Nevin Manimala

J Magn Reson Imaging. 2022 Jun 26. doi: 10.1002/jmri.28288. Online ahead of print.

ABSTRACT

BACKGROUND: Computed diffusion-weighted imaging (cDWI) is a mathematical computation technique that generates DWIs for any b-value by using actual DWI (aDWI) data with at least two different b-values and may improve differentiation of metastatic from nonmetastatic lymph nodes.

PURPOSE: To determine the appropriate b-value for cDWI to achieve a better diagnostic capability for lymph node staging (N-staging) in non-small cell lung cancer (NSCLC) patients compared to aDWI, short inversion time (TI) inversion recovery (STIR) imaging, or positron emission tomography with 2-[fluorine-18] fluoro-2-deoxy-d-glucose combined with computed tomography (FDG-PET/CT).

STUDY TYPE: Prospective.

SUBJECTS: A total of 245 (127 males and 118 females; mean age 72 years) consecutive histopathologically confirmed NSCLC patients.

FIELD STRENGTH/SEQUENCE: A 3 T, half-Fourier single-shot turbo spin-echo sequence, electrocardiogram (ECG)-triggered STIR fast advanced spin-echo (FASE) sequence with black blood and STIR acquisition and DWI obtained by FASE with b-values of 0 and 1000 sec/mm² .

ASSESSMENT: From aDWIs with b-values of 0 and 1000 (aDWI₁₀₀₀ ) sec/mm² , cDWI using 400 (cDWI₄₀₀ ), 600 (cDWI₆₀₀ ), 800 (cDWI₈₀₀ ), and 2000 (cDWI₂₀₀₀ ) sec/mm² were generated. Then, 114 metastatic and 114 nonmetastatic nodes (mediastinal and hilar lymph nodes) were selected and evaluated with a contrast ratio (CR) for each cDWI and aDWI, apparent diffusion coefficient (ADC), lymph node-to-muscle ratio (LMR) on STIR, and maximum standard uptake value (SUV_max ).

STATISTICAL TESTS: Receiver operating characteristic curve (ROC) analysis, Youden index, and McNemar’s test.

RESULTS: Area under the curve (AUC) of CR₆₀₀ was significantly larger than the CR₄₀₀ , CR₈₀₀ , CR₂₀₀₀ , aCR₁₀₀₀ , and SUV_max . Comparison of N-staging accuracy showed that CR₆₀₀ was significantly higher than CR₄₀₀ , CR₂₀₀₀ , ADC, aCR₁₀₀₀ , and SUV_max , although there were no significant differences with CR₈₀₀ (P = 0.99) and LMR (P = 0.99).

DATA CONCLUSION: cDWI with b-value at 600 sec/mm² may have potential to improve N-staging accuracy as compared with aDWI, STIR, and PET/CT.

EVIDENCE LEVEL: 2 TECHNICAL EFFICACY: Stage 2.

PMID:35753082 | DOI:10.1002/jmri.28288

J Occup Environ Med. 2022 Jun 25. doi: 10.1097/JOM.0000000000002597. Online ahead of print.

ABSTRACT

OBJECTIVE: Determine relationships between lockdowns and excess mortality, unemployment and employment growth.

METHODS: Each US states’ mortality data for 2020 were compared to the prior 3-years to determine excess mortality. Data were compared using measures of lockdowns, or state openness scores and adjusted for age, sex, race/ethnicity, and cardiovascular disease. Comparisons were made with unemployment rates and employment growth rates.

RESULTS: The 2020 excess mortality ranged from -9% to 46%. The average openness score was not significant (p = 0.20). However, openness was strongly associated with both unemployment (p = 0.01) and employment growth (p = 0.0008).

CONCLUSIONS: There was no statistical relationship between excess mortality and openness scores, while there were strong relationships with employment measures. These results suggest lockdowns are not sufficiently beneficial for future use in this pandemic and raise concerns for use in future pandemics.

