Category: Nevin Manimala

PLoS Comput Biol. 2023 Mar 13;19(3):e1010952. doi: 10.1371/journal.pcbi.1010952. Online ahead of print.

ABSTRACT

The signature of early cancer dynamics on the spatial arrangement of tumour cells is poorly understood, and yet could encode information about how sub-clones grew within the expanding tumour. Novel methods of quantifying spatial tumour data at the cellular scale are required to link evolutionary dynamics to the resulting spatial architecture of the tumour. Here, we propose a framework using first passage times of random walks to quantify the complex spatial patterns of tumour cell population mixing. First, using a simple model of cell mixing we demonstrate how first passage time statistics can distinguish between different pattern structures. We then apply our method to simulated patterns of mutated and non-mutated tumour cell population mixing, generated using an agent-based model of expanding tumours, to explore how first passage times reflect mutant cell replicative advantage, time of emergence and strength of cell pushing. Finally, we explore applications to experimentally measured human colorectal cancer, and estimate parameters of early sub-clonal dynamics using our spatial computational model. We infer a wide range of sub-clonal dynamics, with mutant cell division rates varying between 1 and 4 times the rate of non-mutated cells across our sample set. Some mutated sub-clones emerged after as few as 100 non-mutant cell divisions, and others only after 50,000 divisions. The majority were consistent with boundary driven growth or short-range cell pushing. By analysing multiple sub-sampled regions in a small number of samples, we explore how the distribution of inferred dynamics could inform about the initial mutational event. Our results demonstrate the efficacy of first passage time analysis as a new methodology in spatial analysis of solid tumour tissue, and suggest that patterns of sub-clonal mixing can provide insights into early cancer dynamics.

PMID:36913406 | DOI:10.1371/journal.pcbi.1010952

PLoS One. 2023 Mar 13;18(3):e0280823. doi: 10.1371/journal.pone.0280823. eCollection 2023.

ABSTRACT

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic has emphasized the importance and challenges of correctly interpreting antibody test results. Identification of positive and negative samples requires a classification strategy with low error rates, which is hard to achieve when the corresponding measurement values overlap. Additional uncertainty arises when classification schemes fail to account for complicated structure in data. We address these problems through a mathematical framework that combines high dimensional data modeling and optimal decision theory. Specifically, we show that appropriately increasing the dimension of data better separates positive and negative populations and reveals nuanced structure that can be described in terms of mathematical models. We combine these models with optimal decision theory to yield a classification scheme that better separates positive and negative samples relative to traditional methods such as confidence intervals (CIs) and receiver operating characteristics. We validate the usefulness of this approach in the context of a multiplex salivary SARS-CoV-2 immunoglobulin G assay dataset. This example illustrates how our analysis: (i) improves the assay accuracy, (e.g. lowers classification errors by up to 42% compared to CI methods); (ii) reduces the number of indeterminate samples when an inconclusive class is permissible, (e.g. by 40% compared to the original analysis of the example multiplex dataset) and (iii) decreases the number of antigens needed to classify samples. Our work showcases the power of mathematical modeling in diagnostic classification and highlights a method that can be adopted broadly in public health and clinical settings.

PMID:36913381 | DOI:10.1371/journal.pone.0280823

PLoS One. 2023 Mar 13;18(3):e0281425. doi: 10.1371/journal.pone.0281425. eCollection 2023.

ABSTRACT

INTRODUCTION: Optimal management of critically ill HIV-positive patients during hospitalization and after discharge is not fully understood. This study describes patient characteristics and outcomes of critically ill HIV-positive patients hospitalized in Conakry, Guinea between August 2017 and April 2018 at discharge and 6 months post-discharge.

METHODS: We carried out a retrospective observational cohort study using routine clinical data. Analytic statistics were used to describe characteristics and outcomes.

