Category: Nevin Manimala

Malar J. 2023 Mar 7;22(1):82. doi: 10.1186/s12936-023-04519-0.

ABSTRACT

BACKGROUND: Carriers of persistent asymptomatic Plasmodium falciparum infections constitute an infectious reservoir that maintains malaria transmission. Understanding the extent of carriage and characteristics of carriers specific to endemic areas could guide use of interventions to reduce infectious reservoir.

METHODS: In eastern Gambia, an all-age cohort from four villages was followed up from 2012 to 2016. Each year, cross-sectional surveys were conducted at the end of the malaria transmission season (January) and just before the start of the next one (June) to determine asymptomatic P. falciparum carriage. Passive case detection was conducted during each transmission season (August to January) to determine incidence of clinical malaria. Association between carriage at the end of the season and at start of the next one and the risk factors for this were assessed. Effect of carriage before start of the season on risk of clinical malaria during the season was also examined.

RESULTS: A total of 1403 individuals-1154 from a semi-urban village and 249 from three rural villages were enrolled; median age was 12 years (interquartile range [IQR] 6, 30) and 12 years (IQR 7, 27) respectively. In adjusted analysis, asymptomatic P. falciparum carriage at the end of a transmission season and carriage just before start of the next one were strongly associated (adjusted odds ratio [aOR] = 19.99; 95% CI 12.57-31.77, p < 0.001). The odds of persistent carriage (i.e. infected both in January and in June) were higher in rural villages (aOR = 13.0; 95% CI 6.33-26.88, p < 0.001) and in children aged 5-15 years (aOR = 5.03; 95% CI 2.47-10.23, p = < 0.001). In the rural villages, carriage before start of the season was associated with a lower risk of clinical malaria during the season (incidence risk ratio [IRR] 0.48, 95% CI 0.27-0.81, p = 0.007).

CONCLUSIONS: Asymptomatic P. falciparum carriage at the end of a transmission season strongly predicted carriage just before start of the next one. Interventions that clear persistent asymptomatic infections when targeted at the subpopulation with high risk of carriage may reduce the infectious reservoir responsible for launching seasonal transmission.

PMID:36882754 | DOI:10.1186/s12936-023-04519-0

BMC Med. 2023 Mar 8;21(1):88. doi: 10.1186/s12916-023-02798-7.

ABSTRACT

BACKGROUND: Understanding the effects of risk factor burden and genetic predisposition on the long-term risk of atrial fibrillation (AF) is important to improve public health initiatives. However, the 10-year risk of AF considering risk factor burden and genetic predisposition is unknown.

METHODS: A total of 348,904 genetically unrelated participants without AF at baseline from the UK were categorized into three groups: index ages 45 years (n = 84,206), 55 years (n=117,520), and 65 years (n=147,178). Optimal, borderline, or elevated risk factor burden was determined by body mass index, blood pressure, diabetes mellitus, alcohol consumption, smoking status, and history of myocardial infarction or heart failure. Genetic predisposition was estimated using the polygenic risk score (PRS), constructed using 165 predefined genetic risk variants. The combined effects of risk factor burden and PRS on the risk of incident AF in 10 years were estimated for each index age. Fine and Gray models were developed to predict the 10-year risk of AF.

RESULTS: The overall 10-year risk of AF was 0.67% (95% CI: 0.61-0.73%) for index age 45 years, 2.05% (95% CI: 1.96-2.13%) for index age 55 years, and 6.34% (95% CI: 6.21-6.46%) for index age 65 years, respectively. An optimal risk factor burden was associated with later AF onset regardless of genetic predisposition and sex (P < 0.001). Significant synergistic interactions were observed for risk factor burden with PRS at each index age (P < 0.05). Participants with an elevated risk factor burden and high PRS had the highest 10-year risk of AF in reference to those who had both an optimal risk factor burden and a low PRS. At younger ages, optimal risk burden and high PRS might also lead to later onset of AF, compared to the joint effect of elevated risk burden and low/intermediate PRS.

