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Nevin Manimala Statistics

Measurement of symphysis fundal height for gestational age estimation in low-to-middle-income countries: A systematic review and meta-analysis

PLoS One. 2022 Aug 25;17(8):e0272718. doi: 10.1371/journal.pone.0272718. eCollection 2022.

ABSTRACT

In low- and middle-income countries (LMIC), measurement of symphysis fundal height (SFH) is often the only available method of estimating gestational age (GA) in pregnancy. This systematic review aims to summarize methods of SFH measurement and assess the accuracy of SFH for the purpose of GA estimation. We searched PubMed, EMBASE, Cochrane, Web of Science, POPLINE, and WHO Global Health Libraries from January 1980 through November 2021. For SFH accuracy, we pooled the variance of the mean difference between GA confirmed by ultrasound versus SFH. Of 1,003 studies identified, 37 studies were included. Nineteen different SFH measurement techniques and 13 SFH-to-GA conversion methods were identified. In pooled analysis of five studies (n = 5838 pregnancies), 71% (95% CI: 66-77%) of pregnancies dated by SFH were within ±14 days of ultrasound confirmed dating. Using the 1 cm SFH = 1wk assumption, SFH underestimated GA compared with ultrasound-confirmed GA (mean bias: -14.0 days) with poor accuracy (95% limits of agreement [LOA]: ±42.8 days; n = 3 studies, 2447 pregnancies). Statistical modeling of three serial SFH measurements performed better, but accuracy was still poor (95% LOA ±33 days; n = 4 studies, 4391 pregnancies). In conclusion, there is wide variation in SFH measurement and SFH-to-GA conversion techniques. SFH is inaccurate for estimating GA and should not be used for GA dating. Increasing access to quality ultrasonography early in pregnancy should be prioritized to improve gestational age assessment in LMIC.

PMID:36007078 | DOI:10.1371/journal.pone.0272718

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Nevin Manimala Statistics

Larval dispersal of Brachyura in one of the largest estuarine/marine systems in the world

PLoS One. 2022 Aug 25;17(8):e0252695. doi: 10.1371/journal.pone.0252695. eCollection 2022.

ABSTRACT

The Amazon Continental Shelf (ACS) is a complex habitat that receives a large annual freshwater discharge into the ocean, producing a superficial plume and carrying with it large amounts of nutrients to the continental shelf along thousands of kilometers while sustaining high biodiversity in the estuary-ocean continuum. For the first time, this study monitored six sites in a wide transect with approximately 240 km radius on the ACS every 2-4 months. The objectives were (1) to analyze the composition of larval Brachyuran crabs and (2) to predict the importance of environmental parameters (temperature, salinity and chlorophyll-a) in structuring their abundance. A total of 17,759 larvae identified were distributed in 8 families and 24 taxa. The water salinity was the best predictor of larval distribution. The statistical models used indicated that Panopeidae and Portunidae larvae are more frequent and more likely to occur in shallow water layers, while Calappidae occur in deeper layers, and Grapsidae, Ocypodidae, Sesarmidae, Pinnotheridae and Leucosiidae occur similarly in both strata. The larval dispersal extent varies among families and throughout the year while the groups are distributed in different salinities along the platform. The probability of occurrence of Portunidae is higher in ocean water (≥ 33.5); Grapsidae, Panopeidae, and Pinnotheridae is higher in intermediate and ocean salinity waters (25.5 to 33.5); Ocypodidae, Sesarmidae and Calappidae is higher in estuarine and intermediate salinity waters (5 to 25.5), whereas Leucosiidae, euryhaline, occur in all salinities (5 to 33.5). Furthermore, the Amazon River seasonal flow and plume movement throughout the year not only regulate the larval distribution and dispersion of estuarine species but are also fundamental for the ACS species, providing the necessary nutrient input for larval development in the region.

PMID:36007076 | DOI:10.1371/journal.pone.0252695

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Nevin Manimala Statistics

Can the establishment of state-level urban agglomeration stimulate enterprise innovation?-Taking Yangtze River Delta and Pearl River Delta as an example

PLoS One. 2022 Aug 25;17(8):e0273154. doi: 10.1371/journal.pone.0273154. eCollection 2022.

