Nevin Manimala

JAMA Netw Open. 2025 Jun 2;8(6):e2515894. doi: 10.1001/jamanetworkopen.2025.15894.

ABSTRACT

IMPORTANCE: Many conditions, including neurodegenerative diseases and psychiatric disorders, can impair financial decision-making in older age. Although banking data offer rich insights, they have not yet been leveraged to understand how the loss of financial capacity is associated with financial behaviors.

OBJECTIVE: To describe the behavioral indicators of financial capacity loss and the association of financial capacity loss with financial vulnerability.

DESIGN, SETTING, AND PARTICIPANTS: In this case-control study, banking data recorded by a major UK bank between January 1, 2009, and April 21, 2023, were used to compare the financial outcomes of a group of 16 742 donors of power of attorney (PoA) registrations with a “loss of financial capacity” marker and a control group of 50 226 individuals with no reported financial capacity loss that matched the demographic and socioeconomic characteristics of the donor group 10 years prior to their PoA registration. Group differences in financial outcomes were examined in the 10-year period leading up to the PoA registration. Analysis took place between December 2023 and December 2024.

EXPOSURES: Bank registrations of PoAs recorded between 2019 and 2023 for which the attorney reported that the donor lost financial capacity.

MAIN OUTCOME MEASURES: A broad range of 344 financial measures capturing day-to-day transactional activity (eg, spending on travel and hobbies) and other financial behaviors (eg, online banking logins).

RESULTS: The group of donors of PoA registrations with a “loss of financial capacity” marker comprised 16 742 individuals (mean [SD] age, 72.8 [8.5] years; 10 285 women [61.4%]), and the control group comprised 50 226 individuals (mean [SD] age, 72.7 [8.2] years; 30 657 women [61.0%]). During the 5 years prior to PoA registration, compared with the control group, donors were increasingly less likely to spend on everyday activities (clothing [difference, -9.1 percentage points (pp); 95% CI, -10.0 to -8.3 pp], travel [eg, hotels; difference, -9.6 pp; 95% CI, -10.5 to -8.8 pp], hobbies [eg, gardening; difference, -7.9 pp; 95% CI, -8.8 to -7.1 pp]) and more likely to spend on items associated with increased time at home (eg, household gas and electricity bills [difference, 5.1 pp; 95% CI, 4.6-5.7 pp]). Signs of heightened financial vulnerability in the donor group compared with the control group included an increase in the frequencies of PIN (personal identification number) reset requests (difference, 0.002 [95% CI, 0.002-0.003]), fraud cases (eg, animal charity difference, 0.0003 [95% CI, 0.0002-0.0003]), and lost or stolen credit or debit cards reported (difference, 0.005 [95% CI, 0.004-0.006]) and increased spending on charity (difference, 1.1 pp [95% CI, 0.5-1.7 pp]). In addition, the donor group exhibited reduced attention to finances compared with the control group via decreased online banking activity (difference in number of monthly online banking logins, -1.0 [95% CI, -1.1 to -0.8]).

CONCLUSIONS AND RELEVANCE: This study highlighted the financial behaviors and vulnerabilities associated with declining financial capacity, such as a decrease in activity across multiple domains of daily life. These findings illustrate how banking data can reveal early behavioral signs and financial harms associated with financial capacity loss.

PMID:40512491 | DOI:10.1001/jamanetworkopen.2025.15894

Public Health Nurs. 2025 Jun 13. doi: 10.1111/phn.13580. Online ahead of print.

ABSTRACT

OBJECTIVES: The aim of this study is to examine the relationship between nursing students’ worry about climate change and their environmental sensitivity.

DESIGN AND METHOD: This research is a descriptive and correlational study. It was conducted with 432 nursing students. The data were collected using a Personal Information Form, the Climate Change Worry Scale, and the Environmental Sensitivity Scale. Descriptive statistics (frequency, percentage, mean, standard deviation), independent groups t-test, Mann-Whitney U test, one-way ANOVA, and multiple regression analysis were used to analyze the data.

RESULTS: The mean score of nursing students on Climate Change Worry Scale was 30.74 ± 6.92, and the mean score on the Environmental Sensitivity Scale was 4.24 ± 0.44. A statistically significant moderate negative correlation was found between nursing students’ worry about climate change and their level of environmental sensitivity (r = -0.694, p < 0.01).

CONCLUSIONS: The study revealed a moderate negative correlation between climate change worry and environmental sensitivity among nursing students. Reducing worry about climate change and enhancing environmental sensitivity may enable the students to take an active role in protecting public health in their professional careers.

PMID:40512470 | DOI:10.1111/phn.13580

Clin Exp Med. 2025 Jun 13;25(1):201. doi: 10.1007/s10238-025-01746-4.

