Category: Nevin Manimala

J Neurosurg Spine. 2025 Jan 24:1-10. doi: 10.3171/2024.9.SPINE24639. Online ahead of print.

ABSTRACT

OBJECTIVE: Smartphones and wearable devices can be effective tools to objectively assess patient mobility and well-being before and after spine surgery. In this retrospective observational study, the authors investigated the relationship between these longitudinal perioperative patient activity data and socioeconomic and demographic correlates, assessing whether smartphone-captured metrics may allow neurosurgeons to distinguish intergroup patterns.

METHODS: A multi-institutional retrospective study of patients who underwent spinal decompression with and without fusion between 2017 and 2021 was conducted. Patients’ home zip codes were used to determine each patient’s Area Deprivation Index (ADI)-an independently validated composite measure of the socioeconomic health of a specific neighborhood relative to the entire United States. Activity data, including steps-taken-per-day across a 2-year perioperative period, were extracted from patient smartphones and statistically normalized to enable interpatient comparisons. Multivariate regression was performed to identify relationships between ADI and patient mobility, while controlling for confounders including age and obesity.

RESULTS: The study included 49 patients. The preoperative activity level of patients living in neighborhoods with an ADI score below the 80th percentile nationally was significantly greater than that of patients living in neighborhoods above the 80th percentile (p = 0.011). A direct positive correlation existed between patients’ ADI scores and the number of days with below-average steps-taken-per-day during the preoperative period (adjusted r2 = 0.822, p = 0.049). Postoperatively, patients with ADI scores above the 80th percentile had significantly greater documented activity levels (p = 0.031).

CONCLUSIONS: The authors’ study demonstrates that individuals living in neighborhoods with an ADI score below the 80th percentile had higher preoperative activity than patients in neighborhoods above the 80th percentile; this disparity diminishes after spine surgery. Though these findings are not generalizable, the authors hypothesized that the relatively faster postoperative recovery of patients living in wealthier neighborhoods is likely multifactorial, possibly due to sustained activity in the preoperative and likely symptomatic period of patients in lower-income neighborhoods, as well as enhanced access to postoperative care for patients in higher-income neighborhoods. Overall, the findings from the authors’ study demonstrate that smartphone-captured activity may be utilized as a metric to study socioeconomic disparities in surgical outcomes. Future studies must specifically isolate socioeconomic variables as potential causal factors to inform improvements in healthcare delivery after surgery.

PMID:39854717 | DOI:10.3171/2024.9.SPINE24639

J Neurosurg. 2025 Jan 24:1-10. doi: 10.3171/2024.9.JNS241208. Online ahead of print.

ABSTRACT

OBJECTIVE: The complex mix of factors, including hemodynamic forces and wall remodeling mechanisms, that drive intracranial aneurysm growth is unclear. This study focuses on the specific regions within aneurysm walls where growth occurs and their relationship to the prevalent hemodynamic conditions to reveal critical mechanisms leading to enlargement.

METHODS: The authors examined hemodynamic models of 67 longitudinally followed aneurysms, identifying 88 growth regions. These regions (of enlargement) were pinpointed through alignment and distance mapping between baseline and follow-up models. Aneurysm wall subdivisions were created based on saccular anatomy and flow-related characteristics, which were used to assess local hemodynamics. The distribution of growing regions across these subdivisions was then studied and stratified by aneurysm location and morphology to reveal distinct growth patterns. Statistical significance was evaluated using the Kruskal-Wallis and Mann-Whitney tests.

RESULTS: Growth predominantly occurred in the body (p < 0.0001) of aneurysms, with anterior communicating artery (ACom) (p < 0.0001) and lateral (p = 0.002) aneurysms showing a significantly greater tendency for growth in this region. In comparison, middle cerebral artery (MCA) (p < 0.0001) and bifurcation (p = 0.0001) aneurysms demonstrated growth in both the dome and the body. Notable differences in growth distribution across saccular regions included ACom versus MCA (neck, p = 0.038), bifurcation versus lateral (neck, p = 0.008), and so forth. The central flow region saw the most growth (p < 0.0001); although not significant, ACom (p = 0.196) and lateral (p = 0.218) aneurysms showed a tendency for growth in inflow and central zones, while MCA (p = 0.001) and bifurcation (p < 0.0001) aneurysms were more likely to grow in the central flow region.

CONCLUSIONS: Two primary mechanisms seem to influence aneurysm growth: high-flow impingement jets in the neck, body, and inflow zones leading to wall degeneration/thinning, mainly in ACom aneurysms; and slow, oscillatory flow conditions in the dome and central flow zones promoting wall remodeling/thickening, mainly in MCA aneurysms. This latter mechanism is also observed as secondary flows in ACom aneurysms. These findings emphasize the need to understand the distinct and sometimes concurrent mechanisms of aneurysm growth, advocating for targeted monitoring and interventions that mitigate rupture risks by considering the unique hemodynamic environments within different aneurysm regions and locations.

