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Nevin Manimala Statistics

The Link Between Spinal Cord Stimulation and the Parasympathetic Nervous System in Patients With Failed Back Surgery Syndrome

Neuromodulation. 2022 Jan;25(1):128-136. doi: 10.1111/ner.13400.

ABSTRACT

OBJECTIVES: In patients with chronic pain, a relative lower parasympathetic activity is suggested based on heart rate variability measurements. It is hypothesized that spinal cord stimulation (SCS) is able to influence the autonomic nervous system. The aim of this study is to further explore the influence of SCS on the autonomic nervous system by evaluating whether SCS is able to influence skin conductance, blood volume pulse, heart rate, and respiration rate.

MATERIALS AND METHODS: Twenty-eight patients with Failed Back Surgery Syndrome (FBSS), who are being treated with SCS, took part in this multicenter study. Skin conductance and cardiorespiratory parameters (blood volume pulse, heart rate, and respiration rate) were measured during on and off states of SCS. Paired statistics were performed on a 5-min recording segment for all parameters.

RESULTS: SCS significantly decreased back and leg pain intensity scores in patients with FBSS. Skin conductance level and blood volume pulse were not altered between on and off states of SCS. Heart rate and respiration rate significantly decreased when SCS was activated.

CONCLUSIONS: Parameters that are regulated by the sympathetic nervous system were not significantly different between SCS on and off states, leading to the hypothesis that SCS is capable of restoring the dysregulation of the autonomic nervous system by primarily increasing the activity of the parasympathetic system in patients with FBSS.

PMID:35041582 | DOI:10.1111/ner.13400

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Nevin Manimala Statistics

Causes-of-Death Specific Estimates from Synthetic Health Measure: A Methodological Framework

Soc Indic Res. 2022 Jan 13:1-22. doi: 10.1007/s11205-021-02870-w. Online ahead of print.

ABSTRACT

Life expectancy at birth has attracted interest in various fields, as a health indicator that measures the quality of life. Its appeal relies on the ability to enclose and summarize all the factors affecting longevity. However, more granular information, provided by social indicators such as cause-of-death mortality rates, plays a crucial role in defining appropriate policies for governments to achieve well-being and sustainability goals. Unfortunately, their availability is not always guaranteed. Exploiting the relationship between life expectancy at birth and cause-of-death mortality rates, in this paper we propose an indirect model to produce estimates of death rates due to specific causes using the summary indicator of life expectancy at birth, thus the general levels of the observed mortality. By leveraging on a constrained optimization procedure, we ensure a robust framework where the cause-specific mortality rates are coherent to the aggregate mortality. The main advantage is that indirect estimations allow us to overcome the data availability problem: very often the cause-specific mortality data are incomplete, whereas data on the aggregate mortality are not. Using data from the Human Cause-of-Death Database, we show a numerical application of our model to two different countries, Russia and Spain, which have experienced a different evolution of life expectancy and different leading causes of death. In Spain, we detected the impact of several public health policies on the lowered levels of cancer deaths and related life expectancy increases. As regards the Russia, our results catch the effects of the anti-alcohol campaign of 1985-1988 on longevity changes.

PMID:35039708 | PMC:PMC8756417 | DOI:10.1007/s11205-021-02870-w

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Nevin Manimala Statistics

Clinical condition, Resuscitation and Medical-Psychological Care of Severe COVID-19 patients (part 2)

Ann Med Psychol (Paris). 2022 Jan 13. doi: 10.1016/j.amp.2022.01.002. Online ahead of print.

ABSTRACT

Respiratory rehabilitation is the penultimate step in the medical management of patients with severe COPD-19. It is an essential step before patients’ returning home, and is usually carried out in specialised Follow-up and Rehabilitation Clinics. When discharged from hospital, patients with post-severe COVID-19 usually progress in their medical condition. However, they may remain frail and have a constant fear of possible deterioration leading to (re)hospitalisation and a return to baseline. Psychological support in this phase can reduce patients’ anxiety and increase their motivation to carry out daily rehabilitation activities. This support provides a stable and consistent basis for patients to focus on their progress, leaving the difficulties behind. Being aware of the improvements in their physical condition allows them to maintain their motivation to continue to be physically active. Psychological support during respiratory rehabilitation aims at preparing patients to return to the normal life they had before the disease. It is usually based on brief psychotherapies that focus on strengthening the patient’s abilities through behavioural changes and through reducing risk behaviours. Only after this phase is it sometimes possible to deal with complex issues and to cope with personality mechanisms and maladaptive behaviour patterns.

PMID:35039685 | PMC:PMC8755421 | DOI:10.1016/j.amp.2022.01.002

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Nevin Manimala Statistics

The relay for human longevity: country-specific contributions to the increase of the best-practice life expectancy

Qual Quant. 2022 Jan 13:1-13. doi: 10.1007/s11135-021-01298-1. Online ahead of print.

