Sinkhole Detection and Characterization Using LiDAR-Derived DEM with Logistic Regression

Depressions due to sinkhole formation cause significant structural damages to buildings and civil infrastructure. Traditionally, visual inspection has been used to detect sinkholes, which is a subjective way and time- and labor-consuming. Remote sensing techniques have been introduced for morphometric studies of karst landscapes. This study presents a methodology for the probabilistic detection of sinkholes using LiDAR-derived digital elevation model (DEM) data. The proposed study provides benefits associated with: (1) Detection of unreported sinkholes in rural and/or inaccessible areas, (2) automatic delineation of sinkhole boundaries, and (3) quantification of the geometric characteristics of those identified sinkholes. Among sixteen morphometric parameters, nine parameters were chosen for logistic regression, which was then employed to compute the probability of sinkhole detection; a cutoff value was back-calculated such that the sinkhole susceptibility map well predicted the reported sinkhole boundaries. According to the results of the LR model, the optimal cutoff value was calculated to be 0.13, and the area under the curve (AUC) of the receiver operating characteristic curve (ROC) was 0.90, indicating the model is reliable for the study area. For those identified sinkholes, the geometric characteristics (e.g., depth, length, area, and volume) were computed.

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D-dimer as a biomarker for assessment of COVID-19 prognosis: D-dimer levels on admission and its role in predicting disease outcome in hospitalized patients with COVID-19

PLoS ONE ◽

10.1371/journal.pone.0256744 ◽

2021 ◽

Vol 16 (8) ◽

pp. e0256744

Author(s):

Ayusha Poudel ◽

Yashasa Poudel ◽

Anurag Adhikari ◽

Barun Babu Aryal ◽

Debika Dangol ◽

...

Keyword(s):

Proportional Hazards ◽

Characteristic Curve ◽

Area Under The Curve ◽

Respiratory Illness ◽

Immunofluorescence Assay ◽

Cox Proportional Hazards ◽

Optimal Cutoff ◽

Cutoff Value ◽

Potential Biomarker ◽

D Dimer

Introduction Coronavirus Disease 2019 is a primarily respiratory illness that can cause thrombotic disorders. Elevation of D-dimer is a potential biomarker for poor prognosis in COVID-19, though optimal cutoff value for D-dimer to predict mortality has not yet been established. This study aims to assess the accuracy of admission D-dimer in the prognosis of COVID-19 and to establish the optimal cutoff D-dimer value to predict hospital mortality. Methods Clinical and laboratory parameters and outcomes of confirmed COVID-19 cases admitted to four hospitals in Kathmandu were retrospectively analyzed. Admitted COVID-19 cases with recorded D-dimer and definitive outcomes were included consecutively. D-dimer was measured using immunofluorescence assay and reported in Fibrinogen Equivalent Unit (μg/ml). The receiver operating characteristic curve was used to determine the accuracy of D-dimer in predicting mortality, and to calculate the optimal cutoff value, based on which patients were divided into two groups and predictive value of D-dimer for mortality was measured. Results 182 patients were included in the study out of which 34(18.7%) died during the hospital stay. The mean admission D-dimer among surviving patients was 1.067 μg/ml (±1.705 μg/ml), whereas that among patients who died was 3.208 μg/ml (±2.613 μg/ml). ROC curve for D-dimer and mortality gave an area under the curve of 0.807 (95% CI 0.728–0.886, p<0.001). Optimal cutoff value for D-dimer was 1.5 μg/ml (sensitivity 70.6%, specificity 78.4%). On Cox proportional hazards regression analysis, the unadjusted hazard ratio for high D-dimer was 6.809 (95% CI 3.249–14.268, p<0.001), and 5.862 (95% CI 2.751–12.489, p<0.001) when adjusted for age. Conclusion D-dimer value on admission is an accurate biomarker for predicting mortality in patients with COVID-19. 1.5 μg/ml is the optimal cutoff value of admission D-dimer for predicting mortality in COVID-19 patients.