CONCLUSIONS: Risk factor burden together with a genetic predisposition is associated with the 10-year risk of AF. Our results may be helpful in selecting high-risk individuals for primary prevention of AF and facilitating subsequent health interventions.

PMID:36882748 | DOI:10.1186/s12916-023-02798-7

BMC Microbiol. 2023 Mar 7;23(1):60. doi: 10.1186/s12866-023-02799-9.

ABSTRACT

BACKGROUND: A common task in analyzing metatranscriptomics data is to identify microbial metabolic pathways with differential RNA abundances across multiple sample groups. With information from paired metagenomics data, some differential methods control for either DNA or taxa abundances to address their strong correlation with RNA abundance. However, it remains unknown if both factors need to be controlled for simultaneously.

RESULTS: We discovered that when either DNA or taxa abundance is controlled for, RNA abundance still has a strong partial correlation with the other factor. In both simulation studies and a real data analysis, we demonstrated that controlling for both DNA and taxa abundances leads to superior performance compared to only controlling for one factor.

CONCLUSIONS: To fully address the confounding effects in analyzing metatranscriptomics data, both DNA and taxa abundances need to be controlled for in the differential analysis.

PMID:36882742 | DOI:10.1186/s12866-023-02799-9

BMC Infect Dis. 2023 Mar 7;23(1):137. doi: 10.1186/s12879-023-08104-3.

ABSTRACT

BACKGROUND: During the novel coronavirus disease-2019 pandemic, a considerable number of pneumothorax (PNX)/pneumomediastinum (PNM) associated with COVID-19 have been reported, and the incidence is higher in critically ill patients. Despite using a protective ventilation strategy, PNX/PNM still occurs in patients on invasive mechanical ventilation (IMV). This matched case-control study aims to identify the risk factors and clinical characteristics of PNX/PNM in COVID-19.

METHODS: This retrospective study enrolled adult patients with COVID-19, admitted to a critical care unit from March 1, 2020, to January 31, 2022. COVID-19 patients with PNX/PNM were compared, in a 1-2 ratio, to COVID-19 patients without PNX/PNM, matched for age, gender, and worst National Institute of Allergy and Infectious Diseases ordinal scale. Conditional logistic regression analysis was performed to assess the risk factors for PNX/PNM in COVID-19.

RESULTS: 427 patients with COVID-19 were admitted during the period, and 24 patients were diagnosed with PNX/PNM. Body mass index (BMI) was significantly lower in the case group (22.8 kg/m² and 24.7 kg/m²; P = 0.048). BMI was statistically significant risk factor for PNX/PNM in univariate conditional logistic regression analysis [odds ratio (OR), 0.85; confidence interval (CI), 0.72-0.996; P = 0.044]. For patients on IMV support, univariate conditional logistic regression analysis showed the statistical significance of the duration from symptom onset to intubation (OR, 1.14; CI, 1.006-1.293; P = 0.041).

CONCLUSIONS: Higher BMI tended to show a protective effect against PNX/PNM due to COVID-19 and delayed application of IMV might be a contributive factor for this complication.

PMID:36882735 | DOI:10.1186/s12879-023-08104-3

BMC Infect Dis. 2023 Mar 7;23(1):141. doi: 10.1186/s12879-023-08009-1.

ABSTRACT

OBJECTIVE: Visceral leishmaniasis (VL) is an endemic parasitic disease in Latin America, and its clinical picture is aggravated in coinfections with the human immunodeficiency virus (HIV). The objective of this study was to investigate clinical factors and laboratory variables associated with VL relapse and death in VL/HIV coinfected patients.

METHODS: A prospective longitudinal study was conducted from January 2013 to July 2020 among 169 patients coinfected with VL and HIV. The outcomes investigated were the occurrence of VL relapse and death. Chi-square test, Mann-Whitney test and logistic regression models were used for statistical analysis.

