Diagnostic tests (1) - sensitivity and specificity

The Role of Aspartate Aminotransferase-to-Lymphocyte Ratio Index (ALRI) in Predicting Mortality in SARS-CoV-2 Infection

COVID-19 has a mortality rate exceeding 5.4 million worldwide. The early identification of patients at a high risk of mortality is essential to save their lives. The AST-to-lymphocyte ratio index (ALRI) is a novel biomarker of survival in patients with hepatocellular carcinoma, an organ susceptible to SARS-CoV-2 infection. For this study, the prognostic value of ALRI as a marker of COVID-19 mortality was evaluated. For this purpose, ALRI was compared with the main biomarkers for COVID-19 mortality (neutrophil-to-lymphocyte ratio [NLR], systemic immune-inflammation index [SII], platelet-to-lymphocyte ratio [PLR], lactate dehydrogenase (LDH)/lymphocyte ratio [LDH/LR]). A retrospective cohort of 225 patients with SARS-CoV-2 infection and without chronic liver disease was evaluated. In the non-survival group, the ALRI, NLR, SII, and LDH/LR were significantly higher than in the survival group (pcorrected < 0.05). ALRI had an area under the curve (AUC) of 0.81, a sensitivity of 70.37%, and a specificity of 75%, with a best cut-off value >42.42. COVID-19 patients with high ALRI levels had a mean survival time of 7.8 days. Multivariate Cox regression revealed that ALRI > 42.42 (HR = 2.32, 95% CI: 1.35-3.97; pcorrected = 0.01) was a prognostic factor of COVID-19 mortality. These findings prove that ALRI is an independent predictor of COVID-19 mortality and that it may help identify high-risk subjects with SARS-CoV-2 infection upon admission.

Two Symptoms to Triage Acute Concussions: Using Decision Tree Modeling to Predict Prolonged Recovery After a Concussion

OBJECTIVE

The objective was to examine the 22 variables from the Sport Concussion Assessment Tool's 5th Edition Symptom Evaluation using a decision tree analysis to identify those most likely to predict prolonged recovery after a sport-related concussion.

DESIGN

A cross-sectional design was used in this study. A total of 273 patients (52% men; mean age, 21 ± 7.6 yrs) initially assessed by either an emergency medicine or sport medicine physician within 14 days of concussion (mean, 6 ± 4 days) were included. The 22 symptoms from the Sport Concussion Assessment Tool's 5th Edition were included in a decision tree analysis performed using RStudio and the R package rpart. The decision tree was generated using a complexity parameter of 0.045, post hoc pruning was conducted with rpart, and the package carat was used to assess the final decision tree's accuracy, sensitivity and specificity.

RESULTS

Of the 22 variables, only 2 contributed toward the predictive splits: Feeling like "in a fog" and Sadness. The confusion matrix yielded a statistically significant accuracy of 0.7636 (P [accuracy > no information rate] = 0.00009678), sensitivity of 0.6429, specificity of 0.8889, positive predictive value of 0.8571, and negative predictive value of 0.7059.

CONCLUSIONS

Decision tree analysis yielded a statistically significant decision tree model that can be used clinically to identify patients at initial presentation who are at a higher risk of having prolonged symptoms lasting 28 days or more postconcussion.

Clinical Utility of Semistructured Interview and Scales to Assess Withdrawal Syndromes With Dose Reduction or Discontinuation of Selective Serotonin Reuptake Inhibitors or Serotonin Norepinephrine Reuptake Inhibitors

BACKGROUND

Withdrawal syndromes can occur after dose reduction or discontinuation of selective serotonin reuptake inhibitors (SSRIs) or serotonin-norepinephrine reuptake inhibitors (SNRIs). Few measurement instruments are available to assess them: Diagnostic Clinical Interview for Drug Withdrawal 1-New Symptoms of SSRI and SNRI (DID-W1) and Discontinuation Emergent Signs and Symptoms (DESS) checklist. We assessed their interrater reliability, verified the percent agreement between the two, and tested DESS sensitivity and specificity on the basis of the diagnoses formulated via the DID-W1.

