Conditional Inference Tree Analysis Research Articles

Extent of traumatic spinal cord injury is lesion level dependent and predictive of recovery: a multicenter neuroimaging study.

Assessing the extent of the intramedullary lesion after spinal cord injury (SCI) might help to improve prognostication. However, since the neurological level of injury (NLI) impacts the recovery potential of SCI patients, the question arises whether lesion size parameters and predictive models based on those parameters are affected as well. In this retrospective observational study, the extent of the intramedullary lesion between individuals who sustained cervical and thoracolumbar SCI was compared and its relation to clinical recovery was assessed. 154 patients with sub-acute SCI (89 individuals with cervical lesions and 65 individuals with thoracolumbar lesions) underwent conventional clinical magnetic resonance imaging (MRI) 1 month after injury and clinical examination at 1 and 12 months. The morphology of the focal lesion within the spinal cord was manually assessed on the midsagittal slice of T2-weighted MR images and compared between cervical and thoracolumbar SCI patients as well as between patients who improved at least one American Spinal Injury Association Impairment Scale (AIS) grade (converters) and patients without AIS grade improvement (non-converters). The predictive value of lesion parameters including lesion length, lesion width, and preserved tissue bridges for predicting AIS grade conversion was assessed using regression models (conditional inference tree analysis). Lesion length was two times longer in thoracolumbar compared to cervical SCI patients (F = 39.48, p < 0.0001), while lesion width and tissue bridges' width did not differ. When comparing AIS grade converters and non-converters, converters showed a smaller lesion length (F = 5.46, p = 0.021), a smaller lesion width (F = 13.75, p = 0.0003) and greater tissue bridges (F = 12.87, p = 0.0005). Using regression models, tissue bridges allowed more refined subgrouping of the heterogenous patient population according to individual recovery profiles between 1 month and 12 months after SCI, while lesion length added no additional information for further subgrouping. This study characterizes differences in the anteroposterior and craniocaudal lesion extent after SCI. The two times greater lesion length in thoracolumbar compared to cervical SCI might be related to differences in the anatomy, biomechanics, and perfusion between the cervical and thoracic spine. Preserved tissue bridges were less influenced by the lesion level, while closely related to the clinical impairment. These results highlight the robustness and utility of tissue bridges as a neuroimaging biomarker for predicting clinical outcome after SCI in heterogeneous patient populations and for patient stratification in clinical trials.

Assessing the knowledge and attitude of middle and higher secondary school students towards waterbirds in Bhutan

ABSTRACT Assessing the knowledge of and attitudes towards species is critical for shaping the next generation of conservationists and environmentally conscious citizens to foster a sense of responsibility and engagement with the natural world. However, no studies have been undertaken from Bhutan to date concerning the knowledge of and attitude towards waterbirds. We conducted an online survey of 741 students encompassing 185 middle and 556 higher secondary schools. The results indicated that the majority of students have a poor level of knowledge but a strong positive attitude towards the waterbirds. Conditional inference tree (CIT) analysis revealed that the most statistically significant factor associated with knowledge was region followed by age, gender and grade, respectively. Similarly, CIT analysis showed that the female students exhibited a stronger positive attitude than males and others. Further, there was a statistically significant but weak positive correlation between knowledge and attitude. The current study suggests that there is a pressing need to address the substantial knowledge gap concerning waterbirds among Bhutanese middle and higher secondary students. Therefore, we recommend that emphasis should also be placed on teaching outdoor waterbird biology, potentially infusing it into school curricula, which would foster a deeper understanding of Bhutan’s waterbirds and their habitats.