ABSTRACT

This study uses a quasi-experimental method, Geographic Regression Discontinuity Design (GRDD), to evaluate the actual effect of establishing Yangtze River Delta and Pearl River Delta urban agglomerations on enterprise innovation. GRDD is a design in which a geographic boundary splits the units into treated and control areas in an as-if random fashion, and the shortest distances from each enterprise’s location to the boundary of urban agglomeration calculated by ArcGIS are considered as the running variable. The actual effect can be identified by the probability of receiving treatment jumps discontinuously at the known cutoff. It is shown that the establishment of Yangtze River Delta and Pearl River Delta urban agglomerations can significantly improve the enterprise innovation, and this outcome is verified by rigorous robustness tests including the placebo test with pseudo-boundary, the bandwidth sensitivity test, the parametric test with different functional forms and the extreme value test. Further, the influence mechanisms of state-level urban agglomerations promoting enterprise innovation are explored by Staggered DID. It is confirmed that the urban agglomeration construction can promote enterprise innovation through financial support and regional coordination channels.

PMID:36007065 | DOI:10.1371/journal.pone.0273154

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Nevin Manimala Statistics

Practical identifiability analysis of a mechanistic model for the time to distant metastatic relapse and its application to renal cell carcinoma

PLoS Comput Biol. 2022 Aug 25;18(8):e1010444. doi: 10.1371/journal.pcbi.1010444. Online ahead of print.

ABSTRACT

Distant metastasis-free survival (DMFS) curves are widely used in oncology. They are classically analyzed using the Kaplan-Meier estimator or agnostic statistical models from survival analysis. Here we report on a method to extract more information from DMFS curves using a mathematical model of primary tumor growth and metastatic dissemination. The model depends on two parameters, α and μ, respectively quantifying tumor growth and dissemination. We assumed these to be lognormally distributed in a patient population. We propose a method for identification of the parameters of these distributions based on least-squares minimization between the data and the simulated survival curve. We studied the practical identifiability of these parameters and found that including the percentage of patients with metastasis at diagnosis was critical to ensure robust estimation. We also studied the impact and identifiability of covariates and their coefficients in α and μ, either categorical or continuous, including various functional forms for the latter (threshold, linear or a combination of both). We found that both the functional form and the coefficients could be determined from DMFS curves. We then applied our model to a clinical dataset of metastatic relapse from kidney cancer with individual data of 105 patients. We show that the model was able to describe the data and illustrate our method to disentangle the impact of three covariates on DMFS: a categorical one (Führman grade) and two continuous ones (gene expressions of the macrophage mannose receptor 1 (MMR) and the G Protein-Coupled Receptor Class C Group 5 Member A (GPRC5a)gene). We found that all had an influence in metastasis dissemination (μ), but not on growth (α).

PMID:36007057 | DOI:10.1371/journal.pcbi.1010444

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Nevin Manimala Statistics

Policy impacts of statistical uncertainty and privacy

Science. 2022 Aug 26;377(6609):928-931. doi: 10.1126/science.abq4481. Epub 2022 Aug 25.

ABSTRACT

Funding formula reform may help address unequal impacts of uncertainty from data error and privacy protections.

PMID:36007047 | DOI:10.1126/science.abq4481

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Nevin Manimala Statistics

Reference rate for post-tonsillectomy haemorrhage in Australia-A 2000-2020 national hospital morbidity database analysis

PLoS One. 2022 Aug 25;17(8):e0273320. doi: 10.1371/journal.pone.0273320. eCollection 2022.

