Nevin Manimala

PLoS One. 2022 Jun 17;17(6):e0270196. doi: 10.1371/journal.pone.0270196. eCollection 2022.

ABSTRACT

BACKGROUND: The ongoing COVID-19 pandemic has claimed >4 million lives globally, and these deaths often occurred in hospitalized patients with comorbidities. Therefore, the proposed review aims to distinguish the inpatient mortality and invasive mechanical ventilation risk in COVID-19 patients treated with the anti-SARS-CoV-2 monoclonal antibodies and/or the antiviral agents.

METHODS: A search in PubMed, Embase, and Scopus will ensue for the publications on randomized controlled trials testing the above, irrespective of the publication date or geographic boundary. Risk of bias assessment of the studies included in the review will occur using the Cochrane risk of bias tool for randomized trials (RoB 2). Frequentist method network meta-analyses (NMA) will compare each outcome’s risk across both types of anti-SARS-CoV-2 agents in one model and each in separate models. Additional NMA models will compare these in COVID-19 patients who were severely or critically ill, immunocompromised, admitted to the intensive care unit, diagnosed by nucleic acid amplification test, not treated with steroids, <18 years old, and at risk of infection due to variants of concern. The plan of excluding non-hospitalized patients from the proposed review is to minimize intransitivity risk. The acceptance of the network consistency assumption will transpire if the local and overall inconsistency assessment indicates no inconsistency. For each NMA model, the effect sizes (risk ratio) and their 95% confidence intervals will get reported in league tables. The best intervention prediction and quality of evidence grading will happen using the surface under the cumulative ranking curve values and the Grading of Recommendations Assessment, Development and Evaluation-based Confidence in Network Meta-Analysis approach, respectively. Sensitivity analysis will repeat the preliminary NMA while excluding the trials at high risk of bias. The Stata statistical software (v16) will be used for analysis. The statistical significance will get determined at p<0.05 and 95% confidence interval.

TRIAL REGISTRATION: PROSPERO Registration No: https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42021277663.

PMID:35714102 | DOI:10.1371/journal.pone.0270196

IEEE Trans Neural Netw Learn Syst. 2022 Jun 17;PP. doi: 10.1109/TNNLS.2022.3174528. Online ahead of print.

ABSTRACT

Brain-computer interface (BCI) actively translates the brain signals into executable actions by establishing direct communication between the human brain and external devices. Recording brain activity through electroencephalography (EEG) is generally contaminated with both physiological and nonphysiological artifacts, which significantly hinders the BCI performance. Artifact subspace reconstruction (ASR) is a well-known statistical technique that automatically removes artifact components by determining the rejection threshold based on the initial reference EEG segment in multichannel EEG recordings. In real-world applications, the fixed threshold may limit the efficacy of the artifact correction, especially when the quality of the reference data is poor. This study proposes an adaptive online ASR technique by integrating the Hebbian/anti-Hebbian neural networks into the ASR algorithm, namely, principle subspace projection ASR (PSP-ASR) and principal subspace whitening ASR (PSW-ASR) that segmentwise self-organize the artifact subspace by updating the synaptic weights according to the Hebbian and anti-Hebbian learning rules. The effectiveness of the proposed algorithm is compared to the conventional ASR approaches on benchmark EEG dataset and three BCI frameworks, including steady-state visual evoked potential (SSVEP), rapid serial visual presentation (RSVP), and motor imagery (MI) by evaluating the root-mean-square error (RMSE), the signal-to-noise ratio (SNR), the Pearson correlation, and classification accuracy. The results demonstrated that the PSW-ASR algorithm effectively removed the EEG artifacts and retained the activity-specific brain signals compared to the PSP-ASR, standard ASR (Init-ASR), and moving-window ASR (MW-ASR) methods, thereby enhancing the SSVEP, RSVP, and MI BCI performances. Finally, our empirical results from the PSW-ASR algorithm suggested the choice of an aggressive cutoff range of c = 1-10 for activity-specific BCI applications and a moderate range of for the benchmark dataset and general BCI applications.

PMID:35714085 | DOI:10.1109/TNNLS.2022.3174528

IEEE Trans Neural Netw Learn Syst. 2022 Jun 17;PP. doi: 10.1109/TNNLS.2022.3181378. Online ahead of print.