#2123 Ageing, renal function and frailty: analysis of the FRASNET study

Abstract Background and Aims Frailty is a common geriatric syndrome of significant public health importance. The kidney is one of the organs that progressively loses function with aging leading a decrease of glomerular filtration rate (GFR). In elderly the definition of eGFR threshold for the diagnosis of CKD is debated. FRASNET study aims of identify the role of kidney function (glomerular and tubular involvement) in determining frailty among not community-dwelling elderly adults, also depending on the genetics of each single subject. Method The FRASNET study was a cross-sectional multicentre observational cohort study involving healthy. The exclusion criteria were: i) severe cognitive impairment, ii) severe health problems. They have been characterised for BP, GFR, sodium intake (Kawasaki formula), cognitive status, quality of life, anamnestic factors, health and socio-economic status. Frailty was determined according to modified Fried index by the presence of three conditions among reduced grip strength, reduced gait speed, low physical activity, self-reported exhaustion. We considered the number of drugs as an index of comorbidity. Genotyping of 20 targeted single nucleotide polymorphisms (SNPs) selected on renal and hypertension was performed. ANOVA and conditional inference tree analysis have been carried out. Results 1183 individuals were included in the study sample. Median age was 72 [IQ 69-77]. 328 (27.7%) subjects were robust, 445 (37.6%) pre-frail, 410 (34.7%) frail. Frailty increases with age, especially after 75 years (from 28.9% to 75.7%). The overall mean GFR was 71.8 ± 16.5 ml/min/1.73 m2. Estimated 24 h urinary sodium excretion was 194.5 mEq/24 h with median fractional excretion of sodium (FeNa) 0.75%. In 31.9% of sample FeNa was greater than 1%. Only 3% of subjects reported CKD. Moreover, 21.1% presented eGFR ≤ 60 and the prevalence of CKD increases according to age from 12.3% to 70.3%. CKD prevalence increases in linear manner across frailty classes from 20% in robust to 47.6% in frail. Conditional inference tree analysis confirmed the role of age, comorbidity and GFR in determining frailty. In oldest subjects (&amp;gt;75 years old), the eGFR level most strongly associated with frailty was below 53 (ml/min/1.73 m2) (Fig. 1). No differences in sodium excretion were observed according to frailty classes. Moreover, we observed an increase of FeNa according to age and frailty classes form 0.71% (median (IQR 0.567)) to 0.79% (median (IQR 0.690)). In frail group exaggerated FeNa (&amp;gt;1%) is more frequent than in robust and pre-frail subjects (Chi-squared p = 0.021). Even after the introduction of these variables in inferential trees the new proposed cut-off for GFR (53) is a main determinant of frailty in oldest (Fig. 2). The eGFR parameter resulted associated with two genetic variants in RAAS system, rs5051 in the angiotensinogen gene (AGT) and rs2131127 in the angiotensin II receptor type 1 (AGTR1). The rs4293393 in uromodulin gene (UMOD) was confirmed associated with eGFR value. Conclusion The present study is part of the complex debate on the relationship among renal function, aging and frailty. We can therefore conclude that glomerular filtration (eGFR below 50 and not the presence of CKD) must be considered among the factors that influence frailty. Our study also showed a deterioration of tubular function in frail subject that can be expression of structural changes due to nephroangiosclerosis.

Acclimation capacity to global warming of amphibians and freshwater fishes: Drivers, patterns, and data limitations.

Amphibians and fishes play a central role in shaping the structure and function of freshwater environments. These organisms have a limited capacity to disperse across different habitats and the thermal buffer offered by freshwater systems is small. Understanding determinants and patterns of their physiological sensitivity across life history is, therefore, imperative to predicting the impacts of climate change in freshwater systems. Based on a systematic literature review including 345 experiments with 998 estimates on 96 amphibian (Anura/Caudata) and 93 freshwater fish species (Teleostei), we conducted a quantitative synthesis to explore phylogenetic, ontogenetic, and biogeographic (thermal adaptation) patterns in upper thermal tolerance (CTmax) and thermal acclimation capacity (acclimation response ratio, ARR) as well as the influence of the methodology used to assess these thermal traits using a conditional inference tree analysis. We found globally consistent patterns in CTmax and ARR, with phylogeny (taxa/order), experimental methodology, climatic origin, and life stage as significant determinants of thermal traits. The analysis demonstrated that CTmax does not primarily depend on the climatic origin but on experimental acclimation temperature and duration, and life stage. Higher acclimation temperatures and longer acclimation times led to higher CTmax values, whereby Anuran larvae revealed a higher CTmax than older life stages. The ARR of freshwater fishes was more than twice that of amphibians. Differences in ARR between life stages were not significant. In addition to phylogenetic differences, we found that ARR also depended on acclimation duration, ramping rate, and adaptation to local temperature variability. However, the amount of data on early life stages is too small, methodologically inconsistent, and phylogenetically unbalanced to identify potential life cycle bottlenecks in thermal traits. We, therefore, propose methods to improve the robustness and comparability of CTmax/ARR data across species and life stages, which is crucial for the conservation of freshwater biodiversity under climate change.