METHODS

One-hundred thirty-four subjects who referred for withdrawal at 3 outpatient facilities were enrolled and assessed via the DESS and the DID-W1. Percent agreement and Cohen κ were calculated to measure DID-W1 and DESS interrater reliability, as well as the agreement between DID-W1 and DESS items. Sensitivity and specificity of DESS were derived from the identification of true-positive, false-negative, true-negative, and false-positive on the DID-W1.

RESULTS

Both tools showed excellent interrater reliability (DID-W1 Cohen κ = 0.958; DESS Cohen κ = 0.81-1). The degree of agreement between DID-W1 and DESS items was poor or fair (Cohen κ < 0.40) for some items and moderate (Cohen κ = 0.41-0.60) for others. Sensitivity and specificity of DESS were 0.937 (true-positive = 60, false-negative = 4) and 0.285 (true-negative = 20, false-positive = 50), respectively.

CONCLUSIONS

DID-W1 was a reliable method to identify and diagnose withdrawal syndromes. The DESS checklist showed to be a useful tool for detecting withdrawal SSRI/SNRI symptoms when the aim is to achieve high sensitivity to identify true positives.

An autoencoder and artificial neural network-based method to estimate parity status of wild mosquitoes from near-infrared spectra

After mating, female mosquitoes need animal blood to develop their eggs. In the process of acquiring blood, they may acquire pathogens, which may cause different diseases in humans such as malaria, zika, dengue, and chikungunya. Therefore, knowing the parity status of mosquitoes is useful in control and evaluation of infectious diseases transmitted by mosquitoes, where parous mosquitoes are assumed to be potentially infectious. Ovary dissections, which are currently used to determine the parity status of mosquitoes, are very tedious and limited to few experts. An alternative to ovary dissections is near-infrared spectroscopy (NIRS), which can estimate the age in days and the infectious state of laboratory and semi-field reared mosquitoes with accuracies between 80 and 99%. No study has tested the accuracy of NIRS for estimating the parity status of wild mosquitoes. In this study, we train an artificial neural network (ANN) models on NIR spectra to estimate the parity status of wild mosquitoes. We use four different datasets: An. arabiensis collected from Minepa, Tanzania (Minepa-ARA); An. gambiae s.s collected from Muleba, Tanzania (Muleba-GA); An. gambiae s.s collected from Burkina Faso (Burkina-GA); and An.gambiae s.s from Muleba and Burkina Faso combined (Muleba-Burkina-GA). We train ANN models on datasets with spectra preprocessed according to previous protocols. We then use autoencoders to reduce the spectra feature dimensions from 1851 to 10 and re-train the ANN models. Before the autoencoder was applied, ANN models estimated parity status of mosquitoes in Minepa-ARA, Muleba-GA, Burkina-GA and Muleba-Burkina-GA with out-of-sample accuracies of 81.9±2.8 (N = 274), 68.7±4.8 (N = 43), 80.3±2.0 (N = 48), and 75.7±2.5 (N = 91), respectively. With the autoencoder, ANN models tested on out-of-sample data achieved 97.1±2.2% (N = 274), 89.8 ± 1.7% (N = 43), 93.3±1.2% (N = 48), and 92.7±1.8% (N = 91) accuracies for Minepa-ARA, Muleba-GA, Burkina-GA, and Muleba-Burkina-GA, respectively. These results show that a combination of an autoencoder and an ANN trained on NIR spectra to estimate the parity status of wild mosquitoes yields models that can be used as an alternative tool to estimate parity status of wild mosquitoes, especially since NIRS is a high-throughput, reagent-free, and simple-to-use technique compared to ovary dissections.

