Category: Statistics

J Bone Joint Surg Am. 2022 Jan 18. doi: 10.2106/JBJS.21.00785. Online ahead of print.

ABSTRACT

BACKGROUND: Next-generation DNA sequencing (NGS) detects bacteria-specific DNA corresponding to the 16S ribosomal RNA gene and can identify bacterial presence with greater accuracy than traditional culture methods. The clinical relevance of these findings is unknown. The purpose of the present study was to compare the results from bacterial culture and NGS in order to characterize the potential use of NGS in orthopaedic trauma patients.

METHODS: A prospective cohort study was performed at a single academic, level-I trauma center. Three patient groups were enrolled: (1) patients undergoing surgical treatment of acute closed fractures (presumed to have no bacteria), (2) patients undergoing implant removal at the site of a healed fracture without infection, and (3) patients undergoing a first procedure for the treatment of a fracture nonunion who might or might not have subclinical infection. Surgical site tissue was sent for culture and NGS. The proportions of culture and NGS positivity were compared among the groups. The agreement between culture and NGS results was assessed with use of the Cohen kappa statistic.

RESULTS: Bacterial cultures were positive in 9 of 111 surgical sites (110 patients), whereas NGS was positive in 27 of 111 surgical sites (110 patients). Significantly more cases were positive on NGS as compared with culture (24% vs. 8.1%; p = 0.001), primarily in the acute closed fracture group. No difference was found in terms of the percent positivity of NGS when comparing the acute closed fracture, implant removal, and nonunion groups. With respect to bacterial identification, culture and NGS agreed in 73% of cases (κ = 0.051; 95% confidence interval, -0.12 to 0.22) indicating only slight agreement compared with expected chance agreement of 50%.

CONCLUSIONS: NGS identified bacterial presence more frequently than culture, but with only slight agreement between culture and NGS. It is possible that the increased frequency of bacterial detection with molecular methods is reflective of biofilm presence on metal or colonization with nonpathogenic bacteria, as culture methods have selection pressure posed by restrictive, artificial growth conditions and there are low metabolic activity and replication rates of bacteria in biofilms. Our data suggest that NGS should not currently substitute for or complement conventional culture in orthopaedic trauma cases with low suspicion of infection.

LEVEL OF EVIDENCE: Diagnostic Level II. See Instructions for Authors for a complete description of levels of evidence.

PMID:35041629 | DOI:10.2106/JBJS.21.00785

Neuromodulation. 2022 Jan;25(1):53-63. doi: 10.1111/ner.13460.

ABSTRACT

OBJECTIVE: The objective of this preclinical study was to examine the responses of the brain to noxious stimulation in the presence and absence of different modes of spinal cord stimulation (SCS) using blood-oxygen-level-dependent functional magnetic resonance imaging (BOLD-fMRI).

MATERIALS AND METHODS: Sprague-Dawley rats were randomized to groups based on the mode of SCS delivered which included tonic stimulation (n = 27), burst stimulation (n = 30), and burst-cycle stimulation (n = 29). The control (sham) group (n = 28) received no SCS. The SCS electrode was inserted between T10 and T12 spinal levels prior to fMRI session. The experimental protocol for fMRI acquisition consisted of an initial noxious stimulation phase, a treatment phase wherein the SCS was turned on concurrently with noxious stimulation, and a residual effect phase wherein the noxious stimulation alone was turned on. The responses were statistically analyzed through paired t-test and the results were presented as z-scores for the quantitative analysis of the fMRI data.

RESULTS: The treatment with different SCS modes attenuated the BOLD brain responses to noxious hindlimb stimulation. The tonic, burst, and burst-cycle SCS treatment attenuated BOLD responses in the caudate putamen (CPu), insula (In), and secondary somatosensory cortex (S2). There was little to no corresponding change in sham control in these three regions. The burst and burst-cycle SCS demonstrated greater attenuation of BOLD signals in CPu, In, and S2 compared to tonic stimulation.

CONCLUSION: The high-resolution fMRI study using a rat model demonstrated the potential of different SCS modes to act on several pain-matrix-related regions of the brain in response to noxious stimulation. The burst and burst-cycle SCS exhibited greater brain activity reduction in response to noxious hindlimb stimulation in the caudate putamen, insula, and secondary somatosensory cortex compared to tonic stimulation.

PMID:35041588 | DOI:10.1111/ner.13460

IEEE Trans Neural Syst Rehabil Eng. 2022 Jan 18;PP. doi: 10.1109/TNSRE.2022.3144169. Online ahead of print.

ABSTRACT

Deep sleep staging networks have reached top performance on large-scale datasets. However, these models perform poorer when training and testing on small sleep cohorts due to data inefficiency. Transferring well-trained models from large-scale datasets (source domain) to small sleep cohorts (target domain) is a promising solution but still remains challenging due to the domain-shift issue. In this work, an unsupervised domain adaptation approach, domain statistics alignment (DSA), is developed to bridge the gap between the data distribution of source and target domains. DSA adapts the source models on the target domain by modulating the domain-specific statistics of deep features stored in the Batch Normalization (BN) layers. Furthermore, we have extended DSA by introducing cross-domain statistics in each BN layer to perform DSA adaptively (AdaDSA). The proposed methods merely need the well-trained source model without access to the source data, which may be proprietary and inaccessible. DSA and AdaDSA are universally applicable to various deep sleep staging networks that have BN layers. We have validated the proposed methods by extensive experiments on two state-of-the-art deep sleep staging networks, DeepSleepNet+ and U-time. The performance was evaluated by conducting various transfer tasks on six sleep databases, including two large-scale databases, MASS and SHHS, as the source domain, four small sleep databases as the target domain. Thereinto, clinical sleep records acquired in Huashan Hospital, Shanghai, were used. The results show that both DSA and AdaDSA could significantly improve the performance of source models on target domains, providing novel insights into the domain generalization problem in sleep staging tasks.

PMID:35041607 | DOI:10.1109/TNSRE.2022.3144169

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

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

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

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

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

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

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