Optic nerve head factors associated with initial central visual field defect in primary open-angle glaucoma

We investigated optic nerve head factors associated with initial parafoveal scotoma (IPFS) in primary open-angle glaucoma. Eighty (80) patients with an IPFS and 84 patients with an initial nasal step (INS) were compared. Central retinal vascular trunk (CRVT) deviation from the Bruch’s membrane opening (BMO) center was measured as a surrogate of lamina cribrosa (LC)/BMO offset, and its obliqueness was defined as the absolute value of angular deviation from the fovea-BMO axis. Proximity of retinal nerve fiber layer defect (RNFLD) was defined as the angular deviation of the inner RNFLD margin from the fovea-BMO axis. Microvasculature dropout (MvD) was defined as a focal sectoral capillary dropout with no visible microvascular network identified in the choroidal layer. Factors associated with IPFS, as compared with INS, were assessed using logistic regression analyses and conditional inference tree analysis. The IPFS group had more oblique CRVT offset (P < 0.001), RNFLD closer to the fovea (P < 0.001), more MvD (P < 0.001), and more LC defects (P < 0.001) compared to the INS group. In logistic regression analyses, obliqueness of CRVT offset (P = 0.002), RNFLD proximity (P < 0.001), and MvD (P = 0.001) were significant factors influencing the presence of IPFS. Conditional inference tree analysis showed that RNFLD closer to the fovea (P < 0.001) in the upper level, more oblique CRVT offset (P = 0.013) and presence of MvD (P = 0.001) in the lower level were associated with the probability of having IPFS. IPFS was associated with closer RNFLD location to the fovea when assessed from the BMO. Oblique LC/BMO offset may not only mask RNFLD proximity to the fovea due to a deviated funduscopic disc appearance, but also potentiate IPFS via focal LC defect and MvD.

Assessing the effect of cultural practices on Mississippi corn production: 2. Grain composition

AbstractGlobal demand for corn (Zea mays L.) is increasing, and it remains one of the most consumed crops by both humans and animals due to its high calorie content. However, corn grain quality research is sparse and often focused only on a few selected influencing factors. Therefore, two side‐by‐side studies (Addition and Deletion) were conducted in 2020 and 2021 in Mississippi to assess the grain composition including protein, starch, oil, and moisture of corn under several management practices. A randomized complete block design was implemented in both experiments involving a complete factorial of three factors including two plant populations (32,000 and 40,000 seed acre−1), two‐row configurations (single and twin), and six combinations of nutrients plus fungicide application (NF). The trials differed based on the manner of NF applications. In the trial termed Addition, all NF treatments were added incrementally, whereas in the Deletion trial they were withheld in a stepwise manner. Conditional inference tree analysis was conducted to examine interaction effects among the three factors over 3 site‐years. Corn protein content ranged between 8.2% and 9.8% across all years and locations. All three factors and certain interactions significantly influenced both protein and starch content. Specifically, single row planting, 40,000 seeds acre−1, and higher rates of N resulted in higher protein content. Contrarily, the starch content was positively influenced by twin row, 32,000 seeds acre−1 and only N application. Single row configuration resulted in higher oil than twin rows. This study determined that different management factors have the potential to positively influence protein, starch, and oil. These management strategies could extend farmers profitability and provide superior products for industrial purposes with additional implications for livestock feed supplements.

Unraveling the Influence of Age, IQ, Education, and Negative Symptoms on Neurocognitive Performance in Schizophrenia: A Conditional Inference Tree Analysis.

The complex nature of neurocognitive impairment in schizophrenia has been discussed in light of the mixed effects of antipsychotic drugs, psychotic symptoms, dopamine D2 receptor blockade, and intelligence quotient (IQ). These factors have not been thoroughly examined before. This study conducted a comprehensive re-analysis of the CATIE data using machine learning techniques, in particular Conditional Inference Tree (CTREE) analysis, to investigate associations between neurocognitive functions and moderating factors such as estimated trough dopamine D2 receptor blockade with risperidone, olanzapine, or ziprasidone, Positive and Negative Syndrome Scale (PANSS), and baseline IQ in 573 patients with schizophrenia. The study reveals that IQ, age, and education consistently emerge as significant predictors across all neurocognitive domains. Furthermore, higher severity of PANSS-negative symptoms was associated with lower cognitive performance scores in several domains. CTREE analysis, in combination with a genetic algorithm approach, has been identified as particularly insightful for illustrating complex interactions between variables. Lower neurocognitive function was associated with factors such as age>52 years, IQ<94/95,<12/13 education years, and more pronounced negative symptoms (score<26). These findings emphasize the multifaceted nature of neurocognitive functioning in patients with schizophrenia, with the PANSS-negative score being an important predictor. This gives rise to a role in addressing negative symptoms as a therapeutic objective for enhancing cognitive impairments in these patients. Further research must examine nonlinear relationships among various moderating factors identified in this work, especially the role of D2 occupancy.