ABSTRACT

This study investigates the long-term dynamics of longevity by taking into account the specific contribution of each country, and how this has changed over time, thus highlighting different timing and speeds of the evolution of life expectancy among the low-lowest mortality countries. Leveraging on quantile regression, we analyze the specific position of countries that have recorded the maximum (BPLE) and second-best life expectancy value at least once in the period 1960-2014, both at ages 0 and 65. Moving in this direction, the purpose of our contribution is to provide new perspectives on the untracked behavior that may be overshadowed by the maximum longevity levels. Our results provide a comprehensive picture of the different phases and transitions experienced by developed countries in the evolution of life expectancy that has led to a continuous increase in the BPLE. This study is a prominent practice in detecting untracked behaviors, providing imminent onsets on the maximum and sub-maximum values, thus contributing to new clues for future longevity.

PMID:35039691 | PMC:PMC8754529 | DOI:10.1007/s11135-021-01298-1

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Nevin Manimala Statistics

Discovery of signatures of fatal neonatal illness in vital signs using highly comparative time-series analysis

NPJ Digit Med. 2022 Jan 17;5(1):6. doi: 10.1038/s41746-021-00551-z.

ABSTRACT

To seek new signatures of illness in heart rate and oxygen saturation vital signs from Neonatal Intensive Care Unit (NICU) patients, we implemented highly comparative time-series analysis to discover features of all-cause mortality in the next 7 days. We collected 0.5 Hz heart rate and oxygen saturation vital signs of infants in the University of Virginia NICU from 2009 to 2019. We applied 4998 algorithmic operations from 11 mathematical families to random daily 10 min segments from 5957 NICU infants, 205 of whom died. We clustered the results and selected a representative from each, and examined multivariable logistic regression models. 3555 operations were usable; 20 cluster medoids held more than 81% of the information, and a multivariable model had AUC 0.83. New algorithms outperformed others: moving threshold, successive increases, surprise, and random walk. We computed provenance of the computations and constructed a software library with links to the data. We conclude that highly comparative time-series analysis revealed new vital sign measures to identify NICU patients at the highest risk of death in the next week.

PMID:35039624 | DOI:10.1038/s41746-021-00551-z

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Nevin Manimala Statistics

Effect of the toothbrush tuft arrangement and bristle stiffness on the abrasive dentin wear

Sci Rep. 2022 Jan 17;12(1):840. doi: 10.1038/s41598-022-04884-x.

ABSTRACT

The geometrical properties of toothbrushes play a role in developing abrasive tooth wear and non-carious cervical lesions. This study investigated the interplay between the toothbrush tuft arrangement (crossed vs. parallel) and bristle stiffness (soft vs. medium) on the abrasive dentin wear using three slurries with different levels of abrasivity (RDA: 67, 121 and 174). Twelve groups of bovine dentin samples (n = 20) were brushed with a combination of the aforementioned variables. Abrasive dentin wear was recorded with a profilometer and the resulting abrasive wear of each group was calculated and compared with each other using two-way ANOVA and pairwise tests. Toothbrushes with parallel tuft arrangement caused statistically significantly higher dentin wear compared to crossed tuft arrangement, regardless of the abrasivity level of the used slurry and the bristle stiffness. Soft crossed tuft toothbrushes caused statistically significantly higher abrasive dentin wear than medium crossed tuft toothbrushes, while soft and medium parallel tuft toothbrushes caused the same amounts of dentin wear, regardless of the RDA value of the used slurry. These results could be helpful for dentists and dental hygienists when advising patients. Crossed tuft toothbrushes could be a less-abrasive choice in comparison to parallel tuft toothbrushes.

PMID:35039599 | DOI:10.1038/s41598-022-04884-x

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Nevin Manimala Statistics

Objective evaluation of deep uncertainty predictions for COVID-19 detection

Sci Rep. 2022 Jan 17;12(1):815. doi: 10.1038/s41598-022-05052-x.

ABSTRACT

Deep neural networks (DNNs) have been widely applied for detecting COVID-19 in medical images. Existing studies mainly apply transfer learning and other data representation strategies to generate accurate point estimates. The generalization power of these networks is always questionable due to being developed using small datasets and failing to report their predictive confidence. Quantifying uncertainties associated with DNN predictions is a prerequisite for their trusted deployment in medical settings. Here we apply and evaluate three uncertainty quantification techniques for COVID-19 detection using chest X-Ray (CXR) images. The novel concept of uncertainty confusion matrix is proposed and new performance metrics for the objective evaluation of uncertainty estimates are introduced. Through comprehensive experiments, it is shown that networks pertained on CXR images outperform networks pretrained on natural image datasets such as ImageNet. Qualitatively and quantitatively evaluations also reveal that the predictive uncertainty estimates are statistically higher for erroneous predictions than correct predictions. Accordingly, uncertainty quantification methods are capable of flagging risky predictions with high uncertainty estimates. We also observe that ensemble methods more reliably capture uncertainties during the inference. DNN-based solutions for COVID-19 detection have been mainly proposed without any principled mechanism for risk mitigation. Previous studies have mainly focused on on generating single-valued predictions using pretrained DNNs. In this paper, we comprehensively apply and comparatively evaluate three uncertainty quantification techniques for COVID-19 detection using chest X-Ray images. The novel concept of uncertainty confusion matrix is proposed and new performance metrics for the objective evaluation of uncertainty estimates are introduced for the first time. Using these new uncertainty performance metrics, we quantitatively demonstrate when we could trust DNN predictions for COVID-19 detection from chest X-rays. It is important to note the proposed novel uncertainty evaluation metrics are generic and could be applied for evaluation of probabilistic forecasts in all classification problems.

