition to patient and country specific factors, environmental factors may contribute to suicidal behavior. Sunlight has multiple diverse impacts on human physiology and behavior. Solar insolation is defined as the electromagnetic energy from the sun striking a surface area on earth. We previously found that a large change in solar insolation between the minimum and maximum monthly values was associated with an increased risk of suicide attempts in patients with bipolar I disorder.

METHODS

The association between solar insolation and a history of suicide attempts in bipolar disorder was again investigated using an international database with 15% more data and more sites at diverse locations and countries.

RESULTS

Data were available from 5641 patients with bipolar I disorder living at a wide range of latitudes in 41 countries in both hemispheres. A large change in solar insolation between the minimum and maximum monthly values was associated with a history of suicide attempts in patients with bipolar I disorder, a replication of our prior analysis. The estimated model also associated state sponsored religion in the onset country, female gender, a history of alcohol or substance abuse, and being part of a younger birth cohort with a history of suicide attempts.

CONCLUSIONS

A large change between the minimum and maximum monthly values of solar insolation was associated with a history of suicide attempts in bipolar I disorder, replicating our prior research. Physicians should be aware that daylight has wide ranging physiological and psychiatric impacts, and that living with large changes in solar insolation may be associated with an increased suicide risk.

Quantification of household food waste in Greece to establish the 2021 national baseline and methodological implications

The aim of this study was to present the national-level quantification of household food waste in Greece for 2021, in alignment with the legal framework of the European Union (EU) for measuring and reporting food waste. An online diary survey was conducted in spring 2021, utilizing pre-tested semi-structured food waste logs. Descriptive statistics were employed to analyze food waste levels and generalized estimating equations (GEE) were performed to assess the influence of diary duration on food waste levels. The final representative sample consisted of 1,133 households. At the national level, the average per-capita annual total food waste generation rate was 86.5 ± 64.5 kg. The predominant share of food waste (47 %) was inedible plant-derived parts, reflecting underlying consumption patterns, whereas 40 % was once-edible food parts. Particularly, vegetables, fruits, and bakery products were the most discarded once-edible food items. Moreover, no statistically significant difference was found between food waste levels across the diary entries, with reporting periods varying from one day to one week. This study marks the first implementation of the EU legislation for household food waste measurement and reporting in Greece. Moreover, the study results indicate that the utilization of diaries with shorter reporting periods than one week, with a sufficiently large sample, may be an appropriate method for measuring nationwide levels, enhancing compliance while mitigating social desirability bias and reducing attrition. Future research should delve into the behaviors driving food waste, motives for prevention in different geographic and cultural contexts, and optimal diary reporting durations.

Interactions between blood lead (Pb) concentration, oxidative stress, cellular immune response and reproductive status in livestock from a mining area

Chronic exposure to lead (Pb) in livestock grazing in abandoned mining areas affects animal welfare and productivity, as well as represents a significant food safety risk. Here, we evaluate the physiological effects of Pb exposure in goats maintained under extensive farming conditions in a non-remediated mining area. We monitored blood, fecal, and milk Pb levels in two groups of goats, pregnant (n = 17) and lactating (n = 24), kept in different enclosures with high soil Pb concentrations (geometric means of 270 and 143 μg/g, respectively) in Sierra Madrona mining district (Spain). We also studied the influence of Pb exposure on the ability to mount a cellular immune response, and on oxidative stress and biochemical biomarkers measured in blood. Blood Pb concentration was higher in pregnant than in lactating goats, but this difference was not observed in fecal Pb concentration. Pb levels in feces and milk concentrations were correlated with those measured in blood, with 11% of milk samples showing Pb concentrations above the maximum level (ML) for Pb in raw milk established by the EU (0.02 μg/g wet weight). Animals with increased blood Pb levels showed reduced concentrations of retinol in plasma, but these Pb levels did not affect the cellular immune response. The stimulation of the cellular immune response in lactating goats was associated with an increase in blood Pb and calcium levels. The reproductive status and age of goats significantly affected several oxidative stress, antioxidants and plasma biochemistry variables. Goats grazing on soils contaminated by past Pb mining activities may be susceptible to detrimental health effects mediated by retinol deficiency. In view of the detected transfer of Pb through milk, special attention should be paid to the food safety of derived products (i.e. cheese).

Exploring the value of arterial spin labeling and six diffusion MRI models in differentiating solid benign and malignant renal tumors

OBJECTIVE

To explore the value of three-dimensional arterial spin labeling (ASL) and six diffusion magnetic resonance imaging (MRI) models in differentiating solid benign and malignant renal tumors.

METHODS

This retrospective study included 89 patients with renal tumors. All patients underwent ASL and ZOOMit diffusion-weighted imaging (DWI) examinations and were divided into three groups: clear cell renal cell carcinoma (ccRCC), non-ccRCC, and benign renal tumors (BRT). The mean and peak renal blood flow (RBFmean and RBFpeak) from ASL and fourteen diffusion parameters from mono-exponential DWI (Mono_DWI), intravoxel incoherent motion (IVIM), diffusion kurtosis imaging (DKI), stretched exponential model (SEM), fractional order calculus (FROC), and continuous-time random-walk (CTRW) model were analyzed. Binary logistic regression was used to determine the optimal parameter combinations. The diagnostic performance of various MRI-derived parameters and their combinations was compared.

RESULTS

Among the six diffusion models, the SEM model achieved the highest performance in differentiating ccRCC from non-ccRCC (area under the receiver operating characteristic curve [AUC] 0.880) and from BRT (AUC 0.891). IVIM model achieved the highest AUC (0.818) in differentiating non-ccRCC from BRT. Among all the MRI-derived parameters, RBFpeak combined with DKI_MK yielded the highest AUC (0.970) in differentiating ccRCC from non-ccRCC, and the combination of RBFpeak, SEM_DDC, and FROC_μ yielded the highest AUC (0.992) for differentiating ccRCC from BRT.

CONCLUSION

ASL and all diffusion models showed similar diagnostic performance in differentiating ccRCC from non-ccRCC or BRT, while the IVIM model performed better in distinguishing non-ccRCC from BRT. Combining ASL with diffusion models can provide additional value in predicting ccRCC.

RELEVANCE STATEMENT

Considering the increasing detection rate of incidental renal masses, accurate discrimination of benign and malignant renal tumors is crucial for decision-making. Combining ASL with diffusion MRI models offers a promising solution to this clinical issue.

