Nevin Manimala

J Appl Lab Med. 2025 Jan 3;10(1):184-191. doi: 10.1093/jalm/jfae126.

ABSTRACT

BACKGROUND: Laboratory stewardship programs are increasingly adopted to enhance test utilization and improve patient care. Despite their potential, implementation within complex healthcare systems remains challenging. Benchmarking metrics helps institutions compare their performance against peers or best practices. However, the application in laboratory stewardship is underrepresented in the literature.

METHODS: The PLUGS (Patient-centered Laboratory Utiliazation Guidance Services) Informatics Working Group developed guidelines to address common test utilization issues. Metrics were based on data that are easily retrievable and calculable. Three key benchmarks were chosen for a pilot study: the ratio of 25-hydroxyvitamin D to 1,25-dihydroxyvitamin D test orders, the ratio of thyroid-stimulating hormone (TSH) to free thyroxine (FT4) test orders, and the percentage of iron workup orders after an initial low mean corpuscular volume (MCV). Institutions analyzed their own data and we established optimal benchmarks through inter-laboratory comparisons.

RESULTS: Nine laboratories evaluated vitamin D testing, with 2 implementing stewardship interventions beforehand. A benchmark of 50:1 was established, where a higher ratio indicates intentional ordering of 1,25-dihydroxyvitamin D. Nine laboratories evaluated thyroid testing, with 3 implementing interventions. The benchmark of 3.5:1 was established, with a higher ratio suggesting judicious TSH ordering. Seven laboratories evaluated iron workups, proposing a benchmark of 50% as a starting metric. Intervention guidelines were provided for laboratories below the benchmarks to promote improvement.

CONCLUSIONS: Benchmarking metrics provide a standardized framework for assessing and enhancing test utilization practices across multiple laboratories. Continued collaboration and refinement of benchmarking methodologies is essential in maximizing the impact of laboratory stewardship programs on patient safety and resource utilization.

PMID:39749447 | DOI:10.1093/jalm/jfae126

J Appl Lab Med. 2025 Jan 3;10(1):73-78. doi: 10.1093/jalm/jfae097.

ABSTRACT

BACKGROUND: Diagnostic stewardship is the science of improving diagnostic test use. Whether electronic health record (EHR) design influences clinician diagnostic testing behavior and electronic medical record interventions can improve diagnostic stewardship outcomes are key questions. We leveraged the natural experiment of a recent change in EHR platforms to investigate if changing how 2 commonly misused tests, blood cultures for acid-fast bacilli (AFB) and fungi, are displayed affected their use.

METHODS: We performed a retrospective chart review of all AFB and fungal blood cultures at 4 hospitals with a shared EHR. The preintervention and postintervention periods were 52 and 26 weeks, respectively. The culture rate was standardized per 1000 patient-days and segmented into 2-week periods. Pre- and postintervention median rates were compared with the Wilcoxon rank sum test and further analyzed with an interrupted time series (ITS) analysis using a quasi-Poisson regression model.

RESULTS: The biweekly median AFB blood culture rate decreased by 41.6% in the postintervention period (0.46/1000 patient-days vs 0.79/1000 patient-days, P < 0.001). The median rate of fungal blood cultures decreased by 54.3% in the postintervention period (0.42/1000 patient-days vs 0.92/1000 patient-days, P < 0.001). In ITS analysis, the EHR change was associated with a level change in AFB (-31.8%, 95% CI: -54.6% to +2.6%) and fungal (-44.6%, 95% CI: -59.3% to -24.7%) blood culture use.

CONCLUSIONS: An electronic medical record design change resulted in decreased use of 2 commonly misused diagnostic tests. This highlights the impact of EHR design on clinician behavior and diagnostic stewardship programs’ potential to reduce waste.

PMID:39749440 | DOI:10.1093/jalm/jfae097

Child Care Health Dev. 2025 Jan;51(1):e70029. doi: 10.1111/cch.70029.

ABSTRACT

BACKGROUND: Malaria remains a major cause of preventable deaths among children worldwide, despite the availability of several interventions for controlling and eliminating the disease. The WHO recommended the first malaria vaccine, RTS, S/AS01 in October 2021 to immunize children in sub-Saharan Africa. In this study, we set out to evaluate the knowledge, awareness and acceptability of the malaria vaccine among mothers of under 5 in south-west Nigeria before the vaccine’s rollout in Nigeria.

METHODS: We employed a hospital-based cross-sectional study for this study. A pretested semistructured, interviewer-administered questionnaire was used to elicit information from the study participants. Data obtained were analysed using the Statistical Package for Social Sciences (SPSS version 20.0).

RESULTS: A total of 797 respondents participated in the study. Only 26.0% of the respondents were aware of the new vaccine. However, the majority (90.0%) were willing to accept the malaria vaccination and to pay for it (82.1%). The crude odds ratio reveals that the odds of awareness of the malaria vaccine were more than 5 times higher among those who have tertiary education (OR = 5.470, CI = 1.224-24.444) compared with those with primary education.