PMID:35753081 | DOI:10.1097/JOM.0000000000002597

BJU Int. 2022 Jun 26. doi: 10.1111/bju.15840. Online ahead of print.

NO ABSTRACT

PMID:35753069 | DOI:10.1111/bju.15840

Mol Ecol Resour. 2022 Jun 26. doi: 10.1111/1755-0998.13672. Online ahead of print.

ABSTRACT

Rapid and repeatable polymorphism analyses have become a necessity with the current amount of genomic data that can be collected in many organisms. Traditionally such analyses are conducted using a variety of tools in combination, often requiring numerous format translation and manipulation. Here we present a massively updated version of our previous software package EggLib, intended to alleviate such costly and error-prone tinkering with the data. EggLib has been streamlined into a Python package and thoroughly updated and optimized to accommodate modern-day sized dataset. We show the main characteristics of the package making it a tool of choice to perform population genetics analyses. Once the data are imported (whatever their encoding), they can be filtered, edited, analyzed and compared to coalescent simulations very easily and efficiently. Furthermore the list of diversity and polymorphism statistics that can now be calculated has been greatly expanded. The software and its full documentation are available at https://egglib.org/.

PMID:35753060 | DOI:10.1111/1755-0998.13672

Genet Epidemiol. 2022 Jun 26. doi: 10.1002/gepi.22489. Online ahead of print.

ABSTRACT

5-hydroxymethylcytosine (5hmC) is a methylation state linked with gene regulation, commonly found in cells of the central nervous system. 5hmC is associated with demethylation of cytosines from 5-methylcytosine (5mC) to the unmethylated state. The presence of 5hmC can be inferred by a paired experiment involving bisulfite and oxidation-bisulfite treatments on the same sample, followed by a methylation assay using a platform such as the Illumina Infinium MethylationEPIC BeadChip (EPIC). Existing methods for analysis of the resulting EPIC data are not ideal. Most approaches ignore the correlation between the two experiments and any imprecision associated with DNA damage from the additional treatment. Estimates of 5mC/5hmC levels free from these limitations are desirable to reveal associations between methylation states and phenotypes. We propose a hierarchical Bayesian method called Constrained HYdroxy Methylation Estimation (CHYME) to simultaneously estimate 5mC/5hmC signals as well as any associations between these signals and covariates or phenotypes, while accounting for the potential impact of DNA damage and dependencies induced by the experimental design. Simulations show that CHYME has valid type 1 error and better power than a range of alternative methods, including the popular OxyBS method and linear models on transformed proportions. Other methods we examined suffer from hugely inflated type 1 error for inference on 5hmC proportions. We use CHYME to explore genome-wide associations between 5mC/5hmC levels and cause of death in postmortem prefrontal cortex brain tissue samples. These analyses indicate that CHYME is a useful tool to reveal phenotypic associations with 5mC/5hmC levels.

PMID:35753057 | DOI:10.1002/gepi.22489

Lifetime Data Anal. 2022 Jun 26. doi: 10.1007/s10985-022-09557-5. Online ahead of print.

ABSTRACT

Large clinical datasets derived from insurance claims and electronic health record (EHR) systems are valuable sources for precision medicine research. These datasets can be used to develop models for personalized prediction of risk or treatment response. Efficiently deriving prediction models using real world data, however, faces practical and methodological challenges. Precise information on important clinical outcomes such as time to cancer progression are not readily available in these databases. The true clinical event times typically cannot be approximated well based on simple extracts of billing or procedure codes. Whereas, annotating event times manually is time and resource prohibitive. In this paper, we propose a two-step semi-supervised multi-modal automated time annotation (MATA) method leveraging multi-dimensional longitudinal EHR encounter records. In step I, we employ a functional principal component analysis approach to estimate the underlying intensity functions based on observed point processes from the unlabeled patients. In step II, we fit a penalized proportional odds model to the event time outcomes with features derived in step I in the labeled data where the non-parametric baseline function is approximated using B-splines. Under regularity conditions, the resulting estimator of the feature effect vector is shown as root-n consistent. We demonstrate the superiority of our approach relative to existing approaches through simulations and a real data example on annotating lung cancer recurrence in an EHR cohort of lung cancer patients from Veteran Health Administration.