KEY POINTS

All assessed models were effective for differentiating ccRCC from non-ccRCC or BRT. ASL and all diffusion models showed similar performance in differentiating ccRCC from non-ccRCC or BRT. Combining ASL with diffusion models significantly improved diagnostic efficacy in predicting ccRCC. IVIM model could better differentiate non-ccRCC from BRT.

Online Mindfulness-Based Intervention (eMBI) in management of dyspnea in patients with interstitial lung disease: A randomized clinical trial

RATIONALE

Dyspnea and cough are frequent symptoms in ILD patients. The management of these symptoms is challenging, and evidence-based therapies are lacking.

OBJECTIVES

To evaluate the effect of an online Mindfulness-Based Intervention (eMBI) on reducing dyspnea in patients affected by different ILDs.

METHODS

This study was a prospective, open-label, controlled trial that included patients ≥18 years and a modified Medical Research Council (mMRC) dyspnea scale score of ≥ 1. Patients were randomized into either the eMBI or the control group (CG) for 8 weeks. The primary outcome was the change in the dyspnea mMRC scale. The Leicester Cough Questionnaire (LCQ), King's Brief Interstitial Lung Disease (K-BILD) questionnaire, and Depression, Anxiety, and Stress Scale (DASS-21) were performed before and after the eight weeks. All analyses were conducted on an intention-to-treat basis. The study was registered at the Brazilian Registry of Clinical Trials (ReBEC), RBR-3s4mf9y.

RESULTS

24 patients in the eMBI and 25 in the CG completed the intervention. In the eMBI group, compared to the control group, there was a greater proportion of patients with a reduction in dyspnea according to the mMRC scale score (48.9 % versus, 15.4 %, p = 0.001). There was no significant difference between the groups in the LCQ (p = 0.666), or in the K-BILD (p = 0.108), depression (p = 0.08), or anxiety (p = 0.869 or stress (p = 0.789). No moderate or severe adverse events were observed in either group.

CONCLUSIONS

Eight weeks eMBI is a potentially viable and safe approach, that can help manage dyspnea in ILD patients.

A longitudinal pre-post study: An evaluation of the Department of the Air Force bundled occupational fall prevention efforts

INTRODUCTION

Fall injuries are the second leading cause of traumatic injury and death for all US workers and are a leading injury concern for the Department of the Air Force (DAF). Bundled interventions can improve the likelihood of injury reduction, especially in large, heterogeneous working populations. In 2013, the DAF implemented the "Air Force Fall Prevention Focus," a bundled intervention of prevention efforts designed to reduce occupational fall injury events among DAF members. The purpose of this study is to describe the burden and risk factors associated with fall injuries and evaluate the effectiveness of the Fall Prevention Focus in reducing the burden of fall injuries.

METHODS

The National Institute for Occupational Safety and Health (NIOSH) partnered with the US Air Force Safety Center (AFSEC) to examine the impact of the Fall Prevention Focus as a bundled intervention. Injury events included a narrative description of the injury event, demographics, work environment, job tasks, and other structured details. Descriptive statistics and pre-post longitudinal modeling were used to evaluate changes in fall injury rates.

RESULTS

The Fall Prevention Focus Implementation (2013-2018) resulted in an annual 10.4% (95% confidence interval [CI]: 8.5%, 12.2%) reduction, and a 6-year cumulative 48.3% (95% CI: 41.4%, 54.3%) reduction in fall injury event rates by 2018.

DISCUSSION

Safety in the DAF involves a comprehensive approach. Documenting the impact of the Fall Prevention Focus may help translate these findings to improve fall prevention efforts in other sectors of the military and high fall-risk industries in the private sector, such as construction.

Tushirikiane-4-Uthabiti (Supporting Each Other For Resilience): study protocol of a mental health, HIV self-testing and livelihoods randomised controlled trial for advancing HIV prevention outcomes among urban refugee youth in Kampala, Uganda

INTRODUCTION

Research with urban refugee youth in Uganda has documented co-occurring social (e.g., poverty) and health (e.g., depression) disparities associated with HIV vulnerabilities. Benefits of HIV self-testing (HIVST) in increasing HIV testing uptake among youth are well established, yet limited interventions have examined if combining HIVST with mental health promotion, or with mental health promotion alongside poverty reduction, is associated with greater improvements in HIV prevention and testing outcomes.

METHODS AND ANALYSIS

The aim is to evaluate the effectiveness of: (1) HIVST alone (standard of care); (2) mobile health (mHealth) and graphic medicine (comic) programme for mental health alongside HIVST; and (3) the combination of HIVST, a livelihoods programme, and mHealth mental health programme, in advancing the primary outcome of HIV testing uptake and secondary outcomes (HIV status knowledge, linkage to confirmatory testing and HIV care, HIV knowledge, consistent condom use, condom use self-efficacy, sexual risk) with urban refugee youth in Kampala, Uganda. A three-arm randomised controlled trial will be implemented from 8 April 2024 to 31 October 2024 with youth across five informal settlements in Kampala, grouped into three sites based on proximity, and randomised in a 1:1:1 design. Approximately 330 participants (110 per arm) are enrolled and data collection will occur at three time points (baseline enrolment, 3-month follow-up and 6-month follow-up).

ETHICS AND DISSEMINATION

The study received ethical approval from the University of Toronto (#37496), Mildmay Uganda Research Ethics Committee (#MUREC-2021-41) and Uganda National Council for Science & Technology (#SS1021ES). The trial is registered at ClinicalTrials.gov (NCT06270160). Study findings will produce new knowledge of the impacts of a mental health programme, and a combined mental health and livelihoods programme, on improving HIV prevention outcomes among urban refugee youth in Kampala. Findings will be shared in peer-reviewed publications, conference presentations and in community dissemination.

TRIAL REGISTRATION NUMBER

NCT06270160 (date of registration: 13 February 2024).

TRIAL SPONSOR

Dr. Carmen Logie, carmen.logie@utoronto.ca.

Impact of the active job openings-to-applicants ratio on the number of ambulance dispatches in Japan, 2003-2021: a longitudinal ecological study

OBJECTIVE

To examine the contribution of the active job openings-to-applicants ratio, a macroeconomic indicator, to the number of ambulance dispatches.

DESIGN

Longitudinal ecological study.

SETTING

Japan, between January 2003 and December 2021.