ABSTRACT

Tensor completion is a fundamental tool for incomplete data analysis, where the goal is to predict missing entries from partial observations. However, existing methods often make the explicit or implicit assumption that the observed entries are noise-free to provide a theoretical guarantee of exact recovery of missing entries, which is quite restrictive in practice. To remedy such drawback, this article proposes a novel noisy tensor completion model, which complements the incompetence of existing works in handling the degeneration of high-order and noisy observations. Specifically, the tensor ring nuclear norm (TRNN) and least-squares estimator are adopted to regularize the underlying tensor and the observed entries, respectively. In addition, a nonasymptotic upper bound of estimation error is provided to depict the statistical performance of the proposed estimator. Two efficient algorithms are developed to solve the optimization problem with convergence guarantee, one of which is specially tailored to handle large-scale tensors by replacing the minimization of TRNN of the original tensor equivalently with that of a much smaller one in a heterogeneous tensor decomposition framework. Experimental results on both synthetic and real-world data demonstrate the effectiveness and efficiency of the proposed model in recovering noisy incomplete tensor data compared with state-of-the-art tensor completion models.

PMID:35714084 | DOI:10.1109/TNNLS.2022.3181378

PLoS One. 2022 Jun 17;17(6):e0269306. doi: 10.1371/journal.pone.0269306. eCollection 2022.

ABSTRACT

We compare several popular methods of estimating the basic reproduction number, R0, focusing on the early stages of an epidemic, and assuming weekly reports of new infecteds. We study the situation when data is generated by one of three standard epidemiological compartmental models: SIR, SEIR, and SEAIR; and examine the sensitivity of the estimators to the model structure. As some methods are developed assuming specific epidemiological models, our work adds a study of their performance in both a well-specified (data generating model and method model are the same) and miss-specified (data generating model and method model differ) settings. We also study R0 estimation using Canadian COVID-19 case report data. In this study we focus on examples of influenza and COVID-19, though the general approach is easily extendable to other scenarios. Our simulation study reveals that some estimation methods tend to work better than others, however, no singular best method was clearly detected. In the discussion, we provide recommendations for practitioners based on our results.

PMID:35714080 | DOI:10.1371/journal.pone.0269306

J Anim Sci. 2022 Jun 17:skac222. doi: 10.1093/jas/skac222. Online ahead of print.

ABSTRACT

Precision feeding (PF) aims to provide the right amount of nutrients at the right time for each animal. Lactating sows generally receive the same diet, which either results in insufficient supply and body reserve mobilization, or excessive supply and high nutrient excretion. With the help of online measuring devices, computational methods, and smart feeders, we introduced the first PF decision support system (DSS) for lactating sows. Precision (PRE) and conventional (STD) feeding strategies were compared in commercial conditions. Every day each PRE sow received a tailored ration that had been computed by the DSS. This ration was obtained by blending a diet with a high AA and mineral content (13.00 g/kg SID Lys, 4.50 g/kg digestible P) and a diet low in AAs and minerals (6.50 g/kg SID Lys, 2.90 g/kg digestible P). All STD sows received a conventional diet (10.08 g/kg SID Lys, 3.78 g/kg digestible P). Before the trial, the DSS was fitted to farm performance for the prediction of piglet average daily gain (PADG) and sow daily feed intake (DFI), with data from 1,691 and 3,712 lactations, respectively. Sow and litter performance were analyzed for the effect of feeding strategy with ANOVA, with results considered statistically significant when P<0.05. The experiment involved 239 PRE and 240 STD sows. DFI was similarly high in both treatments (PRE: 6.59, STD: 6.45 kg/d; P=0.11). Litter growth was high (PRE: 2.96, STD: 3.06 kg/d), although it decreased slightly by about 3% in PRE compared to STD treatments (P<0.05). Sow body weight loss was low, although it was slightly higher in PRE sows (7.7 versus 2.1 kg, P<0.001), which might be due to insufficient AA supply in some sows. Weaning to estrus interval (5.6 d) did not differ. In PRE sows SID Lys intake (PRE: 7.7, STD: 10.0 g/kg; P<0.001) and digestible P intake (PRE: 3.2, STD: 3.8 g/kg; P<0.001) declined by 23% and 14%, respectively, and feed cost decreased by 12%. For PRE sows, excretion of N and P decreased by 28% and 42%, respectively. According to these results, PF appears to be a very promising strategy for lactating sows.

PMID:35714053 | DOI:10.1093/jas/skac222

JMIR Form Res. 2022 Jun 17;6(6):e33089. doi: 10.2196/33089.

ABSTRACT

BACKGROUND: Mobile games can be effective and motivating tools for promoting children’s health.