ABSTRACT

The neutrophil-to-lymphocyte ratio (NLR) has been suggested as a potential biomarker for the prediction and risk stratification of acute kidney injury (AKI), but conflicting results were reported by literature. We therefore conducted a pooled analysis to consolidate available evidence regarding the predictive and prognostic value of NLR in AKI patients. A systematic search was performed in the PubMed/Medline, Embase, and Cochrane Central Register of Controlled Trials (Central) databases from inception to March 2025 for cohort studies investigating the association between NLR and AKI. Quality assessment was performed via the Quality Assessment for Studies of Diagnostic Accuracy (QUADAS-2) tool. The predictive and prognostic value of the NLR for AKI was evaluated via pooled estimates of odds ratio (OR), sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NeLR), diagnostic score (DS), diagnostic odds ratio (DOR), summary receiver operating characteristic (SROC) curves, and the Fagan nomogram. Twenty-nine studies with 102,870 patients were pooled in this meta-analysis. Higher NLR was associated an increased risk of AKI (OR 1.52, 95% CI 1.29-1.79; p < 0.001). The pooled sensitivity and specificity were 0.70 (95% CI 0.65-0.74) and 0.67 (95% CI 0.60-0.74). The combined values of the PLR, NeLR, DS, and DOR were 2.13 (1.74-2.60), 0.45 (0.38-0.52), 1.56 (1.24-1.89), and 4.78 (3.46-6.60), respectively, with a pooled area under the curve (AUC) for the SROC being 0.74 (95% CI 0.70-0.78). Subgroup analysis suggested that the associations remained statistically significant in contrast-associated AKI (p < 0.001) and surgery-associated AKI (p < 0.001), but of boarder line significance in sepsis-associated AKI (p = 0.082). In addition, higher NLR was also found to be related to 1.47-fold increase in mortality among AKI patients (OR 1.47, 95% CI 1.13-1.91, p = 0.004). NLR is not only an effective marker for predicting AKI event, but also a prognostic tool to identify AKI patients with higher risk of death. Future studies are needed to justify its value in different AKI subtypes.

PMID:40512416 | DOI:10.1007/s10238-025-01746-4

Environ Sci Pollut Res Int. 2025 Jun 13. doi: 10.1007/s11356-025-36603-0. Online ahead of print.

ABSTRACT

Black carbon (BC) consists of partially combusted organic matter deriving from biomass and fuels burning. According to the IPCC’s reports, BC emissions are the second-largest contributor to global warming after CO₂. BC enters the marine system via dry deposition or river run-off. Once in the sea, BC has the potential to affect nutrient biogeochemical cycles. In a series of four incubation experiments (Adriatic Sea and Ligurian Sea) and a pilot study, we have challenged the microbes with heavy loads of BC (24 mg L^-1) in order to study the short-term BC effect on microbial dynamics and activities. Upon BC amendment, heterotrophic prokaryotes increased in abundance while viruses decreased. At the microscale, microbes became attached to BC particles, very heterogeneous in shape and size and enriched in proteins over time; these findings were confirmed by Fourier transform-IR spectroscopy and atomic force microscopy. Enzymatic degradative activities, proteases, and alkaline phosphatases were suppressed in the BC treatments despite an enhancement in prokaryotic carbon production. The 16S rRNA gene amplicon sequencing analysis did not show a significant shift in the microbial communities. Despite this, indicator species analysis revealed that Arcobacter and Pseudoalteromonas genera were statistically associated with the BC treatment at 48 h, thus suggesting their adaptive strategies to utilize BC. Our findings reveal that BC has the potential to stimulate intense carbon flow through microbial activity in the sea. Future studies should take account of the contribution of anthropogenic carbon, BC, into the marine biogeochemical C cycle.

PMID:40512408 | DOI:10.1007/s11356-025-36603-0

J Patient Rep Outcomes. 2025 Jun 13;9(1):67. doi: 10.1186/s41687-025-00897-y.

ABSTRACT

BACKGROUND: This study is an external evaluation of the Patient Reported Outcome Measure (PROM) EFAS-DK developed by the European Foot and Ankle Society (EFAS). The evaluation included a test of the psychometric properties.

METHODOLOGY: From October 2019 to September 2022, 101 patients undergoing elective foot or ankle surgery completed questionnaires (EFAS-DK, SEFAS-DK, EQ-5D-5L) prior to surgery and 6 months post-surgery. A subgroup of patients completed a retest. A foot-healthy group control group was added. Testing covered construct validity with hypothesis testing, floor and ceiling effects, internal consistency (Cronbach’s Alpha), test-retest reliability (ICC 2.1), effect size (ES), Standardized Response Mean (SRM), Smallest Detectable Change (SDC) and Minimal Important Change (MIC).

