Tag: pubmed

J Neurosurg Spine. 2024 Nov 15:1-9. doi: 10.3171/2024.7.SPINE24464. Online ahead of print.

ABSTRACT

OBJECTIVE: Surgical correction of adult spinal deformity (ASD) is associated with a high rate of hardware complication that can be challenging to predict. Hardware integrity and alignment after surgery are typically followed with standing radiography, where pedicle screw loosening may be incidentally identified but the clinical significance of which is often unclear. This study aimed to identify the incidence and implications of pedicle screw loosening at the upper instrumented vertebra (UIV) after surgical correction of ASD.

METHODS: A single-institution retrospective analysis was performed on a cohort of 217 patients who underwent long-segment fusion with pelvic fixation for correction of ASD between September 2013 and November 2021. Cases with a minimum 1-year follow-up were included. UIV pedicle screws were graded on radiographs for evidence of loosening with a 0- to 3-point scale: 0, no loosening; 1, lucency within screw threads; 2, lucency around screw threads; and 3, screw dislodgment/backout. Need for hardware revision surgery was assessed as the primary outcome. Patient-reported outcome measures (PROMIS and Oswestry Disability Index scores) were assessed as secondary outcomes among the patients with available scores.

RESULTS: Low-grade UIV screw loosening (grade 1) was identified in 37 patients (17.1%), and high-grade UIV loosening (grade 2 or 3) was identified in 23 patients (10.6%). Low-grade UIV loosening was not associated with eventual need for hardware revision (OR 0.52, 95% CI 0.17-1.61, p = 0.258); however, high-grade loosening was associated with increased odds of hardware revision (OR 5.17, 95% CI 1.74-15.36, p = 0.003), including specifically surgery for correction of proximal junctional kyphosis (OR 5.73, 95% CI 1.27-25.95, p = 0.024). Among patients with PROMIS T-scores, those requiring hardware revision reported worse Pain Interference (65.0 ± 5.1 vs 59.6 ± 7.7, p = 0.001) and Physical Function (33.3 ± 5.6 vs 37.4 ± 7.4; p = 0.011). Patients with high-grade UIV loosening reported higher Oswestry Disability Index scores than those without high-grade loosening (grade 0 or 1), although this failed to reach statistical significance (44.0 ± 8.5 vs 33.7 ± 18.5, p = 0.101).

CONCLUSIONS: Grade 1 UIV pedicle screw loosening may represent a benign incidental finding, whereas high-grade loosening is associated with significantly increased odds of hardware revision surgery. High-grade loosening may also be associated with worse patient-reported disability. The authors’ findings suggest that while low-grade UIV loosening may often be managed expectantly, identification of high-grade UIV pedicle screw loosening on follow-up imaging warrants increased attention and continued surveillance.

PMID:39546785 | DOI:10.3171/2024.7.SPINE24464

J Med Internet Res. 2024 Nov 15;26:e57628. doi: 10.2196/57628.

ABSTRACT

BACKGROUND: Increasing adoption of sensor-based digital health technologies (sDHTs) in recent years has cast light on the many challenges in implementing these tools into clinical trials and patient care at scale across diverse patient populations; however, the methodological approaches taken toward sDHT usability evaluation have varied markedly.

OBJECTIVE: This review aims to explore the current landscape of studies reporting data related to sDHT human factors, human-centered design, and usability, to inform our concurrent work on developing an evaluation framework for sDHT usability.

METHODS: We conducted a scoping review of studies published between 2013 and 2023 and indexed in PubMed, in which data related to sDHT human factors, human-centered design, and usability were reported. Following a systematic screening process, we extracted the study design, participant sample, the sDHT or sDHTs used, the methods of data capture, and the types of usability-related data captured.

RESULTS: Our literature search returned 442 papers, of which 85 papers were found to be eligible and 83 papers were available for data extraction and not under embargo. In total, 164 sDHTs were evaluated; 141 (86%) sDHTs were wearable tools while the remaining 23 (14%) sDHTs were ambient tools. The majority of studies (55/83, 66%) reported summative evaluations of final-design sDHTs. Almost all studies (82/83, 99%) captured data from targeted end users, but only 18 (22%) out of 83 studies captured data from additional users such as care partners or clinicians. User satisfaction and ease of use were evaluated for 83% (136/164) and 91% (150/164) of sDHTs, respectively; however, learnability, efficiency, and memorability were reported for only 11 (7%), 4 (2%), and 2 (1%) out of 164 sDHTs, respectively. A total of 14 (9%) out of 164 sDHTs were evaluated according to the extent to which users were able to understand the clinical data or other information presented to them (understandability) or the actions or tasks they should complete in response (actionability). Notable gaps in reporting included the absence of a sample size rationale (reported for 21/83, 25% of all studies and 17/55, 31% of summative studies) and incomplete sociodemographic descriptive data (complete age, sex/gender, and race/ethnicity reported for 14/83, 17% of studies).

