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Nevin Manimala Statistics

Health-related quality of life in inflammatory bowel disease: a comparison of patients receiving nurse-led versus conventional follow-up care

BMC Health Serv Res. 2022 Dec 31;22(1):1602. doi: 10.1186/s12913-022-08985-1.

ABSTRACT

BACKGROUND: Inflammatory bowel disease (IBD), consisting of Crohn’s disease (CD) and ulcerative colitis (UC), is a chronic disorder with a considerable negative impact on health-related quality of life (HRQoL). During the past decade, IBD nurse specialists have been increasingly involved in follow-up care of IBD outpatients, in a consultative and coordinating role, closely cooperating with gastroenterologists. Whether patients’ HRQoL differs between nurses’ follow-up care (NF) and conventional follow-up care (CF) has not been widely researched and the aim of this study was to compare two different follow-up regimes with respect to patients’ HRQoL.

METHODS: This cross-sectional, multicenter study involved seven centers; five organized as CF, two as NF.

RESULTS: A total of 304 patients aged 18-80 years, 174 females and 130 males, were included, of whom 140 received care under the NF model and 164 under the CF model. Participants in the NF group had a statistically significant higher median total score on the Inflammatory Bowel Disease Questionnaire (IBDQ) (p-value < .001). This pattern could also be seen in the sub-scores of the different IBDQ domains. Despite a trend of higher IBDQ score in all domains in the NF model, the overall result in our study did not reach the limit of 16 points, defined as clinically significant. A higher proportion of NF patients had IBDQ scores defined as remission, as well as a statistically significant higher frequency of outpatient check-ups during a two-year follow-up period.

CONCLUSIONS: Nurse-led models are not inferior to conventional models with regards to patient reported HRQoL except in the social domain where the model showed to be clinically significant better. Further studies are needed to advance efforts to implement these models and increase access to IBD care.

PMID:36587197 | DOI:10.1186/s12913-022-08985-1

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Nevin Manimala Statistics

Effects of syphilis infection among HIV-1-positive individuals on suppressive antiretroviral therapy

AIDS Res Ther. 2022 Dec 31;19(1):69. doi: 10.1186/s12981-022-00493-w.

ABSTRACT

INTRODUCTION: Incident syphilis leads to changes in plasma HIV-1 RNA and CD4 + T-cell level in people with HIV (PWH) with viraemia. Its effect in PWH on suppressive antiretroviral therapy (ART) is less clear.

METHODS: PWH on suppressive ART (plasma HIV-1 RNA < 50copies/mL) followed at the Queen Elizabeth Hospital, Hong Kong, China were regularly screened for syphilis. Their plasma HIV-1 RNA, CD4 + and CD8 + T-cell, and total lymphocyte levels before syphilis, during syphilis, and after successful treatment were compared.

RESULTS: Between 2005 and 2020, 288 syphilis episodes from 180 individuals were identified; 287 episodes were related to male, with a median age of 41 at diagnosis; 221 (77%) were syphilis re-infection. The rates of plasma HIV-1 suppression were statistically unchanged across the time-points (97% pre-syphilis, 98% during syphilis, and 99% post-treatment). Total lymphocyte, CD4+ and CD8+ T-cell levels decreased during incident syphilis (p<0.01), and rebounded post-treatment (p<0.01). VDRL titre was associated with declines in CD4+ T-cell (p=0.045), CD8+ T-cell (p=0.004), and total lymphocyte levels (p=0.021). Pre-syphilis CD4/CD8 ratio was associated with increases in CD8+ T-cell (p=0.001) and total lymphocyte levels (p=0.046) during syphilis. Syphilis re-infection was associated with an increase in total lymphocyte level (p=0.037). In the multivariable analysis, only pre-syphilis CD4/CD8 ratio was independently associated with increases in CD8+ T-cell (p=0.014) and total lymphocyte levels (p=0.039) during syphilis.

CONCLUSIONS: Among virally-suppressed PWH, total lymphocyte, CD4+, and CD8+ T-cell levels declined during incident syphilis but rebounded post-treatment. The status of plasma HIV suppression was unaffected by syphilis.

PMID:36587188 | DOI:10.1186/s12981-022-00493-w

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Nevin Manimala Statistics

Nonnegative spatial factorization applied to spatial genomics

Nat Methods. 2022 Dec 31. doi: 10.1038/s41592-022-01687-w. Online ahead of print.