Precisión discriminatoria de pruebas serológicas para Trypanosoma cruzi aplicando metodología estándar y de curva COR

Introducción. Las pruebas serológicas se utilizan para detectar infección por Trypanosoma cruzi y su precisión discriminatoria depende del umbral de decisión establecido. La metodología estándar y la de curva característica operativa del receptor (COR) permiten obtener tal umbral.Objetivo. Comparar la precisión discriminatoria de la metodología estándar y la metodología de curva COR en lo que respecta a pruebas serológicas para detectar infección por T. cruzi.Materiales y métodos. Se utilizó un conjunto de valores de anticuerpos contra T. cruzi de individuos clasificados como chagásicos o sanos y se realizaron simulaciones computarizadas en condiciones homocedásticas y heterocedásticas. Se calculó sensibilidad, especificidad, sensibilidad=100%, especificidad=100% y decisión-perfecta.Resultados. La precisión discriminatoria de la metodología estándar favoreció la especificidad (98.22% a 99.56%) sobre la sensibilidad (67.25% a 87.14%), mientras que la de la curva COR mostró un equilibrio entre sensibilidad (94.56% y 96.44%) y especificidad (90.35% y 92.11%). Esta última metodología también evidenció una mayor proporción de decisión-perfecta, la cual llegó a ser >90% en condiciones de homocedasticidad. Los umbrales de decisión fueron afectados por las condiciones de heterocedasticidad.Conclusión. La metodología de la curva COR mostró una mejor precisión discriminatoria, por lo que se recomienda su uso para el cálculo de umbrales de decisión en pruebas serológicas para la enfermedad de Chagas.

Assessment of a new low-cost, PCR-based strategy for high-risk human papillomavirus DNA detection for cervical cancer prevention

Background

HPV test implementation as a primary screening tool has the potential to decrease cervical cancer incidence as shown by several studies around the world. However, in many low-resource settings, the HPV test introduction has been backed down mainly due to its price. In this study, we present a novel low-cost strategy involving simple devices and techniques for high-risk human papillomavirus (HR-HPV) detection. The analytical performance to detect HR-HPV infections of this novel strategy was assessed by comparing it with the Hybrid Capture 2 system (HC2), which is used as gold standard.

Methods

Paired-cervical samples were collected from 541 women assisting to gynecological services in an outpatient clinic. One sample was transported in the Hybrid Capture Standard Transport Medium for HR-HPV detection by the HC2. The second sample was transported on glass slide for detection by PCR-based techniques (GP-EIA, BSGP-EIA and pU 1 M-L/2R).

Results

The level of agreement between the PCR-based techniques and HC2 system was determined with the Cohen’s kappa value. The kappa values between HC2 and GP-EIA, BSGP-EIA and pU 1 M-L/2R were 0.71 (CI 95% 0.63–0.78), 0.78 (CI 95% 0.71–0.84) and 0.63 (CI 95% 0.55–0.72), respectively. However, when the results from both BSGP-EIA and pU 1 M-L/2R were combined, the level of agreement with HC2 was increased to 0.82 (CI 95% 0.76–0.88), reflecting a very good agreement between the two HR-HPV detection strategies. Furthermore, the sensitivity of both techniques combined was also increased compared to the BSGP-EIA (88.7% vs 77.4%) and the pU (88.7 vs 60.9%) without penalizing the specificity obtained with the BSGP-EIA (95.1% vs 96.9%) and the pU (95.1% vs 96.5%).

Conclusions

This novel strategy, combining two PCR-based techniques for HR-HPV detection, could be useful for cervical cancer screening in self-collected samples in low-income countries.

Age grading An. gambiae and An. arabiensis using near infrared spectra and artificial neural networks

Background

Near infrared spectroscopy (NIRS) is currently complementing techniques to age-grade mosquitoes. NIRS classifies lab-reared and semi-field raised mosquitoes into < or ≥ 7 days old with an average accuracy of 80%, achieved by training a regression model using partial least squares (PLS) and interpreted as a binary classifier.