PMID:35753014 | DOI:10.1007/s10985-022-09557-5

Clin Invest Med. 2022 Jun 26;45(2):E21-27. doi: 10.25011/cim.v45i2.38100.

ABSTRACT

PURPOSE: Disease prevalence estimates from population-based administrative databases are often biased due to measurement (misclassification) errors. The purpose of this article is to review the methodology for estimating disease prevalence in administrative data, with a focus on bias correction.

SOURCE: Several approaches to bias correction in administrative data were reviewed and application of these methods was demonstrated using an example from the literature: physician claims and hospitalization data were employed to estimate diabetes prevalence in Ontario, Canada.

FINDINGS: Misclassification bias in prevalence estimates from administrative data can be reduced by developing and selecting an optimal algorithm for case identification, applying a bias correction formula, or using statistical modelling. An algorithm for which sensitivity equals positive predictive value provides an unbiased estimate of prevalence. Bias reduction methods generally require information about the measurement properties of the algorithm, such as sensitivity, specificity, or predictive value. These properties depend on disease type, prevalence, algorithm definition (including the observation window), and may vary by population and time. Prevalence estimates can be improved by applying multivariable disease prediction models.

CONCLUSION: Frequency of a positive case identification algorithm in administrative data is generally not equivalent to disease prevalence. Although prevalence estimates can be corrected for bias using known measurement properties of the algorithm, these properties may be difficult to estimate accurately; therefore, disease prevalence estimates based on administrative data must be treated with caution.

PMID:35752980 | DOI:10.25011/cim.v45i2.38100

Swiss Med Wkly. 2022 Jun 22;152:w30180. doi: 10.4414/smw.2022.w30180. eCollection 2022 Jun 20.

ABSTRACT

BACKGROUND: Due to Switzerland’s shortage of general practitioners (GPs), task shifting through interprofessional collaboration is needed to relieve GPs’ workload and allow the continued provision of quality care. The profession of specialized medical assistant (SMA) was created in Switzerland several years ago to provide a career advancement opportunity for medical practice assistants (MPAs) and intended to counteract the increasing scarcity of resources in primary care. Clinical specialized medical assistants (CSMAs) are trained to care for a set of chronic conditions, such as diabetes.

OBJECTIVE: We aimed to compare the quality of care for patients with type 2 diabetes in practices with and without CSMAs. Further, we aimed to investigate whether evidence exists that CSMA care models may allow for task shifting and the provision of interprofessional care while maintaining a high quality of care and to assess patient experiences with diabetes care in both care models.

METHODS: The present study was a paper-based cross-sectional survey of patient data. A total of 171 patients with type 2 diabetes who had been under the care of either a GP with CSMA (91 patients) or a GP without CSMA (80 patients) for at least one year were consecutively recruited for the study. Data were collected from mid-September 2020 to mid-June 2021. For the statistical analyses, we used descriptive statistics and t-tests.

RESULTS: Patients from both practice types were comparable in age, gender and diabetes-relevant factors such as Body Mass Index, smoking status and blood pressure. Overall, patients in both models received a high quality of care (Diabetes Treatment Satisfaction Questionnaire, DTSQ >32/36 points, SGED >75 points) and a low treatment burden (Treatment Burden Questionnaire, TBQ <20/150 points). When comparing patients’ DTSQ, SGED and TBQ in both groups, we found no significant differences in diabetes-specific satisfaction (32.1 [SD 3.6] vs. 32.4 [SD 3.8], p = 0.7), SGED score (80.2 [SD 8.5] vs. 75.9 [SD 4.8], p = 0.18) or treatment burden (19.2 [SD 15.6] vs. 18.8 [SD 21.4], p = 0.89).