ABSTRACT

This study aims to provide a national benchmark rate of post-tonsillectomy haemorrhage (PTH) in Australia. Using data from Australia’s National Hospital Morbidity Database (NHMD) from 1 July 2000 to 30 June 2020, we have conducted a nation-wide population-based study to estimate a reference rate of PTH. Outcomes of interest included the overall rate and time-trend of PTH, the relationship between PTH rates with age and gender as well as the epidemiology of tonsillectomy procedures. A total of 941,557 tonsillectomy procedures and 15,391 PTH episodes were recorded for the study period. Whilst the incidence of tonsillectomy procedures and the number of day-stay tonsillectomy procedures have increased substantially over time, the overall rate of PTH for all ages has remained relatively constant (1.6% [95% CI: 1.61 to 1.66]) with no significant association observed between the annual rates of PTH and time (year) (Spearman correlation coefficient, Rs = 0.24 (95% CI: -0.22 to 0.61), P = 0.3). However, the rate of PTH in adults (aged 15 years and over) experienced a statistically significant mild to moderate upward association with time (year) Rs = 0.64 (95% CI: 0.28 to 0.84), P = 0.003. Analysis of the odds of PTH using the risk factors of increasing age and male gender showed a unique age and gender risk pattern for PTH where males aged 20 to 24 years had the highest risk of PTH odds ratio 7.3 (95% CI: 6.7 to 7.8) compared to patients aged 1 to 4 years. Clinicians should be mindful of the greater risk of PTH in male adolescents and young adults. The NHMD datasets can be continually used to evaluate the benchmark PTH rate in Australia and to facilitate tonsillectomy surgical audit activities and quality improvement programs on a national basis.

PMID:36006990 | DOI:10.1371/journal.pone.0273320

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Nevin Manimala Statistics

Quantitative bile and serum proteomics for the screening and differential diagnosis of primary sclerosing cholangitis

PLoS One. 2022 Aug 25;17(8):e0272810. doi: 10.1371/journal.pone.0272810. eCollection 2022.

ABSTRACT

BACKGROUND: Primary sclerosing cholangitis (PSC) is a chronic liver disease characterized by biliary strictures, cholestasis, and a markedly increased risk of cholangiocarcinoma. New markers for the screening and differential diagnosis of PSC are needed. In this pilot study, we have analyzed both the bile and serum proteomic profiles of 80 PSC patients and non-PSC controls (n = 6 for bile and n = 18 for serum).

AIM: The aim of this study was to discover candidates for new biomarkers for the differential diagnosis of PSC.

METHODS: Bile and serum samples were processed and subsequently analyzed using ultra performance liquid chromatography-ultra definition mass spectrometry (UPLC-UDMSE). Further analysis included statistical analyses such as receiver operating characteristic curve analysis as well as pathway analysis using Ingenuity Pathway Analysis.

RESULTS AND CONCLUSIONS: In bile, we discovered 64 proteins with significantly different levels between the groups, with fold changes of up to 129. In serum, we discovered 112 proteins with significantly different levels. Receiver operating characteristic curve analysis found multiple proteins with high area under the curve values, up to 0.942, indicating that these serum proteins are of value as new non-invasive classifiers of PSC. Pathway analysis revealed multiple canonical pathways that were enriched in the dataset, which have roles in bile homeostasis and metabolism. We present several serum proteins that could serve as new blood-based markers for the diagnosis of PSC after further validation. The measurement of serum levels of these proteins could be of use in the screening of patients with suspected PSC.

PMID:36006970 | DOI:10.1371/journal.pone.0272810

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Nevin Manimala Statistics

Mitigation of noise-induced bias of PET radiomic features

PLoS One. 2022 Aug 25;17(8):e0272643. doi: 10.1371/journal.pone.0272643. eCollection 2022.

ABSTRACT

INTRODUCTION: One major challenge in PET radiomics is its sensitivity to noise. Low signal-to-noise ratio (SNR) affects not only the precision but also the accuracy of quantitative metrics extracted from the images resulting in noise-induced bias. This phantom study aims to identify the radiomic features that are robust to noise in terms of precision and accuracy and to explore some methods that might help to correct noise-induced bias.

METHODS: A phantom containing three 18F-FDG filled 3D printed inserts, reflecting heterogeneous tracer uptake and realistic tumor shapes, was used in the study. The three different phantom inserts were filled and scanned with three different tumor-to-background ratios, simulating a total of nine different tumors. From the 40-minute list-mode data, ten frames each for 5 s, 10 s, 30 s, and 120 s frame duration were reconstructed to generate images with different noise levels. Under these noise conditions, the precision and accuracy of the radiomic features were analyzed using intraclass correlation coefficient (ICC) and similarity distance metric (SDM) respectively. Based on the ICC and SDM values, the radiomic features were categorized into four groups: poor, moderate, good, and excellent precision and accuracy. A “difference image” created by subtracting two statistically equivalent replicate images was used to develop a model to correct the noise-induced bias. Several regression methods (e.g., linear, exponential, sigmoid, and power-law) were tested. The best fitting model was chosen based on Akaike information criteria.