Methods and findings

We explore whether using an artificial neural network (ANN) analysis instead of PLS regression improves the current accuracy of NIRS models for age-grading malaria transmitting mosquitoes. We also explore if directly training a binary classifier instead of training a regression model and interpreting it as a binary classifier improves the accuracy. A total of 786 and 870 NIR spectra collected from laboratory reared An. gambiae and An. arabiensis, respectively, were used and pre-processed according to previously published protocols. The ANN regression model scored root mean squared error (RMSE) of 1.6 ± 0.2 for An. gambiae and 2.8 ± 0.2 for An. arabiensis; whereas the PLS regression model scored RMSE of 3.7 ± 0.2 for An. gambiae, and 4.5 ± 0.1 for An. arabiensis. When we interpreted regression models as binary classifiers, the accuracy of the ANN regression model was 93.7 ± 1.0% for An. gambiae, and 90.2 ± 1.7% for An. arabiensis; while PLS regression model scored the accuracy of 83.9 ± 2.3% for An. gambiae, and 80.3 ± 2.1% for An. arabiensis. We also find that a directly trained binary classifier yields higher age estimation accuracy than a regression model interpreted as a binary classifier. A directly trained ANN binary classifier scored an accuracy of 99.4 ± 1.0 for An. gambiae and 99.0 ± 0.6% for An. arabiensis; while a directly trained PLS binary classifier scored 93.6 ± 1.2% for An. gambiae and 88.7 ± 1.1% for An. arabiensis. We further tested the reproducibility of these results on different independent mosquito datasets. ANNs scored higher estimation accuracies than when the same age models are trained using PLS. Regardless of the model architecture, directly trained binary classifiers scored higher accuracies on classifying age of mosquitoes than regression models translated as binary classifiers.

Conclusion

We recommend training models to estimate age of An. arabiensis and An. gambiae using ANN model architectures (especially for datasets with at least 70 mosquitoes per age group) and direct training of binary classifier instead of training a regression model and interpreting it as a binary classifier.

A Non-Invasive Medical Device for Parkinson's Patients with Episodes of Freezing of Gait

A critical symptom of Parkinson’s disease (PD) is the occurrence of Freezing of Gait (FOG), an episodic disorder that causes frequent falls and consequential injuries in PD patients. There are various auditory, visual, tactile, and other types of stimulation interventions that can be used to induce PD patients to escape FOG episodes. In this article, we describe a low cost wearable system for non-invasive gait monitoring and external delivery of superficial vibratory stimulation to the lower extremities triggered by FOG episodes. The intended purpose is to reduce the duration of the FOG episode, thus allowing prompt resumption of gait to prevent major injuries. The system, based on an Android mobile application, uses a tri-axial accelerometer device for gait data acquisition. Gathered data is processed via a discrete wavelet transform-based algorithm that precisely detects FOG episodes in real time. Detection activates external vibratory stimulation of the legs to reduce FOG time. The integration of detection and stimulation in one low cost device is the chief novel contribution of this work. We present analyses of sensitivity, specificity and effectiveness of the proposed system to validate its usefulness.

Prostate cancer screening in a low prevalence population. Is it worth it?

OBJECTIVES

To embrace a national screening program for prostate cancer, putting into consideration the cost, and the attitude of the general population towards such screening.

METHODS

Men aged greater than 45 and less than 70 years were invited to participate in the current prospective study conducted at  King Saud University Medical City, Riyadh, Saudi Arabia between December 2014 and July 2015. Those with confirmed high prostate-specific antigen (PSA) (≥4 ng/ml) were referred to the urology clinic, then subjected to magnetic resonance imaging.

RESULTS

  The total cohort screened were 2898, we  found 118 cases with high PSA (≥4 ng/ml). Fifty-two cases (60.4%) were confirmed high PSA. All of them were subjected to MRI and biopsy. The confirmed prostate cancer were 7 cases (0.24%). The age of confirmed prostate cancer cases ranged from 49 years to 68 years, Gleason score for 4 cases was low grade (3+3), while it was 3+4 for 2 cases, and only one case had advanced cancer (3+5). Approximately 12% of cases with high PSA did not show up for confirmation of their results for further examination.

CONCLUSIONS

  The present study recommends against mass screening among Saudi population; however, men before 50 years of age should start PSA blood testing until before 70 years after discussing the benefits and harms of such screening through shared decision making.

