Category: Nevin Manimala

JMIR Mhealth Uhealth. 2024 Jun 3;12:e53411. doi: 10.2196/53411.

ABSTRACT

BACKGROUND: There are no recent studies comparing the compliance rates of both patients and observers in tuberculosis treatment between the video-observed therapy (VOT) and directly observed therapy (DOT) programs.

OBJECTIVE: This study aims to compare the average number of days that patients with pulmonary tuberculosis and their observers were compliant under VOT and DOT. In addition, this study aims to compare the sputum conversion rate of patients under VOT with that of patients under DOT.

METHODS: Patient and observer compliance with tuberculosis treatment between the VOT and DOT programs were compared based on the average number of VOT and DOT compliance days and sputum conversion rates in a 60-day cluster randomized controlled trial with patients with pulmonary tuberculosis (VOT: n=63 and DOT: n=65) with positive sputum acid-fast bacilli smears and 38 observers equally randomized into the VOT and DOT groups (19 observers per group and n=1-5 patients per observer). The VOT group submitted videos to observers via smartphones; the DOT group followed standard procedures. An intention-to-treat analysis assessed the compliance of both the patients and the observers.

RESULTS: The VOT group had higher average compliance than the DOT group (patients: mean difference 15.2 days, 95% CI 4.8-25.6; P=.005 and observers: mean difference 21.2 days, 95% CI 13.5-28.9; P<.001). The sputum conversion rates in the VOT and DOT groups were 73% and 61.5%, respectively (P=.17).

CONCLUSIONS: Smartphone-based VOT significantly outperformed community-based DOT in ensuring compliance with tuberculosis treatment among observers. However, the study was underpowered to confirm improved compliance among patients with pulmonary tuberculosis and to detect differences in sputum conversion rates.

TRIAL REGISTRATION: Thai Clinical Trials Registry (TCTR) TCTR20210624002; https://tinyurl.com/3bc2ycrh.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.2196/38796.

PMID:38830205 | DOI:10.2196/53411

Cornea. 2024 May 29. doi: 10.1097/ICO.0000000000003584. Online ahead of print.

ABSTRACT

PURPOSE: Principal component analysis (PCA) is a descriptive exploratory statistical technique that is widely used in complex fields for data mining. However, it is rarely used in ophthalmology. We explored its research potential with a large series of eyes that underwent 3 keratoplasty techniques: Descemet membrane endothelial keratoplasty (DMEK), conventional Descemet stripping automated endothelial keratoplasty (ConDSAEK), or ultrathin-DSAEK (UT-DSAEK).

METHODS: All consecutive DMEK/DSAEK cases conducted in 2016 to 2022 that had ≥24 months of follow-up were included. ConDSAEK and UT-DSAEK were defined as preoperative central graft thickness ≥130 and <130 μm, respectively. Seventy-six patient, disease, surgical practice, and temporal outcome variables were subjected to PCA, including preoperative anterior keratometry, the use of sulfur hexafluoride gas (SF6) versus air for primary tamponade, and postoperative best corrected visual acuity and endothelial cell density. Associations of interest that were revealed by PCA were assessed with the Welch t test or Pearson test.

RESULTS: A total of 331 eyes were treated with DMEK (n = 165), ConDSAEK (n = 95), or UT-DSAEK (n = 71). PCA showed that ConDSAEK and UT-DSAEK clustered closely, including regarding postoperative best corrected visual acuity, and were clearly distinct from DMEK. PCA and follow-up univariate analyses suggested that in DMEK, 1) flatter preoperative anterior keratometry (average, K1, and K2) associated with more rebubbling (P = 0.004-0.089) and graft detachment (P = 0.007-0.022); 2) graft marking did not affect postoperative ECD; and 3) lower postoperative endothelial cell density associated with SF6 use (all P > 0.001) and longer surgery (P = 0.005-0.091). All associations are currently under additional investigation in our hospital.

CONCLUSIONS: PCA is a powerful technique that can rapidly reveal clinically relevant associations in complex ophthalmological datasets.

PMID:38830189 | DOI:10.1097/ICO.0000000000003584

Comput Inform Nurs. 2024 Jun 1;42(6):405-409. doi: 10.1097/CIN.0000000000001135.

NO ABSTRACT

PMID:38830135 | DOI:10.1097/CIN.0000000000001135

Med Phys. 2024 Jun 3. doi: 10.1002/mp.17238. Online ahead of print.