OBJECTIVE: We aimed to determine the comparative use of 2 prototype serious games for health and assess their effects on healthy lifestyle knowledge in youth aged 9-16 years at risk for type 2 diabetes (T2D).

METHODS: A 3-arm parallel pilot randomized controlled trial was undertaken to determine the feasibility and preliminary effectiveness of 2 serious games. Feasibility aspects included recruitment, participant attitudes toward the games, the amount of time the participants played each game at home, and the effects of the games on healthy lifestyle and T2D knowledge. Participants were allocated to play Diabetic Jumper (n=7), Ari and Friends (n=8), or a control game (n=8). All participants completed healthy lifestyle and T2D knowledge questionnaires at baseline, immediately after game play, and 4 weeks after game play. Game attitudes and preferences were also assessed. The primary outcome was the use of the game (specifically, the number of minutes played over 4 weeks).

RESULTS: In terms of feasibility, we were unable to recruit our target of 60 participants. In total, 23 participants were recruited. Participants generally viewed the games positively. There were no statistical differences in healthy lifestyle knowledge or diabetes knowledge over time or across games. Only 1 participant accessed the game for an extended period, playing the game for a total of 33 min over 4 weeks.

CONCLUSIONS: It was not feasible to recruit the target sample for this trial. The 2 prototype serious games were unsuccessful at sustaining long-term game play outside a clinic environment. Based on positive participant attitudes toward the games, it is possible to use these games or similar games as short-term stimuli to engage young people with healthy lifestyle and diabetes knowledge in a clinic setting; however, future research is required to explore this area.

TRIAL REGISTRATION: Australia New Zealand Clinical Trials Registry ACTRN12619000380190; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=377123.

PMID:35713955 | DOI:10.2196/33089

JMIR Med Inform. 2022 Jun 17;10(6):e34204. doi: 10.2196/34204.

ABSTRACT

Real-world data (RWD) collected in routine health care processes and transformed to real-world evidence have become increasingly interesting within the research and medical communities to enhance medical research and support regulatory decision-making. Despite numerous European initiatives, there is still no cross-border consensus or guideline determining which qualities RWD must meet in order to be acceptable for decision-making within regulatory or routine clinical decision support. In the absence of guidelines defining the quality standards for RWD, an overview and first recommendations for quality criteria for RWD in pharmaceutical research and health care decision-making is needed in Austria. An Austrian multistakeholder expert group led by Gesellschaft für Pharmazeutische Medizin (Austrian Society for Pharmaceutical Medicine) met regularly; reviewed and discussed guidelines, frameworks, use cases, or viewpoints; and agreed unanimously on a set of quality criteria for RWD. This consensus statement was derived from the quality criteria for RWD to be used more effectively for medical research purposes beyond the registry-based studies discussed in the European Medicines Agency guideline for registry-based studies. This paper summarizes the recommendations for the quality criteria of RWD, which represents a minimum set of requirements. In order to future-proof registry-based studies, RWD should follow high-quality standards and be subjected to the quality assurance measures needed to underpin data quality. Furthermore, specific RWD quality aspects for individual use cases (eg, medical or pharmacoeconomic research), market authorization processes, or postmarket authorization phases have yet to be elaborated.

PMID:35713954 | DOI:10.2196/34204

JMIR Res Protoc. 2022 Jun 17;11(6):e30656. doi: 10.2196/30656.

ABSTRACT

BACKGROUND: Time is considered an essential determinant in the initial care of trauma patients. In Norway, response time (ie, time from dispatch center call to ambulance arrival at scene) is a controversial national quality indicator. However, no national requirements for response times have been established. There is an ongoing debate regarding the optimal configuration of the Norwegian trauma system. The recent centralization of trauma services and closure of emergency hospitals have increased prehospital transport distances, predominantly for rural trauma patients. However, the impact of trauma system configuration on early trauma management in urban and rural areas is inadequately described.

OBJECTIVE: The project will assess injured patients’ initial pathways through the trauma system and explore differences between central and rural areas in a Norwegian trauma cohort. This field is unexplored at the national level, and existing evidence for an optimal organization of trauma care is still inconclusive regarding the impact of prehospital time.

METHODS: Three quantitative registry-based retrospective cohort studies are planned. The studies are based on data from the Norwegian Trauma Registry (NTR; studies 1, 2, and 3) and the local Emergency Medical Communications Center (study 2). All injured patients admitted to a Norwegian hospital and registered in the NTR in the period between January 1, 2015, and December 31, 2020, will be included in the analysis. Trauma registry data will be analyzed using descriptive and relevant statistical methods to compare prehospital time in rural and central areas, including regression analyses and adjusting for confounders.