CONCLUSION: Our comparison of patient-reported outcomes and SGED criteria of patients with type 2 diabetes in practices with and without CSMAs showed an equally high quality of care and a low treatment burden. More research is needed on the long-term effects and benefits of the care provided by CSMAs and which other tasks could be shifted to CSMAs to reduce the burden on GPs in the future. At the same time, an increasing number of patients with type 2 diabetes will require high-quality primary care.

PMID:35752968 | DOI:10.4414/smw.2022.w30180

Swiss Med Wkly. 2022 Jun 16;152:w30175. doi: 10.4414/smw.2022.w30175. eCollection 2022 Jun 6.

ABSTRACT

BACKGROUND: Over recent years, the incidence of renal cell carcinoma (RCC) has remained unchanged in Switzerland and is low compared with other European countries. Partial or radical nephrectomy is the mainstay of treatment in patients with localised disease.

METHODS: We conducted an analysis of data from the cancer registry of Eastern Switzerland on patients with surgery for RCC from 2009 to 2018, focusing on a comparison of surgical technique and outcome in tertiary and non-tertiary hospitals.

RESULTS: 492 nephrectomies were performed. Out of 441 curative procedures, 226 were radical and 195 partial nephrectomies (20 unknown). At the tertiary hospital, statistically significantly more partial nephrectomies were performed in non-metastatic patients than at non-tertiary hospitals. We demonstrate a trend towards better disease-free survival after partial compared with radical nephrectomy. The 5-year overall survival for patients diagnosed between 2009 and 2013 was 85%, 83%, and 70% in stage I, II, and III, respectively, compared with 96%, 78%, and 72% for patients diagnosed between 2014 and 2018.

CONCLUSION: RCC incidence in Switzerland has been stable during the past decade in contrast to other European countries, and no stage migration occurred. We demonstrated that patients with localised renal cancer at our tertiary centre were more likely to be treated with renal preserving surgery compared with non-tertiary hospitals. This analysis underlines the importance of local cancer registries in the comparison of treatment and outcome over time.

PMID:35752957 | DOI:10.4414/smw.2022.w30175

West Afr J Med. 2022 Jun 24;39(6):614-622.

ABSTRACT

BACKGROUND: Mini-Mental State Examination (MMSE) is one of the most widely used patient-rated assessment tools but may not be applicable among an overwhelming majority of Nigerians older adults. This is because MMSE was designed and adapted for English speakers, and some of its items are challenging to understand for those with low literacy levels.

OBJECTIVES: This study aimed at translating and adapting MMSE into the Hausa language and also evaluates the psychometric properties of the modified Hausa version of MMSE.

METHODOLOGY: The MMSE was translated and adapted into Hausa language by an Hausa language expert and focus group of experts and the validity of the adapted Hausa MMSE was evaluated against a gold standard (Diagnostic and Statistical Manual of Mental Disorder V criteria for neurocognitive disorders), among older adults participants (N=100). Descriptive statistics and inferential statistics (Receiver Operating Curve analysis and Cronbach alpha coefficient approach) were employed for data analysis and the alpha level was set at 0.05.

RESULTS: The adapted Hausa MMSE has item content validity index of 0.97 and the mean expert proportion relevant rating, across all the experts was 0.99. The adapted Hausa version of MMSE shows 66.7% sensitivity and 84.7% specificity, when the original MMSE cut off point of 24 was used. With ROC analysis, optimal cut-offs derived were 25 and 26 with Area Under Curve of 0.886 (95% CI: 0.816-0.956; Std.Err: 0.036; P=0.000). However, at the optimal cut off of 26, derived using ROC analysis, the modified Hausa MMSE had sensitivity of 93.3% and specificity of 71.8% and the tool internal consistency reliability had alpha value of 0.64.

CONCLUSION: Hausa adapted versions of MMSE is a valid cognitive screening tool for Hausa older adult patients although its use for Screening and for monitoring changes warrant considerations for two separate cut- off points.

PMID:35752953