Category: Nevin Manimala

J Neurodev Disord. 2022 Jun 11;14(1):37. doi: 10.1186/s11689-022-09447-9.

ABSTRACT

BACKGROUND: In over half of pediatric cases, ADHD presents with comorbidities, and often, it is unclear whether the symptoms causing impairment are due to the comorbidity or the underlying ADHD. Comorbid conditions increase the likelihood for a more severe and persistent course and complicate treatment decisions. Therefore, it is highly important to establish an algorithm that identifies ADHD and comorbidities in order to improve research on ADHD using biorepository and other electronic record data.

METHODS: It is feasible to accurately distinguish between ADHD in isolation from ADHD with comorbidities using an electronic algorithm designed to include other psychiatric disorders. We sought to develop an EHR phenotype algorithm to discriminate cases with ADHD in isolation from cases with ADHD with comorbidities more effectively for efficient future searches in large biorepositories. We developed a multi-source algorithm allowing for a more complete view of the patient’s EHR, leveraging the biobank of the Center for Applied Genomics (CAG) at Children’s Hospital of Philadelphia (CHOP). We mined EHRs from 2009 to 2016 using International Statistical Classification of Diseases and Related Health Problems (ICD) codes, medication history and keywords specific to ADHD, and comorbid psychiatric disorders to facilitate genotype-phenotype correlation efforts. Chart abstractions and behavioral surveys added evidence in support of the psychiatric diagnoses. Most notably, the algorithm did not exclude other psychiatric disorders, as is the case in many previous algorithms. Controls lacked psychiatric and other neurological disorders. Participants enrolled in various CAG studies at CHOP and completed a broad informed consent, including consent for prospective analyses of EHRs. We created and validated an EHR-based algorithm to classify ADHD and comorbid psychiatric status in a pediatric healthcare network to be used in future genetic analyses and discovery-based studies.

RESULTS: In this retrospective case-control study that included data from 51,293 subjects, 5840 ADHD cases were discovered of which 46.1% had ADHD alone and 53.9% had ADHD with psychiatric comorbidities. Our primary study outcome was to examine whether the algorithm could identify and distinguish ADHD exclusive cases from ADHD comorbid cases. The results indicate ICD codes coupled with medication searches revealed the most cases. We discovered ADHD-related keywords did not increase yield. However, we found including ADHD-specific medications increased our number of cases by 21%. Positive predictive values (PPVs) were 95% for ADHD cases and 93% for controls.

CONCLUSION: We established a new algorithm and demonstrated the feasibility of the electronic algorithm approach to accurately diagnose ADHD and comorbid conditions, verifying the efficiency of our large biorepository for further genetic discovery-based analyses.

TRIAL REGISTRATION: ClinicalTrials.gov, NCT02286817 . First posted on 10 November 2014.

CLINICALTRIALS: gov, NCT02777931 . First posted on 19 May 2016.

CLINICALTRIALS: gov, NCT03006367 . First posted on 30 December 2016.

CLINICALTRIALS: gov, NCT02895906 . First posted on 12 September 2016.

PMID:35690720 | DOI:10.1186/s11689-022-09447-9

BMC Cardiovasc Disord. 2022 Jun 11;22(1):262. doi: 10.1186/s12872-022-02702-w.

ABSTRACT

BACKGROUND: Previous studies have observed inconsistent associations between coronavirus disease 2019 (COVID-19) and heart failure (HF), but these studies were prone to bias based on reverse causality and residual confounding factors. We aimed to investigate genetic liability between COVID-19 and heart failure using a bidirectional Mendelian randomization study.

METHODS: The causal relationship between COVID-19 (including COVID-19, hospitalized COVID-19 compared with the general population, and severe COVID-19) and HF are determined by using a bidirectional Mendelian randomization analysis. We drew on summary statistics from the largest HF genome-wide association study (GWAS) meta-analysis on individuals of European ancestry, which included 47,309 HF patients and 930,014 controls. The inverse variance weighted (IVW), an adaption of the Egger regression (MR-Egger), the weighted median, and weighted model were conducted for the Mendelian randomization analysis to estimate a causal effect. To confirm the stability, we performed a “leave-one-out” approach for the sensitivity analysis.