RESULTS: The occurrence rates were 41.4% for VL relapse and 11.2% for death. Splenomegaly and adenomegaly were associated with the increased risk of VL relapse. Patients with VL relapse had higher levels of urea (p = .005) and creatinine (p < .001). Patients who died had lower red blood cell counts (p = .012), hemoglobin (p = .017) and platelets (p < .001). The adjusted model showed that antiretroviral therapy for more than 6 months was associated with a decrease in VL relapse, and adenomegaly was associated with an increase in VL relapse. In addition, edema, dehydration, poor general health status, and paleness were associated with an increase in hospital death.

CONCLUSION: The findings suggest that adenomegaly, antiretroviral therapy, and renal abnormalities can be associated with VL relapse, while hematological abnormalities, and clinical manifestations like paleness, and edema can be associated with an increased odds of hospital death.

TRIAL REGISTRATION NUMBER: The study was submitted to the Ethics and Research Committee of the Federal University of Maranhão (Protocol: 409.351).

PMID:36882732 | DOI:10.1186/s12879-023-08009-1

BMC Bioinformatics. 2023 Mar 7;24(1):87. doi: 10.1186/s12859-023-05185-4.

ABSTRACT

BACKGROUND: Variation in omics data due to intrinsic biological stochasticity is often viewed as a challenging and undesirable feature of complex systems analyses. In fact, numerous statistical methods are utilized to minimize the variation among biological replicates.

RESULTS: We demonstrate that the common statistics relative standard deviation (RSD) and coefficient of variation (CV), which are often used for quality control or part of a larger pipeline in omics analyses, can also be used as a metric of a physiological stress response. Using an approach we term Replicate Variation Analysis (RVA), we demonstrate that acute physiological stress leads to feature-wide canalization of CV profiles of metabolomes and proteomes across biological replicates. Canalization is the repression of variation between replicates, which increases phenotypic similarity. Multiple in-house mass spectrometry omics datasets in addition to publicly available data were analyzed to assess changes in CV profiles in plants, animals, and microorganisms. In addition, proteomics data sets were evaluated utilizing RVA to identify functionality of reduced CV proteins.

CONCLUSIONS: RVA provides a foundation for understanding omics level shifts that occur in response to cellular stress. This approach to data analysis helps characterize stress response and recovery, and could be deployed to detect populations under stress, monitor health status, and conduct environmental monitoring.

PMID:36882728 | DOI:10.1186/s12859-023-05185-4

JMIR Mhealth Uhealth. 2023 Mar 7;11:e38506. doi: 10.2196/38506.

ABSTRACT

BACKGROUND: Chronic hand and foot eczema is a polyetiological dermatological condition. Patients experience pain, itching, and sleep disturbances and have a reduced quality of life. Skin care programs and patient education can improve the clinical outcome. eHealth devices offer a new opportunity to better inform and monitor patients.

OBJECTIVE: This study aimed to systematically analyze the effect of a monitoring smartphone app combined with patient education on the quality of life and clinical outcome of patients with hand and foot eczema.

METHODS: Patients in the intervention group received an educational program; attended study visits on weeks 0, 12, and 24; and had access to the study app. Patients in the control group attended the study visits only. The primary end point was a statistically significant reduction in Dermatology Life Quality Index, pruritus, and pain at weeks 12 and 24. The secondary end point was a statistically significant reduction in the modified Hand Eczema Severity Index (HECSI) score at weeks 12 and 24. This is an interim analysis at week 24 of the 60-week randomized controlled study.

RESULTS: In total, 87 patients were included in the study and randomized to the intervention group (n=43, 49%) or control group (n=44, 51%). Of the 87 patients, 59 (68%) completed the study visit at week 24. There were no significant differences between the intervention and control groups regarding quality of life, pain, itch, activity, and clinical outcome at weeks 12 and 24. Subgroup analysis revealed that, compared with the control group, the intervention group with an app use frequency of fewer than once every 5 weeks had a significant improvement in the Dermatology Life Quality Index at weeks 12 (P=.001) and 24 (P=.05), in pain measured on a numeric rating scale at weeks 12 (P=.02) and 24 (P=.02), and in the HECSI score at week 12 (P=.02). In addition, the HECSI scores assessed on the basis of pictures taken by the patients of their hands and feet correlated strongly with the HECSI scores recorded by physicians during regular personal visits (r=0.898; P=.002) even when the quality of the images was not that good.