RESULTS: 401 patients were hospitalized during the study period, 230 (57%) were female, median age was 36 (IQR: 28-45). At admission, 229 patients (57%) were on ART, median CD4 was 64 cells/mm3, 166 (41%) had a VL >1000 copies/ml, and 97 (24%) had interrupted treatment. 143 (36%) patients died during hospitalisation. Tuberculosis was the major cause of death for 102 (71%) patients. Of 194 patients that were followed after hospitalization a further 57 (29%) were lost-to-follow-up (LTFU) and 35 (18%) died, 31 (89%) of which had a TB diagnosis. Of all patients who survived a first hospitalisation, 194 (46%) were re-hospitalised at least once more. Amongst those LTFU, 34 (59%) occurred immediately after hospital discharge.

CONCLUSION: Outcomes for critically ill HIV-positive patients in our cohort were poor. We estimate that 1-in-3 patients remained alive and in care 6 months after their hospital admission. This study shows the burden of disease on a contemporary cohort of patients with advanced HIV in a low prevalence, resource limited setting and identifies multiple challenges in their care both during hospitalisation as well as during and after re-transitioning to ambulatory care.

PMID:36913379 | DOI:10.1371/journal.pone.0281425

PLoS One. 2023 Mar 13;18(3):e0282976. doi: 10.1371/journal.pone.0282976. eCollection 2023.

ABSTRACT

BACKGROUND: Nasopharyngeal swab (NPS) remains the recommended sample type for Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) diagnosis. However, the collection procedure causes discomfort and irritation to the patients, lowering the quality of the sample and exposing healthcare workers to risk. Furthermore, there is also a shortage of flocked swabs and personnel protective equipment in low-income settings. Therefore, this necessitates an alternative diagnostic specimen. The purpose of this study was to evaluate the performance of saliva against NPS for SARS-CoV-2 detection using RT-qPCR among COVID-19 suspected patients at Jigjiga, Eastern Ethiopia.

METHODS: Comparative cross-sectional study was conducted from June 28 to July 30, 2022. A total of 227 paired saliva and NPS samples were collected from 227 COVID-19 suspected patients. Saliva and NPS samples were collected and transported to the Somali Regional Molecular Laboratory. Extraction was conducted using DaAn kit (DaAn Gene Co., Ltd China). Veri-Q RT-qPCR was used for amplification and detection (Mico BioMed Co, Ltd, Republic of Korea). The data were entered into Epi-data version 4.6 and analyzed using SPSS 25. McNemar’s test was used to compare the detection rate. Agreement between NPS and saliva was performed using Cohen’s Kappa. The mean and median of cycle threshold values were compared using paired t-tests and the correlation between cycle threshold values was measured using Pearson correlation coefficient. P value < 0.05 was considered statistically significant.

RESULTS: The overall positivity rate of SARS-CoV-2 RNA was 22.5% (95% CI 17-28%). Saliva showed higher sensitivity (83.8%, 95% CI, 73-94.5%) than NPS (68.9%, 95% CI 60.8-76.8%). The specificity of saliva was 92.6% (95% CI, 80.6% – 100%) compared to NPS (96.7%, 95% CI, 87% – 100%). The positive, negative, and overall percent agreement between NPS and saliva was 83.8%, 92.6%, and 91.2% respectively (κ = 0.703, 95% CI 0.58-0.825, P = 0.00). The concordance rate between the two samples was 60.8%. NPS showed a higher viral load than saliva. There was low positive correlation between the cycle threshold values of the two samples (r = 0.41, 95% CI -1.69 to -0.98, P >0.05).

CONCLUSION: Saliva showed a higher detection rate for SARS-CoV-2 molecular diagnosis than NPS and there was significant agreement between the two specimens. Therefore, saliva could be suitable and easily obtainable alternative diagnostic specimen for SARS-CoV-2 molecular diagnosis.

PMID:36913377 | DOI:10.1371/journal.pone.0282976

PLoS One. 2023 Mar 13;18(3):e0282826. doi: 10.1371/journal.pone.0282826. eCollection 2023.