PARTICIPANTS

All ambulance dispatches.

PRIMARY AND SECONDARY OUTCOME MEASURES

The contribution of the active job openings-to-applicants ratio in a month, adjusted by the number of older people, mean temperature and total population, to the number of ambulance dispatches in that specific month was examined and the primary model was compared to the conventional model considering only the older population, mean temperature, and total population.

RESULTS

There were 108 724 969 ambulance dispatches during this period. The active job openings-to-applicants ratio was significantly associated with the number of ambulance dispatches (the increase rate of monthly ambulance dispatches for 1% rise in the active job openings-to-applicants ratio, 1.00082; 95% CI 1.00052 to 1.00112). Additionally, the primary model effectively demonstrated better fitness to the actual trend than the conventional model (the quasi-likelihood under the independence model criteria were -2 626 817 720 and -2 626 775 185, respectively).

CONCLUSIONS

The number of ambulance dispatches was correlated with the active job openings-to-applicants ratio. Macroeconomic perspectives may be needed to address the issue of increasing ambulance dispatches.

Influence of Antibiotic Exposure Intensity on the Risk of Clostridioides difficile Infection

BACKGROUND

Antibiotics are a strong risk factor for Clostridioides difficile infection (CDI), and CDI incidence is often measured as an important outcome metric for antimicrobial stewardship interventions aiming to reduce antibiotic use. However, risk of CDI from antibiotics varies by agent and dependent on the intensity (ie, spectrum and duration) of antibiotic therapy. Thus, the impact of stewardship interventions on CDI incidence is variable, and understanding this risk requires a more granular measure of intensity of therapy than traditionally used measures like days of therapy (DOT).

METHODS

We performed a retrospective cohort study to measure the independent association between intensity of antibiotic therapy, as measured by the antibiotic spectrum index (ASI), and hospital-associated CDI (HA-CDI) at a large academic medical center between January 2018 and March 2020. We constructed a marginal Poisson regression model to generate adjusted relative risks for a unit increase in ASI per antibiotic day.

RESULTS

We included 35 457 inpatient encounters in our cohort. Sixty-eight percent of patients received at least 1 antibiotic. We identified 128 HA-CDI cases, which corresponds to an incidence rate of 4.1 cases per 10 000 patient-days. After adjusting for known confounders, each additional unit increase in ASI per antibiotic day was associated with 1.09 times the risk of HA-CDI (relative risk = 1.09; 95% CI: 1.06-1.13).

CONCLUSIONS

The ASI was strongly associated with HA-CDI and could be a useful tool in evaluating the impact of antibiotic stewardship on HA-CDI rates, providing more granular information than the more commonly used DOT.

Influencing factors of effective lens position in patients with Marfan syndrome and ectopia lentis

AIMS

The aim of this study was to analyse the effective lens position (ELP) in patients with Marfan syndrome (MFS) and ectopia lentis (EL).

METHODS

Patients with MFS undergoing lens removal and primary intraocular lens (IOL) implantation were enrolled in the study. The back-calculated ELP was obtained with the vergence formula and compared with the theoretical ELPs. The back-calculated ELP and ELP error were evaluated among demographic and biometric parameters, including axial length (AL), corneal curvature radius (CCR) and white-to-white (WTW).

RESULTS

A total of 292 eyes from 200 patients were included. The back-calculated ELP was lower in patients undergoing scleral-fixated IOL than those receiving in-the-bag IOL implantation (4.54 (IQR 3.65-5.20) mm vs 4.98 (IQR 4.56-5.67) mm, p<0.001). The theoretical ELP of the SRK/T formula exhibited the highest accuracy, with no difference from the back-calculated ELP in patients undergoing in-the-bag IOL implantation (5.11 (IQR 4.83-5.65) mm vs 4.98 (IQR 4.56-5.67) mm, p=0.209). The ELP errors demonstrated significant correlations with refraction prediction error (PE): a 1 mm ELP error led to PE of 2.42D (AL<22 mm), 1.47D (22 mm≤AL<26 mm) and 0.54D (AL≥26 mm). Multivariate analysis revealed significant correlations of ELP with AL (b=0.43, p<0.001), CCR (b=-0.85, p<0.001) and WTW (b=0.41, p=0.004).

CONCLUSION

This study provides novel insights into the origin of PE in patients with MFS and EL and potentially refines existing formulas.

The novel developed and validated multiparametric MRI-based fusion radiomic and clinicoradiomic models predict the postoperative progression of primary skull base chordoma

Local progression of primary skull base chordoma (PSBC) is a sign of treatment failure. Predicting the postoperative progression of PSBC can aid in the development of individualized treatment plans to improve patients' progression-free survival (PFS) after surgery. This study aimed to develop a multiparametric MRI-based fusion radiomic model (FRM) and clinicoradiomic model (CRM) via radiomic and clinical analysis and to explore their validity in predicting postoperative progression in PSBC patients before surgery. In this retrospective study, a total of 129 patients with PSBC from our institution, including 57 patients with progression, were enrolled and randomized to the training set (TS) or the validation set (VS) at a 2:1 ratio. Radiomic features were extracted and dimensionally reduced from 3.0 T/axial T2-weighted imaging (T2WI), T1-weighted imaging (T1WI) and contrast-enhanced T1-weighted imaging (CE-T1WI) sequences for each patient, and the features were used for radiomic analysis. Univariate and multivariate Cox regression analyses were used to screen for key clinical factors. We constructed models on the basis of multivariate logistic regression analysis. Receiver operating characteristic (ROC) curve, calibration curve, and decision curve analyses were performed to evaluate the performance of the clinical model (CM), FRM and CRM. Through analysis, we found that blood supply was the only significantly different clinical factor in the CM. For the FRM, the area under the receiver operating characteristic curve (AUC) of the TS was 0.925, and the calibration curves were consistent across the TS. In the CRM, the AUC of the TS was 0.929, the calibration curve analysis was consistent for both the TS and the VS, and the DCA showed that the net benefit was greater at a threshold probability of > 0% for both the TS and the VS. Our proposed FRM can help clinicians better predict PSBC progression preoperatively, and the use of the CRM can lead to the development of more appropriate protocols to improve patients' PFS after surgery.

Can human brain connectivity explain verbal working memory?