CONCLUSIONS: An educational program combined with a monitoring app that connects patients with their treating dermatologists can improve quality of life if the app is not used too frequently. In addition, telemedical care can at least partially replace personal care in patients with hand and foot eczema because the analysis of the pictures taken by the patients correlates strongly with that of the in vivo images. A monitoring app such as the one presented in this study has the potential to improve patient care and should be implemented in daily practice.

TRIAL REGISTRATION: Deutsches Register Klinischer Studien DRKS00020963; https://drks.de/search/de/trial/DRKS00020963.

PMID:36881465 | DOI:10.2196/38506

Int J Radiat Biol. 2023 Mar 7:1-12. doi: 10.1080/09553002.2023.2181998. Online ahead of print.

ABSTRACT

BACKGROUND: Exposure to different forms of ionizing radiation occurs in diverse occupational, medical, and environmental settings. Improving the accuracy of the estimated health risks associated with exposure is therefore, essential for protecting the public, particularly as it relates to chronic low dose exposures. A key aspect to understanding health risks is precise and accurate modeling of the dose-response relationship. Toward this vision, benchmark dose (BMD) modeling may be a suitable approach for consideration in the radiation field. BMD modeling is already extensively used for chemical hazard assessments and is considered statistically preferable to identifying low and no observed adverse effects levels. BMD modeling involves fitting mathematical models to dose-response data for a relevant biological endpoint and identifying a point of departure (the BMD, or its lower bound). Recent examples in chemical toxicology show that when applied to molecular endpoints (e.g. genotoxic and transcriptional endpoints), BMDs correlate to points of departure for more apical endpoints such as phenotypic changes (e.g. adverse effects) of interest to regulatory decisions. This use of BMD modeling may be valuable to explore in the radiation field, specifically in combination with adverse outcome pathways, and may facilitate better interpretation of relevant in vivo and in vitro dose-response data. To advance this application, a workshop was organized on June 3rd, 2022, in Ottawa, Ontario that brought together BMD experts in chemical toxicology and the radiation scientific community of researchers, regulators, and policy-makers. The workshop’s objective was to introduce radiation scientists to BMD modeling and its practical application using case examples from the chemical toxicity field and demonstrate the BMDExpress software using a radiation dataset. Discussions focused on the BMD approach, the importance of experimental design, regulatory applications, its use in supporting the development of adverse outcome pathways, and specific radiation-relevant examples.

CONCLUSIONS: Although further deliberations are needed to advance the use of BMD modeling in the radiation field, these initial discussions and partnerships highlight some key steps to guide future undertakings related to new experimental work.

PMID:36881459 | DOI:10.1080/09553002.2023.2181998

JMIR Res Protoc. 2023 Mar 7;12:e42267. doi: 10.2196/42267.

ABSTRACT

BACKGROUND: HIV incidence estimates are published each year for all Ending the HIV Epidemic (EHE) counties, but they are not stratified by the demographic variables highly associated with risk of infection. Regularly updated estimates of HIV incident diagnoses available at local levels are required to monitor the epidemic in the United States over time and could contribute to background incidence rate estimates for alternative clinical trial designs for new HIV prevention products.

OBJECTIVE: We describe methods using existing, robust data sources within areas in the United States to reliably estimate longitudinal HIV incident diagnoses stratified by race and age categories among men who have sex with other men (MSM) eligible for pre-exposure prophylaxis (PrEP) but not taking it.

METHODS: This is a secondary analysis of existing data sources to develop new estimates of incident HIV diagnoses in MSM. We reviewed past methods used to estimate incident diagnoses and explored opportunities to improve these estimates. We will use existing surveillance data sources and population sizes of HIV PrEP-eligible MSM estimated from population-based data sources (eg, US Census data and pharmaceutical prescription databases) to develop metropolitan statistical area-level estimates of new HIV diagnoses among PrEP-eligible MSM. Required parameters are number of new diagnoses among MSM, estimates of MSM with an indication for PrEP, and prevalent PrEP use including median duration of use; these parameters will be stratified by jurisdiction and age group or race or ethnicity. Preliminary outputs will be available in 2023, and updated estimates will be produced annually thereafter.