CONCLUSION: The level of awareness of the malarial vaccine is low among the caregivers of under 5 children living in south-western Nigeria. However, the willingness to accept the vaccine is high. Recruiting, training and retraining of healthcare providers and other stakeholders with the designated role of providing health education on malaria prevention and vaccines are key in ensuring the success of malaria vaccination.

PMID:39749414 | DOI:10.1111/cch.70029

Nat Genet. 2025 Jan 2. doi: 10.1038/s41588-024-01994-2. Online ahead of print.

ABSTRACT

Complex diseases often have distinct mechanisms spanning multiple tissues. We propose tissue-gene fine-mapping (TGFM), which infers the posterior inclusion probability (PIP) for each gene-tissue pair to mediate a disease locus by analyzing summary statistics and expression quantitative trait loci (eQTL) data; TGFM also assigns PIPs to non-mediated variants. TGFM accounts for co-regulation across genes and tissues and models uncertainty in cis-predicted expression models, enabling correct calibration. We applied TGFM to 45 UK Biobank diseases or traits using eQTL data from 38 Genotype-Tissue Expression (GTEx) tissues. TGFM identified an average of 147 PIP > 0.5 causal genetic elements per disease or trait, of which 11% were gene-tissue pairs. Causal gene-tissue pairs identified by TGFM reflected both known biology (for example, TPO-thyroid for hypothyroidism) and biologically plausible findings (for example, SLC20A2-artery aorta for diastolic blood pressure). Application of TGFM to single-cell eQTL data from nine cell types in peripheral blood mononuclear cells (PBMCs), analyzed jointly with GTEx tissues, identified 30 additional causal gene-PBMC cell type pairs.

PMID:39747598 | DOI:10.1038/s41588-024-01994-2

Nat Genet. 2025 Jan 2. doi: 10.1038/s41588-024-01997-z. Online ahead of print.

ABSTRACT

Profiling tumors with single-cell RNA sequencing has the potential to identify recurrent patterns of transcription variation related to cancer progression, and to produce therapeutically relevant insights. However, strong intertumor heterogeneity can obscure more subtle patterns that are shared across tumors. Here we introduce a statistical method, generalized binary covariance decomposition (GBCD), to address this problem. We show that GBCD can decompose transcriptional heterogeneity into interpretable components-including patient-specific, dataset-specific and shared components relevant to disease subtypes-and that, in the presence of strong intertumor heterogeneity, it can produce more interpretable results than existing methods. Applied to data on pancreatic ductal adenocarcinoma, GBCD produced a refined characterization of existing tumor subtypes, and identified a gene expression program prognostic of poor survival independent of tumor stage and subtype. The gene expression program is enriched for genes involved in stress responses, and suggests a role for the integrated stress response in pancreatic ductal adenocarcinoma.

PMID:39747597 | DOI:10.1038/s41588-024-01997-z

Nat Genet. 2025 Jan 2. doi: 10.1038/s41588-024-01982-6. Online ahead of print.

ABSTRACT

Complete characterization of the genetic effects on gene expression is needed to elucidate tissue biology and the etiology of complex traits. In the present study, we analyzed 2,344 subcutaneous adipose tissue samples and identified 34,774 conditionally distinct expression quantitative trait locus (eQTL) signals at 18,476 genes. Over half of eQTL genes exhibited at least two eQTL signals. Compared with primary eQTL signals, nonprimary eQTL signals had lower effect sizes, lower minor allele frequencies and less promoter enrichment; they corresponded to genes with higher heritability and higher tolerance for loss of function. Colocalization of eQTLs with genome-wide association study (GWAS) signals for 28 cardiometabolic traits identified 1,835 genes. Inclusion of nonprimary eQTL signals increased discovery of colocalized GWAS-eQTL signals by 46%. Furthermore, 21 genes with ≥2 colocalized GWAS-eQTL signals showed a mediating gene dosage effect on the GWAS trait. Thus, expanded eQTL identification reveals more mechanisms underlying complex traits and improves understanding of the complexity of gene expression regulation.

PMID:39747594 | DOI:10.1038/s41588-024-01982-6

Eur Radiol. 2025 Jan 2. doi: 10.1007/s00330-024-11325-y. Online ahead of print.

NO ABSTRACT

PMID:39747591 | DOI:10.1007/s00330-024-11325-y

Eur Radiol. 2025 Jan 2. doi: 10.1007/s00330-024-11298-y. Online ahead of print.

NO ABSTRACT

PMID:39747590 | DOI:10.1007/s00330-024-11298-y

Eur Radiol. 2025 Jan 2. doi: 10.1007/s00330-024-11256-8. Online ahead of print.