Screening for Dyslexia in University Students: a Standardized Procedure Based on Conditional Inference Trees.

The focus of this study is on providing tools to enable researchers and practitioners to screen for dyslexia in adults entering university. The first aim is to validate and provide diagnostic properties for a set of seven tests including a 1-min word reading test, a 2-min pseudoword reading test, a phonemic awareness test, a spelling test, the Alouette reading fluency test, a connected-text reading fluency test, and the self-report Adult Reading History Questionnaire (ARHQ). The second, more general, aim of this study was to devise a standardized and confirmatory procedure for dyslexia screening from a subset of the initial seven tests. We used conditional inference tree analysis, a supervised machine learning approach to identify the most relevant tests, cut-off scores, and optimal order of test administration. A combined sample of 60 university students with dyslexia (clinical validation group) and 65 university students without dyslexia (normative group) provided data to determine the diagnostic properties of these tests including sensitivity, specificity, and cut-off scores. Results showed that combinations of four tests (ARHQ, text reading fluency, phonemic awareness, pseudoword reading) and their relative conditional cut-off scores optimize powerful discriminatory screening procedures for dyslexia, with an overall classification accuracy of approximately 90%. The novel use of the conditional inference tree methodology explored in the present study offered a way of moving toward a more efficient screening battery using only a subset of the seven tests examined. Both clinical and theoretical implications of these findings are discussed.

A Large Cohort Analysis of Epiglottic Phenotypes and Pharyngeal Residue.

To describe the phenotypic characteristics of the epiglottis at rest and their impact on vallecular residue. Videofluoroscopic studies (VFSS) were pooled from 2 Laryngology practices, and Image J was used to measure epiglottic anatomic features at rest. Studies were rated by the MBSImp and presence of vallecular residue following swallow of thin and puree boluses. A conditional inference tree analysis was performed to isolate which epiglottic parameters were risk factors for presence of vallecular reside followed by logistic regression. The majority of patients had a normal shaped epiglottis, followed by omega shape. The mean angle of the epiglottis from the hyoid was approximately 90°. Only abnormal epiglottic movement was associated with increased risk of residue for thin boluses (OR 35.09, CI 10.93-158.66, P < .001). However, in those with normal epiglottic movement, age >70 years old was associated with increased risk of residue (OR 3.98, CI 1.73-9.23, P = .001). For puree boluses, a normal or omega shaped epiglottis was associated with residue (OR 5.19, CI 2.41-11.51, P < .001), and this relationship was further modulated by increased distance of the epiglottic tip from the posterior pharyngeal wall. No other anatomic features of the resting epiglottis were associated with residue. Comorbidities potentially affecting swallow were infrequent in the cohort and were not associated with residue. Abnormal epiglottic movement is associated with aspiration, and in this study we find that abnormal epiglottic movement increases the risk of vallecular residue and that older age is a risk factor for residue. The resting properties of the epiglottis do not appear to be associated with abnormal epiglottic movement or residue.

Fuel-flexible biomass off-gassing: The impact of antioxidant spent coffee grains on emissions of CO2, CO, CH4, and VOCs, physical deposits, and combustion in wood pellets

The surging global demand for sustainable energy has propelled the solid biofuel industry, particularly wood pellets. However, the industry grapples with persistent challenges involving off-gassing during storage and transportation. This study introduces an alternative: harnessing a biogenic extract from spent coffee grains (SCG) to manage emissions of carbon monoxide (CO), carbon dioxide (CO2), methane (CH4), and volatile organic compounds (VOCs). Our approach involves applying SCG extract to pinewood sawdust pellets in controlled volumes (0.1 L) and concentrations (0.05 %, 0.1 %, 0.2 %, and 0.4 employing an airbrush compressor for even distribution. To assess emissions, triplicate 0.1 kg samples were placed in gastight chambers at regulated temperatures (25, 35, and 50 °C) and humidity levels (30 %, 60 %, and 90 %). They were measured at five-day intervals over six months. Pellets with the antioxidant additive at 0.05 % exhibited approximately 18,269 ppm of gases (CO2, CO, CH4, and VOCs), compared to 21,039 ppm in untreated pellets, indicating a consistent 13.2 % reduction in total off-gassing. Specifically, CO concentrations in treated and untreated pellets were 3795 ppm and 5012 ppm, respectively, translating into a 24.3 % reduction. Significant reductions were also observed in CO2 (12.95 %), CH4 (19.35 %), and VOCs (5.45 %). Environmental factors, particularly humidity levels above 60% and elevated temperatures within the range of 35–50 °C, were identified as influencing factors in these emissions. This insight was elucidated through a conditional inference tree (CIT) analysis. Stakeholders can leverage these findings to optimize pellet storage and transportation practices, aligning with the global commitment to advancing sustainable energy solutions.