PMID:39854706 | DOI:10.3171/2024.9.JNS241208

JMIR Public Health Surveill. 2025 Jan 24;11:e67078. doi: 10.2196/67078.

ABSTRACT

BACKGROUND: Prevalences of mental disorders are increasing worldwide. However, many people with mental health problems do not receive adequate treatment. An important factor preventing individuals from seeking professional help is negative attitudes toward psychotherapeutic treatment. Although a positive shift in attitudes has been observed in recent years, there is still substantial stigma surrounding psychotherapeutic treatment. First studies have linked higher health literacy with more positive attitudes toward psychotherapy, but more research is needed in this area.

OBJECTIVE: This study aimed to examine how general and mental health literacy are associated with attitudes toward psychotherapeutic treatment in Germany. Additionally, associations between sociodemographic factors, experience with psychotherapy, and attitudes toward psychotherapy were explored.

METHODS: A random sample was drawn from a panel representative of the German-speaking population with internet access in Germany and invited to participate in the study via email. Overall, 2000 individuals aged ≥16 years completed the web-based survey with standardized questionnaires in September and October 2022. Attitudes toward psychotherapy and both general and mental health literacy were assessed using the Questionnaire on Attitudes Towards Psychotherapeutic Treatment (QAPT) with 2 subscales (“positive attitudes” and “non-acceptance of society”), the European Health Literacy Survey instrument (HLS-EU-Q16) and the Mental Health Literacy Tool for the Workplace (MHL-W-G). Associations between the questionnaire scales were assessed with Pearson correlations. Additionally, basic sociodemographic information and information on personal and family experiences with psychotherapy were collected. Pearson correlations (age), ANOVAs (level of education and subjective social status), and t tests (experience with psychotherapy, gender, and migration background) were used to analyze how these relate to attitudes toward psychotherapy.

RESULTS: More favorable attitudes toward psychotherapy and lower perceived societal nonacceptance were found in those with higher general (r=0.14, P<.001; r=-0.32, P<.001, respectively) and mental health literacy (r=0.18, P<.001; r=-0.23, P<.001, respectively). Participants with treatment experience for mental health problems (t_1260.12=-10.40, P<.001, Cohen d=-0.49; t_1050.95=3.06, P=.002, Cohen d=0.16) and who have relatives with treatment experience (t_1912.06=-5.66, P<.001, Cohen d=-0.26; t₁₉₂₆=4.77, P<.001, Cohen d=0.22) reported more positive attitudes and higher perceived societal acceptance than those without treatment experience. In terms of sociodemographic differences, being a woman (t₁₉₉₂=-3.60, P<.001, Cohen d=-0.16), younger age (r=-0.11, P<.001), higher subjective social status (F_2,1991=5.25, P=.005, η²=.005), and higher levels of education (F_2,1983=22.27, P<.001, η²=.021) were associated with more positive attitudes toward psychotherapeutic treatment. Being a man (t₁₉₉₄=5.29, P<.001, Cohen d=0.24), younger age (r=-0.08, P<.001), and lower subjective social status (F_2,1993=7.71, P<.001, η²=.008) were associated with higher perceived nonacceptance of psychotherapy.

CONCLUSIONS: Positive associations between attitudes toward psychotherapy and both general and mental health literacy were delineated. Future studies should investigate whether targeted health literacy interventions directed at individuals with lower general and mental health literacy might also help to improve attitudes toward psychotherapeutic treatment and help-seeking behavior.

PMID:39854696 | DOI:10.2196/67078

J Med Internet Res. 2025 Jan 24;27:e56155. doi: 10.2196/56155.

ABSTRACT

BACKGROUND: Sepsis, a critical global health challenge, accounted for approximately 20% of worldwide deaths in 2017. Although the Sequential Organ Failure Assessment (SOFA) score standardizes the diagnosis of organ dysfunction, early sepsis detection remains challenging due to its insidious symptoms. Current diagnostic methods, including clinical assessments and laboratory tests, frequently lack the speed and specificity needed for timely intervention, particularly in vulnerable populations such as older adults, intensive care unit (ICU) patients, and those with compromised immune systems. While bacterial cultures remain vital, their time-consuming nature and susceptibility to false negatives limit their effectiveness. Even promising existing machine learning approaches are restricted by reliance on complex clinical factors that could delay results, underscoring the need for faster, simpler, and more reliable diagnostic strategies.

OBJECTIVE: This study introduces innovative machine learning models using complete blood count with differential (CBC+DIFF) data-a routine, minimally invasive test that assesses immune response through blood cell measurements, critical for sepsis identification. The primary objective was to implement this model within an artificial intelligence-clinical decision support system (AI-CDSS) to enhance early sepsis detection and management in critical care settings.