The ability of humans to store spoken words in verbal working memory and build extensive vocabularies is believed to stem from evolutionary changes in cortical connectivity across primate species. However, the underlying neurobiological mechanisms remain unclear. Why can humans acquire vast vocabularies, while non-human primates cannot? This study addresses this question using brain-constrained neural networks that realize between-species differences in cortical connectivity. It investigates how these structural differences support the formation of neural representations for spoken words and the emergence of verbal working memory, crucial for human vocabulary building. We develop comparative models of frontotemporal and occipital cortices, reflecting human and non-human primate neuroanatomy. Using meanfield and spiking neural networks, we simulate auditory word recognition and examine verbal working memory function. The "human models", characterized by denser inter-area connectivity in core language areas, produced larger cell assemblies than the "monkey models", with specific topographies reflecting semantic properties of the represented words. Crucially, longer-lasting reverberant neural activity was observed in human versus monkey architectures, compatible with robust verbal working memory, a necessary condition for vocabulary building. Our findings offer insights into the structural basis of human-specific symbol learning and verbal working memory, shedding light on humans' unique capacity for large vocabulary acquisition.

Using Multilevel Models and Generalized Estimating Equation Models to Account for Clustering in Neurology Clinical Research

In clinical and health services research, clustered data (also known as data with a multilevel or hierarchical structure) are frequently encountered. For example, patients may be clustered or nested within hospitals. Understanding when data have a multilevel structure is important because clustering of individuals can induce a homogeneity in outcomes within clusters, so that, even after adjusting for measured covariates, outcomes for 2 individuals in the same cluster are more likely to be similar than outcomes for 2 individuals from different clusters. Using conventional statistical regression models to analyze clustered data can result in incorrect conclusions being drawn. In particular, estimated CIs may be artificially narrow, and significance levels may be artificially low. As a result, one may conclude that there is a statistically significant association when there is none. To avoid this problem, investigators should ensure that their analyses use techniques that account for clustering of data. Generalized linear models estimated using generalized estimating equation (GEE) methods and multilevel regression models (also known as hierarchical regression models, mixed-effects models, or random-effects models) are two such techniques. We provide an introduction to clustered or multilevel data and describe how GEE models or multilevel models can be used for the analysis of multilevel data.

Association between preterm birth and economic and educational outcomes in adulthood: A population-based matched cohort study

BACKGROUND AND OBJECTIVES

Preterm birth (PTB) affects ~10% of births worldwide; however, most literature focused on short-term clinical outcomes, with much less focus on long-term socioeconomic outcomes after PTB. We examined associations between PTB and individuals' income, employment, and educational outcomes during early adulthood.

METHODS

We conducted a population-level matched cohort study including all live births in Canada between 1990 and 1996, followed until 2018. Outcomes included Employment income per year in 2018 CAD and employment between ages 18 and 28 years, postsecondary education enrollment (18-22 years), and maximum educational attainment at age 22-27 years. Mean differences and risk ratios (RR) and differences (RD) were estimated using generalized estimating equation regression models for economic outcomes and multinomial logistic regression models for educational outcomes.

RESULTS

Of 2.4 million births, 7% were born preterm (0.3%, 0.6%, 0.8%, and 5.4% born extremely preterm (24-27 weeks), very preterm (28-31 weeks), moderately preterm (32-33 weeks), and late preterm (34-36 weeks) respectively). After matching on baseline characteristics (e.g., sex, province of birth, and parental demographics) and adjusting for age and period effects, preterm-born individuals, on average, had $958 CAD less employment income per year (95% CI: $854-$1062), 6% lower income per year, than term-born individuals, and were 2.13% less likely to be employed (1.98-2.29%). PTB was also negatively associated with university enrollment (RR 0.93 (0.91-0.94) and graduation with a university degree (RR 0.95 (0.94-0.97)). Mean income differences for those born 24-27 weeks were -$5,463 CAD per year (17% lower), and adjusted RR were 0.55 for university enrollment and graduation.

CONCLUSION

In this population-based study, preterm birth was associated with lower economic and educational achievements at least until the late twenties. The associations were stronger with decreasing GA at birth. Policymakers, clinicians, and parents should be aware that the socioeconomic impact of PTB is not limited to the early neonatal period but extends into adulthood.

Temporal and spatial variation patterns of chlorophyll a in marine ranching under global interannual events

Marine ecosystems are facing numerous environmental challenges due to global climate change. In response to these challenges, the establishment and growth of marine ranching has emerged as a pivotal solution. Chlorophyll a concentration (Chla) is recognized as a valuable indicator for the ecological assessment of marine ranching. This study focused on the spatiotemporal distribution of Chla and its response to environmental factors according to the dataset in the marine ranching area of Haizhou Bay (Lianyungang, Jiangsu, China) from 2003 to 2022. The results showed that Chla had a significant cycle of summer > spring > autumn and was distributed evenly in the central area of the marine ranching. During interannual changes, Chla patches were centered in the central region during 2014, 2015, and 2016. The Chla patches predominantly focused on the eastern area in 2018-2019, shifting to the western area in 2020-2021. The generalized additive model (GAM) indicated that salinity, depth, temperature, biological oxygen demand (BOD5) and SiO3--Si were the main environmental factors affecting Chla during spring, summer and autumn. However, during El Niño events, salinity, depth, temperature, BOD5 and transparency became the main environmental factors. We concluded that salinity, depth and temperature consistently played a crucial role in determining Chla under various climate conditions, and SiO3--Si and transparency will no longer be an environmental factor limiting Chla. In addition, The effect of interannual variability on upwelling and vertical mixing of water layers may potentially alter the spatial distribution pattern of Chla. These findings can offer ideas into predicting the variation of Chla in marine ranching under global interannual events in the future. Furthermore, this can contribute to the comprehensive assessment of ecological benefits and the in-depth construction of marine ranching. Ultimately, it can provide essential data and scientific references for offshore ecological environment assessment and ecosystem restoration.