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Relationship between aspartate aminotransferase to platelet ratio index and liver injury in pediatric sepsis

Paediatrica Indonesiana ◽

10.14238/pi61.3.2021.149-54 ◽

2021 ◽

Vol 61 (3) ◽

pp. 149-54

Author(s):

Robby Godlief ◽

Dzulfikar Djalil Lukmanul Hakim ◽

Dwi Prasetyo

Keyword(s):

Logistic Regression ◽

Liver Injury ◽

Aspartate Aminotransferase ◽

Clinical Manifestations ◽

Area Under The Curve ◽

Secondary Data ◽

Multiple Organ ◽

Chi Square ◽

Cutoff Value ◽

Pediatric Sepsis

Background Sepsis-associated liver injury (SALI) is one of the main clinical manifestations of sepsis, as well as an independent risk factor for multiple organ dysfunction syndrome and mortality in pediatric sepsis. The early warning biomarkers for identifying SALI remain poorly defined. Objective To analyze the relationship between aspartate aminotransferase to platelet ratio index (APRi) and liver injury occurrence in pediatric sepsis, as well as determine the APRi cutoff value for early identification of SALI. Methods This retrospective study used secondary data derived from January 2019 to August 2020. The study population comprised admitted children aged 1 month to <18 years who met the criteria for sepsis, and had aspartate aminotransferase (AST) and platelet laboratory parameters checked in the first 24 hours of sepsis and before administration of antibiotics. Pearson’s Chi-square test was used to analyze for correlations. Estimation of the APRi cutoff value in the early occurrence of SALI was performed with logistic regression analysis and receiver operating characteristic (ROC) curve. Results Of the 112 subjects, 94.6% were categorized as having septic shock and 48.2% had SALI. Logistic regression revealed that APRi was a significant predictor of SALI, as indicated by cut-off 4.726 [OR 1.098; 95%CI 1.002 to1.203; P=0.045]. The area under the curve (AUC) was 0.831 or 83.1%, which was classified as strong (80-90%). Conclusion The APRi is a reliable early predictor of SALI in pediatric sepsis, as indicated by an increase in APRi (> 4.726) within the first 24 hours of sepsis.

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The Optimal Cutoff Value of D-dimer Levels to Predict in Hospital Mortality in Severe Cases of Coronavirus Disease 2019

Open Access Macedonian Journal of Medical Sciences ◽

10.3889/oamjms.2021.7600 ◽

2021 ◽

Vol 9 (B) ◽

pp. 1561-1564

Author(s):

Ngakan Ketut Wira Suastika ◽

Ketut Suega

Keyword(s):

Hospital Mortality ◽

Receiver Operating Characteristic Curve ◽

Receiver Operating Characteristic ◽

Operating Characteristic ◽

Characteristic Curve ◽

Area Under The Curve ◽

Optimal Cutoff ◽

Cutoff Value ◽

Operating Characteristic Curve ◽

D Dimer

Introduction: Coronavirus disease 2019 (Covid-19) can cause coagulation parameters abnormalities such as an increase of D-dimer levels especially in severe cases. The purpose of this study is to determine the differences of D-dimer levels in severe cases of Covid-19 who survived and non-survived and determine the optimal cut-off value of D-dimer levels to predict in-hospital mortality. Method: Data were obtained from confirmed Covid-19 patients who were treated from June to September 2020. The Mann-Whitney U test was used to determine differences of D-dimer levels in surviving and non-surviving patients. The optimal cut-off value and area under the curve (AUC) of the D-dimer level in predicting mortality were obtained by the receiver operating characteristic curve (ROC) method. Results: A total of 80 patients were recruited in this study. Levels of D-dimer were significantly higher in non-surviving patients (median 3.346 mg/ml; minimum – maximum: 0.939 – 50.000 mg/ml) compared to surviving patients (median 1.201 mg/ml; minimum – maximum: 0.302 – 29.425 mg/ml), p = 0.012. D-dimer levels higher than 1.500 mg/ml are the optimal cut-off value for predicting mortality in severe cases of Covid-19 with a sensitivity of 80.0%; specificity of 64.3%; and area under the curve of 0.754 (95% CI 0.586 - 0.921; p = 0.010). Conclusions: D-dimer levels can be used as a predictor of mortality in severe cases of Covid-19.

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Volume, conductivity, and scatter parameters of leukocytes as early markers of sepsis and treatment response

Journal of Laboratory Physicians ◽

10.4103/jlp.jlp_102_18 ◽

2019 ◽

Vol 11 (01) ◽

pp. 029-033

Author(s):

Parul Arora ◽

Praveen Kumar Gupta ◽

Raghavendra Lingaiah ◽

Asok Kumar Mukhopadhyay

Keyword(s):

