The influence of weather types over northern Greece on respiratory and cardio-vascular mortality.

Extreme ambient temperatures are well-known for their adverse impact on public health, in the form of increased mortality and morbidity due to respiratory and cardio-vascular diseases. However, to capture the total impact of weather on cause-specific mortality/morbidity, the synoptic atmospheric conditions over the region under study need to be taken into account. The objective of this work is to identify weather types over Thessaloniki, Greece, statistically associated with mortality from circulatory and respiratory diseases, in an attempt to holistically determine the impact of weather on cause-specific mortality in the region. For this purpose, we employed datasets from the NCEP/NCAR Reanalysis comprising intrinsic daily data, gridded at a resolution of 2.5°×2.5° and covering a 41-year period (1980-2020). The first set used contains data of 500 hPa and 1,000 hPa geopotential heights for the main geographical domain of the Mediterranean region (30°N-45°N, 10°Ε-35°E). The second set comprises meteorological variables (2 m temperature, specific humidity, 2 m zonal and 2 m meridional wind and total cloud cover) for a geographical domain of north Greece (40.95°Ν, 22.50°Ε-26.25°E). We applied a combination of principal components analysis (PCA) as a dimensionality reduction tool and k-means cluster analysis (CA) in order to group days with homogeneous synoptic meteorological parameters. The derived weather types were statistically correlated with respiratory and mortality data for the time-period 1999-2018. It was concluded that the most fatal conditions for public health in Thessaloniki were associated with weather types bringing low/extremely low ambient temperature over north Greece.

A meta-analysis of agricultural conservation intentions, behaviors, and practices: Insights from 35 years of quantitative literature in the United States.

Conservation practices (CPs) are integral to maintaining the long-term viability of agro-ecological systems. Because farming systems and farmers' values and attitudes are heterogeneous, factors that consistently predict conservation behaviors remain elusive. Moreover, heterogeneity is present among studies regarding the type of CPs examined, and whether behavioral intentions or actual behaviors were measured. This study considers the characteristics of each CP, and whether a given study measured behavioral intention or actual behavior, to better understand farmers' adoption of CPs. We reviewed and analyzed 35 years (1982-2017) of quantitative conservation adoption literature in the United States. We categorized CPs based on their primary purpose, the type of benefit they provide, and whether they are operational or structural. We also examined the following five CPs: conservation tillage, buffers or borders, soil testing, grassed waterways, and cover crops. In our behavioral intention and actual behavior analysis, we found that attitudinal factors predicted both conservation intention and action (actual behavior), whereas current or previous use of practices only influenced actions, not stated conservation intentions. In our analysis focusing on CP characteristics, we found that having specific knowledge about and positive attitudes toward the CP, adoption of other CPs, seeking and using information, larger farm size, and vulnerable land predicted actual adoption across nearly all CP categorizations. Nuances emerge when comparing predictors of CPs that share a particular characteristic. For example, we found farm characteristics to be comparatively more important in predicting adoption of soil management CPs than nutrient and livestock management CPs, and farmers' stewardship identity to be more important for permanent practices than operational practices.

Higher sensitivity with the lever sign test for diagnosis of anterior cruciate ligament rupture in the emergency department.

INTRODUCTION: The objective of this study was to assess the diagnostic value of the "lever sign test" to diagnose ACL rupture and to compare this test to the two most commonly used, the Lachman and anterior drawer test. METHOD: This prospective study was performed in the ED of the Cliniques Universitaires Saint-Luc (Brussels, Belgium) from March 2017 to May 2019. 52 patients were included undergoing knee trauma, within 8 days, with an initial radiograph excluding a fracture (except Segond fracture or tibial spine fracture). On clinical investigation, patients showed a positive lever sign test and/or a positive Lachman test and/or a positive anterior drawer test. Exclusion criteria were a complete rupture of the knee extensor mechanism and patellar dislocation. All the physicians involved in this study were residents in training. An MRI was performed within 3 weeks for all included patients after the clinical examination. Sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) were investigated for all three tests with MRI used as our reference standard. RESULTS: Forty out of 52 patients suffered an ACL rupture (77%) and 12 did not (23%). The sensitivity, specificity, PPV and NPV of the lever sign test were respectively 92.5%, 25% 82% and 50%. Those of the Lachman test were 54%, 54.5%, 81% and 25%, and those of the anterior drawer test were 56%, 82%, 90.5% and 37.5%. Twelve out of 40 ACL ruptures (30%) were diagnosed exclusively with a positive lever sign test. CONCLUSION: When investigating acute ACL ruptures (< 8 days) in the ED, the lever sign test offers a sensitivity of 92.5%, far superior to that of other well-known clinical tests. The lever sign test is relatively pain-free, easy to perform and its visual interpretation requires less experience. Positive lever sign test at the ED should lead to an MRI to combine high clinical sensitivity with high MRI specificity.