Risk factors for the introduction of Salmonella spp. serogroups B and D into Dutch dairy herds

Salmonella spp. infections in animals are a concern due to their zoonotic nature, welfare effects and economic impact on the livestock industry. To enable targeted surveillance, it is important to identify risk factors for the introduction of Salmonella spp. in a herd. Since 2009, Dutch dairy processors require herds delivering milk to their plants to participate in a Salmonella programme. In this programme, bulk milk is tested three times a year (i.e. test rounds) by ELISA on presence of antibodies against Salmonella spp. serogroups B and D. Based on these bulk milk results we identified newly infected herds, and aimed to identify associated risk factors. Effects of putative risk factors for becoming newly infected were studied using a multivariable population average logistic regression (PA-GEE) model with binomial distribution. Per test round in 2019-2021, 0.85-4.10 % of the Dutch dairy herds at risk became newly infected, with large regional differences. Several risk factors for becoming newly infected in the context of the low herd-level prevalence were identified. The most evident risk factors that were identified were having at least one infected or recently recovered dairy herd within 500 m (OR = 2.67), on-farm presence of pigs (OR = 1.63), introduction of more than 2 cattle from other herds in the previous 12 months (OR = 1.17), being in an area with a relative soil moisture of >0.54 % (OR = 1.31), being located in an area with a high water surface area (>2 %; OR = 1.14) and a larger herd size (OR = 1.65). These results indicate that, in addition to introduction of cattle, local transmission plays an important role in the between-herd transmission of Salmonella spp. Information on risk factors for becoming newly infected based on regularly collected data, can be used to improve surveillance and to implement targeted control measures against salmonellosis.

Normative Values and Anthropometric Prediction Models for Lean Mass and Fat Mass in the Northeastern Thai Population

Background: Data on reference values for lean mass (LM) and fat mass (FM) in the Southeast Asian populations are currently lacking. Therefore, we aimed to estimate the normative values and generate anthropometric prediction models for LM and FM in the Thai population. Methods: Consecutive community-dwelling individuals aged 20-90 years were recruited from Srinagarind Hospital, Khon Kaen, Thailand, between 2010 and 2015. LM and FM were measured using dual energy X-ray absorptiometry. Age and sex stratified percentile of LM and FM were presented. Anthropometric prediction models for LM and FM were developed by using linear regression to generate competing models. Results: A total of 832 individuals (334 males and 498 females) were included in the study. The mean ± SD age, LM, and FM were 50.0 ± 16.2 years, 38.9 ± 8.0 kg, and 15.5 ± 7.7 kg, respectively. LM decreased with age from 49.4 kg in 20-29 years group to 42.3 kg in ≥70 years group in male and 34.6 kg in 30-39 years group to 30.8 kg in ≥70 years group in females. FM has an inverse U-shaped association with age, which peaked at 11.9 kg in 60-69 years group in males and 20.7 kg in 50-59 years group in females. Among the various anthropometric models, the models incorporating age, sex, weight, and height were considered the best fit for predicting both LM and FM. Conclusion: In the Thai population, peak LM was reached during early adulthood and decline with age, whereas FM showed an inverse U-shaped association with age. The prediction models incorporating age, sex, weight, and height were proposed as practical tools for assessing LM and FM in clinical practice.

Geographically weighted accelerated failure time model for spatial survival data: application to ovarian cancer survival data in New Jersey

BACKGROUND

In large multiregional cohort studies, survival data is often collected at small geographical levels (such as counties) and aggregated at larger levels, leading to correlated patterns that are associated with location. Traditional studies typically analyze such data globally or locally by region, often neglecting the spatial information inherent in the data, which can introduce bias in effect estimates and potentially reduce statistical power.

METHOD

We propose a Geographically Weighted Accelerated Failure Time Model for spatial survival data to investigate spatial heterogeneity. We establish a weighting scheme and bandwidth selection based on quasi-likelihood information criteria. Theoretical properties of the proposed estimators are thoroughly examined. To demonstrate the efficacy of the model in various scenarios, we conduct a simulation study with different sample sizes and adherence to the proportional hazards assumption or not. Additionally, we apply the proposed method to analyze ovarian cancer survival data from the Surveillance, Epidemiology, and End Results cancer registry in the state of New Jersey.

RESULTS

Our simulation results indicate that the proposed model exhibits superior performance in terms of four measurements compared to existing methods, including the geographically weighted Cox model, when the proportional hazards assumption is violated. Furthermore, in scenarios where the sample size per location is 20-25, the simulation data failed to fit the local model, while our proposed model still demonstrates satisfactory performance. In the empirical study, we identify clear spatial variations in the effects of all three covariates.

CONCLUSION

Our proposed model offers a novel approach to exploring spatial heterogeneity of survival data compared to global and local models, providing an alternative to geographically weighted Cox regression when the proportional hazards assumption is not met. It addresses the issue of certain counties' survival data being unable to fit the model due to limited samples, particularly in the context of rare diseases.

Predictors of moderate-to-severe side-effects following COVID-19 mRNA booster vaccination: a prospective cohort study among primary health care providers in Belgium

BACKGROUND

COVID-19 vaccine effectiveness declines months after vaccination. Therefore, it is likely that during the next few years, people may be repeatedly offered a booster vaccine to enhance humoral immunity levels. A growing number of people are questioning whether the benefits of a booster vaccine outweigh the side-effects.

OBJECTIVE

This study aims (1) to identify the most frequently reported side-effects after different doses of COVID-19 mRNA vaccines, (2) and the longest lasting symptoms; and (3) to predict the likelihood of having moderate-to-severe side-effects after a booster COVID-19 mRNA vaccine given individual- and vaccine-specific characteristics.

DESIGN, SETTING, AND PARTICIPANTS

Secondary analysis of a prospective cohort study in primary health care providers (PHCPs) in Belgium conducted between December 2020 and December 2021, and in February-March 2023.

METHODS

In nine subsequent surveys over a period of 2 years vaccine dose-number and side-effects after COVID-19 vaccines were collected. A Generalized Estimation Equations approach on the data of the first and second booster dose was used to investigate the probability of having moderate-to-severe side-effects after mRNA booster vaccination. Predictive performance of a binary classifier was assessed by looking at discrimination (i.e., quantified in terms of the area under the receiver operating characteristic curve). The final prediction model was validated using data with regard to the third booster by assessing misclassification rate, sensitivity and specificity.

RESULTS

In total, 11% of the PHCPs had moderate-to-severe side-effects after their booster COVID-19 mRNA vaccine. The most common side-effects of COVID-19 mRNA doses included fatigue, local pain at the injection site, general pains, and headache. These side-effects typically lasted for a median of 1 to 2 days. The final model included five predictors: sex, alcohol consumption, history of moderate-to-severe side-effects after any previous dose, recent COVID-19 infection, and the booster dose-number (first, second). Having experienced moderate-to-severe side-effects after any previous dose was the strongest predictor of moderate-to-severe side-effects following an mRNA vaccine booster, with an odds ratio (OR) of 3.64 (95% CI: 2.80-4.75). The OR for female sex was 1.49 (95% CI: 1.21-1.84) implying that females have a higher odds of moderate-to-severe side-effects following booster vaccination. The differences in effect for booster dose-number, alcohol consumption and recent COVID-19 infection was not significant.