ABSTRACT

BACKGROUND: Nigeria has been consistently targeted in sub-Saharan Africa as an HIV-priority country. Its main mode of transmission is heterosexual, and consequently, a key population of interest is female sex workers (FSWs). While HIV prevention services are increasingly implemented by community-based organizations (CBOs) in Nigeria, there is a paucity of evidence on the implementation costs of these organizations. This study seeks to fill this gap by providing new evidence about service delivery unit cost for HIV education (HIVE), HIV counseling and testing (HCT), and sexually transmitted infection (STI) referral services.

METHODS: In a sample of 31 CBOs across Nigeria, we calculated the costs of HIV prevention services for FSWs taking a provider-based perspective. We collected 2016 fiscal year data on tablet computers during a central data training in Abuja, Nigeria, in August 2017. Data collection was part of a cluster-randomized trial examining the effects of management practices in CBOs on HIV prevention service delivery. Staff costs, recurrent inputs, utilities, and training costs were aggregated and allocated to each intervention to produce total cost calculations, and then divided by the number of FSWs served to produce unit costs. Where costs were shared across interventions, a weight proportional to intervention outputs was applied. All cost data were converted to US dollars using the mid-year 2016 exchange rate. We also explored the cost variation across the CBOs, particularly the roles of service scale, geographic location, and time.

RESULTS: The average annual number of services provided per CBO was 11,294 for HIVE, 3,326 for HCT, and 473 for STI referrals. The unit cost per FSW tested for HIV was 22 USD, the unit cost per FSW reached with HIV education services was 19 USD, and the unit cost per FSW reached by STI referrals was 3 USD. We found heterogeneity in total and unit costs across CBOs and geographic location. Results from the regression models show that total cost and service scale were positively correlated, while unit costs and scale were consistently negatively correlated; this indicates the presence of economies of scale. By increasing the annual number of services by 100 percent, the unit cost decreases by 50 percent for HIVE, 40 percent for HCT, and 10 percent for STI. There was also evidence that indicates that the level of service provision was not constant over time across the fiscal year. We also found unit costs and management to be negatively correlated, though results were not statistically significant.

CONCLUSIONS: Estimates for HCT services are relatively similar to previous studies. There is substantial variation in unit costs across facilities, and evidence of a negative relationship between unit costs and scale for all services. This is one of the few studies to measure HIV prevention service delivery costs to female sex workers through CBOs. Furthermore, this study also looked at the relationship between costs and management practices-the first of its kind to do so in Nigeria. Results can be leveraged to strategically plan for future service delivery across similar settings.

PMID:36913371 | DOI:10.1371/journal.pone.0282826

PLoS One. 2023 Mar 13;18(3):e0283045. doi: 10.1371/journal.pone.0283045. eCollection 2023.

ABSTRACT

BACKGROUND: Observational research on the advance care planning (ACP) process is limited by a lack of easily accessible ACP variables in many large datasets. The objective of this study was to determine whether International Classification of Disease (ICD) codes for do-not-resuscitate (DNR) orders are valid proxies for the presence of a DNR recorded in the electronic medical record (EMR).

METHODS: We studied 5,016 patients over the age of 65 who were admitted to a large, mid-Atlantic medical center with a primary diagnosis of heart failure. DNR orders were identified in billing records from ICD-9 and ICD-10 codes. DNR orders were also identified in the EMR by a manual search of physician notes. Sensitivity, specificity, positive predictive value and negative predictive value were calculated as well as measures of agreement and disagreement. In addition, estimates of associations with mortality and costs were calculated using the DNR documented in EMR and the DNR proxy identified in ICD codes.

RESULTS: Relative to the gold standard of the EMR, DNR orders identified in ICD codes had an estimated sensitivity of 84.6%, specificity of 96.6%, positive predictive value of 90.5%, and negative predictive value of 94.3%. The estimated kappa statistic was 0.83, although McNemar’s test suggested there was some systematic disagreement between the DNR from ICD codes and the EMR.