ABSTRACT

Nonnegative matrix factorization (NMF) is widely used to analyze high-dimensional count data because, in contrast to real-valued alternatives such as factor analysis, it produces an interpretable parts-based representation. However, in applications such as spatial transcriptomics, NMF fails to incorporate known structure between observations. Here, we present nonnegative spatial factorization (NSF), a spatially-aware probabilistic dimension reduction model based on transformed Gaussian processes that naturally encourages sparsity and scales to tens of thousands of observations. NSF recovers ground truth factors more accurately than real-valued alternatives such as MEFISTO in simulations, and has lower out-of-sample prediction error than probabilistic NMF on three spatial transcriptomics datasets from mouse brain and liver. Since not all patterns of gene expression have spatial correlations, we also propose a hybrid extension of NSF that combines spatial and nonspatial components, enabling quantification of spatial importance for both observations and features. A TensorFlow implementation of NSF is available from https://github.com/willtownes/nsf-paper .

PMID:36587187 | DOI:10.1038/s41592-022-01687-w

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Nevin Manimala Statistics

Prediction and risk assessment of sepsis-associated encephalopathy in ICU based on interpretable machine learning

Sci Rep. 2022 Dec 31;12(1):22621. doi: 10.1038/s41598-022-27134-6.

ABSTRACT

Sepsis-associated encephalopathy (SAE) is a major complication of sepsis and is associated with high mortality and poor long-term prognosis. The purpose of this study is to develop interpretable machine learning models to predict the occurrence of SAE after ICU admission and implement the individual prediction and analysis. Patients with sepsis admitted to ICU were included. SAE was diagnosed as glasgow coma score (GCS) less than 15. Statistical analysis at baseline was performed between SAE and non-SAE. Six machine learning classifiers were employed to predict the occurrence of SAE, and the adjustment of model super parameters was performed by using Bayesian optimization method. Finally, the optimal algorithm was selected according to the prediction efficiency. In addition, professional physicians were invited to evaluate our model prediction results for further quantitative assessment of the model interpretability. The preliminary analysis of variance showed significant differences in the incidence of SAE among patients with pathogen infection. There were significant differences in physical indicators like respiratory rate, temperature, SpO2 and mean arterial pressure (P < 0.001). In addition, the laboratory results were also significantly different. The optimal classification model (XGBoost) indicated that the best risk factors (cut-off points) were creatinine (1.1 mg/dl), mean respiratory rate (18), pH (7.38), age (72), chlorine (101 mmol/L), sodium (138.5 k/ul), SAPSII score (23), platelet count (160), and phosphorus (2.4 and 5.0 mg/dL). The ranked features derived from the best model (AUC is 0.8837) were mechanical ventilation, duration of mechanical ventilation, phosphorus, SOFA score, and vasopressin usage. The SAE risk prediction model based on XGBoost created here can make very accurate predictions using simple indicators and support the visual explanation. The interpretable model was effectively evaluated by professional physicians and can help them predict the occurrence of SAE more intuitively.

PMID:36587113 | DOI:10.1038/s41598-022-27134-6

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Nevin Manimala Statistics

Comparison of changes in lipid profiles of premenopausal women with early-stage breast cancer treated with different endocrine therapies

Sci Rep. 2022 Dec 31;12(1):22650. doi: 10.1038/s41598-022-27008-x.