Linking environmental monitoring data and the predicted effects of climate change for urban coastal management: A case study of Dublin Bay

Environmental managers of coastal regions must consider the combined effects of climate change and multiple other stressors simultaneously. While routine monitoring programmes exist, this information is usually summarised as a metric or index for ecological status classification and does not integrate the biological and environmental data in a format that is useful for managers. We present a framework using conditional inference tree analyses and Bayesian Network methodology that synthesises monitoring data, identifies links between environmental and biological variables, and predicts the effects of climate change for Dublin Bay, Ireland. The ecological quality status of phytoplankton biomass was usually high but degraded when silica became limiting. Sediment organic content was positively related to benthic invertebrate richness and the abundance of wading birds, although invertebrate communities were most indicative of pristine conditions when sediment organic content was low. Importantly, climate change simulations showed that the ecological status of Dublin Bay will decline in future, which highlights the importance of removing other stressors from the ecosystem.

Should realignment goals vary based on patient frailty status in adult spinal deformity?

The objective of this study was to adjust the sagittal age-adjusted score (SAAS) to accommodate frailty in alignment considerations and thereby increase the predictability of clinical outcomes and junctional failure. Surgical adult spinal deformity (ASD) patients with 2-year data were included. Frailty was assessed with the continuous ASD modified frailty index (ASD-mFI). Two-year outcomes were proximal junctional kyphosis (PJK), proximal junctional failure (PJF), major mechanical complications, and best clinical outcome (BCO), defined as Oswestry Disability Index (ODI) score < 15 and Scoliosis Research Society outcomes questionnaire total score > 4.5 by 2 years. Linear regression analysis established a 6-week score based on the component scores of SAAS, frailty, and US normal values for ODI score. Logistic regression analysis followed by conditional inference tree run forest analysis generated categorical thresholds. Multivariate analysis, controlling for age, baseline deformity, and history of revision, was used to compare outcome rates, and logistic regression generated odds ratios for the continuous score. Thirty percent of the cohort was used as a random sample for internal validation. In total, 412 patients were included (mean ± SD age 60.1 ± 14.2 years, 80% female, BMI 26.9 ± 5.4 kg/m2). Baseline frailty categories were as follows: 57% not frail, 30% frail, and 14% severely frail. Overall, by 2 years, 39% of patients had developed PJK, 8% PJF, and 21% mechanical complications; 22% had undergone a reoperation; and 15% met BCO. When the cohort as a whole was assessed, the 6-week SAAS had a correlation with the development of PJK and PJF, but not mechanical complications, reoperation, or BCO. Development of mechanical complications, PJF, reoperation, and BCO demonstrated correlations with ASD-mFI (all p < 0.05). Regression analysis modifying SAAS on the basis of ODI norms and frailty generated the following equation: frailty-adjusted SAAS (FAS) = 0.108 × T1 pelvic angle + 0.162 × pelvic tilt - 0.39 × pelvic incidence - lumbar lordosis - 0.03 × ASD-mFI - 1.6771. With conditional inference tree analysis, thresholds were derived for FAS: aligned < 1.7, offset 1.7-2.2, and severely offset > 2.2. Significance between FAS categories was found for PJK, PJF, mechanical complications, reoperation, and BCO by 2 years. Binary logistic regression, controlling for baseline deformity and revision status, demonstrated significance between FAS and all 5 outcome variables (all p < 0.01). Internal validation saw each outcome variable maintain significance between categories, with even greater odds for PJF (OR 13.4, 95% CI 4.7-38.3, p < 0.001). Consideration of physiological age, in addition to chronological age, may be beneficial in the management of operative goals to maximize clinical outcomes while minimizing junctional failure. This combination enables the spine surgeon to fortify a surgical plan for even the most challenging patients undergoing ASD corrective surgery.

Associations of past-year stigma and psychosocial syndemic conditions: Considerations for intersectional stigma measures among Black Sexual Minority Men.