RESULTS: Data to parameterize new HIV diagnoses among PrEP-eligible MSM are available with varying levels of public availability and timeliness. In early 2023, the most recent available data on new HIV diagnoses were from the 2020 HIV surveillance report, which reports 30,689 new HIV infections in 2020, and 24,724 of them occurred in an MSA with a population of ≥500,000. Updated estimates for PrEP coverage based on commercial pharmacy claims data through February 2023 will be generated. The rate of new HIV diagnoses among MSM can be estimated from new diagnoses within each demographic group (numerator) and the total person-time at risk of diagnosis for each group (denominator) by metropolitan statistical area and year. To estimate time at risk, the person-time of individuals on PrEP or person-time after incident HIV infection but before diagnosis should be removed from stratified population size estimates of the total number of person-years with indications for PrEP.

CONCLUSIONS: Reliable, serial, cross-sectional estimates for rates of new HIV diagnoses for MSM with PrEP indications can serve as benchmark community estimates of failures of HIV prevention and opportunities to improve services and will support public health epidemic monitoring and alternative clinical trial designs.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/42267.

PMID:36881450 | DOI:10.2196/42267

JMIR Form Res. 2023 Mar 7;7:e43296. doi: 10.2196/43296.

ABSTRACT

BACKGROUND: The experience sampling methodology (ESM) has long been considered as the gold standard for gathering data in everyday life. In contrast, current smartphone technology enables us to acquire data that are much richer, more continuous, and unobtrusive than is possible via ESM. Although data obtained from smartphones, known as mobile sensing, can provide useful information, its stand-alone usefulness is limited when not combined with other sources of information such as data from ESM studies. Currently, there are few mobile apps available that allow researchers to combine the simultaneous collection of ESM and mobile sensing data. Furthermore, such apps focus mostly on passive data collection with only limited functionality for ESM data collection.

OBJECTIVE: In this paper, we presented and evaluated the performance of m-Path Sense, a novel, full-fledged, and secure ESM platform with background mobile sensing capabilities.

METHODS: To create an app with both ESM and mobile sensing capabilities, we combined m-Path, a versatile and user-friendly platform for ESM, with the Copenhagen Research Platform Mobile Sensing framework, a reactive cross-platform framework for digital phenotyping. We also developed an R package, named mpathsenser, which extracts raw data to an SQLite database and allows the user to link and inspect data from both sources. We conducted a 3-week pilot study in which we delivered ESM questionnaires while collecting mobile sensing data to evaluate the app’s sampling reliability and perceived user experience. As m-Path is already widely used, the ease of use of the ESM system was not investigated.

RESULTS: Data from m-Path Sense were submitted by 104 participants, totaling 69.51 GB (430.43 GB after decompression) or approximately 37.50 files or 31.10 MB per participant per day. After binning accelerometer and gyroscope data to 1 value per second using summary statistics, the entire SQLite database contained 84,299,462 observations and was 18.30 GB in size. The reliability of sampling frequency in the pilot study was satisfactory for most sensors, based on the absolute number of collected observations. However, the relative coverage rate-the ratio between the actual and expected number of measurements-was below its target value. This could mostly be ascribed to gaps in the data caused by the operating system pushing away apps running in the background, which is a well-known issue in mobile sensing. Finally, some participants reported mild battery drain, which was not considered problematic for the assessed participants’ perceived user experience.

CONCLUSIONS: To better study behavior in everyday life, we developed m-Path Sense, a fusion of both m-Path for ESM and Copenhagen Research Platform Mobile Sensing. Although reliable passive data collection with mobile phones remains challenging, it is a promising approach toward digital phenotyping when combined with ESM.

PMID:36881444 | DOI:10.2196/43296