METHODS: This retrospective study at Tri-Service General Hospital (September to December 2023) analyzed 746 ICU patients with suspected pneumonia-induced sepsis (supported by radiographic evidence and a SOFA score increase of ≥2 points), alongside 746 stable outpatients as controls. Sepsis infection sources were confirmed through positive sputum, blood cultures, or FilmArray results. The dataset incorporated both basic hematological factors and advanced neutrophil characteristics (side scatter light intensity, cytoplasmic complexity, and neutrophil-to-lymphocyte ratio), with data from September to November used for training and data from December used for validation. Machine learning models, including light gradient boosting machine (LGBM), random forest classifier, and gradient boosting classifier, were developed using CBC+DIFF data and were assessed using metrics such as area under the curve, sensitivity, and specificity. The best-performing model was integrated into the AI-CDSS, with its implementation supported through workshops and training sessions.

RESULTS: Pathogen identification in ICU patients found 243 FilmArray-positive, 411 culture-positive, and 92 undetected cases, yielding a final dataset of 654 (43.8%) sepsis cases out of 1492 total cases. The machine learning models demonstrated high predictive accuracy, with LGBM achieving the highest area under the curve (0.90), followed by the random forest classifier (0.89) and gradient boosting classifier (0.88). The best-performing LGBM model was selected and integrated as the core of our AI-CDSS, which was built on a web interface to facilitate rapid sepsis risk assessment using CBC+DIFF data.

CONCLUSIONS: This study demonstrates that by providing streamlined predictions using CBC+DIFF data without requiring extensive clinical parameters, the AI-CDSS can be seamlessly integrated into clinical workflows, enhancing rapid, accurate identification of sepsis and improving patient care and treatment timeliness.

PMID:39854695 | DOI:10.2196/56155

Cancer Invest. 2025 Jan 24:1-11. doi: 10.1080/07357907.2025.2457144. Online ahead of print.

ABSTRACT

Accurate and timely diagnosis of t(9;22)-positive leukemias is vital to improving survival in pediatric patients. In low-resource settings, where healthcare disparities are exacerbated by limited resources, cost-effective and efficient diagnostic methods are essential for bridging these gaps and ensuring better outcomes. Among the diagnostic tools evaluated among 23 patients sample, RT-PCR demonstrated superior sensitivity (100%) and the shortest turnaround time (7 days), significantly outperforming FISH and karyotyping in both accuracy and timeliness. This capability of RT-PCR to provide reliable and rapid results enables earlier treatment initiation, which is critical in managing these aggressive leukemias. Simplified statistical reporting underscores RT-PCR’s unmatched sensitivity, while FISH and karyotyping, though useful, showed moderate performance with longer delays. By adopting RT-PCR as the primary diagnostic tool in LMICs, healthcare systems can make faster and more accurate treatment decisions, reduce overall treatment costs by avoiding diagnostic delays, and ultimately improve survival rates in pediatric leukemia patients.

PMID:39851090 | DOI:10.1080/07357907.2025.2457144

Palliat Support Care. 2025 Jan 24;23:e39. doi: 10.1017/S1478951524001640.

ABSTRACT

OBJECTIVES: To incorporate a longitudinal palliative care curriculum into obstetrics and gynecology (Ob-Gyn) residency that could become standardized to ensure competencies in providing end of life (EOL) care.

METHODS: This was a prospective cohort study conducted among 23 Ob-Gyn residents at a tertiary training hospital from 2021 to 2022. A curriculum intervention was provided via lecture and simulation. An inpatient palliative care rotation was also created for the intern class. Scores for knowledge and confidence were compared pre- and post-curriculum. Performance on patient simulations was compared for interns who had the inpatient palliative rotation versus those that had not in a crossover fashion. Number of palliative care consults was also compared before and during the curriculum. A pooled, weighted rank-based test was used for analysis of the data with a p-value < 0.05 considered significant.

RESULTS: One hundred percent of the 23 eligible participants participated in this study. A statistically significant increase in scores on all quizzes (p-values 0.047, <0.001, and <0.001) and confidence surveys (composite score p-value < 0.001) was seen after curriculum completion. No statistically significant difference was able to be identified in standardized patient simulation performance. Palliative care consultation increased by 55%.

SIGNIFICANCE OF RESULTS: EOL care is a critical component of any physician’s practice including obstetrician gynecologists. However, prior studies demonstrate a lack of standardized training. Our study demonstrates that a multimodal palliative care curriculum is an effective method to train Ob-Gyn residents and improve palliative care involvement in patient care.

PMID:39851085 | DOI:10.1017/S1478951524001640

Palliat Support Care. 2025 Jan 24;23:e36. doi: 10.1017/S1478951524001330.