This secondary analysis of a mixed serostatus sample of Black sexual minority men (BSMM) used conditional inference tree methods to explore associations of past-year experienced stigma and psychosocial syndemic conditions. Experienced stigmas were attributed to race, sexuality, socioeconomic status, HIV status or some "other" reason. Psychosocial syndemic conditions studied included physical assault, intimate partner violence, polysubstance use, and depression symptomology. Data are from Promoting Our Worth, Equality and Resilience (POWER), a serial, cross-sectional study conducted between 2014-2017 (N=4430). Experiences of multiple stigmas were reported by n=938 (22.1%) of BSMM. Conditional inference tree results revealed that HIV-related stigma and its intersection with "other" stigma showed the greatest variance in psychosocial condition prevalence. Our findings suggest that when developing intercategorical intersectional analyses with BSMM, there are important stigmas for BSMM beyond those attributed to race, sexuality, and SES, particularly intersecting with HIV-related stigma. Conditional inference tree analysis shows promise in quantitative explorations of intersectional stigma with BSMM, but will benefit from the inclusion of additional forms of stigma, which should be considered by the field moving forward.

More Than Identity: An Intersectional Approach to Understanding Mental-Emotional Well-Being of Emerging Adults by Centering Lived Experiences of Marginalization.

Understanding social determinants that shape pertinent developmental shifts during emerging adulthood (i.e., ages 18-25 years) and their associations with psychological health requires a nuanced approach. In our exploratory study, we investigated how multiple social identities and lived experiences generated by systems of marginalization and power (e.g., racism, classism, sexism) intersect in connection to the mental-emotional well-being of emerging adults (EAs). Eating and Activity Over Time (EAT, 2010-2018) data were collected from 1,568 EAs (mean age= 22.2 (standard deviation, 2.0) years) recruited initially in 2010 from Minneapolis/St. Paul schools. Conditional inference tree analyses were employed to treat "social location" and systems of marginalization and power as interdependent social factors influencing EAs' mental-emotional well-being outcomes: depressive symptoms, stress, self-esteem, and self-compassion. Conditional inference tree analyses identified EAs' subgroups with differing mean levels of mental-emotional well-being outcomes, distinguished primarily by marginalized social experiences (e.g., discrimination, financial difficulties) rather than social identities themselves. The relative positioning of EAs' experiences of social marginalization (e.g., discrimination) to their social identities (e.g., race/ethnicity) suggests that the social experiences generated by systems of privilege and oppression (e.g., racism) are more adjacent social determinants of mental-emotional well-being than the social identities used in public health research to proxy the oppressive systems that give them social meaning.

Prognostication and risk factor stratification for survival of patients with hepatocellular carcinoma: a nationwide big data analysis

This study was conducted to identify risk factors affecting overall survival (OS) and provide prognostication for patients with hepatocellular carcinoma (HCC) using nationwide big data. Between January 2008 and December 2014, 10,573 adult patients with new HCC were registered in a nationwide database. Among them, 6830 patients without missing data were analyzed to construct a prognostication system. A validation cohort of 4580 patients was obtained from a tertiary hospital. All patients were assumed to have received the best treatment. A conditional inference tree analysis was performed to establish a prognostic system. The C-index and calibration plot for 5-year survival were estimated for validation. As a result, the tumor burden (TB) grade was the most significant factor in determining OS, and the cutoff was TB3 (TB1‒3 versus TB4). The patients were ultimately divided into 13 prognosis groups. The C-indexes were 0.714 and 0.737 (95% confidence interval, 0.733–0.742) in the nationwide (derivation) and hospital (validation) cohorts, respectively. In the calibration plot, the 5-year survival of the validation cohort largely matched the 45-degree line. In conclusion, the proposed prognostication system with a simple tree structure enabled the detailed stratification of patient prognosis and visualized the strata of risk factors affecting OS.