RESULTS: Moderate construct validity with 59% confirmed hypothesis. High content validity, no floor ceiling effects. Cronbach’s alpha 0.88, ICC 0.93. ES and SRM were both 1.06. SDC 4 and MIC 6. Control group score changes was insignificant.

CONCLUSION: EFAS-DK is a valid, reliable, and responsive foot and ankle PROM score. EFAS-DK can detect a clinically subjective relevant change score of 6 (25% of the total scale), which makes it useful for implementation in the clinic when evaluating patients undergoing foot and ankle surgery. Comparison with a control group showed results that significantly differ from the patients.

LEVEL OF EVIDENCE: IIa prospective observational analytic cohort study.

PMID:40512400 | DOI:10.1186/s41687-025-00897-y

Support Care Cancer. 2025 Jun 13;33(7):573. doi: 10.1007/s00520-025-09619-y.

ABSTRACT

PURPOSE: This study aims to explore the level of supportive care needs among hospitalized lung cancer patients in China, explore the key influencing factors and use machine learning (ML) to develop predictive models for the level of supportive care needs among hospitalized lung cancer patients.

METHODS: This cross-sectional study collected data on the supportive care needs, demographics, and clinical information of 486 hospitalized lung cancer patients. Univariate and multivariate analyses identified factors associated with these needs. Predictive models were developed using six machine learning methods-logistic regression, linear regression, k-nearest neighbors, support vector machine, random forest, and adaptive boosting-to assess their performance, followed by a visualization of feature importance. The code used for model development and analysis is publicly available at https://github.com/zimengcc/predict_cancer_scn.

RESULTS: Among the factors influencing the supportive care needs of hospitalized lung cancer patients, age, education level, occupation, tumor stage, and household per capita monthly income have a significant impact on supportive care needs scores. Multiple linear regression analysis revealed that education level and household per capita monthly income were statistically significant predictors of supportive care needs scores. In the predictive tasks, the random forest model performed the best, with a mean absolute error (MAE) of 4.45 for predicting the total supportive care needs score. Furthermore, to predict the dimension with the highest level of supportive care needs, the model achieved an accuracy of 88. 42%, an F1 score of 87. 49%, and an ROC-AUC of 0.9061.

CONCLUSION: Our study explored the factors influencing the level of supportive care needs among hospitalized lung cancer patients. While the machine learning models demonstrate promising predictive performance, it is important to note that all results were derived solely through cross-validation. Therefore, potential overfitting and overestimation of model performance should be considered when interpreting these findings. Nevertheless, these models may serve as a foundation for developing tools to support personalized care planning in clinical settings.

PMID:40512392 | DOI:10.1007/s00520-025-09619-y

Theor Appl Genet. 2025 Jun 12;138(7):151. doi: 10.1007/s00122-025-04928-6.

ABSTRACT

A theoretical framework for AI and ensembled prediction for crop improvement is introduced and demonstrated using the logistic map. Symbolic/sub-symbolic AI-based prediction can increase predictive skill with increase in system complexity. The curse of dimensionality in genomic prediction has been established and hampers genetic gain for complex traits. Artificial intelligence (AI) that fuses symbolic and sub-symbolic approaches to prediction is emerging as an approach that can deal effectively with this problem. By leveraging information across physiological and genetic networks, it is plausible to increase prediction accuracy by harnessing prior knowledge and computation approaches. Ensembles of models de facto implement the diversity prediction theorem, and thus enable breeders identify subnetworks of genetic and physiological networks underpinning crop response to management (M) and environment (E). Here, we introduce a theoretical framework for AI-enabled prediction in crop improvement. This framework brings together elements of dynamical systems modeling, ensembles, Bayesian statistics and optimization. We demonstrate properties of this framework and limits to predictability using a simple logistic map. We show that heritability and level of predictability decrease with increase in system complexity that conforms well with prior empirical evidence. We show that predicting systems states is an inferior strategy to predicting system process rates for complex systems. This holds for both the level of predictability and for the ability to use the data generating functions to produce a view of the system state space that can help breeders develop an intuition for how biological interventions can affect the performance of the crops. By integrating biological knowledge and computational approaches to prediction, it is feasible to increase predictive accuracy in breeding systems and therefore hasten the rate of genetic gain.

PMID:40512386 | DOI:10.1007/s00122-025-04928-6

J Craniofac Surg. 2025 Jun 13. doi: 10.1097/SCS.0000000000011367. Online ahead of print.