CONCLUSIONS: Based on our findings, we suggest four actionable recommendations for future studies that will help to advance the implementation of sDHTs: (1) consider an in-depth assessment of technology usability beyond user satisfaction and ease of use, (2) expand recruitment to include important user groups such as clinicians and care partners, (3) report the rationale for key study design considerations including the sample size, and (4) provide rich descriptive statistics regarding the study sample to allow a complete understanding of generalizability to other patient populations and contexts of use.

PMID:39546781 | DOI:10.2196/57628

JMIR Form Res. 2024 Nov 15;8:e64476. doi: 10.2196/64476.

ABSTRACT

BACKGROUND: Experimentation is crucial in chemistry education as it links practical experience with theoretical concepts. However, practical chemistry courses typically rely on real laboratory experiments and often face challenges such as limited resources, equipment shortages, and logistical constraints in university settings. To address these challenges, computer-based laboratories have been introduced as a potential solution, offering electronic simulations that replicate real laboratory experiences.

OBJECTIVE: This study examines the effect of virtual laboratories on the academic achievement of undergraduate chemistry students and evaluates their potential as a viable alternative or complement to traditional laboratory-based instruction.

METHODS: A quasi-experimental design was implemented to examine the cause-and-effect relationship between instructional methods and student outcomes. The study involved 60 fourth-year BSc chemistry students from Dilla University, divided into 3 groups: a real laboratory group (n=20), which performed real laboratory experiments; a virtual group (n=20), which used virtual laboratory simulations; and a lecture group (n=20), which received lecture-based instruction. Quantitative data were collected through tests administered before and after the intervention to assess academic performance. The data analysis used descriptive and inferential statistics, such as means and SDs, 1-way ANOVA, the Tukey honestly significant difference test, and independent-sample t tests (2-tailed), with a P value of .05 set for determining statistical significance.

RESULTS: Before the intervention, the results indicated no significant differences in academic achievement among the 3 groups (P=.99). However, after the intervention, notable differences were observed in student performance across the methods. The real laboratory group had the highest mean posttest score (mean 62.6, SD 10.7), followed by the virtual laboratory group (mean 55.5, SD 6.8) and the lecture-only group, which had the lowest mean score (mean 43.7, SD 11.5). ANOVA results confirmed significant differences between the groups (F_2,57=18.429; P<.001). The Tukey post hoc test further revealed that the real laboratory group significantly outperformed the lecture-only group (mean difference 18.88; P<.001), while the virtual laboratory group also performed significantly better than the lecture-only group (mean difference 11.7; P=.001). However, no statistically significant difference was found between the real laboratory and virtual laboratory groups (mean difference 7.12; P=.07). In addition, gender did not significantly influence performance in the virtual laboratory group (P=.21), with no substantial difference in posttest scores between male and female students.

CONCLUSIONS: These findings suggest that computer-based laboratories are a viable and effective alternative when real laboratories are unavailable, enhancing learning outcomes when compared with traditional lecture-based methods. Therefore, universities should consider integrating computer-based laboratories into their practical chemistry curricula to provide students with interactive and engaging learning experiences, especially when physical laboratories are inaccessible.

PMID:39546770 | DOI:10.2196/64476

Am J Manag Care. 2024 Nov;30(11):584-588. doi: 10.37765/ajmc.2024.89627.

ABSTRACT

OBJECTIVES: Provider directory inaccuracies have important implications for care navigation and access as well as ongoing regulatory efforts. We assessed the extent to which identified provider directory inaccuracies persisted across 7 specialties (cardiology, dermatology, endocrinology, gastroenterology, neurology, obstetrics-gynecology, primary care) and 5 carriers in the Pennsylvania Affordable Care Act insurance marketplace.

STUDY DESIGN: A secret shopper survey recontacted inaccurately listed providers (N = 1802) between 403 and 574 days after they were identified in an earlier secret shopper survey.

METHODS: Descriptive analyses, with tests of proportion and t tests to assess whether differences across carriers, specialties, and geographic locations were statistically significant.

RESULTS: Of 1802 inaccurate provider listings, 451 (25.0%) had been removed at follow-up, 966 providers (53.6%) were successfully contacted, and 385 providers (21.4%) could not be reached. Of the recontacted providers, 240 (13.3%) were listed accurately at follow-up and 726 (40.3%) were listed with various inaccuracies, including 31.0% (n = 558) with inaccurate contact information, 11.2% (n = 201) listed under the wrong specialty, and 1.9% (n = 34) erroneously listed as being in network despite being out of network. We found substantial differences across carriers and specialties but not by rurality. Inaccuracies also were less likely to persist in the state’s 2 metropolitan areas. Among inaccurate provider listings, on average, 540 days (median, 544 days) had passed between the initial and subsequent contacts.