ROLE OF NATRIURESIS AND FRAILTY IN BLOOD PRESSURE REGULATION IN ELDERLY PEOPLE

Objective: The objective of the study is to investigate, in elderly people, the relationship between natriuresis, frailty and blood pressure (BP). Design and method: The FRASNET geriatric population (1204 subjects) is an Italian observational cohort that includes frail (35%), pre-frail (37.3%) and robust (27.7%) subjects. They have been characterised for BP, renal function, sodium intake (by Kawasaki formula), anthropometric data, cognitive status, quality of life, comorbidities, and chronic therapies. ANOVA and conditional inference tree analyses have been carried out. Results: 745 participants out of 1203 (60%) were under anti-hypertensive treatment. Increased visceral fat, male sex and lower number of medications taken are risk factors for suboptimal control of BP (71.4%). An inferential analysis evidenced (Fig. 1) a first node between male and female, a second one according to age (75 y), a third with natriuresis (217 mEq/24h). Non-frail subjects presented the highest values for both systolic and diastolic BP; the frail group presents systolic BP values below the threshold of 140 mmHg. BPs are negatively correlated with frailty status (systolic p = 0.048, diastolic p &lt;0.001, Figure 2). Conclusions: Frailty and blood pressure follow an inverse tendency: the higher the severity of the frail status, the lower the blood pressure. The relationship between BP and natriuresis is preserved only in young women whereas in very old people (&gt;75 y) is no more present. This evidence is supported by physiological explanations and suggest to be cautious in salt reduction intake in elderly people.

Calibration of a comprehensive predictive model for the development of proximal junctional kyphosis and failure in adult spinal deformity patients with consideration of contemporary goals and techniques.

The objective of this study was to calibrate an updated predictive model incorporating novel clinical, radiographic, and prophylactic measures to assess the risk of proximal junctional kyphosis (PJK) and failure (PJF). Operative patients with adult spinal deformity (ASD) and baseline and 2-year postoperative data were included. PJK was defined as ≥ 10° in sagittal Cobb angle between the inferior uppermost instrumented vertebra (UIV) endplate and superior endplate of the UIV + 2 vertebrae. PJF was radiographically defined as a proximal junctional sagittal Cobb angle ≥ 15° with the presence of structural failure and/or mechanical instability, or PJK with reoperation. Backstep conditional binary supervised learning models assessed baseline demographic, clinical, and surgical information to predict the occurrence of PJK and PJF. Internal cross validation of the model was performed via a 70%/30% cohort split. Conditional inference tree analysis determined thresholds at an alpha level of 0.05. Seven hundred seventy-nine patients with ASD (mean 59.87 ± 14.24 years, 78% female, mean BMI 27.78 ± 6.02 kg/m2, mean Charlson Comorbidity Index 1.74 ± 1.71) were included. PJK developed in 50.2% of patients, and 10.5% developed PJF by their last recorded visit. The six most significant demographic, radiographic, surgical, and postoperative predictors of PJK/PJF were baseline age ≥ 74 years, baseline sagittal age-adjusted score (SAAS) T1 pelvic angle modifier > 1, baseline SAAS pelvic tilt modifier > 0, levels fused > 10, nonuse of prophylaxis measures, and 6-week SAAS pelvic incidence minus lumbar lordosis modifier > 1 (all p < 0.015). Overall, the model was deemed significant (p < 0.001), and internally validated receiver operating characteristic analysis returned an area under the curve of 0.923, indicating robust model fit. PJK and PJF remain critical concerns in ASD surgery, and efforts to reduce the occurrence of PJK and PJF have resulted in the development of novel prophylactic techniques and enhanced clinical and radiographic selection criteria. This study demonstrates a validated model incorporating such techniques that may allow for the prediction of clinically significant PJK and PJF, and thus assist in optimizing patient selection, enhancing intraoperative decision making, and reducing postoperative complications in ASD surgery.

Vegetation type change in California’s Northern Bay Area: A comparison of contemporary and historical aerial imagery