A multi-template multiplex PCR assay for hepatitis B virus and human β-globin

The Hepatitis B surface antigen (HBsAg) is the hallmark of HBV infection. Detection of antibodies to HBs and the core (ie, HBsAg and HBcAb) are primary serological algorithms in the laboratory diagnosis of HBV. Detection of HBsAg DNA is an important supplement to serological diagnosis especially in clinical cases. Simultaneous amplification of internal cellular controls is a good indicator of sample quality. Human β-globin is a well characterized housekeeping gene (HKG) that is often applied as internal controls (IC) in molecular diagnosis. In this study, individual plasmid clones of the human β-globin and HBs genes were constructed. These plasmid constructs have been applied to characterize a multiplex PCR assays for HBs and β-globin genes. The findings suggest detection limits of less than 10 genome copies of either template In vitro using conventional and multiplex PCR conditions. Under the multiplex conditions, co-amplification of β-globin and HBsAg DNA had a resultant effect on assay sensitivity. This study further highlights the importance of molecular diagnosis in HBV infectious individuals. If fully optimized, this assay could provide a possible diagnostic complement to serological detection in developing countries.

The incidence rate of prostate cancer in Saudi Arabia: an observational descriptive epidemiological analysis of data from the Saudi Cancer Registry 2001-2008

BACKGROUND

This study presents descriptive epidemiological data related to prostate cancer cases diagnosed from 2001 to 2008 among Saudi men, including the frequency and percentage of cases, the crude incidence rate (CIR) and the age-standardised incidence rate (ASIR) adjusted by region and year of diagnosis.

METHODS

This is a retrospective descriptive epidemiological analysis of all Saudi prostate cancer cases recorded in the Saudi Cancer Registry (SCR) between January 2001 and December 2008. Statistical analyses were conducted using descriptive statistics, the Poisson regression model, a simple linear regression model and analysis of variance with the Statistical Package for the Social Sciences version 20.0 (SPSS).

RESULTS

A total of 1739 cases were registered in the SCR between January 2001 and December 2008. The eastern region of Saudi Arabia had the highest overall ASIR at 10.1 per 100,000 men, followed by Riyadh at 7.1 and Makkah at 5.2, while Jizan and Najran had the lowest average ASIRs at 1.4 and at 2.0, respectively. The Poisson regression model for the region of Jizan shows that the incidence rate ratio (IRR) was significantly higher (p < 0.001); for the regions of Riyadh at 3.43 times (95% CI, 3.13-3.73), followed by Makkah at 2.56 (95% CI, 2.38-2.74) and the eastern province at 1.93 (95% CI, 1.64-2.23). The annual prediction of the CIR of prostate cancer in Saudi Arabia could be defined by the equation 1.53 + (0.094 × Years), and the prediction of the ASIR could be defined by the equation 2.98 + (0.182 × Years).

CONCLUSION

There was a steady increase in the CIRs and ASIRs for prostate cancer between 2001 and 2008. The eastern region, Riyadh and Makkah had the highest overall ASIR in Saudi Arabia. Further effective screening programmes and active treatment measures are needed to control prostate cancer disease among Saudi men.

Magnetization transfer contrast imaging reveals amyloid pathology in Alzheimer's disease transgenic mice

The presence of amyloid plaques in the brain is one of the pathological hallmarks of Alzheimer's disease, which might already be present in the early stage of the disease. Therefore it is important to track amyloid plaques as early as possible. In this paper, we report magnetization transfer contrast magnetic resonance imaging (MTC MRI) as a novel approach to detect amyloid plaques in vivo. Two mice models, APP/PS1 and BRI, developing amyloid pathology were investigated with MTC MRI, T2 relaxation measurements and immunohistochemistry (IHC). MT-ratios of several brain regions were compared to T2-values and correlated with quantitative IHC, revealing amyloid load and gliosis in different brain regions. APP/PS1 mice develop large compact plaques, resembling late stage Alzheimer's disease, while rather small and diffuse plaques are deposited in BRI mice, reflecting early stage of Alzheimer's disease. We found significantly higher MT-ratio's in the brain of APP/PS1 mice as compared to their controls and similar trends in BRI mice. A region based MT-ratio and IHC analysis and correlations between MT-ratios and quantitative IHC indicate amyloid plaques as the main substrate for altered MT-ratios in transgenic animals. We additionally demonstrated the improved sensitivity of MTC MRI to amyloid pathology as compared to traditional T2 relaxation measurements. Our results suggest that MTC MRI reveals extensive, and potentially even early amyloid pathology. Further unraveling the MT-effect of each pathological feature during each stage of AD might indicate MTC MRI as a useful diagnostic technique.