CONCLUSIONS: A large number of provider directory inaccuracies persist well beyond the 90-day expectation mandated by federal regulations, raising substantial concerns about compliance. These inaccuracies may impose substantial barriers to patient access and may render existing assessments of network adequacy ineffective.

PMID:39546760 | DOI:10.37765/ajmc.2024.89627

Am J Manag Care. 2024 Nov;30(11):548-554. doi: 10.37765/ajmc.2024.89625.

ABSTRACT

OBJECTIVES: We assessed whether proactive care management for artificial intelligence (AI)-identified at-risk patients reduced preventable emergency department (ED) visits and hospital admissions (HAs).

STUDY DESIGN: Stepped-wedge cluster randomized design.

METHODS: Adults receiving primary care at 48 UCLA Health clinics and determined to be at risk based on a homegrown AI model were included. We employed a stepped-wedge cluster randomized design, assigning groups of clinics (pods) to 1 of 4 single-cohort waves during which the proactive care intervention was implemented. The primary end points were potentially preventable HAs and ED visits; secondary end points were all HAs and ED visits. Within each wave, we used an interrupted time series and segmented regression analysis to compare utilization trends.

RESULTS: In the pooled analysis of high-risk and highest-risk patients (n = 3007), potentially preventable HAs showed a statistically significant level drop (-27% [95% CI, -44% to -6%]), without any corresponding change in trends. Potentially preventable ED visits did not show a substantial level drop in response to the intervention, although a nonsignificant differential change in trend was observed, with visit rates decelerating 7% faster in the intervention cohorts (95% CI, -13% to 0%). Nonsignificant drops were observed for all HAs (-19% [95% CI, -35% to 1%]; P = .06) and ED visits (-15% [95% CI, -28% to 1%]; P = .06).

CONCLUSIONS: A care management intervention targeting AI-identified at-risk patients was followed by a onetime, significant, sizable reduction in preventable HA rates. Further exploration is needed to assess the potential of integrating AI and care management in preventing acute hospital encounters.

PMID:39546757 | DOI:10.37765/ajmc.2024.89625

J Urol. 2024 Nov 15:101097JU0000000000004333. doi: 10.1097/JU.0000000000004333. Online ahead of print.

ABSTRACT

BACKGROUND.: The contribution of 11-oxygenated androgens to the progression of lethal prostate cancer (PCa) remains unresolved. We hypothesized that evaluating circulating levels of 11-oxygenated androgens, such as the androgen receptor agonist 11-ketotestosterone (11KT), could serve as a potential predictor of the onset of castration resistant prostate cancer (CRPC).

METHODS.: We used mass spectrometry to quantify 11-oxygenated androgens in post-operative plasma samples acquired from 145 patients who subsequently received androgen deprivation therapy (ADT) for biochemical recurrence (BCR) and achieved castrated testosterone (T) levels. Kaplan-Meier survival analyses and multivariable Cox models were used to investigate relationships between steroids and CRPC.

RESULTS.: Of 145 patients, 31 developed CRPC with a median time to CRPC of 57 months. 11-oxygenated androgens levels were unaffected by ADT, which stands in contrast to the observed changes in T and other steroids. 11KT was the most abundant androgen but was not linked to clinical features. Kaplan-Meier analysis revealed that 11KT levels above the median of 273 pg/mL were associated with a shorter time to CRPC (P = 0.03). In multivariable analyses, this was supported with an adjusted hazard ratio of 2.17 (95% confidence interval (CI) 0.99-4.71; P = 0.05).

CONCLUSION.: 11KT is a key component of the hormonal profile predictive of earlier onset of CRPC. Enhancing our understanding of the specific role of 11KT in the progression to CRPC could help optimize hormonal therapy for castration sensitive PCa and CRPC patients.

PMID:39546743 | DOI:10.1097/JU.0000000000004333

Opt Lett. 2024 Nov 15;49(22):6561-6564. doi: 10.1364/OL.533546.

ABSTRACT

To enhance the accuracy of space debris localization, spaceborne single-photon LiDAR (SSPL) presents a promising technique for accurate target ranging. Extended Kalman filtering (EKF) plays a crucial role in range gating under high dynamic and nonlinear motion conditions of space debris, ensuring accurate state estimation and prior distance data. However, unknown and time-varying statistics of process and measurement noise significantly degrade state estimation accuracy, posing risks of filter divergence and reduced photon reception, ultimately rendering range gating ineffective. To address this challenge, we propose an adaptive range gating method based on variational Bayesian adaptive extended Kalman filtering (ARG-VBAEKF). This method leverages variational Bayesian (VB) posterior approximation to estimate the joint distribution of state and noise. Simulation results demonstrate that ARG-VBAEKF achieves accurate state and noise estimation, thereby effectively enhancing range gating performance in SSPL-based space debris ranging.