CONCLUSIONS: ICD codes appear to provide a reasonable proxy for DNR orders among hospitalized older adults with heart failure. Further research is necessary to determine if billing codes can identify DNR orders in other populations.

PMID:36913366 | DOI:10.1371/journal.pone.0283045

PLoS One. 2023 Mar 13;18(3):e0276419. doi: 10.1371/journal.pone.0276419. eCollection 2023.

ABSTRACT

Understanding the common topological characteristics of the human brain network across a population is central to understanding brain functions. The abstraction of human connectome as a graph has been pivotal in gaining insights on the topological properties of the brain network. The development of group-level statistical inference procedures in brain graphs while accounting for the heterogeneity and randomness still remains a difficult task. In this study, we develop a robust statistical framework based on persistent homology using the order statistics for analyzing brain networks. The use of order statistics greatly simplifies the computation of the persistent barcodes. We validate the proposed methods using comprehensive simulation studies and subsequently apply to the resting-state functional magnetic resonance images. We found a statistically significant topological difference between the male and female brain networks.

PMID:36913351 | DOI:10.1371/journal.pone.0276419

PLoS One. 2023 Mar 13;18(3):e0281981. doi: 10.1371/journal.pone.0281981. eCollection 2023.

ABSTRACT

The pandemic of COVID-19 is a severe threat to human life and the global economy. Despite the success of vaccination efforts in reducing the spread of the virus, the situation remains largely uncontrolled due to the random mutation in the RNA sequence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which demands different variants of effective drugs. Disease-causing gene-mediated proteins are usually used as receptors to explore effective drug molecules. In this study, we analyzed two different RNA-Seq and one microarray gene expression profile datasets by integrating EdgeR, LIMMA, weighted gene co-expression network and robust rank aggregation approaches, which revealed SARS-CoV-2 infection causing eight hub-genes (HubGs) including HubGs; REL, AURKA, AURKB, FBXL3, OAS1, STAT4, MMP2 and IL6 as the host genomic biomarkers. Gene Ontology and pathway enrichment analyses of HubGs significantly enriched some crucial biological processes, molecular functions, cellular components and signaling pathways that are associated with the mechanisms of SARS-CoV-2 infections. Regulatory network analysis identified top-ranked 5 TFs (SRF, PBX1, MEIS1, ESR1 and MYC) and 5 miRNAs (hsa-miR-106b-5p, hsa-miR-20b-5p, hsa-miR-93-5p, hsa-miR-106a-5p and hsa-miR-20a-5p) as the key transcriptional and post-transcriptional regulators of HubGs. Then, we conducted a molecular docking analysis to determine potential drug candidates that could interact with HubGs-mediated receptors. This analysis resulted in the identification of top-ranked ten drug agents, including Nilotinib, Tegobuvir, Digoxin, Proscillaridin, Olysio, Simeprevir, Hesperidin, Oleanolic Acid, Naltrindole and Danoprevir. Finally, we investigated the binding stability of the top-ranked three drug molecules Nilotinib, Tegobuvir and Proscillaridin with the three top-ranked proposed receptors (AURKA, AURKB, OAS1) by using 100 ns MD-based MM-PBSA simulations and observed their stable performance. Therefore, the findings of this study might be useful resources for diagnosis and therapies of SARS-CoV-2 infections.

PMID:36913345 | DOI:10.1371/journal.pone.0281981

Int J Surg. 2023 Feb 16. doi: 10.1097/JS9.0000000000000170. Online ahead of print.

ABSTRACT

OBJECTIVES: Post-prostatectomy urinary incontinence (PPUI) is a major complication that reduces the quality of life in patients undergoing prostatectomy for benign prostate hyperplasia (BPH) and prostate cancer (PCa). However, there are currently limited guidelines on which surgical techniques are preferred after conservative treatment for PPUI. In this study, a systematic review and network meta-analysis (NMA) that can help determine the priority for the selection of surgical methods were performed.