The North Bay area of California is a populous and ecologically diverse area that has experienced significant changes in the past century, as well as a series of recent wildfires, after over a century of fire suppression practices. While much research has been conducted quantifying drivers and patterns of vegetation change in conifer-dominated ecosystems, and how such changes have influenced current trends in fire behavior, studies of similar focus and scale are rarer in non-conifer ecosystems, including mixed-hardwood forests or shrub-dominated ecosystems in central and coastal Northern California. This is despite the fact that ecosystems other than conifer forests make up the majority of area burned in California wildfires. As such, expanding research focused on patterns of large-scale vegetation change as a possible driver of this trend in this area is a priority. In this study, we sought to map the overall extent and patch sizes of broad vegetation classes across a 52,000 ha study area based on historical (1948) and contemporary (2014) aerial imagery and to investigate shifts in vegetation patterns, as well as potential pathways and drivers of detected changes. We classified vegetation types through segmenting our imagery into homogenous polygons, and assigning broad vegetation categories using a random forest algorithm. We then analyzed patterns of change using spatial statistics and conditional inference tree analyses. We detected a large increase (12%) in the relative landscape proportion and average patch size of the forest class, characterized by dense tree canopy cover. Woodlands and shrub patches were most susceptible to type change, with the majority (57% and 65%, respectively) of converted areas subsequently identified as denser forest stands. By contrast, herbaceous and forest patches were most persistent. We additionally found that disturbance history, specifically whether an area burned or not, and topographic variables, including elevation and aspect, were important influences on the likelihood of vegetation persistence, while slope and water availability were not. Historical aerial imagery, which provides fine resolution and accurate data over a large spatial scale, is a useful tool for detecting landscape-scale vegetation shifts in ecosystems where widespread vegetation monitoring was not common historically. The marked increase in dense forest we detected, specifically due to the conversion of large areas of shrub and woodland vegetation may correspond to higher surface and ladder fuel load and continuity, and potentially higher wildfire risk. Fuel reduction treatments typically implemented in conifer-dominated forests may also be warranted in these mixed hardwood forests. However, more research is needed to understand drivers of change in non-conifer-dominated ecosystems in California and how such change influences wildfire behavior.

Per- and polyfluorinated alkyl substances (PFAS) in Pennsylvania surface waters: A statewide assessment, associated sources, and land-use relations

The objectives of this study are to identify per- and polyfluoroalkyl substances (PFAS) in Pennsylvania surface waters, corresponding associations with potential sources of PFAS contamination (PSOC) and other parameters, and compare raw surface water concentrations to human and ecological benchmarks. Surface water samples from 161 streams were collected in September 2019 and were analyzed for 33 target PFAS and water chemistry. Land use and physical attributes in upstream catchments and geospatial counts of PSOC in local catchments are summarized. The hydrologic yield of the sum of 33 PFAS (∑PFAS) for each stream was computed by normalizing each site's load by the drainage area of the upstream catchment. Utilizing conditional inference tree analysis, the percentage of development (>7.58 %) was identified as a primary driver of the ∑PFAS hydrologic yields. When percentage of development was removed from analysis, ∑PFAS yields were closely related to surface water chemistry associated with landscape alteration (e.g., development or agricultural cropland), such as concentrations of total nitrogen, chloride, and ammonia, but also to count of water pollution control facilities (agricultural, industrial, stormwater, and/or municipal waste pollution abatement facilities). In oil and gas development regions, ∑PFAS yields were associated with combined sewage outfalls. Sites surrounded by ≥2 electronic manufacturing facilities had elevated ∑PFAS yields (median = 241 ng/s/km2). Study results are critical to guide future research, regulatory policy, best practices that will mitigate PFAS contamination, and the communication of human health and ecological risks associated with PFAS exposure from surface waters.

Meteorological conditions and snow-avalanche occurrence over three snow seasons (2017–2020) in Tasiapik Valley, Umiujaq, Nunavik

ABSTRACT In this article, we study snow avalanche activity during the snow seasons of 2017–2020 using four automatic time-lapse cameras strategically positioned along the southwestern slope of Tasiapik Valley, near the village of Umiujaq, in Nunavik (northern Québec, Canada). Over the three snow seasons, cameras helped to detect evidence of 130 avalanche events, scattered over seventy-eight distinct avalanche days. The evolution of weather conditions prior to each avalanche release was detailed according to data from a nearby weather station. Moreover, the time of release, the release type, the surface texture, and whether rocky material was present in the deposits were documented from the photographs. To explore relationships between weather data and avalanche releases, conditional inference tree (CIT) analysis was conducted. Results of the CIT analysis showed that there are different weather patterns associated with avalanche releases depending on the season, and significant thresholds values were defined. In winter, the avalanche probability was greater when three-day snowfall total exceeded 10 cm. In spring, the avalanche probability was greater when cumulative melting degree-days were less than forty-six and when daily minimum air temperature was greater than 2°C. Moreover, cornice failures were found to be a major component of the avalanche dynamic in Tasiapik Valley, mainly because of the slope’s morphology. They have also been the cause of the three largest volume and longest runout avalanches observed by cameras in this study, highlighting potential risks for local communities. The probability of observing cornice failures is enhanced on days when maximum air temperature is greater than −8°C in winter conditions, whereas in spring conditions it is enhanced by daily maximum air temperature greater than 2.5°C. This study represents a necessary first step toward avalanche forecasting based on weather data in Nunavik. Efforts should be continued given the expected higher frequency of natural hazards in northern regions as a consequence of recent climate changes.