Effectiveness of lever sign test for diagnosing anterior cruciate ligament rupture.

Objective: To evaluate the effectiveness of the Lever Sign test (LST) for diagnosing anterior cruciate ligament (ACL) ruptures. Methods: This prospective trial was conducted from January to December 2020. A total of 73 patients, aged 18 to 65 years, presenting with chief complaint as acute knee pain rated < 7/10 on a verbal numerical rating scale, having a minimum 20 to 120° range of motion and undergoing magnetic resonance imaging (MRI) were enrolled. Detailed history, physical examination and standard radiographic evaluation were done in all subjects. For the assessment of the integrity of the ACL, the anterior drawer, Lachman, pivot-shift and LST were performed on each symptomatic knee by a senior orthopedic consultant with a minimum five years post-fellowship experience. Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and accuracy of the LST were recorded with respect to standard reference MRI findings. Results: Out of a total of 73 patients, there were 49 (67.1%) males. Mean age was noted to be 34.5±8.1 years. Area of residence was rural among 42 (57.5%) patients. Mean time since injury was noted to be 11.2±4.6 months. The MRI findings showed ACL intact among 31 (42.4%) patients while it showed ACL torn among 42 (57.5%) patients. The LST showed positive findings for ACL rupture in 39 (53.5%) patients while it was negative in remaining 34 (46.5%). The sensitivity, specificity, PPV, NPV and accuracy of LST with respect to standard reference finding (MRI) was found to be 86%, 90%, 92%, 82% and 88% respectively. Conclusion: The LST was found to have good specificity, sensitivity, PPV, NPV and accuracy to detect the status of the ACL. The LST is easy to perform can be used along with other standard assessment techniques to further increase the validation of the status of the ACL diagnosis.

Generalized two-tailed hypothesis testing for quantiles applied to the psychosocial status during the COVID-19 pandemic.

Nonparametric tests do not rely on data belonging to any particular parametric family of probability distributions, which makes them preferable in case of doubt about the underlying population. Although the two-tailed sign test is likely the most common nonparametric test for location problems, practitioners face serious drawbacks, such as its lack of statistical power and its inapplicability when information regarding data and hypotheses is uncertain or imprecise. In this paper, we generalize the two-tailed sign test by embedding fuzzy hypotheses caused by uncertainty/imprecision regarding linguistic statements on fractions of underlying quantiles. By achieving this objective, (1) crucial limitations of the common two-tailed sign test are mitigated/overcome, (2) various further strengths are incorporated into the sign test (e.g., meeting the trade-off between point- and interval-valued hypotheses, facilitated formulation of fuzzy hypotheses, standardization of membership functions), and (3) shortcomings that often come along with fuzzy hypothesis testing are avoided (e.g., higher complexity, fuzzy test decision, possibilistic interpretation of test results). In addition, we conduct a comprehensive case study using a real data set on the psychosocial status during the COVID-19 pandemic. The results of the case study clearly indicate that the generalized two-tailed sign test is preferable to the two-tailed sign test with point- or interval-valued hypotheses.

Nonparametric fuzzy hypothesis testing for quantiles applied to clinical characteristics of COVID-19.

The sign test is one of the most popular nonparametric tests for location problems and allows testing for any quantile of a population. However, the common sign test has serious drawbacks such as loss of information by considering solely signs of observations but not their magnitudes, various problems related to handling of ties in the data, and the lack of embedding uncertainty regarding the fraction of underlying quantile. To address these issues, we present an extended sign test based on fuzzy categories and fuzzy formulated hypotheses that improves the generality, versatility, and practicability of the common sign test. This generalized test procedure is neat in theory and practice and avoids disadvantages that are often associated with fuzzy tests (e.g., a considerably higher complexity of the underlying model, a fuzzy test decision, and a possibilistic instead of a probabilistic interpretation of test results). In addition, we perform a comprehensive case study on COVID-19 in HIV-infected individuals with a focus on human body temperature and related measurement problems. The results of the study clearly indicate that fuzzy categories and fuzzy hypotheses improve the performance of the sign test.

The "Lever Sign": a new clinical test for the diagnosis of anterior cruciate ligament rupture.