ABSTRACT

Adjuvant endocrine therapy improves the prognosis of early breast cancer with hormone receptor positivity. However, there is no systematic report on the effect of endocrine therapy (particularly ovarian function suppression, OFS) on serum lipids in premenopausal women. This retrospective cohort study aimed to determine whether various endocrine treatments had different effects on blood lipids. This study enrolled 160 premenopausal patients with stage I-III breast cancer in eastern China. The initial diagnostic information was retrieved from patient’s medical records, including age at the time of diagnosis, tumor characteristics, anticancer treatment and past medical history. The changes in blood lipids in patients receiving different types of endocrine therapy were compared at the 3rd, 6th, 12th, and 24th months after initiating endocrine therapy. Generalized linear mixed model was used in our analyses. Our data revealed that low-density lipoprotein cholesterol (LDL-C) levels in patients with tamoxifen (TAM) were significantly lower in the 6th, 12th, and 24th months than that in the 3rd month, while high-density lipoprotein cholesterol (HDL-C) levels in the 6th, 12th, and 24th months were significantly higher than that in the 3rd month, indicating that blood lipid levels generally improved with time. While in TAM plus OFS group, HDL-C levels were significantly higher in the 24th month than in the 3rd month, total cholesterol (TC) levels were significantly higher in the 24th month than in the 6th month. The lipid profiles of OFS plus aromatase inhibitor (AI) group did not show significant differences at any time point but were significantly higher than those of the other two groups especially in LDL and TC. TAM group tended to have lower serum lipid levels. With longer follow-up, no statistically significant difference in values was observed between TAM and TAM plus OFS groups at various time points. Compared with the other two groups, OFS plus AI group presented an increasing trend toward LDL-C and TC. The risk of dyslipidemia requires further investigation using a large sample size.

PMID:36587111 | DOI:10.1038/s41598-022-27008-x

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Nevin Manimala Statistics

Visualizing Neurons Under Tension In Vivo with Optogenetic Molecular Force Sensors

Methods Mol Biol. 2023;2600:239-266. doi: 10.1007/978-1-0716-2851-5_16.

ABSTRACT

The visualization of mechanical stress distribution in specific molecular networks within a living and physiologically active cell or animal remains a formidable challenge in mechanobiology. The advent of fluorescence-resonance energy transfer (FRET)-based molecular tension sensors overcame a significant hurdle that now enables us to address previously technically limited questions. Here, we describe a method that uses genetically encoded FRET tension sensors to visualize the mechanics of cytoskeletal networks in neurons of living animals with sensitized emission FRET and confocal scanning light microscopy. This method uses noninvasive immobilization of living animals to image neuronal β-spectrin cytoskeleton at the diffraction limit, and leverages multiple imaging controls to verify and underline the quality of the measurements. In combination with a semiautomated machine-vision algorithm to identify and trace individual neurites, our analysis performs simultaneous calculation of FRET efficiencies and visualizes statistical uncertainty on a pixel by pixel basis. Our approach is not limited to genetically encoded spectrin tension sensors, but can also be used for any kind of ratiometric imaging in neuronal cells both in vivo and in vitro.

PMID:36587102 | DOI:10.1007/978-1-0716-2851-5_16

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Nevin Manimala Statistics

Tibial quantitative ultrasound compared to dual-energy X-ray absorptiometry in preterm infants

J Perinatol. 2022 Dec 31. doi: 10.1038/s41372-022-01588-y. Online ahead of print.

ABSTRACT

OBJECTIVE: The gold standard for diagnosing metabolic bone disease in pediatrics is dual-energy x-ray absorptiometry (DXA). Bone quantitative ultrasound (QUS) has increasing applications. This study compared the relationship of DXA to QUS in preterm infants.

DESIGN: Prospective observational study of preterm infants ≤32 weeks gestation or ≤1800 grams at birth. DXA scans measuring bone mineral content (BMC) and tibial QUS scans measuring bone speed of sound (SOS) were obtained near term gestation.

RESULTS: 41 infants had bone scans at mean corrected gestation 37.7 ± 2.1 weeks. BMC and SOS showed weak inverse correlation (R2 0.163, p < 0.01). BMC and SOS correlated with parameters at corrected gestational age at the time of the bone scans (p < 0.05-0.001). SOS correlated with birth gestational age (p < 0.001), not BMC.

CONCLUSIONS: A statistically significant weak inverse correlation between DXA and QUS was observed. QUS may have advantages over DXA.

PMID:36587053 | DOI:10.1038/s41372-022-01588-y

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Nevin Manimala Statistics

Comparison of Prognostic Accuracy of 3 Delirium Prediction Models

Am J Crit Care. 2023 Jan 1;32(1):43-50. doi: 10.4037/ajcc2023213.

ABSTRACT

BACKGROUND: Delirium is a severe complication in critical care patients. Accurate prediction could facilitate determination of which patients are at risk. In the past decade, several delirium prediction models have been developed.

OBJECTIVES: To compare the prognostic accuracy of the PRE-DELIRIC, E-PRE-DELIRIC, and Lanzhou models, and to investigate the difference in prognostic accuracy of the PRE-DELIRIC model between patients receiving and patients not receiving mechanical ventilation.

