UNASSIGNED: Canine lymphoma is the most common hematopoietic cancer in dogs. Numerous studies have evaluated the prognostic value of hematological abnormalities and ratios in both humans and dogs with lymphoma.
UNASSIGNED: To compare hematological parameters and complete blood count ratios between a population of dogs affected by lymphoma and healthy dogs to identify potential prognostic markers for lymphoma.
UNASSIGNED: This retrospective case-control study compares hematological parameters and complete blood count ratios between a population of 114 dogs affected by multicentric large B-cell lymphoma (LBCL) and 60 healthy dogs.
UNASSIGNED: The study found several statistically significant differences between the hematological indices of LBCL dogs and healthy dogs, but no correlation between these parameters and the survival times of 78 dogs treated with chemotherapy Madison Wisconsin protocol. In addition, hematological alterations were evaluated such as anemia, leukocytosis, and thrombocytopenia.
UNASSIGNED: Hematological ratios have been suggested as potential prognostic markers for canine LBCL but their real prognostic value remains controversial and requires future investigation.

This study aimed to validate the role of the D-dimer to lymphocyte ratio (DLR) for mortality prediction in a large national cohort of hospitalized coronavirus disease 2019 (COVID-19) patients.
A retrospective, multicenter, observational study that included hospitalized patients due to SARS-CoV-2 infection in Spain was conducted from March 2020 to March 2022. All biomarkers and laboratory indices analyzed were measured once at admission.
A total of 10,575 COVID-19 patients were included in this study. The mean age of participants was 66.9 (±16) years, and 58.6% (6202 patients) of them were male. The overall mortality rate was 16.3% (n = 1726 patients). Intensive care unit admission was needed in 10.5% (n = 1106 patients), non-invasive mechanical ventilation was required in 8.8% (n = 923 patients), and orotracheal intubation was required in 7.5% (789 patients). DLR presented a c-statistic of 0.69 (95% CI, 0.68-0.71) for in-hospital mortality with an optimal cut-off above 1. Multivariate analysis showed an independent association for in-hospital mortality for DLR > 1 (adjusted OR 2.09, 95% CI 1.09-4.04; p = 0.03); in the same way, survival analysis showed a higher mortality risk for DLR > 1 (HR 2.24; 95% CI 2.03-2.47; p < 0.01). Further, no other laboratory indices showed an independent association for mortality in multivariate analysis.
This study confirmed the usefulness of DLR as a prognostic biomarker for mortality associated with SARS-CoV-2 infection, being an accessible, cost-effective, and easy-to-use biomarker in daily clinical practice.

Media, social scientists and public health researchers often present comparisons across countries, and policy makers use such comparisons to take evidence-based action. For a meaningful comparison among countries, one often needs to normalize the measure for differences in population size. To address this issue, the first choice is usually to calculate per capita ratios. Such ratios, however, normalize the measure for differences in population size directly only under the highly restrictive assumption of a proportional increase of the measure with population size. Violation of this assumption frequently leads to misleading conclusions. We compare per capita ratios with an approach based on regression, a widely used statistical procedure that eliminates many of the problems with ratios and allows for straightforward data interpretation. It turns out that the per capita measures in three global datasets (gross domestic product, COVID-19-related mortality and CO2 production) systematically overestimate values in countries with small populations, while countries with large populations tend to have misleadingly low per capita ratios owing to the large denominators. Unfortunately, despite their biases, comparisons based on per capita ratios are still ubiquitous, and they are used for influential recommendations by various global institutions. Their continued use can cause significant damage when employed as evidence for policy actions and should therefore be replaced by a more scientifically substantiated and informative method, such as a regression-based approach.

Mucopolysaccharidoses (MPS) screening is tedious and still performed by analysis of total glycosaminoglycans (GAG) using 1,9-dimethylmethylene blue (DMB) photometric assay, although false positive and negative tests have been reported. Analysis of differentiated GAGs have been pursued classically by gel electrophoresis or more recently by quantitative LC-MS assays. Secondary elevations of GAGs have been reported in urinary tract infections (UTI). In this manuscript, we describe the diagnostic accuracy of urinary GAG measurements by LC-MS for MPS typing in 68 untreated MPS and mucolipidosis (ML) patients, 183 controls and 153 UTI samples. We report age-dependent reference values and cut-offs for chondroitin sulfate (CS), dermatan sulfate (DS), heparan sulfate (HS) and keratan sulfate (KS) and specific GAG ratios. The use of HS/DS ratio in combination to GAG concentrations normalized to creatinine improves the diagnostic accuracy in MPS type I, II, VI and VII. In total 15 samples classified to the wrong MPS type could be correctly assigned using HS/DS ratio. Increased KS/HS ratio in addition to increased KS improves discrimination of MPS type IV by excluding false positives. Some samples of UTI patients showed elevation of specific GAGs, mainly CS, KS and KS/HS ratio and could be misclassified as MPS type IV. Finally, DMB photometric assay performed in MPS and ML samples reveal four false negative tests (sensitivity of 94%). In conclusion, specific GAG ratios in complement to quantitative GAG values obtained by LC-MS enhance discrimination of MPS types. Exclusion of patients with UTI improve diagnostic accuracy in MPS IV but not in other types.