RESULTS: Several radiomic features derived from low SNR images have high repeatability, with 68% of radiomic features having ICC ≥ 0.9 for images with a frame duration of 5 s. However, most features show a systematic bias that correlates with the increase in noise level. Out of 143 features with noise-induced bias, the SDM values were improved based on a regression model (53 features to excellent and 67 to good) indicating that the noise-induced bias of these features can be, at least partially, corrected.

CONCLUSION: To have a predictive value, radiomic features should reflect tumor characteristics and be minimally affected by noise. The present study has shown that it is possible to correct for noise-induced bias, at least in a subset of the features, using a regression model based on the local image noise estimates.

PMID:36006959 | DOI:10.1371/journal.pone.0272643

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Nevin Manimala Statistics

Effectiveness of graded motor imagery protocol in phantom limb pain in amputed patient: Protocol of a randomized clinical trial

PLoS One. 2022 Aug 25;17(8):e0273356. doi: 10.1371/journal.pone.0273356. eCollection 2022.

ABSTRACT

OBJECTIVE: The aim of this study is to analyse the effectiveness of the Graded Motor Imagery (GraMI) protocol in phantom limb pain in amputee patients.

MATERIALS AND METHODS: A randomised clinical trial will be conducted, with two parallel groups and simple blinding, and a phenomenological study with semi-structured interviews. People over the age of 18, with amputation of one limb, with a minimum score of 3 on the visual analogue scale of pain, who are pharmacologically stable and have been discharged from hospital, will be recruited. An initial assessment, a post-intervention assessment (9 weeks) and a follow-up assessment (12 weeks post-intervention) will be performed, in which pain, quality of life, functionality and psychological aspects will be assessed. The aim of the qualitative study is to find out about the experience of living with phantom limb pain and to identify the satisfaction with the intervention. A descriptive, univariate and bivariate quantitative statistical analysis will be performed using the SPSS program, with a 95% confidence level and a statistical significance level of p < 0.05. The qualitative analysis will be carried out using the Atlas.ti 8.0 program, where the different interviews will be analysed, coded and categorised.

DISCUSSION: The GraMI protocol allows the patient to work on motor learning through brain reorganisation, analytical movements, sensory stimulation, and functional activities. In addition, it can help to standardise the use of graded motor imagery in future studies and in clinical practice with this patient profile.

TRIAL REGISTRATION: NCT05083611.

PMID:36006951 | DOI:10.1371/journal.pone.0273356

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Nevin Manimala Statistics

A distinct four-value blood signature of pyrexia under combination therapy of malignant melanoma with dabrafenib and trametinib evidenced by an algorithm-defined pyrexia score

PLoS One. 2022 Aug 25;17(8):e0273478. doi: 10.1371/journal.pone.0273478. eCollection 2022.

ABSTRACT

Pyrexia is a frequent adverse event of BRAF/MEK-inhibitor combination therapy in patients with metastasized malignant melanoma (MM). The study’s objective was to identify laboratory changes which might correlate with the appearance of pyrexia. Initially, data of 38 MM patients treated with dabrafenib plus trametinib, of which 14 patients developed pyrexia, were analysed retrospectively. Graphical visualization of time series of laboratory values suggested that a rise in C-reactive-protein, in parallel with a fall of leukocytes and thrombocytes, were indicative of pyrexia. Additionally, statistical analysis showed a significant correlation between lactate dehydrogenase (LDH) and pyrexia. An algorithm based on these observations was designed using a deductive and heuristic approach in order to calculate a pyrexia score (PS) for each laboratory assessment in treated patients. A second independent data set of 28 MM patients, 8 with pyrexia, was used for the validation of the algorithm. PS based on the four parameters CRP, LDH, leukocyte and thrombocyte numbers, were statistically significantly higher in pyrexia patients, differentiated between groups (F = 20.8; p = <0.0001) and showed a significant predictive value for the diagnosis of pyrexia (F = 6.24; p = 0.013). We provide first evidence that pyrexia in patients treated with BRAF/MEK-blockade can be identified by an algorithm that calculates a score.

PMID:36006943 | DOI:10.1371/journal.pone.0273478