RESULTS: Genetically predicted severe COVID-19 was not significantly associated with the risk of HF [odds ratio (OR), 1.003; 95% confidence interval (CI), 0.969-1.037; p = 0.867]. The IVW demonstrated that there was no association between genetically hospitalized COVID-19 infection and HF risk [OR, 1.009; 95% CI, 0.939-1.085; p = 0.797]. There was no evidence to support the association between genetically determined COVID-19 and the risk of HF [OR, 1.066; 95% CI, 0.955-1.190; p = 0.253]. In addition, genetically predicted HF was also not causally associated with COVID-19 [OR, 1.162; 95% CI, 0.824-1.639; p = 0.393]. MR-Egger analysis indicated no evidence of directional pleiotropy.

CONCLUSION: The current bidirectional Mendelian randomization analysis overcomes the limitations of observational studies. Our findings indicated that there is no causal association between COVID-19 and HF.

PMID:35690714 | DOI:10.1186/s12872-022-02702-w

Geroscience. 2022 Jun 11. doi: 10.1007/s11357-022-00602-7. Online ahead of print.

ABSTRACT

Observational studies have implied associations between multiple cytokines and cognitive decline, anti-inflammatory drugs however did not yield any protective effects on cognitive decline. We aimed to assess the associations of systemic inflammation, as measured by multiple cytokine and growth factor, with cognitive performance and brain atrophy using two-sample Mendelian randomization (MR). Independent genetic instruments (p < 5e – 8 and p < 5e – 6) for 41 systemic inflammatory markers were retrieved from a genome-wide association study conducted in 8293 Finnish participants. Summary statistics for gene-outcome associations were obtained for cognitive performance (N = 257,841) and for brain atrophy measures of cerebral cortical surface area and thickness (N = 51,665) and hippocampal volume (N = 33,536). To rule out the heterogeneity in the cognitive performance, we additionally included three domains: the fluid intelligence score (N = 108,818), prospective memory result (N = 111,099), and reaction time (N = 330,069). Main results were computed by inverse-variance weighting; sensitivity analyses taking pleiotropy and invalid instruments into account were performed by using weighted-median estimator, MR-Egger, and MR PRESSO. After correcting for multiple testing using false discovery rate, only genetically predicted (with p < 5e – 6 threshold) per-SD (standard deviation) higher IL-8 was associated with – 0.103 (- 0.155, – 0.051, p_adjusted = 0.004) mm³ smaller hippocampal volume and higher intelligence fluid score [β: 0.103 SD (95% CI: 0.042, 0.165), p_adjusted = 0.041]. Sensitivity analyses generally showed similar results, and no pleiotropic effect, heterogeneity, or possible reverse causation was detected. Our results suggested a possible causal association of high IL-8 levels with better cognitive performance but smaller hippocampal volume among the general healthy population, highlighting the complex role of inflammation in dementia-related phenotypes. Further research is needed to elucidate mechanisms underlying these associations.

PMID:35689786 | DOI:10.1007/s11357-022-00602-7

Int Urol Nephrol. 2022 Jun 11. doi: 10.1007/s11255-022-03192-7. Online ahead of print.

ABSTRACT

PURPOSE: Patients with chronic kidney disease (CKD) have an associated burden of coronary artery disease, including chronic total occlusions (CTO). It is unclear how the presence of CKD affects the outcomes of CTO revascularization. Previous reviews have not taken into account all relevant published studies that examined the association of CKD with outcomes of CTO revascularization.

METHODS: A systematic search was conducted using PubMed, Scopus, and Google Scholar databases for studies investigating patients with or without CKD who also had coronary chronic total occlusion undergoing revascularization procedures Statistical analysis was performed using STATA software. Effect sizes were reported as pooled relative risk (RR).

RESULTS: A total of 13 studies were included. CKD patients showed elevated risk of in-hospital mortality (RR 4.25, 95% CI 2.64, 6.82) and mortality at latest follow-up (RR 3.24, 95% CI 2.56, 4.11), elevated risk of major cardio or cerebrovascular events (RR 1.65, 95% CI 1.38, 1.98), major bleeding (RR 2.85, 95% CI 1.96, 4.13), and contrast-induced acute kidney injury (RR 3.06, 95% CI 1.70, 5.52). CKD patients also showed lower chances of technical success (RR 0.95, 95% CI 0.91, 1.00).

CONCLUSIONS: The presence of CKD increases the risk of mortality, complications and adversely affects the success of CTO revascularization. Patients with CKD undergoing revascularization should have their kidney function comprehensively evaluated and these patients should be carefully monitored.

PMID:35689780 | DOI:10.1007/s11255-022-03192-7

Environ Sci Pollut Res Int. 2022 Jun 11. doi: 10.1007/s11356-022-21008-0. Online ahead of print.

