Nevin Manimala

Otol Neurotol. 2021 Oct 25. doi: 10.1097/MAO.0000000000003398. Online ahead of print.

ABSTRACT

INTRODUCTION: Superior canal dehiscence syndrome (SCDS) is a rare disorder characterized by an array of audiovestibular symptoms due to a dehiscence of bone overlying the superior semicircular canal (SSC). In the presence of debilitating symptoms, surgical management, to plug or resurface the SCC is performed. Although computed tomography (CT) may overestimate the size or presence of a dehiscence due to a partial volume effect, it remains an invaluable diagnostic tool.

OBJECTIVES: To assess for correlation between the arc and length of dehiscence and clinical symptomology.

METHOD: A single-center, single-operator retrospective analysis of 42 patients who underwent trans mastoid plugging of SCC with confirmed radiological dehiscence of their SSC between January 2008 and July 2019 was undertaken. Patients were assessed based on seven predefined clinical symptoms. Length and arc of dehiscence’s were evaluated by means of high resolution (0.5 mm) CT (HRCT), using multiplanar reconstruction (MPR). Receiver operating characteristics (ROC), and more specifically the area under the ROC curve (AUROC) were used to assess for statistical significance.

RESULTS: Our results demonstrate overall very little correlation between the arc and size of the dehiscence and symptoms. The only statistically significant correlation we found was between length of dehiscence and the presence of aural fullness.

CONCLUSION: SCDS is a debilitating condition with an array of symptoms on presentation. While dehiscence length demonstrated a correlation with aural fullness, no other symptomology in patients with radiologically evident SCDS demonstrated a statistically significant correlation either against the length or arc of dehiscence.

PMID:34699403 | DOI:10.1097/MAO.0000000000003398

IEEE Trans Med Imaging. 2021 Oct 26;PP. doi: 10.1109/TMI.2021.3123300. Online ahead of print.

ABSTRACT

Despite the promise of Convolutional neural network (CNN) based classification models for histopathological images, it is infeasible to quantify its uncertainties. Moreover, CNNs may suffer from overfitting when the data is biased. We show that Bayesian-CNN can overcome these limitations by regularizing automatically and by quantifying the uncertainty. We have developed a novel technique to utilize the uncertainties provided by the Bayesian-CNN that significantly improves the performance on a large fraction of the test data (about 6% improvement in accuracy on 77% of test data). Further, we provide a novel explanation for the uncertainty by projecting the data into a low dimensional space through a nonlinear dimensionality reduction technique. This dimensionality reduction enables interpretation of the test data through visualization and reveals the structure of the data in a low dimensional feature space. We show that the Bayesian-CNN can perform much better than the state-of-the-art transfer learning CNN (TL-CNN) by reducing the false negative and false positive by 11% and 7.7% respectively for the present data set. It achieves this performance with only 1.86 million parameters as compared to 134.33 million for TL-CNN. Besides, we modify the Bayesian-CNN by introducing a stochastic adaptive activation function. The modified Bayesian-CNN performs slightly better than Bayesian-CNN on all performance metrics and significantly reduces the number of false negatives and false positives (3% reduction for both). We also show that these results are statistically significant by performing McNemar’s statistical significance test. This work shows the advantages of Bayesian-CNN against the state-of-the-art, explains and utilizes the uncertainties for histopathological images. It should find applications in various medical image classifications.

PMID:34699354 | DOI:10.1109/TMI.2021.3123300

Physiother Theory Pract. 2021 Oct 26:1-9. doi: 10.1080/09593985.2021.1996497. Online ahead of print.

ABSTRACT

INTRODUCTION: Respiratory exercise in post-COVID-19 significantly improves pulmonary function, exercise capacity and quality of life. Our study aimed to investigate the effect of respiratory exercise on partial pressures of oxygen, carbon dioxide and oxygen saturation in arterial blood and anxiety assessed by the GAD-7 scale in the acute phase of COVID-19 infection.