PURPOSE: A new clinical test for the diagnosis of ACL rupture is described: the so-called "Lever Sign". This prospective study on four groups of patients divided subjects on the basis of MRI findings (complete or partial ACL lesion) and the clinical phase of the injury (acute or chronic). The hypothesis was that this manual test would be diagnostic for both partial and complete tears of the ACL regardless of the elapsed time from injury. METHODS: A total of 400 patients were evaluated and divided into four, equal-sized groups based on time elapsed from injury and MRI findings: Group A (acute phase with positive MRI for complete ACL rupture), Group B (chronic phase with positive MRI for complete ACL rupture), Group C (acute phase with positive MRI for partial ACL rupture), and Group D (chronic phase with positive MRI for partial ACL rupture). Clinical assessment was performed with the Lachman test, the Anterior Drawer test, the Pivot Shift test, and the Lever Sign test. The Lever Sign test involves placing a fulcrum under the supine patient's calf and applying a downward force to the quadriceps. Depending on whether the ACL is intact or not, the patient's heel will either rise off of the examination table or remain down. Additionally, the Lever Sign test was performed on the un-injured leg of all 400 patients as a control. RESULTS: All tests were nearly 100 % sensitive for patients with chronic, complete tears of the ACL. However, for patients with acute, partial tears, the sensitivity was much lower for the Lachman test (0.42), Anterior Drawer test (0.29), and Pivot Shift test (0.11), but not the Lever Sign test (1.00). CONCLUSION: In general, chronic, complete tears were most successfully diagnosed but acute, partial tears were least successfully diagnosed. The Lever Sign test is more sensitive to correctly diagnosing both acute and partial tears of the ACL compared with other common manual tests. The clinical relevance is that some ACL ruptures may be more accurately diagnosed.

An improved electromagnetism-like mechanism algorithm and its application to the prediction of diabetes mellitus.

Recently, the use of artificial intelligence based data mining techniques for massive medical data classification and diagnosis has gained its popularity, whereas the effectiveness and efficiency by feature selection is worthy to further investigate. In this paper, we presents a novel method for feature selection with the use of opposite sign test (OST) as a local search for the electromagnetism-like mechanism (EM) algorithm, denoted as improved electromagnetism-like mechanism (IEM) algorithm. Nearest neighbor algorithm is served as a classifier for the wrapper method. The proposed IEM algorithm is compared with nine popular feature selection and classification methods. Forty-six datasets from the UCI repository and eight gene expression microarray datasets are collected for comprehensive evaluation. Non-parametric statistical tests are conducted to justify the performance of the methods in terms of classification accuracy and Kappa index. The results confirm that the proposed IEM method is superior to the common state-of-art methods. Furthermore, we apply IEM to predict the occurrence of Type 2 diabetes mellitus (DM) after a gestational DM. Our research helps identify the risk factors for this disease; accordingly accurate diagnosis and prognosis can be achieved to reduce the morbidity and mortality rate caused by DM.

Wilcoxon's signed-rank statistic: what null hypothesis and why it matters.

In statistical literature, the term 'signed-rank test' (or 'Wilcoxon signed-rank test') has been used to refer to two distinct tests: a test for symmetry of distribution and a test for the median of a symmetric distribution, sharing a common test statistic. To avoid potential ambiguity, we propose to refer to those two tests by different names, as 'test for symmetry based on signed-rank statistic' and 'test for median based on signed-rank statistic', respectively. The utility of such terminological differentiation should become evident through our discussion of how those tests connect and contrast with sign test and one-sample t-test. Published 2014. This article is a U.S. Government work and is in the public domain in the USA.

Lever sign test for anterior cruciate ligament injuries: a diagnostic meta-analysis.

BACKGROUND: Sports-related ACL (anterior cruciate ligament) injuries are frequent. Successful management requires early diagnosis and treatment. One of the clinical tests used to identify ACL damage is the lever sign test. This meta-analysis aimed to assess the lever sign test's diagnostic efficacy for ACL injuries. METHODS: An extensive investigation of the Cochrane Library, Embase, and PubMed databases was conducted until April 2023. Studies assessing the lever sign test's diagnostic efficacy for ACL injuries were also included. A bivariate random-effects model was employed to acquire the pooled estimates of diagnostic odds ratios, specificity, positive and negative likelihood ratios, sensitivity, and curves of the summary receiver operating characteristic (SROC). RESULTS: The meta-analysis comprised twelve investigations with a total of 1365 individuals. The lever sign test's combined sensitivity and specificity for the purpose of diagnosing injuries to the ACL were 0.810 (95% confidence interval [CI] 0.686-0.893) and 0.784 (95% CI 0.583-0.904), respectively. The positive and negative likelihood ratios were 3.148 (95% CI 1.784-5.553) and 0.210 (95% CI 0.084-0.528), respectively. The study revealed a diagnostic odds ratio of 17.656, with a 95% CI ranging from 4.800 to 64.951. The SROC curve's area was determined to be 0.912 (95% CI 0.857-0.967). CONCLUSION: With high specificity and sensitivity, the lever sign test is a reliable diagnostic modality for ACL injuries. However, the test should be used in combination with other diagnostic tests to increase the accuracy of the diagnosis. Further investigations are warranted to assess the clinical practicability of the lever sign test in various populations and settings.