ABSTRACT

BACKGROUND: Direction Modulated Brachytherapy (DMBT) enables conformal dose distributions. However, clinicians may face challenges in creating viable treatment plans within a fast-paced clinical setting, especially for a novel technology like DMBT, where cumulative clinical experience is limited. Deep learning-based dose prediction methods have emerged as effective tools for enhancing efficiency.

PURPOSE: To develop a voxel-wise dose prediction model using an attention-gating mechanism and a 3D UNET for cervical cancer high-dose-rate (HDR) brachytherapy treatment planning with DMBT six-groove tandems with ovoids or ring applicators.

METHODS: A multi-institutional cohort of 122 retrospective clinical HDR brachytherapy plans treated to a prescription dose in the range of 4.8-7.0 Gy/fraction was used. A DMBT tandem model was constructed and incorporated onto a research version of BrachyVision Treatment Planning System (BV-TPS) as a 3D solid model applicator and retrospectively re-planned all cases by seasoned experts. Those plans were randomly divided into 64:16:20 as training, validating, and testing cohorts, respectively. Data augmentation was applied to the training and validation sets to increase the size by a factor of 4. An attention-gated 3D UNET architecture model was developed to predict full 3D dose distributions based on high-risk clinical target volume (CTV_HR) and organs at risk (OARs) contour information. The model was trained using the mean absolute error loss function, Adam optimization algorithm, a learning rate of 0.001, 250 epochs, and a batch size of eight. In addition, a baseline UNET model was trained similarly for comparison. The model performance was evaluated on the testing dataset by analyzing the outcomes in terms of mean dose values and derived dose-volume-histogram indices from 3D dose distributions and comparing the generated dose distributions against the ground-truth dose distributions using dose statistics and clinically meaningful dosimetric indices.

RESULTS: The proposed attention-gated 3D UNET model showed competitive accuracy in predicting 3D dose distributions that closely resemble the ground-truth dose distributions. The average values of the mean absolute errors were 1.82 ± 29.09 Gy (vs. 6.41 ± 20.16 Gy for a baseline UNET) in CTV_HR, 0.89 ± 1.25 Gy (vs. 0.94 ± 3.96 Gy for a baseline UNET) in the bladder, 0.33 ± 0.67 Gy (vs. 0.53 ± 1.66 Gy for a baseline UNET) in the rectum, and 0.55 ± 1.57 Gy (vs. 0.76 ± 2.89 Gy for a baseline UNET) in the sigmoid. The results showed that the mean absolute error (MAE) for the bladder, rectum, and sigmoid were 0.22 ± 1.22 Gy (3.62%) (p = 0.015), 0.21 ± 1.06 Gy (2.20%) (p = 0.172), and -0.03 ± 0.54 Gy (1.13%) (p = 0.774), respectively. The MAE for D₉₀, V_100%, and V_150% of the CTV_HR were 0.46 ± 2.44 Gy (8.14%) (p = 0.018), 0.57 ± 11.25% (5.23%) (p = 0.283), and -0.43 ± 19.36% (4.62%) (p = 0.190), respectively. The proposed model needs less than 5 s to predict a full 3D dose distribution of 64 × 64 × 64 voxels for any new patient plan, thus making it sufficient for near real-time applications and aiding with decision-making in the clinic.

CONCLUSIONS: Attention gated 3D-UNET model demonstrated a capability in predicting voxel-wise dose prediction, in comparison to 3D UNET, for DMBT intracavitary brachytherapy planning. The proposed model could be used to obtain dose distributions for near real-time decision-making before DMBT planning and quality assurance. This will guide future automated planning, making the workflow more efficient and clinically viable.

PMID:38830129 | DOI:10.1002/mp.17238

Proc Natl Acad Sci U S A. 2024 Jun 11;121(24):e2317707121. doi: 10.1073/pnas.2317707121. Epub 2024 Jun 3.