METHODS: The study was conducted at the Clinical Center, Kragujevac, from June to July 2020. The study was a prospective clinical trial and included 62 patients with the acute-phase of COVID-19 infection (61.3% males, mean age 60.82 ± 11.72). The duration of the comprehensive pulmonary rehabilitation program was 14 days ± 2.28 days. Oxygen saturation and heart rate were determined by using the pulse oximeter, oxygen flow, and arterial blood gas analysis values by using the gas analyzer. The anxiety assessment was measured using the Generalized Anxiety Disorder (GAD-7).

RESULTS: The values of oxygen saturation significantly differed before and after the respiratory exercise sessions (95.77 vs 98.02, respectively; p < .001). After the respiratory exercise program, significantly lower values of the GAD-7 scale were observed compared to the values before the respiratory exercise program (p = .049). A significant negative correlation was observed between oxygen saturation after respiratory exercise and age and presence of chronic obstructive pulmonary disease (ρ = -0.329; p = .013; ρ = -0.334; p = .009, respectively). GAD-7 score after respiratory exercise negatively correlated with chronic obstructive pulmonary disease and malignancy (ρ = -0.285; p = .025; ρ = -0.350; p = .005, respectively).

CONCLUSION: The respiratory exercise program significantly improves oxygen saturation and anxiety levels in COVID-19 patients.

PMID:34698591 | DOI:10.1080/09593985.2021.1996497

Clin Appl Thromb Hemost. 2021 Jan-Dec;27:10760296211048815. doi: 10.1177/10760296211048815.

ABSTRACT

BACKGROUND: A new clinical syndrome has been recognized following the COVID-19 vaccine, termed thrombosis with thrombocytopenia syndrome (TTS). The following systematic review focuses on extrapolating thrombotic risk factors, clinical manifestations, and outcomes of patients diagnosed with TTS following the COVID-19 vaccine.

METHODS: We utilized the World Health Organization’s criteria for a confirmed and probable case of TTS following COVID-19 vaccination and conducted a systematic review and posthoc analysis using the PRISMA 2020 statement. Data analysis was conducted using SPSS V25 for factors associated with mortality, including age, gender, anti-PF4/heparin antibodies, platelet nadir, D-dimer peak, time to event diagnosis, arterial or venous thrombi.

RESULTS: Of the 175 studies identified, a total of 25 studies with 69 patients were included in this systematic review and post hoc analysis. Platelet nadir (P < .001), arterial or venous thrombi (χ2 = 41.911, P = .05), and chronic medical conditions (χ2 = 25.507, P = .041) were statistically associated with death. The ROC curve analysis yielded D-dimer (AUC = .646) and platelet nadir (AUC = .604) as excellent models for death prediction.

CONCLUSION: Adenoviral COVID-19 vaccines have been shown to trigger TTS, however, reports of patients having received mRNA COVID-19 vaccines are also present. Healthcare providers are recommended to maintain a high degree of suspicion among individuals who have received the COVID-19 vaccine within the last 4 weeks.

PMID:34698582 | DOI:10.1177/10760296211048815

Eval Rev. 2021 Oct 26:193841X211053937. doi: 10.1177/0193841X211053937. Online ahead of print.

ABSTRACT

Propensity score methods provide data preprocessing tools to remove selection bias and attain statistically comparable groups – the first requirement when attempting to estimate causal effects with observational data. Although guidelines exist on how to remove selection bias when groups in comparison are large, not much is known on how to proceed when one of the groups in comparison, for example, a treated group, is particularly small, or when the study also includes lots of observed covariates (relative to the treated group’s sample size). This article investigates whether propensity score methods can help us to remove selection bias in studies with small treated groups and large amount of observed covariates. We perform a series of simulation studies to study factors such as sample size ratio of control to treated units, number of observed covariates and initial imbalances in observed covariates between the groups of units in comparison, that is, selection bias. The results demonstrate that selection bias can be removed with small treated samples, but under different conditions than in studies with large treated samples. For example, a study design with 10 observed covariates and eight treated units will require the control group to be at least 10 times larger than the treated group, whereas a study with 500 treated units will require at least, only, two times bigger control group. To confirm the usefulness of simulation study results for practice, we carry out an empirical evaluation with real data. The study provides insights for practice and directions for future research.