CONCLUSION AND RELEVANCE

COVID-19 mRNA booster vaccination implies a low prevalence of moderate-to-severe side-effects among PHCPs, with a short median duration of symptoms if any. The strongest predictors are a history of moderate-to-severe side-effects after any previous dose and being female. These reassuring findings can help addressing concerns about booster vaccination and encourage their uptake.

TRIAL REGISTRATION

NCT04779424 (registration date: 2021-02-22).

Trends in Veteran hospitalizations and associated readmissions and emergency department visits during the MISSION Act era

OBJECTIVE

To examine changes in hospitalization trends and healthcare utilization among Veterans following Maintaining Internal Systems and Strengthening Integrated Outside Networks (MISSION) Act implementation.

DATA SOURCES AND STUDY SETTING

VA Corporate Data Warehouse and Centers for Medicare and Medicaid Services datasets.

STUDY DESIGN

Retrospective cohort study to compare 7- and 30-day rates for unplanned readmission and emergency department visits following index hospital stays based on payor type (VHA facility stay, VA-funded stay in community facility [CC], or Medicare-funded community stay [CMS]). Segmented regression models were used to compare payors and estimate changes in outcome levels and slopes following MISSION Act implementation.

DATA COLLECTION/EXTRACTION METHODS

Veterans with active VA primary care utilization and ≥1 acute hospitalization between January 1, 2016 and December 31, 2021.

PRINCIPAL FINDINGS

Monthly index stays increased for all payors until MISSION Act implementation, when VHA and CMS admissions declined while CC admissions accelerated and overtook VHA admissions. In December 2021, CC admissions accounted for 54% of index admissions, up from 25% in January 2016. From adjusted models, just prior to implementation (May 2019), Veterans with CC admissions had 47% greater risk of 7-day readmission (risk ratio [RR]: 1.47, 95% confidence interval [CI]: 1.43, 1.51) and 20% greater risk of 30-day readmission (RR: 1.20, 95% CI: 1.19, 1.22) compared with those with VHA admissions; both effects persisted post-implementation. Pre-implementation CC admissions were also associated with higher 7- and 30-day ED visits, but both risks were substantially lower by study termination (RR: 0.90, 95% CI: 0.88, 0.91) and (RR: 0.89, 95% CI: 0.87, 0.90), respectively.

CONCLUSIONS

MISSION Act implementation was associated with substantial shifts in treatment site and federal payor for Veteran hospitalizations. Post-implementation readmission risk was estimated to be higher for those with CC and CMS index admissions, while post-implementation risk of ED utilization following CC admissions was estimated to be lower compared with VHA index admissions. Reasons for this divergence require further investigation.

Factors associated with weight gain in pre- and post-menopausal women receiving adjuvant endocrine therapy for breast cancer

PURPOSE

Weight gain after breast cancer poses health risks. We aimed to identify factors associated with weight gain during adjuvant endocrine therapy (AET).

METHODS

Women initiating AET enrolled in a prospective cohort. Participants completed FACT-ES plus PROMIS pain interference, depression, anxiety, fatigue, sleep disturbance and physical function measures at baseline, 3, 6, 12, 24, 36, 48 and 60 months. Treatment-emergent symptoms were defined as changes in scores in the direction indicative of worsening symptoms that exceeded the minimal important difference at 3 and/or 6 months compared to baseline. We used logistic regression to evaluate associations of clinicodemographic features and treatment-emergent symptoms with clinically significant weight gain over 60 months (defined as ≥ 5% compared to baseline) in pre- and post-menopausal participants.

RESULTS

Of 309 participants, 99 (32%) were pre-menopausal. The 60 months cumulative incidence of clinically significant weight gain was greater in pre- than post-menopausal participants (67% vs 43%, p < 0.001). Among pre-menopausal participants, treatment-emergent pain interference (OR 2.49), aromatase inhibitor receipt (OR 2.8), mastectomy, (OR 2.06) and White race (OR 7.13) were associated with weight gain. Among post-menopausal participants, treatment-emergent endocrine symptoms (OR 2.86), higher stage (OR 2.25) and White race (OR 2.29) were associated with weight gain while treatment-emergent physical function decline (OR 0.30) was associated with lower likelihood of weight gain.

CONCLUSIONS

Weight gain during AET is common, especially for pre-menopausal women. Clinicodemographic features and early treatment-emergent symptoms may identify at risk individuals.

IMPLICATIONS FOR CANCER SURVIVORS

Patients at risk for weight gain can be identified early during AET.

CLINICAL TRIALS

GOV IDENTIFIER

NCT01937052, registered September 3, 2013.

Analysis of Cerebral Spinal Fluid Drainage and Intracranial Pressure Peaks in Patients with Subarachnoid Hemorrhage

BACKGROUND

After aneurysmal subarachnoid hemorrhage (aSAH), elevated intracranial pressure (ICP) due to disrupted cerebrospinal fluid (CSF) dynamics is a critical concern. An external ventricular drainage (EVD) is commonly employed for management; however, optimal strategies remain debated. The randomized controlled Earlydrain trial showed that an additional prophylactic lumbar drainage (LD) after aneurysm treatment improves neurological outcome. We performed a post hoc investigation on the impact of drainage volumes and critical ICP values on patient outcomes after aSAH.

METHODS

Using raw patient data from Earlydrain, we analyzed CSF drainage amounts and ICP measurements in the first 8 days after aSAH. Outcomes were the occurrence of secondary infarctions and the score on the modified Rankin scale after 6 months, dichotomized in values of 0-2 as favorable and 3-6 as unfavorable. Repeated measurements were considered with generalized estimation equations.

RESULTS

Earlydrain recruited 287 patients, of whom 221 received an EVD and 140 received an LD. Higher EVD volumes showed a trend to more secondary infarctions (p = 0.09), whereas higher LD volumes were associated with less secondary infarctions (p = 0.009). The mean total CSF drainage was 1052 ± 659 mL and did not differ concerning infarction and neurological outcome. Maximum ICP values were higher in patients with poor outcomes but not related to drainage volumes via EVD. After adjustment for aSAH severity and total CSF drainage, higher LD volume was linked to favorable outcome (per 100 mL: odds ratio 0.61 (95% confidence interval 0.39-0.95), p = 0.03), whereas higher EVD amounts were associated with unfavorable outcome (per 100 mL: odds ratio 1.63 (95% confidence interval 1.05-2.54), p = 0.03).