RESULTS: The project received funding in fall 2020 and was approved by the Oslo University Hospital data protection officer, case number 18/02592. Registry data including approximately 40,000 trauma patients will be extracted during the first quarter of 2022, and analysis will begin immediately thereafter. Results are expected to be ready for publication from the third quarter of 2022.

CONCLUSIONS: Findings from the study will contribute to new knowledge regarding existing quality indicators and with an increasing centralization of hospitals and residents, the study will contribute to further development of the Norwegian trauma system. A high generalizability to other trauma systems is expected, given the similarities between demographical changes and trauma systems in many high-income countries.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/30656.

PMID:35713952 | DOI:10.2196/30656

Cytopathology. 2022 Jun 17. doi: 10.1111/cyt.13159. Online ahead of print.

ABSTRACT

OBJECTIVES: Oral cancer screening can assist in the early detection of oral potentially malignant lesions (OPMLs) and prevention of oral cancers. It can be challenging for clinicians to differentiate OPMLs from benign conditions. Adjunct screening tools such as fluorescence visualization (FV) and DNA image cytometry (DNA-ICM) have shown success in identifying OPMLs in high-risk clinics. For the first time we aimed to assess these technologies into Indian rural settings and evaluate if these tools helped clinicians identify high-risk lesions during screening.

METHODS: Dental students and residents screened participants in five screening camps held in villages outside of Hyderabad, India, using extraoral, intraoral, and FV examinations. Lesion and normal tissue brushings were collected for DNA-ICM analysis and cytology.

RESULTS: Of the 1116 participants screened, 184 lesions were observed in 152 participants. Based on white light examination (WLE), 45 lesions were recommended for biopsy. Thirty-five were completed on site; 25(71%) were diagnosed with low-grade dysplasias (17 mild dysplasia, 8 moderate dysplasia) and the remaining 10 showed no signs of dysplasia. FV loss was noted in all but one dysplastic lesion and showed a sensitivity of 96% and specificity of 17%. Cytology combined with DNA-ICM had a 64% sensitivity and 86% specificity in detecting dysplasia.

CONCLUSION: DNA-ICM combined with cytology identified majority of dysplastic lesions and identified additional lesions, which were not considered high-risk during WLE to biopsy on site. Efforts to follow-up with these participants are ongoing. FV identified most high-risk lesions but added limited value over WLE.

PMID:35713951 | DOI:10.1111/cyt.13159

Traffic Inj Prev. 2022 Jun 17:1-6. doi: 10.1080/15389588.2022.2078812. Online ahead of print.

ABSTRACT

OBJECTIVE: Some child restraint system (CRS) manufacturers specify a minimum distance between the CRS and the seatback, whereas others require that the CRS may contact the seatback but cannot be “braced”; however, few studies have investigated these interactions. Therefore, the aim was to investigate the interactions between the front row seat and rearward-facing CRS models with and without a support leg during frontal crashes.

METHODS: Sled tests using the FMVSS 213 frontal crash pulse were performed with the Q1.5 and Q3 anthropomorphic test devices (ATDs) seated in rearward-facing infant and convertible CRS models, respectively. A front row vehicle seat was in front of the test bench in three track positions: brace, touch and gap. For the touch condition, the front row seat was translated aftward until the seatback contacted the CRS. For the brace condition, the front row seat was translated 20 mm aftward. For the gap condition, the front row seat was translated 50 mm forward. Each condition was tested with and without the support leg of the CRS.

RESULTS: The tests with a support leg were associated with significantly (p = 0.007) lower resultant linear head acceleration 3 ms clip compared to the tests without a support leg, but the reduction of head injury criterion 15 ms (HIC15) was not significant (p = 0.057). The Q1.5 ATD in the rearward-facing infant CRS with a support leg had the lowest injury metrics for the touch and gap conditions, whereas the Q3 in the rearward-facing convertible CRS had the lowest head injury metrics for the brace condition.

CONCLUSIONS: The use of a support leg provided a clear benefit in terms of reducing head injury metrics for the Q1.5 in the rearward-facing infant CRS, especially for the touch and gap conditions. The rearward-facing convertible CRS in the current study appears to benefit from being braced against the front row seat. However, further tests are required to allow further statistical comparisons and determine if these preliminary findings extend to other rearward-facing CRS models.

PMID:35713941 | DOI:10.1080/15389588.2022.2078812