PMID:34698560 | DOI:10.1177/0193841X211053937

mSystems. 2021 Oct 26;6(5):e0009521. doi: 10.1128/mSystems.00095-21. Epub 2021 Oct 26.

ABSTRACT

The novel coronavirus SARS-CoV-2, which emerged in late 2019, has since spread around the world and infected hundreds of millions of people with coronavirus disease 2019 (COVID-19). While this viral species was unknown prior to January 2020, its similarity to other coronaviruses that infect humans has allowed for rapid insight into the mechanisms that it uses to infect human hosts, as well as the ways in which the human immune system can respond. Here, we contextualize SARS-CoV-2 among other coronaviruses and identify what is known and what can be inferred about its behavior once inside a human host. Because the genomic content of coronaviruses, which specifies the virus’s structure, is highly conserved, early genomic analysis provided a significant head start in predicting viral pathogenesis and in understanding potential differences among variants. The pathogenesis of the virus offers insights into symptomatology, transmission, and individual susceptibility. Additionally, prior research into interactions between the human immune system and coronaviruses has identified how these viruses can evade the immune system’s protective mechanisms. We also explore systems-level research into the regulatory and proteomic effects of SARS-CoV-2 infection and the immune response. Understanding the structure and behavior of the virus serves to contextualize the many facets of the COVID-19 pandemic and can influence efforts to control the virus and treat the disease. IMPORTANCE COVID-19 involves a number of organ systems and can present with a wide range of symptoms. From how the virus infects cells to how it spreads between people, the available research suggests that these patterns are very similar to those seen in the closely related viruses SARS-CoV-1 and possibly Middle East respiratory syndrome-related CoV (MERS-CoV). Understanding the pathogenesis of the SARS-CoV-2 virus also contextualizes how the different biological systems affected by COVID-19 connect. Exploring the structure, phylogeny, and pathogenesis of the virus therefore helps to guide interpretation of the broader impacts of the virus on the human body and on human populations. For this reason, an in-depth exploration of viral mechanisms is critical to a robust understanding of SARS-CoV-2 and, potentially, future emergent human CoVs (HCoVs).

PMID:34698547 | DOI:10.1128/mSystems.00095-21

J Comput Biol. 2021 Oct 25. doi: 10.1089/cmb.2021.0306. Online ahead of print.

ABSTRACT

This article presents a novel scalable character-based phylogeny algorithm for dense viral sequencing data called SPHERE (Scalable PHylogEny with REcurrent mutations). The algorithm is based on an evolutionary model where recurrent mutations are allowed, but backward mutations are prohibited. The algorithm creates rooted character-based phylogeny trees, wherein all leaves and internal nodes are labeled by observed taxa. We show that SPHERE phylogeny is more stable than Nextstrain’s, and that it accurately infers known transmission links from the early pandemic. SPHERE is a fast algorithm that can process >200,000 sequences in <2 hours, which offers a compact phylogenetic visualization of Global Initiative on Sharing All Influenza Data (GISAID).

PMID:34698524 | DOI:10.1089/cmb.2021.0306

Nurs Educ Perspect. 2021 Nov-Dec 01;42(6):371-373. doi: 10.1097/01.NEP.0000000000000786.

ABSTRACT

The purpose of this quasi-experimental study was to evaluate best strategies for teaching intimate partner violence (IPV) education in an undergraduate community health nursing course. Results suggest gaming was a more effective strategy than storytelling for knowledge acquisition and storytelling was more effective for knowledge retention. IPV-related nursing interventions can impact client outcomes; therefore, education is needed prior to entering the workforce. The evaluation of strategies to improve knowledge acquisition and retention of IPV content is essential to ensure best practices for detection and intervention.