CONCLUSIONS

Findings indicate that effects of CSF drainage via EVD and LD differ. Higher amounts and higher proportions of LD volumes were associated with better outcomes, suggesting a potential quantity-dependent protective effect. Optimizing LD volume and mitigating ICP spikes may be a strategy to improve patient outcomes after aSAH.

CLINICAL TRIAL REGISTRATION

ClinicalTrials.gov identifier: NCT01258257.

Supportive periodontal care with or without subgingival instrumentation: Microbiological results of a 2-year randomized clinical trial

AIM

To compare the subgingival microbiota of patients receiving supportive periodontal care (SPC) with and without subgingival instrumentation, over 2 years.

MATERIALS AND METHODS

This study was a randomized clinical trial that included 62 participants (50.97 ± 9.26 years old; 40 females) who completed non-surgical periodontal therapy. Participants were randomly assigned to receive oral prophylaxis with oral hygiene instructions alone (test) or in combination with subgingival instrumentation (control) during SPC. Pooled subgingival biofilm samples were obtained from four sites per patient at SPC baseline and at 3, 6, 12, 18, and 24 months. Real-time polymerase chain reaction was used for absolute quantification of Eubacteria and the target bacteria Porphyromonas gingivalis, Tannerella forsythia, and Treponema denticola. Data were analysed using generalized estimating equations, taking into consideration the clustering of observations within individuals.

RESULTS

No significant differences were found between the experimental groups regarding the mean counts of Eubacteria and target bacteria, as well as the periodontal parameters at the sampled sites. Although significant variability in bacterial counts was present during SPC, all counts after 2 years were not statistically different from those at baseline. Bacterial counts were associated with the presence of plaque, bleeding on probing, mean probing depth ≥3 mm, and follow-up period.

CONCLUSIONS

SPC with or without subgingival instrumentation can result in comparable subgingival microbiological outcomes.

CLINICAL TRIAL REGISTRATION

clinicaltrials.gov: NCT01598155 (https://clinicaltrials.gov/study/NCT01598155?intr=supragingival%20control&rank=4#study-record-dates).

Repetitive head impacts among professional fighters: a pilot study evaluating Traumatic Encephalopathy Syndrome and postural balance

OBJECTIVES

Clinical criteria for Traumatic Encephalopathy Syndrome (ccTES) were developed for research purposes to reflect the clinical symptoms of Chronic Traumatic Encephalopathy (CTE). The aims of this study were to 1) determine whether there was an association between the research diagnosis of TES and impaired postural balance among retired professional fighters, and 2) determine repetitive head impacts (RHI) exposure thresholds among both TES positive and TES negative groups in retired professional fighters when evaluating for balance impairment.

METHODS

This was a pilot study evaluating postural balance among participants of the Professional Athletes Brain Health Study (PABHS). Among the cohort, 57 retired professional fighters met the criteria for inclusion in this study. A generalized linear model with generalized estimating equations was used to compare various balance measures longitudinally between fighters with and without TES.

RESULTS

A significant association was observed between a TES diagnosis and worsening performance on double-leg balance assessments when stratifying by RHI exposure thresholds. Additionally, elevated exposure to RHI was significantly associated with increased odds of developing TES; The odds for TES diagnosis were 563% (95% CI = 113, 1963; p-value = 0.0011) greater among athletes with 32 or more professional fights compared to athletes with less than 32 fights when stratifying by balance measures. Likewise, the odds for TES diagnosis were 43% (95% CI = 10, 102; p-value = 0.0439) greater with worsening double leg stance balance in athletes exposed to 32 or more fights.

CONCLUSION

This pilot study provides preliminary evidence of a relationship between declining postural balance and a TES diagnosis among retired professional fighters with elevated RHI exposure. Further research exploring more complex assessments such as the Functional Gait Assessment may be of benefit to improve clinical understanding of the relationship between TES, RHI, and balance.

Radiomics of multi-parametric MRI for the prediction of lung metastasis in soft-tissue sarcoma: a feasibility study

PURPOSE

To investigate the value of multi-parametric MRI-based radiomics for preoperative prediction of lung metastases from soft tissue sarcoma (STS).

METHODS

In total, 122 patients with clinicopathologically confirmed STS who underwent pretreatment T1-weighted contrast-enhanced (T1-CE) and T2-weighted fat-suppressed (T2FS) MRI scans were enrolled between Jul. 2017 and Mar. 2021. Radiomics signatures were established by calculating and selecting radiomics features from the two sequences. Clinical independent predictors were evaluated by statistical analysis. The radiomics nomogram was constructed from margin and radiomics features by multivariable logistic regression. Finally, the study used receiver operating characteristic (ROC) and calibration curves to evaluate performance of radiomics models. Decision curve analyses (DCA) were performed to evaluate clinical usefulness of the models.

RESULTS

The margin was considered as an independent predictor (p < 0.05). A total of 4 MRI features were selected and used to develop the radiomics signature. By incorporating the margin and radiomics signature, the developed nomogram showed the best prediction performance in the training (AUCs, margin vs. radiomics signature vs. nomogram, 0.609 vs. 0.909 vs. 0.910) and validation (AUCs, margin vs. radiomics signature vs. nomogram, 0.666 vs. 0.841 vs. 0.894) cohorts. DCA indicated potential usefulness of the nomogram model.

CONCLUSIONS

This feasibility study evaluated predictive values of multi-parametric MRI for the prediction of lung metastasis, and proposed a nomogram model to potentially facilitate the individualized treatment decision-making for STSs.

Improved Prediction of Epidermal Growth Factor Receptor Status by Combined Radiomics of Primary Nonsmall-Cell Lung Cancer and Distant Metastasis

OBJECTIVES

This study aimed to investigate radiomics based on primary nonsmall-cell lung cancer (NSCLC) and distant metastases to predict epidermal growth factor receptor (EGFR) mutation status.