Characteristic Curve ◽

Area Under The Curve ◽

Receiver Operator Characteristic Curve ◽

Sepsis Group ◽

Control Group ◽

Cutoff Value ◽

Volume Conductivity ◽

Gram Positive Bacteria ◽

Automated Hematology Analyzer ◽

Culture Positive

Abstract INTRODUCTION: Morphologic changes in the size and granularity of leukocytes seen in sepsis could be measured using the volume, conductivity, and scatter (VCS parameters) from the automated hematology analyzers. The objective of this study is to find the clinical usefulness of VCS parameters as possible indicators of sepsis and to determine the effect of treatment on these parameters. METHODS: This observational study was conducted in a tertiary level hospital in India. Hemogram and VCS parameters obtained from LH 750 (Beckman coulter, Fullerton, CA) from 134 proven blood culture-positive cases of sepsis were reviewed on the day of culture positivity (day 0), day 3, and day 7 were analyzed and compared with those of samples from otherwise healthy 100 participants. Statistical analysis of data was done, and cutoff value was established using receiver-operator characteristic curve. RESULTS: Out of 134 culture-positive cases, 55.2% (n = 74) Gram-negative and 44.8% (n = 60) Gram-positive bacteria were isolated. The mean neutrophil volume (MNV) and mean monocyte volume (MMV) were higher in the sepsis group compared to that of the control group (165.43 ± 18.21 vs. 140.59 ± 7.6, P = 0.001 for MNV and 179.8 ± 14.16 vs. 164.54 ± 9.6, P = 0.001 for MMV). A significant decrease in MNV and MMV was observed with the initiation of the treatment. Significant changes in scatter and conductivity parameters were also noticed. A cutoff value of 150.2 for MNV gave a sensitivity and specificity of 79.1% and 95%, respectively, with an area under the curve (AUC) of 92.3%. With a cutoff of 168.3, MMV had a sensitivity of 80.6% and specificity of 77.5%, AUC of 83%. CONCLUSION: VCS parameters such as MNV and MMV can be easily obtained by an automated hematology analyzer and could be used for early detection and therapeutic response in sepsis.

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Combined 18F-FET PET and diffusion kurtosis MRI in post-treatment glioblastoma: differentiation of true progression from treatment related changes

Neuro-Oncology Advances ◽

10.1093/noajnl/vdab044 ◽

2021 ◽

Author(s):

Francesco D’Amore ◽

Farida Grinberg ◽

Jörg Mauler ◽

Norbert Galldiks ◽

Ganna Blazhenets ◽

...

Keyword(s):

Logistic Regression ◽

Diagnostic Accuracy ◽

Diffusion Mri ◽

Tumour Progression ◽

Characteristic Curve ◽

Area Under The Curve ◽

Regions Of Interest ◽

Fet Pet ◽

Diffusion Kurtosis ◽

And Diffusion

Abstract Background Radiological differentiation of tumour progression (TPR) from treatment-related changes (TRC) in pre-treated glioblastoma is crucial. This study aimed to explore the diagnostic value of diffusion kurtosis MRI combined with information derived from O-(2-[ 18F]-fluoroethyl)-L-tyrosine ( 18F-FET) PET for the differentiation of TPR from TRC in patients with pre-treated glioblastoma. Methods Thirty-two patients with histomolecularly defined and pre-treated glioblastoma suspected of having TPR were included in this retrospective study. Twenty-one patients were included in the TPR group, and 11 patients in the TRC group, as assessed by neuropathology or clinicoradiological follow-up. 3D regions-of-interest were generated based on increased 18F-FET uptake using a brain-to-tumour ratio of 1.6. Furthermore, diffusion MRI kurtosis maps were obtained from the same regions-of-interests using co-registered 18F-FET PET images, and an advanced histogram analysis of diffusion kurtosis map parameters was applied to generated 3D regions-of-interest. Diagnostic accuracy was analysed by receiver-operating characteristic curve analysis and combinations of PET and MRI parameters using multivariate logistic regression. Results Parameters derived from diffusion MRI kurtosis maps show high diagnostic accuracy, up to 88%, for differentiating between TPR and TRC. Logistic regression revealed that the highest diagnostic accuracy of 94% (area under the curve, 0.97; sensitivity, 94%; specificity, 91%) was achieved by combining the maximum tumour-to-brain ratio of 18F-FET uptake and diffusion MRI kurtosis metrics. Conclusions The combined use of 18F-FET PET and MRI diffusion kurtosis maps appears to be a promising approach to improve the differentiation of TPR from TRC in pre-treated glioblastoma and warrants further investigation.

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Predictive impact of C-reactive protein to albumin ratio for recurrent or metastatic head and neck squamous cell carcinoma receiving nivolumab

Scientific Reports ◽

10.1038/s41598-021-82448-1 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Kenro Tanoue ◽

Shingo Tamura ◽

Hitoshi Kusaba ◽

Yudai Shinohara ◽

Mamoru Ito ◽

...