PMID:34698473 | DOI:10.1097/01.NEP.0000000000000786

Diagn Cytopathol. 2021 Oct 26. doi: 10.1002/dc.24896. Online ahead of print.

ABSTRACT

BACKGROUND: Preserving the optimal quality of DNA and RNA is mandatory for molecular testing in lung adenocarcinoma cytological smears (LACSs).

METHODS: DNA and RNA were isolated from 90 frozen unstained and 46 May Grünwald Giemsa (MGG) stained LACSs prepared from bronchial washing (BW), bronchial brushing (BB), and pleural effusion (PE) samples during 3 years. Concentrations of nucleic acids in all LACSs were assessed by spectrophotometric analysis. Fragmentation of DNA and RNA was determined by PCR amplification of selected genes. Amplicons of 100, 200, 300, 400, and 600 bp were used for DNA and 108 bp-long HPRT1 transcript fragment for RNA fragmentation analysis.

RESULTS: Among 90 frozen LACSs, significantly lower DNA concentrations of BB and RNA concentrations of BW samples frozen for 6-10 months were observed in comparison with samples frozen for longer periods (p < .05). Among 46 paired LACSs, 44 (95.7%) frozen and 15 (32.6%) MGG-stained samples showed 600 bp-long DNA amplicons. Statistically significant difference (p < .05) in the fragmentation of DNA between frozen and MGG-stained LACSs was observed (p < .05), with DNA being less fragmented in frozen LACSs. In addition, 33 (71.7%) frozen and 36 (78.2%) MGG-stained LASCs showed HPRT1 gene amplicon of 108 bp. RNA was less fragmented in 3-year old MGG-stained samples than in LACSs frozen for 3 years.

CONCLUSION: DNA and RNA extracted from frozen and MGG-stained LACSs showed different results depending on the time of storage and/or type of samples, but in general all samples had adequate quantity and quality for downstream molecular testing.

PMID:34698443 | DOI:10.1002/dc.24896

Pediatr Transplant. 2021 Oct 26:e14158. doi: 10.1111/petr.14158. Online ahead of print.

ABSTRACT

BACKGROUND: The aim of this study was to assess improvements in long-term survival of pediatric patients after liver transplantation by analyzing outcomes in transplant recipients who survived beyond 1 year after transplantation. There has been a marked increase in the 1-year survival of pediatric patients, from 78% in transplant recipients between 1987 and 1990 to 95% in transplant recipients between 2011 and 2017. The long-term outcomes have not seen a similar trend, creating a disparity that warrants analysis.

METHODS: We analyzed 13 753 pediatric patients who survived for 1 year after receiving orthotopic liver transplantation between 1987 and 2017. The study period was divided into six eras. Outcomes were analyzed using the Kaplan-Meier method for time-to-event analysis, and multivariable Cox regression.

RESULTS: There were no significant gains in long-term outcomes among 1-year survivors over the past three decades. Log-rank tests for equality of survivor functions between each era and 1987-1990 were not statistically significant. Cause of death analysis revealed that although infections caused 20.6% of deaths in patients transplanted between 1987 and 1990, this number dropped to 5.6% in those transplanted between 2011 and 2017 (p = .01). Malignancy caused 10.6% of deaths in 1987-1990 but caused 22.2% of the deaths in 2011-2017 (p = .04).

CONCLUSION: Despite the gratifying gains in short-term survival of pediatric patients, 1-year survivors have no significant improvements in long-term survival after undergoing a liver transplantation. Long-term sequelae of immunosuppression, such as malignancy and infection, continue to be the most common causes of death. This study highlights the necessity for better long-term management of immunosuppression.

PMID:34698432 | DOI:10.1111/petr.14158