METHODS

A total of 290 patients (mean age, 58.21 ± 9.28) diagnosed with brain (BM, n = 150) or spinal bone metastasis (SM, n = 140) from primary NSCLC were enrolled as a primary cohort. An external validation cohort, consisting of 69 patients (mean age, 59.87 ± 7.23; BM, n = 36; SM, n = 33), was enrolled from another center. Thoracic computed tomography-based features were extracted from the primary tumor and peritumoral area and selected using the least absolute shrinkage and selection operator regression to build a radiomic signature (RS-primary). Contrast-enhanced magnetic resonance imaging-based features were calculated and selected from the BM and SM to build RS-BM and RS-SM, respectively. The RS-BM-Com and RS-SM-Com were developed by integrating the most important features from the primary tumor, BM, and SM.

RESULTS

Six computed tomography-based features showed high association with EGFR mutation status: 3 from intratumoral and 3 from peritumoral areas. By combination of features from primary tumor and metastases, the developed RS-BM-Com and RS-SM-Com performed well with areas under curve in the training (RS-BM-Com vs RS-BM, 0.936 vs 0.885, P = 0.177; RS-SM-Com vs RS-SM, 0.929 vs 0.843, P = 0.003), internal validation (RS-BM-Com vs RS-BM, 0.920 vs 0.858, P = 0.492; RS-SM-Com vs RS-SM, 0.896 vs 0.859, P = 0.379), and external validation (RS-BM-Com vs RS-BM, 0.882 vs 0.805, P = 0.263; RS-SM-Com vs RS-SM, 0.865 vs 0.816, P = 0.312) cohorts.

CONCLUSIONS

This study indicates that the accuracy of detecting EGFR mutations significantly enhanced in the presence of metastases in primary NSCLC. The established radiomic signatures from this approach may be useful as new predictors for patients with distant metastases.

Habitat-Based Radiomics for Predicting EGFR Mutations in Exon 19 and 21 From Brain Metastasis

RATIONALE AND OBJECTIVES

To explore and externally validate habitat-based radiomics for preoperative prediction of epidermal growth factor receptor (EGFR) mutations in exon 19 and 21 from MRI imaging of non-small cell lung cancer (NSCLC)-originated brain metastasis (BM).

METHODS

A total of 170, 62 and 61 patients from center 1, center 2 and center 3, respectively were included. All patients underwent contrast-enhanced T1-weighted (T1CE) and T2-weighted (T2W) MRI scans. Radiomics features were extracted from the tumor active (TA) and peritumoral edema (PE) regions in each MRI slice. The most important features were selected by the least absolute shrinkage and selection operator regression to develop radiomics signatures based on TA (RS-TA), PE (RS-PE) and their combination (RS-Com). Receiver operating characteristic (ROC) curve analysis was performed to access performance of radiomics models for both internal and external validation cohorts.

RESULTS

10, four and six most predictive features were identified to be strongly associated with the EGFR mutation status, exon 19 and exon 21, respectively. The RSs derived from the PE region outperformed those from the TA region for predicting the EGFR mutation, exon 19 and exon 21. The RS-Coms generated the highest performance in the primary training (AUCs, RS-EGFR-Com vs. RS-exon 19-Com vs. RS-exon 21-Com, 0.955 vs. 0.946 vs. 0.928), internal validation (AUCs, RS-EGFR-Com vs. RS-exon 19-Com vs. RS-exon 21-Com, 0.879 vs. 0.819 vs. 0.882), external validation 1 (AUCs, RS-EGFR-Com vs. RS-exon 19-Com vs. RS-exon 21-Com, 0.830 vs. 0.825 vs. 0.822), and external validation 2 (AUCs, RS-EGFR-Com vs. RS-exon 19-Com vs. RS-exon 21-Com, 0.812 vs. 0.818 vs. 0.800) cohort.

CONCLUSION

The developed habitat-based radiomics model can be used to accurately predict the EGFR mutation subtypes, which may potentially guide personalized treatments for NSCLC patients with BM.

Cognitive subtypes in youth at clinical high risk for psychosis

Introduction

Schizophrenia is a mental health condition that severely impacts well-being. Cognitive impairment is among its core features, often presenting well before the onset of overt psychosis, underscoring a critical need to study it in the psychosis proneness (clinical high risk; CHR) stage, to maximize the benefits of interventions and to improve clinical outcomes. However, given the heterogeneity of cognitive impairment in this population, a one-size-fits-all approach to therapeutic interventions would likely be insufficient. Thus, identifying cognitive subtypes in this population is crucial for tailored and successful therapeutic interventions. Here we identify, validate, and characterize cognitive subtypes in large CHR samples and delineate their baseline and longitudinal cognitive and functional trajectories.

Methods

Using machine learning, we performed cluster analysis on cognitive measures in a large sample of CHR youth (n = 764), and demographically comparable controls (HC; n = 280) from the North American Prodrome Longitudinal Study (NAPLS) 2, and independently validated our findings with an equally large sample (NAPLS 3; n = 628 CHR, 84 HC). By utilizing several statistical approaches, we compared the clusters on cognition and functioning at baseline, and over 24 months of followup. We further delineate the conversion status within those clusters.

Results

Two main cognitive clusters were identified, "impaired" and "intact" across all cognitive domains in CHR compared to HC. Baseline differences between the cognitively intact cluster and HC were found in the verbal abilities and attention and working memory domains. Longitudinally, those in the cognitively impaired cluster group demonstrated an overall floor effect and did not deteriorate further over time. However, a "catch up" trajectory was observed in the attention and working memory domain. This group had higher instances of conversion overall, with these converters having significantly more non-affective psychotic disorder diagnosis versus bipolar disorder, than those with intact cognition. In the cognitively intact group, we observed differences in trajectory based on conversion status, where those who start with intact cognition and later convert demonstrate a sharp decline in attention and functioning. Functioning was significantly better in the cognitively intact than in the impaired group at baseline. Most of the cognitive trajectories demonstrate a positive relationship with functional ones.

Conclusion

Our findings provide evidence for intact and impaired cognitive subtypes in youth at CHR, independent of conversion status. They further indicate that attention and working memory are important to distinguish between the CHR with intact cognition and controls. The cognitively intact CHR group becomes less attentive after conversion, while the cognitively impaired one demonstrates a catch up trajectory on both attention and working memory. Overall, early evaluation, covering several cognitive domains, is crucial for identifying trajectories of improvement and deterioration for the purpose of tailoring intervention for improving outcomes in individuals at CHR for psychosis.