PMID:35039620 | DOI:10.1038/s41598-022-05052-x

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Nevin Manimala Statistics

Joint analysis of the intention to vaccinate and to use contact tracing app during the COVID-19 pandemic

Sci Rep. 2022 Jan 17;12(1):793. doi: 10.1038/s41598-021-04765-9.

ABSTRACT

Pharmacological and non-pharmacological measures will overlap for a period after the onset of the pandemic, playing a strong role in virus containment. We explored which factors influence the likelihood to adopt two different preventive measures against the COVID-19 pandemic. An online snowball sampling (May-June 2020) collected a total of 448 questionnaires in Italy. A Bayesian bivariate Gaussian regression model jointly investigated the willingness to get vaccinated against COVID-19 and to download the national contact tracing app. A mixed-effects cumulative logistic model explored which factors affected the motivation to adopt one of the two preventive measures. Despite both COVID-19 vaccines and tracing apps being indispensable tools to contain the spread of SARS-CoV-2, our results suggest that adherence to the vaccine or to the national contact tracing app is not predicted by the same factors. Therefore, public communication on these measures needs to take in consideration not only the perceived risk associated with COVID-19, but also the trust people place in politics and science, their concerns and doubts about vaccinations, and their employment status. Further, the results suggest that the motivation to comply with these measurements was predominantly to protect others rather than self-protection.

PMID:35039550 | DOI:10.1038/s41598-021-04765-9

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Nevin Manimala Statistics

Long-term metal fume exposure assessment of workers in a shipbuilding factory

Sci Rep. 2022 Jan 17;12(1):790. doi: 10.1038/s41598-021-04761-z.

ABSTRACT

This study aims to assess the metal fume exposure of welders and to determine exposure rates for similar exposure groups in a shipyard through the use of Near-field/Far-field (NF/FF) mathematical model and Bayesian decision analysis (BDA) technique. Emission rates of various metal fumes (i.e., total chromium (Cr), iron (Fe), lead (Pb), manganese (Mn), and nickel (Ni)) were experimentally determined for the gas metal arc welding and flux cored arc welding processes, which are commonly used in shipyards. Then the NF/FF field model which used the emission rates were further validated by welding simulation experiment, and together with long-term operation condition data obtained from the investigated shipyard, the predicted long-term exposure concentrations of workers was established and used as the prior distribution in the BDA. Along with the field monitoring metal fume concentrations which served as the likelihood distribution, the posterior decision distributions in the BDA were determined and used to assess workers’ long-term metal exposures. Results show that the predicted exposure concentrations (Cp) and the field worker’s exposure concentrations (Cm) were statistically correlated, and the high R2 (= 0.81-0.94) indicates that the proposed surrogate predicting method by the NF and FF model was adequate for predicting metal fume concentrations. The consistency in both prior and likelihood distributions suggests the resultant posterior would be more feasible to assess workers’ long-term exposures. Welders’ Fe, Mn and Pb exposures were found to exceed their corresponding action levels with a high probability (= 54%), indicating preventive measures should be taken immediately. The proposed approach provides a universal solution for conducting exposure assessment with usual limited number of personal exposure data.

PMID:35039543 | DOI:10.1038/s41598-021-04761-z

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Nevin Manimala Statistics

The impairment of speech perception in noise following pure tone hearing recovery in patients with sudden sensorineural hearing loss

Sci Rep. 2022 Jan 17;12(1):866. doi: 10.1038/s41598-021-03847-y.

ABSTRACT

To explore whether patients with unilateral idiopathic sudden sensorineural hearing loss (uISSNHL) have normal speech in noise (SIN) perception under different masking conditions after complete recovery of pure tone audiometry. Eight completely recovered uISSNHL patients were enrolled in ISSNHL group, while 8 normal-hearing adults matched with age, gender, and education experience were selected as the control group. Each group was tested SIN under four masking conditions, including noise and speech maskings with and without spatial separation cues. For both ISSNHL and control groups a two-way ANOVA showed a statistically significant effect of masking type (p = 0.007 vs p = 0.012). A significant effect of perceived spatial separation (p < 0.001 vs p < 0.001). A significant interaction between masking type and perceived spatial separation was found (p < 0.001 vs p < 0.001). A paired sample T-test showed that the SIN perception of the control group was statistically significant lower than that of ISSNHL patients only under speech masking without spatial separation cues (p = 0.011). There were still abnormalities in the auditory center shortly after complete recovery in the ISSNHL group (within 2 weeks). However, the auditory periphery and higher-level ability to use spatial cues was normal.

PMID:35039548 | DOI:10.1038/s41598-021-03847-y