ABSTRACT

This study involves an optimum balance between ordering cost reduction and product deterioration in controllable carbon emissions for a sustainable green warehouse. The sensitivity analysis is to simulate the impact of those attributes. Industries are foraging to find a proper balance between the use of fossil fuels and reducing carbon emissions, as burning fossil fuels is also indispensable for industrialization. Carbon can emit through inevitable logistic activities in the chains (e.g., lighting, heating, air-conditioning, product deterioration). An industry always attempts to curb those emissions through energy-efficient green technology. The green warehouse is a popular store system in present supply chains to limit the carbons. Product deterioration, particularly for perishable items, is also important for a practitioner to decide how to preserve a perishable product for maximum shelf-life. There is a common tendency among industries to increase order frequencies and volumes in search of a better preservation strategy, increasing the ordering cost and the probability of carbon emissions due to increased transportation. A realistic mathematical model is proposed based on those decision parameters by a sensitivity analysis to demonstrate the impacts. The results showed an increase of 46.30% profit is achieved when all three proposed reduction attributes, but shortages are considered. This improvement is significant without shortage, whereas the increased profit is 94.75%.

PMID:35689774 | DOI:10.1007/s11356-022-21008-0

Environ Sci Pollut Res Int. 2022 Jun 11. doi: 10.1007/s11356-022-21296-6. Online ahead of print.

ABSTRACT

Firms’ collaborative activities have created increasing opportunities for eco-innovation in modern society. Based on unbalanced panel data from the Chinese National Innovation Survey between 2011 and 2015, this paper explored the influences of different modes of cooperation, i.e., vertical cooperation, horizontal cooperation, and mixed cooperation, on the eco-innovation of Chinese manufacturing firms. The results indicated that three types of cooperation all had positive and statistically significant effects on the firms’ eco-innovation, and mixed cooperation had promoted eco-innovation more dramatically. The extent of such impacts may vary depending on the heterogeneity of the characteristic of enterprises. We also verified that knowledge spillovers from cooperative partners have played a mediating role between cooperation and eco-innovation. Our results suggest the potential benefits of diversified collaborative activities and appropriate intellectual property protection for firms’ eco-innovation in China.

PMID:35689768 | DOI:10.1007/s11356-022-21296-6

Environ Sci Pollut Res Int. 2022 Jun 11. doi: 10.1007/s11356-022-21237-3. Online ahead of print.

ABSTRACT

With the implementation of Chinese carbon neutrality policy, the Yangtze River Delta calls for great concern. As a benchmark for the development of Chinese logistics industry, it accompanies energy consumption and environmental problems. This study explores how Chinese logistics industry can achieve energy conservation and emission reduction and high-quality development in the context of carbon neutrality. It analyzes the relationship between the logistics industry and economy, energy, as well as environment in Yangtze River Delta. The data is based on China Statistical Yearbook from 2001 to 2019, by means of the entropy method and panel vector autoregressive (PVAR) model. The main findings are summarized as follows: firstly, the economy, industrial structure, energy, and environment have significant impact on the development of logistics industry in Yangtze River Delta. Secondly, the development of logistics industry in Yangtze River Delta is not balanced. The provinces including Jiangsu, Shanghai, Zhejiang, and Anhui have great differences in economy, industrial structure, demographic dividend, energy consumption, and environmental protection, but they show the possibility of complementary advantages. Thirdly, the economic development and energy consumption have bidirectional effects. Environmental protection is relevant to economic development, industrial structure, energy consumption and logistics supply. Finally, some suggestions are provided on how to realize the high-quality development of logistics industry in Yangtze River Delta. In the context of carbon neutrality, it is necessary to consider energy conservation and emission reduction.

PMID:35689767 | DOI:10.1007/s11356-022-21237-3

Sports Med. 2022 Jun 11. doi: 10.1007/s40279-022-01698-9. Online ahead of print.

ABSTRACT

BACKGROUND: An increasing number of musculoskeletal injury prediction models are being developed and implemented in sports medicine. Prediction model quality needs to be evaluated so clinicians can be informed of their potential usefulness.

OBJECTIVE: To evaluate the methodological conduct and completeness of reporting of musculoskeletal injury prediction models in sport.

METHODS: A systematic review was performed from inception to June 2021. Studies were included if they: (1) predicted sport injury; (2) used regression, machine learning, or deep learning models; (3) were written in English; (4) were peer reviewed.