MATERIALS AND METHODS: We retrieved data from electronic literature searches of PubMed and the Cochrane Library through August 2021. We searched for randomized controlled trials (RCT) studies on the surgical treatment of PPUI after surgery for BPH or PCa and included the terms artificial urethral sphincter (AUS), adjustable sling, non-adjustable sling, and injection of the bulking agent.The NMA pooled the odds ratios (OR) and 95% credible intervals (CrI) using the number of patients achieving urinary continence, weight of pads used per day, number of pads used per day, and the International Consultation on Incontinence Questionnaire (ICIQ) score. The therapeutic effect of each intervention on PPUI was compared and ranked using the surface under the cumulative ranking curve (SUCRA).

RESULTS: A final 11 studies, including 1116 participants, were included in our NMA. The pooled overall ORs of patients achieving urinary continence compared with no treatment was 3.31 (95% CrI: 0.749, 15.710) in AUS, 2.97 (95% CrI: 0.412, 16.000) in adjustable sling, 2.33 (95% CrI: 0.559, 8.290) in non-adjustable sling, and 0.26 (95% CrI: 0.025, 2.500) in injection of bulking agent. In addition, this study shows the SUCRA values of ranking probabilities for each treatment performance, which indicated that AUS ranked first in terms of continence rate, ICIQ, pad weight, and pad use count.

CONCLUSION: The results of this study suggested that only AUS had a statistically significant effect compared to the non-treatment group and the highest PPUI treatment effect ranking among other surgical treatments.

PMID:36912884 | DOI:10.1097/JS9.0000000000000170

JMIR Form Res. 2023 Mar 13;7:e41408. doi: 10.2196/41408.

ABSTRACT

BACKGROUND: The use of information and communication technologies for health-eHealth-is described as having potential to improve the quality of health care service delivery. Consequently, there is an increased global trend toward adoption of eHealth interventions by health care systems worldwide. Despite the proliferation of eHealth solutions, many health care institutions especially in transitioning countries are struggling to attain effective data governance approaches. The Ministry of Health in Botswana is an exemplar institution continually seeking better approaches to strengthen health data governance (HDG) approaches following the adoption of eHealth solutions. Recognizing the need for a global HDG framework, the Transform Health coalition conceptualized HDG principles that are structured around 3 interconnected objectives: protecting people, promoting the value of health, and prioritizing equity.

OBJECTIVE: The aim of the study is to solicit and evaluate perceptions and attitudes of health sector workers in Botswana toward the HDG principles by Transform Health and derive any future guidance.

METHODS: Purposive sampling was used to select participants. A total of 23 participants from various health care organizations in Botswana completed a web-based survey and 10 participated in a follow-up remote round-table discussion. The aim of the round-table discussion was to gain further insight into participants’ responses from the web-based survey. Participants were from the following health care cadres: nurses, doctors, information technology professionals, and health informaticians. Both validity and reliability testing were performed for the survey tool before sharing it with study participants. An analysis of participants’ close-ended responses from the survey was performed using descriptive statistics. Thematic analysis of open-ended responses from the questionnaire and the round-table discussion was achieved using the Delve software and the widely accepted principles of thematic analysis.

RESULTS: Although some participants highlighted having measures in place similar to the HDG principles, there were some who either did not know or disagreed that their organizations already had in place mechanisms similar to the proposed HDG principles. Participants further expressed relevance and importance of the HDG principles in the context of Botswana. However, some modifications to the principles were also suggested.

CONCLUSIONS: This study highlights the necessity of data governance in health care particularly toward meeting the requirements for Universal Health Coverage. The existence of other health data governance frameworks calls for a critical analysis to assess the most appropriate and applicable framework in the context of Botswana and similar transitioning countries. An organization-centered approach may be most appropriate, as well as strengthening of existing organizations’ HDG practices with the Transform Health principles.

PMID:36912870 | DOI:10.2196/41408