METHODS: This retrospective study involved adult patients admitted to the intensive care unit during a 2-year period. Delirium was assessed by using the Confusion Assessment Method for the Intensive Care Unit or any administered dose of haloperidol or quetiapine. Model discrimination was assessed by calculating the area under the receiver operating characteristic curve (AUC); values were compared using the DeLong test.

RESULTS: The study enrolled 1353 patients. The AUC values were calculated as 0.716 (95% CI, 0.688-0.745), 0.681 (95% CI, 0.650-0.712), and 0.660 (95% CI, 0.629-0.691) for the PRE-DELIRIC, E-PRE-DELIRIC, and Lanzhou models, respectively. The difference in model discrimination was statistically significant for comparison of the PRE-DELIRIC with the E-PRE-DELIRIC (AUC difference, 0.035; P = .02) and Lanzhou models (AUC difference, 0.056; P < .001). In the PRE-DELIRIC model, the AUC was 0.711 (95% CI, 0.680-0.743) for patients receiving mechanical ventilation and 0.664 (95% CI, 0.586-0.742) for those not receiving it (difference, 0.047; P = .27).

CONCLUSION: Statistically significant differences in prognostic accuracy were found between delirium prediction models. The PRE-DELIRIC model was the best-performing model and can be used in patients receiving or not receiving mechanical ventilation.

PMID:36587002 | DOI:10.4037/ajcc2023213

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Nevin Manimala Statistics

Perspectives on determinism in quantum mechanics: Born, Bohm, and the “Quantal Newtonian” laws

J Chem Phys. 2022 Dec 28;157(24):244106. doi: 10.1063/5.0130945.

ABSTRACT

Quantum mechanics has a deterministic Schrödinger equation for the wave function. The Göttingen-Copenhagen statistical interpretation is based on the Born Rule that interprets the wave function as a “probability amplitude.” A precept of this interpretation is the lack of determinism in quantum mechanics. The Bohm interpretation is that the wave function is a source of a field experienced by the electrons, thereby attributing determinism to quantum theory. In this paper, we present a new perspective on such determinism. The ideas are based on the equations of motion or “Quantal Newtonian” Laws obeyed by each electron. These Laws, derived from the temporal and stationary-state Schrödinger equation, are interpreted in terms of “classical” fields whose sources are quantal expectations of Hermitian operators taken with respect to the wave function. According to the Second Law, each electron experiences an external field-the quantal Coulomb-Lorentz law. It also experiences an internal field representative of properties of the system: correlations due to Coulomb repulsion and Pauli principle; the density; kinetic effects; and an internal magnetic field component. There is a response field. The First Law states that the sum of the external and internal fields experienced by each electron vanishes. These fields are akin to those of classical physics: They pervade all space; their structure is descriptive of the quantum system; the energy of the system is stored in these fields. It is in the classical behavior of these fields, which arise from quantal sources that one may then speak of determinism in quantum mechanics.

PMID:36586987 | DOI:10.1063/5.0130945

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Nevin Manimala Statistics

Sonic boom reflection over urban areas

J Acoust Soc Am. 2022 Dec;152(6):3323. doi: 10.1121/10.0016442.

ABSTRACT

Sonic boom propagation over urban areas is studied using numerical simulations based on the Euler equations. Two boom waves are examined: a classical N-wave and a low-boom wave. Ten urban geometries, generated from the local climate zone classification [Stewart and Oke (2012), Bull. Am. Meteorol. Soc. 93(12), 1879-1900], are considered representative of urban forms. They are sorted into two classes, according to the aspect ratio of urban canyons. For compact geometries with a large aspect ratio, the noise levels and the peak pressure, especially for the N-wave, are highly variable between canyons. For open geometries with a small aspect ratio, these parameters present the same evolution in each urban canyon, corresponding to that obtained for isolated buildings. A statistical analysis of the noise levels in urban canyons is then performed. For both boom waves, the median of the perceived noise levels mostly differs by less than 1 dB from the value obtained for flat ground. The range of variation is greater for open geometries than for compact ones. Finally, low-frequency oscillations, associated with resonant modes of the canyons, are present for both compact and open geometries. Their amplitude, frequency and decay rate vary greatly from one canyon to another.

PMID:36586837 | DOI:10.1121/10.0016442