ABSTRACT

Teaching death, spirituality, and palliative care equips students with critical skills and perspectives for holistic patient care. This interdisciplinary approach fosters empathy, resilience, and personal growth while enhancing competence in end-of-life care. Using experiential methods like simulations and real patient interactions, educators bridge theory and practice. Integrating theological insights and inclusive-pluralism encourages meaningful dialogue, preparing students to address patients’ physical, emotional, and spiritual needs. This holistic pedagogy not only improves patient outcomes but also promotes collaboration and compassion in healthcare.

PMID:39851082 | DOI:10.1017/S1478951524001330

Mol Cancer Ther. 2025 Jan 24. doi: 10.1158/1535-7163.MCT-23-0614. Online ahead of print.

ABSTRACT

TIGIT and PVRIG are immune checkpoints co-expressed on activated T and NK cells, contributing to tumor immune evasion. Simultaneous blockade of these pathways may enhance therapeutic efficacy, positioning them as promising dual targets for cancer immunotherapy. This study aimed to develop a bispecific antibody (BsAb) to co-target TIGIT and PVRIG. Expression of TIGIT and PVRIG was assessed on tumor-infiltrating lymphocytes (TILs) from patients with various cancers, including non-small cell lung cancer (n=63) and colorectal cancer (n=26). The BsAb was engineered by fusing anti-PVRIG nanobodies to the N terminus of anti-TIGIT antibodies. Functional characterization of the BsAb was performed in vitro and in vivo, including assessments of T and NK cell activation and cytotoxicity. Pharmacokinetics and safety profiles were evaluated in cynomolgus monkeys. Statistical analyses were conducted using the Student’s t-test. The results showed that the BsAb effectively blocked TIGIT and PVRIG from binding their respective ligands, CD155 and CD112, leading to significant increases in T cell activation (2.8-fold, p<0.05) and NK cell cytotoxicity (1.8-fold, p<0.05). In vivo, the BsAb demonstrated potent anti-tumor activity, both as a monotherapy and in combination with anti-PD-1 or anti-PD-L1, in humanized PBMC and transgenic mouse models. Pharmacokinetic studies in cynomolgus monkeys revealed a favorable profile, with no dose-limiting toxicities observed after four repeated doses of 200 mg/kg. These findings provide compelling preclinical evidence for the therapeutic potential of targeting the TIGIT-PVRIG axis with a bispecific antibody. This approach shows promise for enhancing anti-tumor immunity and warrants further investigation in clinical trials.

PMID:39851063 | DOI:10.1158/1535-7163.MCT-23-0614

Circ Genom Precis Med. 2025 Jan 24:e004631. doi: 10.1161/CIRCGEN.124.004631. Online ahead of print.

ABSTRACT

BACKGROUND: Lp(a; Lipoprotein[a]) is a predictor of atherosclerotic cardiovascular disease (ASCVD); however, there are few algorithms incorporating Lp(a), especially from real-world settings. We developed an electronic health record (EHR)-based risk prediction algorithm including Lp(a).

METHODS: Utilizing a large EHR database, we categorized Lp(a) cut points at 25, 50, and 75 mg/dL and constructed 10-year ASCVD risk prediction models incorporating Lp(a), with external validation in a pooled cohort of 4 US prospective studies. Net reclassification improvement was determined among borderline-intermediate risk patients.

RESULTS: We included 5902 patients aged ≥18 years (mean age 48.7±16.7 years, 51.2% women, and 7.7% Black). Our EHR model included Lp(a), age, sex, Black race/ethnicity, systolic blood pressure, total and high-density lipoprotein cholesterol, diabetes, smoking, and hypertension medication. Over a mean follow-up of 6.8 years, ASCVD event rates (per 1000 people-years) ranged from 8.7 to 16.7 across Lp(a) groups. A 25 mg/dL increment in Lp(a) was associated with an adjusted hazard ratio of 1.23 (95% CI, 1.10-1.37) for composite ASCVD. Those with Lp(a) ≥75 mg/dL had an 88% higher risk of ASCVD (hazard ratio, 1.88 [95% CI, 1.30-2.70]) and more than double the risk of incident stroke (hazard ratio, 2.55 [95% CI, 1.54-4.23]). C-statistics for our EHR and EHR+Lp(a) models in our EHR training data set were 0.7475 and 0.7556, respectively, with external validation in our pooled cohort (n=21 864) of 0.7350 and 0.7368, respectively. Among those at borderline/intermediate risk, the net reclassification improvement was 21.3%.

CONCLUSIONS: We show the feasibility of developing an improved ASCVD risk prediction model incorporating Lp(a) based on a real-world adult clinic population. The inclusion of Lp(a) in ASCVD prediction models can reclassify risk in patients who may benefit from more intensified ASCVD prevention efforts.

PMID:39851061 | DOI:10.1161/CIRCGEN.124.004631