ABSTRACT

Human pose, defined as the spatial relationships between body parts, carries instrumental information supporting the understanding of motion and action of a person. A substantial body of previous work has identified cortical areas responsive to images of bodies and different body parts. However, the neural basis underlying the visual perception of body part relationships has received less attention. To broaden our understanding of body perception, we analyzed high-resolution fMRI responses to a wide range of poses from over 4,000 complex natural scenes. Using ground-truth annotations and an application of three-dimensional (3D) pose reconstruction algorithms, we compared similarity patterns of cortical activity with similarity patterns built from human pose models with different levels of depth availability and viewpoint dependency. Targeting the challenge of explaining variance in complex natural image responses with interpretable models, we achieved statistically significant correlations between pose models and cortical activity patterns (though performance levels are substantially lower than the noise ceiling). We found that the 3D view-independent pose model, compared with two-dimensional models, better captures the activation from distinct cortical areas, including the right posterior superior temporal sulcus (pSTS). These areas, together with other pose-selective regions in the LOTC, form a broader, distributed cortical network with greater view-tolerance in more anterior patches. We interpret these findings in light of the computational complexity of natural body images, the wide range of visual tasks supported by pose structures, and possible shared principles for view-invariant processing between articulated objects and ordinary, rigid objects.

PMID:38830105 | DOI:10.1073/pnas.2317707121

Proc Natl Acad Sci U S A. 2024 Jun 11;121(24):e2315700121. doi: 10.1073/pnas.2315700121. Epub 2024 Jun 3.

ABSTRACT

Given the importance of climate in shaping species’ geographic distributions, climate change poses an existential threat to biodiversity. Climate envelope modeling, the predominant approach used to quantify this threat, presumes that individuals in populations respond to climate variability and change according to species-level responses inferred from spatial occurrence data-such that individuals at the cool edge of a species’ distribution should benefit from warming (the “leading edge”), whereas individuals at the warm edge should suffer (the “trailing edge”). Using 1,558 tree-ring time series of an aridland pine (Pinus edulis) collected at 977 locations across the species’ distribution, we found that trees everywhere grow less in warmer-than-average and drier-than-average years. Ubiquitous negative temperature sensitivity indicates that individuals across the entire distribution should suffer with warming-the entire distribution is a trailing edge. Species-level responses to spatial climate variation are opposite in sign to individual-scale responses to time-varying climate for approximately half the species’ distribution with respect to temperature and the majority of the species’ distribution with respect to precipitation. These findings, added to evidence from the literature for scale-dependent climate responses in hundreds of species, suggest that correlative, equilibrium-based range forecasts may fail to accurately represent how individuals in populations will be impacted by changing climate. A scale-dependent view of the impact of climate change on biodiversity highlights the transient risk of extinction hidden inside climate envelope forecasts and the importance of evolution in rescuing species from extinction whenever local climate variability and change exceeds individual-scale climate tolerances.

PMID:38830099 | DOI:10.1073/pnas.2315700121

Proc Natl Acad Sci U S A. 2024 Jun 11;121(24):e2402375121. doi: 10.1073/pnas.2402375121. Epub 2024 Jun 3.

ABSTRACT

Recent work has emphasized the disproportionate bias faced by minorities when interacting with law enforcement. However, research on the topic has been hampered by biased sampling in administrative data, namely that records of police interactions with citizens only reflect information on the civilians that police elect to investigate, and not civilians that police observe but do not investigate. In this work, we address a related bias in administrative police data which has received less empirical attention, namely reporting biases around investigations that have taken place. Further, we investigate whether digital monitoring tools help mitigate this reporting bias. To do so, we examine changes in reports of interactions between law enforcement and citizens in the wake of the New York City Police Department’s replacement of analog memo books with mobile smartphones. Results from a staggered difference in differences estimation indicate a significant increase in reports of citizen stops once the new smartphones are deployed. Importantly, we observe that the rise is driven by increased reports of “unproductive” stops, stops involving non-White citizens, and stops occurring in areas characterized by a greater concentration of crime and non-White residents. These results reinforce the recent observation that prior work has likely underestimated the extent of racial bias in policing. Further, they highlight that the implementation of digital monitoring tools can mitigate the issue to some extent.

PMID:38830090 | DOI:10.1073/pnas.2402375121

Continuum (Minneap Minn). 2024 Jun 1;30(3):878-903. doi: 10.1212/CON.0000000000001433.

ABSTRACT

OBJECTIVE: This article synthesizes the current literature on prognostication in neurocritical care, identifies existing challenges, and proposes future research directions to reduce variability and enhance scientific and patient-centered approaches to neuroprognostication.