ABSTRACT

Unicoronal synostosis creates facial asymmetry typified by torsion of the midface to the contralateral side. Whether the facial tort corrects spontaneously after frontal orbital advancement surgery remains debatable. The authors aimed to evaluate the degree of clinically evident spontaneous correction of facial torsion after bifrontal orbital advancement. The authors performed a retrospective review of nonsyndromic unicoronal craniosynostosis patients treated with frontal orbital advancement between 1994 and 2016 by evaluating preoperative and postoperative clinical photographs. Preoperative and postoperative facial torsion was serially measured on AP photographs by angulation of the nasal tip from the mid-sagittal plane. Facial torsion was classified as perceptible or not perceptible for qualitative review and angle measurements were recorded for quantification. Sixty-two patients were included. The mean age at surgery was 11 months with the mean follow-up of 57 months. Two hundred sixty-three photographs were reviewed. Mean nasal tip angulation was 6.2±2.1 degrees at the first review with a correction of 1.6±1.82 degrees observed at the final review. All patients had persistent perceptible facial torsion. A statistically significant correction of facial torsion by 1.6 degrees was present but did not lead to a perceptible improvement in facial torsion. The qualitative evaluation demonstrated that perceptible facial torsion was present in both short-term and long-term postoperative photographs in all cases. Although the severity of perceptible asymmetry was not quantified, a subjective degree of perceptible facial torsion preoperatively was unchanged in long-term follow-up despite statistically significant quantitative correction.

PMID:40512385 | DOI:10.1097/SCS.0000000000011367

Support Care Cancer. 2025 Jun 13;33(7):574. doi: 10.1007/s00520-025-09607-2.

ABSTRACT

OBJECTIVE: Lung cancer (LC) and surgery cause physical and psychological distress to patients. This study aimed to investigate the impact of loaded deep breathing training combined with the PERMA model (PERMA-LDBT) on physical and psychological symptoms, functional capacity, and quality of life (QoL) in patients undergoing LC surgery.

METHODS: A three-arm randomized controlled trial was conducted. Patients undergoing LC surgery were randomly assigned to the LDBT plus routine care (IG), PERMA-LDBT plus routine care (CIG), and the routine care (CG). Primary variables included exercise capacity (6MWD), dyspnea (mMRC), anxiety and depression (HADS), and quality of life (EORTC-QQL-C30). Secondary variables comprised adherence, postoperative pulmonary complications (PPCs), length of hospitalization, duration of postoperative thoracic drainage tube, and adverse events. Socio-demographic variables comprised age, gender, smoking status, BMI, comorbidity with COPD, pulmonary function, length of hospitalization, cancer stage, and lobectomy location. Data were collected at admission, the day before surgery, two days after surgery, and the day of discharge.

RESULTS: A total of 148 patients were recruited. Forty-six were excluded, and 102 patients were randomized into three groups of 34 each. Significant improvements in dyspnea, exercise capacity, anxiety, depression, and QoL were observed in both the CIG and IG compared to the CG. However, no statistically significant differences were found in PPCs, length of hospitalization, or postoperative chest drain retention time. The CIG demonstrated statistically significant improvements in adherence and anxiety levels compared to the IG.

CONCLUSION: This study provides evidence that PERMA-LDBT intervention can effectively improve perioperative outcomes in LC patients.

TRIAL REGISTRATION NUMBER: (ChiCTR2400080214) and date of registration (2024-01-23) “retrospectively registration”.

PMID:40512375 | DOI:10.1007/s00520-025-09607-2

J Nephrol. 2025 Jun 13. doi: 10.1007/s40620-025-02319-0. Online ahead of print.

ABSTRACT

Cross-lagged analysis is a statistical method employed to examine directional relationships between variables over time, making it especially valuable for addressing causality challenges in clinical research. This method is essential for comprehending complex bidirectional relationships, such as stress and immunity, dietary habits and metabolic conditions, or medication adherence and health outcomes. By analyzing longitudinal data, cross-lagged analysis establishes temporal precedence, tests reciprocal influences, and controls for confounding variables, thereby enhancing causal inferences. In nephrology, this approach can be beneficial for studying the interaction between acute kidney injury (AKI) and chronic kidney disease (CKD), clarifying whether AKI episodes accelerate CKD progression or if pre-existing CKD increases susceptibility to AKI. It also illuminates the relationship between CKD and cardiovascular diseases, investigating whether CKD exacerbates heart failure or vice versa while considering shared risk factors like hypertension and diabetes. Furthermore, cross-lagged analysis can elucidate the kidney-brain connection by examining whether CKD leads to cognitive decline through mechanisms such as uremic toxin accumulation or if neurological dysfunction worsens kidney outcomes through sympathetic overactivation. Cross-lagged analysis accommodates latent variables and measurement errors, allowing researchers to explore how variables interact over time. This method provides a strong framework for understanding dynamic relationships in nephrology, offering critical insights to guide interventions and advance knowledge of disease progression mechanisms.

PMID:40512355 | DOI:10.1007/s40620-025-02319-0