Keyword(s):

Head And Neck ◽

Characteristic Curve ◽

Area Under The Curve ◽

Progression Free Survival ◽

C Reactive Protein ◽

Optimal Cutoff ◽

Poor Overall Survival ◽

Albumin Ratio ◽

Cutoff Value ◽

Reactive Protein

AbstractAlthough the neutrophil to lymphocyte ratio (NLR) was reported to be a predictive biomarker for clinical outcomes in various types of cancer, including recurrent or metastatic head and neck cancer (R/M HNSCC) treated with nivolumab, the usefulness of the pretreatment C-reactive protein/albumin ratio (CAR) as a prognostic marker remains to be clarified. This study aimed to analyze the clinical usability of the CAR in comparison with that of the NLR. 46 R/M HNSCC patients treated with nivolumab were retrospectively analyzed. The optimal cutoff value for the CAR was calculated using receiver operating characteristic curve analysis. The optimal cutoff value for the CAR was set to 0.30. On multivariate analyses, a high CAR was significantly associated with poor overall survival (adjusted HR, 2.19; 95% CI, 1.42–3.47; p < 0.01) and progression-free survival (adjusted HR, 1.98; 95% CI, 1.38–2.80; p < 0.01). The overall response rate and disease control rate for the high CAR patients were lower than for the low CAR patients. The CAR had significantly higher area under the curve values than the NLR at 2 and 4 months. The pretreatment CAR might be an independent marker for prognosis and efficacy in R/M HNSCC patients treated with nivolumab.

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Increased carotid stiffness detected by ultrafast ultrasound imaging is associated with the Gensini score

Medical Ultrasonography ◽

10.11152/mu-2323 ◽

2020 ◽

Vol 22 (2) ◽

pp. 183

Author(s):

Yang Li ◽

Ying Zhang ◽

Xu Geng ◽

Shuai Zhao ◽

Yi-Xue Sun ◽

...

Keyword(s):

Ultrasound Imaging ◽

Characteristic Curve ◽

Area Under The Curve ◽

Intima Media Thickness ◽

Carotid Intima Media Thickness ◽

Gensini Score ◽

Cross Sectional ◽

Cutoff Value ◽

Carotid Stiffness ◽

Normal Controls

Aim: To test the ability of carotid stiffness evaluated by using ultrafast ultrasound imaging to indicate coronary atherosclerosis and its association with the severity of coronary artery disease (CAD).Material and methods: This cross-sectional study included 131 patients with CAD and 60 normal controls. Carotid intima-media thickness (cIMT) was measured by two-dimensional ultrasound. Carotid stiffness was determined by ultrafast ultrasound imaging, with which the carotid pulse wave velocity at the beginning (PWVBS) and end (PWVES) of systole were calculated. Gensini scores based on coronary angiography were used to estimate the severity of CAD.Results: Compared with normal controls, the CAD patients had higher carotid diameters, cIMT, PWVBS and PWVES (p < 0.05). In the CAD group, Gensini scores correlated significantly with cIMT, PWVBS and PWVES (r = 0.279, p = 0.001; r = 0.661, p < 0.001; r = 0.620, p < 0.001; respectively). The multivariate analysis further indicated that PWVBS, PWVES and body mass index were independently associated with the Gensini score (β = 0.466, p < 0.001; β = 0.308, p < 0.001; and β = 0.209, p = 0.001; respectively). In addition, the sensitivity and specificity were 54% and 83%, respectively, for PWVBS (cutoff value, 6.9 m/s; area under the receiver operating characteristic curve, 0.70) and 64% and 83%, respectively, for PWVES (cutoff value, 8.0 m/s; area under the curve, 0.73).Conclusions: Increased carotid PWVBS and PWVES detected by ultrafast ultrasound imaging as indices of carotid stiffness might serve as promising indicators for CAD and its severity.

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S-100β in predicting the need of hyperbaric oxygen in CO-induced delayed neurological sequels

Human & Experimental Toxicology ◽

10.1177/0960327119897104 ◽

2019 ◽

Vol 39 (5) ◽

pp. 614-623

Author(s):

Amal SAF Hafez ◽

Ghada N El-Sarnagawy

Keyword(s):