LATEST DEVELOPMENTS: Patients with severe acute brain injury often lack the capacity to make their own medical decisions, leaving surrogate decision makers responsible for life-or-death choices. These decisions heavily rely on clinicians’ prognostication, which is still considered an art because of the previous lack of specific guidelines. Consequently, there is significant variability in neuroprognostication practices. This article examines various aspects of neuroprognostication. It explores the cognitive approach to prognostication, highlights the use of statistical modeling such as Bayesian models and machine learning, emphasizes the importance of clinician-family communication during prognostic disclosures, and proposes shared decision making for more patient-centered care.

ESSENTIAL POINTS: This article identifies ongoing challenges in the field and emphasizes the need for future research to ameliorate variability in neuroprognostication. By focusing on scientific methodologies and patient-centered approaches, this research aims to provide guidance and tools that may enhance neuroprognostication in neurocritical care.

PMID:38830074 | DOI:10.1212/CON.0000000000001433

J Craniofac Surg. 2024 Jun 3. doi: 10.1097/SCS.0000000000010385. Online ahead of print.

ABSTRACT

The purpose of this study was to compare speech outcomes in patients with submucous cleft palate (SMCP) between speech therapy alone and double-opposing Z-plasty (DOZ) combined with speech therapy. The subjects were 67 patients with SMCP (overt type, 45 males, 22 females), who were divided into the observation group (n=18), the speech therapy group (n=24; duration, 17.8 mo), and the DOZ and speech therapy (DOZ-speech therapy) group (n=25; median age at DOZ, 5.3 years, duration, 18.6 mo). The median age at initial and final speech assessments were 3 and 5 years. After age, sex, syndromic status, duration of speech therapy, surgery timing, and speech outcomes were investigated, statistical analysis was performed. After tailored interventions, both isolated and non-isolated SMCP patients experienced significant improvements in speech outcomes, including nasal emission, hypernasality, compensatory articulation, and unintelligible speech. Since comparable improvements were observed, there were no significant differences in the final assessments regardless of initial speech issues between the speech therapy group and the DOZ-speech therapy group (all P>0.05). In the DOZ-speech therapy group, the rate of achieving “socially acceptable” speech was 92.3% in isolated cases and 90% in non-isolated cases. Multivariate analysis revealed that DOZ showed a tendency to reduce hypernasality, compensatory articulation, and “unintelligible” speech; syndromic or developmental conditions influenced outcomes in nasal emission and hypernasality; and initial hypernasality and compensatory articulation were correlated with outcomes. Therefore, DOZ surgery could be recommended to resolve hypernasality and compensatory articulation in SMCP patients before speech issues worsen.

PMID:38830053 | DOI:10.1097/SCS.0000000000010385

Ann Med. 2024 Dec;56(1):2362880. doi: 10.1080/07853890.2024.2362880. Epub 2024 Jun 3.

ABSTRACT

BACKGROUND: Nocturnal blood pressure (BP) is correlated with an increased risk of cardiovascular events and is an important predictor of cardiovascular death in hypertensive patients.

OBJECTIVE: Nocturnal BP control is of great importance for cardiovascular risk reduction. This systematic review and meta-analysis aimed to explore the efficacy of angiotensin receptor blockers (ARBs) for nocturnal BP reduction in patients with mild to moderate hypertension.

METHODS: PICOS design structure was used to formulate the data extraction. All statistical calculations and analyses were performed with R.

RESULTS: Seventy-seven studies with 13,314 participants were included. The overall analysis indicated that nocturnal BP drop varied considerably among different ARBs. Allisartan (13.04 [95% CI (-18.41, -7.68)] mmHg), olmesartan (11.67 [95% CI (-14.12, -9.21)] mmHg), telmisartan (11.11 [95% CI (-12.12, -10.11)] mmHg) were associated with greater reduction in nocturnal systolic BP. In the aspect of the nocturnal-diurnal BP drop ratio, only allisartan was greater than 1. While, the variation tendency of last 4-6 h ambulatory BP was basically consistent with nocturnal BP. Additionally, allisartan showed improvement effect in the proportion of patients with dipping BP pattern.

CONCLUSIONS: This study demonstrates that for patients with mild to moderate hypertension, allisartan, olmesartan and telmisartan have more advantages in nocturnal BP reduction among the ARBs, while allisartan can reduce nighttime BP more than daytime BP and improve the dipping pattern.

PMID:38830046 | DOI:10.1080/07853890.2024.2362880