RESULTS: Thirty studies (204 models) were included; 60% of studies utilized only regression methods, 13% only machine learning, and 27% both regression and machine learning approaches. All studies developed a prediction model and no studies externally validated a prediction model. Two percent of models (7% of studies) were low risk of bias and 98% of models (93% of studies) were high or unclear risk of bias. Three studies (10%) performed an a priori sample size calculation; 14 (47%) performed internal validation. Nineteen studies (63%) reported discrimination and two (7%) reported calibration. Four studies (13%) reported model equations for statistical predictions and no machine learning studies reported code or hyperparameters.

CONCLUSION: Existing sport musculoskeletal injury prediction models were poorly developed and have a high risk of bias. No models could be recommended for use in practice. The majority of models were developed with small sample sizes, had inadequate assessment of model performance, and were poorly reported. To create clinically useful sports musculoskeletal injury prediction models, considerable improvements in methodology and reporting are urgently required.

PMID:35689749 | DOI:10.1007/s40279-022-01698-9

J Fluoresc. 2022 Jun 11. doi: 10.1007/s10895-022-02975-6. Online ahead of print.

ABSTRACT

Fluorescence correlation spectroscopy (FCS) has been widely used to investigate molecular diffusion behavior in various samples. The use of the maximum entropy method (MEM) for FCS data analysis provides a unique means to determine multiple distinct diffusion coefficients without a priori assumption of their number. Comparison of the MEM-based FCS method (MEM-FCS) with another method will reveal its utility and advantage as an analytical tool to investigate diffusion dynamics. Herein, we measured diffusion of fluorescent probes doped into nanostructured thin films using MEM-FCS, and validated the results with single molecule tracking (SMT) data. The efficacy of the MEM code employed was first demonstrated by analyzing simulated FCS data for systems incorporating one and two diffusion modes with broadly distributed diffusion coefficients. The MEM analysis accurately afforded the number of distinct diffusion modes and their mean diffusion coefficients. These results contrasted with those obtained by fitting the simulated data to conventional two-component and anomalous diffusion models, which yielded inaccurate estimates of the diffusion coefficients. Subsequently, the MEM analysis was applied to FCS data acquired from hydrophilic dye molecules incorporated into microphase-separated polystyrene-block-poly(ethylene oxide) (PS-b-PEO) thin films characterized under a water-saturated N₂ atmosphere. The MEM analysis revealed distinct fast and slow diffusion components attributable to molecules diffusing on the film surface and inside the film, respectively. SMT studies of the same materials yielded trajectories for mobile molecules that appear to follow the curved PEO microdomains. Diffusion coefficients obtained from the SMT data were consistent with those obtained for the slow diffusion component detected by MEM-FCS. These results highlight the utility of MEM-FCS and SMT for gaining complementary information on molecular diffusion processes in heterogeneous material systems.

PMID:35689743 | DOI:10.1007/s10895-022-02975-6

J Assist Reprod Genet. 2022 Jun 11. doi: 10.1007/s10815-022-02535-8. Online ahead of print.

ABSTRACT

PURPOSE: To describe spermatozoa extraction rate by testicular sperm extraction (TESE) for posthumous sperm retrieval (PMSR) and examine harvest time impact on sperm motility; to compare long-term sperm usage between married vs. single deceased men.

METHODS: This retrospective study included all PMSR cases in Shamir Medical Center during 2003-2021. We evaluated sperm cryopreservation according to latency time after death. Then, we assessed sperm usage according to Israeli PMSR regulations.

RESULTS: The study included 69 (35 married and 34 singles) deceased men with average age of 30.3 ± 7.8 years. Sperm was cryopreserved in 65 cases (94.2%) after maximum and average harvest time of 40 and 16.5 ± 8.1 h, respectively. Motile sperm extraction was associated with significantly shorter harvest time compared with non-motile sperm (13.8 ± 7.3 vs. 18.7 ± 8.1 h, p = 0.046). Sperm usage among married deceased was significantly higher than single (15.6% vs. 0%, p = 0.05). Disposal requests were lower among single compared to married men relatives without reaching statistical difference. Eventually, single men had significantly higher rate of non-used cryopreserved samples (93.8% vs 69.6%, p = 0.01).

CONCLUSION: This large long-term cohort study demonstrates high efficacy of PMSR. We found significant harvest latency time difference between motile and non-motile preserved sperm. Clinical sperm usage rate justifies the efforts for PMSR among married deceased. However, contradicting policy on the topic of single men (which implies liberal sperm preservation but rigid prevention of usage) results with high non-used sperm rate and relatives’ extremely sophisticated emotional burden.

PMID:35689734 | DOI:10.1007/s10815-022-02535-8