PMID:39546719 | DOI:10.1364/OL.533546

Psychiatr Danub. 2024 Aug;Psychiatr Danub(2):207-218. doi: 10.24869/psyd.2024.207.

ABSTRACT

The outbreak of the Covid-19 pandemic impacted on everyday life and made necessary to deploy remote medical services. Delivering psychiatric health care remotely for children and adolescents posed a major challenge to healthcare professionals. The study aimed to describe the status and trends in remote psychotherapy used during the pandemic Covid-19 and lockdown in Poland with focus on factors affecting the decisions made by therapists, particularly those specific to child and adolescent therapy. An on-line survey on psychotherapy professionals was conducted in Poland at the beginning of the lockdown. Descriptive statistics and the chi-square test were used. There were 386 completed questionnaires. The higher levels found of accepting remote therapy were linked to working in the private sector, to using audio+video facilities, having previously experienced remote therapy and knowing both the theoretical background to remote therapy along with an appropriate level of internet literacy. There were no associations found between subject categories, gender, age nor theoretical specializations of the respondents. Remote psychotherapy may become permanently introduced into mental healthcare systems, providing safe and effective methods of treatment. Further studies are however required, and medical, organizational and administrative standards need to be developed.

PMID:39546649 | DOI:10.24869/psyd.2024.207

Med Phys. 2024 Nov 15. doi: 10.1002/mp.17517. Online ahead of print.

ABSTRACT

BACKGROUND: One of the main challenges of utilizing spot-scanning proton arc therapy (SPArc) in routine clinics is treatment delivery efficiency. Spot reduction, which relies on spot sparsity optimization (SSO), is crucial for achieving high delivery efficiency in SPArc.

PURPOSE: This study aims to develop a novel SSO approach based on the alternating directions method of multipliers (ADMM) for SPArc to achieve high treatment delivery efficiency and maintain optimal dosimetric plan quality.

METHODS: In this study, SSO for SPArc is based on the least-square dose fidelity term with L0-norm regularization. The novel optimization approach is based on the ADMM framework, in which the minimum monitor unit constraint was considered to improve the plan quality. A state-of-the-art SSO method, the primal-dual active set with continuation (PDASC) algorithm published previously, was utilized as a benchmark. Two SPArc plan groups with the same beam assignment and clinical constraint were generated, in which the former group was SPArc plan with SSO utilizing ADMM, denoted as ${\text{SPArc}}_{\text{ADMM}}$ , and the later group was SPArc with SSO utilizing PDASC, denoted as ${\text{SPArc}}_{\text{PDASC}}$ . Nine clinical cases included five different cancer sites (brain, lung, liver, prostate, and head&neck cancer) were used. The SSO method’s performance was evaluated in terms of spot sparsity level (the number of zero-valued elements divided by the total number of elements), beam delivery time, dosimetric plan quality, and plan robustness.

RESULTS: Compared to the ${\text{SPArc}}_{\text{PDASC}}$ plan, the ${\text{SPArc}}_{\text{ADMM}}$ plan exhibits superior sparsity and higher delivery efficiency while maintaining good plan quality.

CONCLUSIONS: This study introduces a novel spot sparsity optimization approach using the ADMM framework to improve the delivery efficiency of SPArc. Compared to the existing state-of-the-art SSO method, such an approach could further enhance delivery efficiency while maintaining good plan quality, which could promote the implementation of SPArc in the clinic’s.

PMID:39546642 | DOI:10.1002/mp.17517

NCHS Data Brief. 2024 Oct;(512).

ABSTRACT

OBJECTIVES: This report explores changes in the overall rate of triplet and higher-order births from 1998 to 2023 by detailed plurality, maternal race and Hispanic origin, and age.

METHODS: Data are from the National Vital Statistics System birth files. Triplet and higher-order birth rates (number of triplet and higher-order births per 100,000 births) from 1998 to 2023 are presented. Also presented are the number of triplet, triplet and higher-order, and quadruplet and higher-order births, and triplet and higher-order multiple birth rates by maternal race and Hispanic origin and maternal age for 1998, 2009, and 2023.

RESULTS: From 1998 to 2023, the triplet and higher-order multiple birth rate declined 62%, from 193.5 per 100,000 total births to 73.8; the largest declines were from 2009 to 2023. The number of triplet and higher-order births declined from 7,625 to 2,653. Declines in triplet and higher-order birth rates were observed for White non-Hispanic (71%) and Hispanic (25%) mothers, while the rate for Black non-Hispanic mothers increased (25%). Triplet and higher-order birth rates declined for all age groups 20 and older from 1998 to 2023, and the largest declines were for mothers age 30 and older.

PMID:39546621