ABSTRACT

OBJECTIVES: Incidentally detected pulmonary nodules present a challenge in clinical routine with demand for reliable support systems for risk classification. We aimed to evaluate the performance of the lung-cancer-prediction-convolutional-neural-network (LCP-CNN), a deep learning-based approach, in comparison to multiparametric statistical methods (Brock model and Lung-RADS®) for risk classification of nodules in cohorts with different risk profiles and underlying pulmonary diseases.

MATERIALS AND METHODS: Retrospective analysis was conducted on non-contrast and contrast-enhanced CT scans containing pulmonary nodules measuring 5-30 mm. Ground truth was defined by histology or follow-up stability. The final analysis was performed on 297 patients with 422 eligible nodules, of which 105 nodules were malignant. Classification performance of the LCP-CNN, Brock model, and Lung-RADS® was evaluated in terms of diagnostic accuracy measurements including ROC-analysis for different subcohorts (total, screening, emphysema, and interstitial lung disease).

RESULTS: LCP-CNN demonstrated superior performance compared to the Brock model in total and screening cohorts (AUC 0.92 (95% CI: 0.89-0.94) and 0.93 (95% CI: 0.89-0.96)). Superior sensitivity of LCP-CNN was demonstrated compared to the Brock model and Lung-RADS® in total, screening, and emphysema cohorts for a risk threshold of 5%. Superior sensitivity of LCP-CNN was also shown across all disease groups compared to the Brock model at a threshold of 65%, compared to Lung-RADS® sensitivity was better or equal. No significant differences in the performance of LCP-CNN were found between subcohorts.

CONCLUSION: This study offers further evidence of the potential to integrate deep learning-based decision support systems into pulmonary nodule classification workflows, irrespective of the individual patient risk profile and underlying pulmonary disease.

KEY POINTS: Question Is a deep-learning approach (LCP-CNN) superior to multiparametric models (Brock model, Lung-RADS®) in classifying pulmonary nodule risk across varied patient profiles? Findings LCP-CNN shows superior performance in risk classification of pulmonary nodules compared to multiparametric models with no significant impact on risk profiles and structural pulmonary diseases. Clinical relevance LCP-CNN offers efficiency and accuracy, addressing limitations of traditional models, such as variations in manual measurements or lack of patient data, while producing robust results. Such approaches may therefore impact clinical work by complementing or even replacing current approaches.

PMID:39747589 | DOI:10.1007/s00330-024-11256-8

Eur Radiol. 2025 Jan 2. doi: 10.1007/s00330-024-11304-3. Online ahead of print.

ABSTRACT

OBJECTIVE: Intensive medical management has been recommended for ischemic stroke of intracranial atherosclerosis (ICAS), but 9.4-15% probability of recurrent stroke remains an inevitable reality. The characteristics of high-risk intracranial plaque that contribute to stroke recurrence after intensive therapy are unclear.

METHODS: The patients of acute ischemic stroke due to ICAS from two centers were prospectively analyzed, who underwent the 3D high-resolution head and neck vessel wall magnetic resonance imaging (hr-VW-MRI) at baseline and received intensive medical management within 90 days. The morphological features, such as minimal lumen area (MLA), and histogram parameters including entropy were assessed based on hr-VW-MR images. The recurrence of ischemic events after 6 months was defined as hyperintensity on diffusion-weighted images in the ipsilateral vascular territory. Cox regression analysis was used to calculate the hazard ratio (HR) and 95% confidence interval (CI) for recurrent events.

RESULTS: A total of 222 patients (age 59.5 ± 12.1; males 153) were finally included, and 38 had recurrent stroke after 6 months. After adjusting the age and gender, Cox regression demonstrated that smoking (HR = 4.321; 95% CI, 1.838-10.161; p = 0.001), taking exercise (HR = 0.409; 95% CI, 0.198-0.843; p = 0.015), blood pressure management (HR = 0.180; 95% CI, 0.073-0.443; p = 0.001), MLA (HR = 0.771; 95% CI, 0.625-0.951; p = 0.015) and entropy (HR = 0.274; 95% CI, 0.130-0.576; p = 0.001) were significant predictors of recurrent ischemic stroke. However, the area under curve value of MRI parameters was significantly higher than that of traditional clinical factors (0.86 vs 0.79; p = 0.01).

CONCLUSIONS: The plaque characteristics based on hr-VW-MRI may provide complementary values over traditional clinical features in predicting ischemic recurrence for ICAS.

KEY POINTS: Question The study addresses recurrent ischemic stroke in intracranial atherosclerosis patients, identifying high-risk plaque features that contribute to recurrence despite intensive medical management. Findings Plaque features on high-resolution vessel wall magnetic resonance imaging (hr-VW-MRI), such as minimal lumen area and entropy, improve prediction of stroke recurrence over clinical factors. Clinical relevance This two-center prospective study improves patient care by using hr-VW-MRI and histogram factors like entropy to better predict stroke recurrence, allowing for more personalized treatment strategies and potentially reducing ischemic events in patients with intracranial atherosclerosis.

PMID:39747588 | DOI:10.1007/s00330-024-11304-3