Carbon Monoxide ◽

Hyperbaric Oxygen ◽

Operating Characteristic ◽

Characteristic Curve ◽

Area Under The Curve ◽

Curve Analysis ◽

Co Poisoning ◽

Cutoff Value ◽

The Mean ◽

Operating Characteristic Curve

Background: Delayed neurological sequels (DNS) have been described after carbon monoxide (CO) poisoning. There is a need to find a new prognostic marker to guide the use of hyperbaric oxygen (HBO) therapy. Aim: To evaluate serum S-100β level in patients presenting with acute CO poisoning as an indicator of poisoning severity and predictor of DNS occurrence and HBO need in those patients. Methods: This prospective cohort study included patients with acute CO poisoning. On admission, carboxyhemoglobin (COHb) and S-100β levels were measured. Patients were followed up for 6 months for signs of DNS. Results: Out of 50 patients, 6 only developed DNS. The mean of S-100β levels was significantly higher in patients with severe poisoning and those with DNS. Receiver operating characteristic curve analysis revealed that S-100β had an area under the curve 0. 871; at a cutoff value ≥ 0.67 µg/L, its sensitivity and specificity were 100% and 77.3%, respectively. The sensitivity of S-100β was significantly higher than that of COHb, while its specificity and overall accuracy were significantly higher than those of HBO criteria. Conclusion: Serum S-100β level on admission could be a marker of poisoning severity and a predictor of CO-induced DNS development that guides the use of HBO therapy.

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Exploring the potential relationship between the occurrence of debris flow and landslide

10.5194/nhess-2020-294 ◽

2020 ◽

Author(s):

Zhu Liang ◽

Changming Wang ◽

Donghe Ma ◽

Kaleem Ullah Jan Khan

Keyword(s):

Random Forest ◽

Debris Flow ◽

Characteristic Curve ◽

Area Under The Curve ◽

Susceptibility Map ◽

Relative Operating Characteristic ◽

Conditioning Factors ◽

Statistical Measures ◽

Potential Relationship ◽

Major Factors

Abstract. he aim of the present study is to explore the potential relationship between debris flow and soil slide by establishing susceptibility zoning maps (SZM) separately with the use of random forest. Longzi County, located in Southeastern Tibet, where historical landslides occurred commonly, was selected as the study area. The work has been carried out with the following steps: (1) An inventory map consisting of 448 landslides (399 soil slides and 49 debris flows) was determined; (2) Slope units and 11 conditioning factors were prepared for the susceptibility modelling of landslide while watershed units and 12 factors for debris flow; (3) SZM were constructed for landslide and debris flow, respectively, with the use of random forest; (4) The performance of two models were evaluated by 5-fold cross-validation using relative operating characteristic curve (ROC), area under the curve (AUC) and statistical measures; (5) The potential relationship between soil slide and debris flow was explored by the superimposition of two zoning maps; (6) Gini index was applied to determined the major factors and analyze the difference between debris flow and soil slide; (7) A combined susceptibility map with two kinds of disaster was obtained. Two models had demonstrated great predictive capabilities, of which accuracy and AUC was 87.33 %, 0.902 and 85.17 %, 0.892, respectively. The loose sources need by the debris flow were not necessarily brought by the landslides although most landslides can be converted into debris flow. The area prone to debris flow did not promote the occurrence of landslide. A susceptibility zoning map composed of two or more natural disasters is comprehensive and significant in this regard, which provides valuable reference for researches of disaster-chain and engineering applications.

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The Association between Trajectories of Anthropometric Variables and Risk of Diabetes among Prediabetic Chinese

Nutrients ◽

10.3390/nu13124356 ◽

2021 ◽

Vol 13 (12) ◽

pp. 4356

Author(s):

Fang Li ◽

Lizhang Chen

Keyword(s):

Logistic Regression ◽

Weight Control ◽

Characteristic Curve ◽

Area Under The Curve ◽

Growth Mixture Modeling ◽

Growth Mixture ◽

Arm Circumference ◽

Bmi Trajectories ◽

Body Weight Control ◽

Mid Upper Arm Circumference

In order to explore the association between trajectories of body mass index (BMI) and mid-upper arm circumference (MUAC) and diabetes and to assess the effectiveness of the models to predict diabetes among Chinese prediabetic people, we conducted this study. Using a national longitudinal study, 1529 cases were involved for analyzing the association between diabetes and BMI trajectories or MUAC trajectories. Growth mixture modeling was conducted among the prediabetic Chinese population to explore the trajectories of BMI and MUAC, and logistic regression was applied to evaluate the association between these trajectories and the risk of diabetes. The receiver operating characteristic curve (ROC) and the area under the curve (AUC) were applied to assess the feasibility of prediction. BMI and MUAC were categorized into 4-class trajectories, respectively. Statistically significant associations were observed between diabetes in certain BMI and MUAC trajectories. The AUC for trajectories of BMI and MUAC to predict diabetes was 0.752 (95% CI: 0.690–0.814). A simple cross-validation using logistic regression indicated an acceptable efficiency of the prediction. Diabetes prevention programs should emphasize the significance of body weight control and maintaining skeletal muscle mass and resistance training should be recommended for prediabetes.

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