UNASSIGNED: A significant body of work has linked high nurse or midwife workload to negative patient outcomes. Anecdotal reports suggest that mandated ratio models enhance patient care and improve nurse job satisfaction. However, there is limited focused research.
UNASSIGNED: To identify key outcomes, implementation processes, and research needs regarding nurse/midwife-to-patient ratios in the Australian healthcare context.
UNASSIGNED: Scoping review.
UNASSIGNED: Data sources were CINAHL, Open Dissertations, Medline, and Scopus. 289 articles screened, and 53 full text documents independently assessed against criteria by two reviewers and conflicts resolved by a third reviewer, using Covidence™. Three studies were included in this review.
UNASSIGNED: Studies focused on nurse (job satisfaction, burnout), patient (mortality, readmission, length of stay) and system (costs) outcomes with limited information on implementation processes and no midwifery research.
UNASSIGNED: Ratios provide benefits for patients, nurses, and hospitals although there is limited research in Australia. Implementation was poorly reported..

UNASSIGNED: To investigate whether linear measurements or ratios on the Graf\'s \"standard plane\" ultrasound images of the neonatal/infantile hip, can support the clinically important differentiation between type I and type II hips.
UNASSIGNED: A total of 60 Graf type II hips and 124 randomly selected Graf type I hips, matched to the gestational age at delivery, birth weight, delivery mode, and age at the time of the examination, were identified through our hip screening service, during a period of two years. The images were diagnostically suitable, following anatomical identification and usability check, according to Graf. Anatomical landmarks including the lower limb of the os ilium, the bony rim, the silhouette of the os ilium, the labrum and the femoral head\'s borders, were used to determine the measurements and ratios which quantified their inter-relationships.
UNASSIGNED: The indices which differed significantly between type I and type II hips included: (a) the width of the \"bony roof\" (cut-off value 5.91 mm, sensitivity: 75%, specificity: 70%), (b) the ratio of the width of the \"bony roof\" to the femoral head\'s width (cut-off value 0.40, sensitivity 83%, specificity 71%), and (c) the ratio of the cartilaginous acetabular roof\'s width (including the labrum), to the width of the femoral head (cut-off value 0.450, sensitivity 82%, specificity 67%).
UNASSIGNED: Newly introduced measurements and calculated ratios on \"standard plane\" ultrasound images can be used as additional indices in the differentiation between Graf\'s types of \"centered hips\", thus increasing the diagnostic certainty of the examiner in borderline cases and limiting unnecessary re-examinations or treatment.

Today, in the great majority of buildings in Morocco, the exterior envelope is not insulated and is therefore not performant from a thermal point of view. This data article describes and analyses a dataset of ratios (cost by square meter that we elaborated for the estimation of the cost of buildings at an early phase of construction. The ratios also allow to take into consideration the generated cost caused by the integration of insulation materials. Based on the primary data that were collected by the economic observatory of the provincial delegation of the Ministry of Urbanism, Habitat, Territory and City Policy, we performed our analysis to come up with our own secondary data which are the ratios of the cost (DH/m2). We focused on four elements of the building envelope namely: the external walls, the windows, the roof, and the floor. The ratios are of a great significance for construction economists and architects allowing them to make cost trade-off between different technical solutions throughout the stages of the building thus, potentially leading to a life cycle cost optimization.

BACKGROUND: Pleural effusion (PE) is a common clinical feature that presents a diagnostic challenge for clinicians. In this retrospective study, we aimed to assess the biomarkers, ratios, and multiple indicators in serum and Pleural effusion for the differential diagnosis of tuberculous pleural effusion (TPE) from non-tuberculosis effusion (non-TPE).
METHODS: The participants, who were divided into two groups: TPE and non-TPE (MPE and PPE), from Ningbo First Hospital, were incorporated in this study. The clinical and laboratory features were collected and analyzed using logistic regression analysis. Twelve biomarkers and their ratios in serum and PE were investigated for TPE versus non-TPE. Additionally, the value of multiple indicators for joint diagnosis was estimated.
RESULTS: Biomarkers and ratios showed good diagnostic performance. The five variables including Serum ADA, IGRA, Effusion ADA, Effusion ADA/Serum ADA and Effusion LDH/Effusion ADA were identified as valuable parameters for differential diagnosis of TPE from non-TPE. The combined diagnosis of the five indexes yielded the highest diagnostic accuracy for TPE with an AUC (0.919), sensitivity (90.30%), and specificity (94.50%).
CONCLUSIONS: The biomarkers and ratios demonstrated strong diagnostic performance, and the utilization of multiple indicators for joint diagnosis can improve the diagnostic efficacy of tuberculous pleurisy.

The marginality principle guides analysts to avoid omitting lower-order terms from models in which higher-order terms are included as covariates. Lower-order terms are viewed as \"marginal\" to higher-order terms. We consider how this principle applies to three cases: regression models that may include the ratio of two measured variables; polynomial transformations of a measured variable; and factorial arrangements of defined interventions. For each case, we show that which terms or transformations are considered to be lower-order, and therefore marginal, depends on the scale of measurement, which is frequently arbitrary. Understanding the implications of this point leads to an intuitive understanding of the curse of dimensionality. We conclude that the marginality principle may be useful to analysts in some specific cases but caution against invoking it as a context-free recipe.

Relative growth rate (RGR) has a long history of use in biology. In its logged form, RGR = ln[(M + ΔM)/M], where M is size of the organism at the commencement of the study, and ΔM is new growth over time interval Δt. It illustrates the general problem of comparing non-independent (confounded) variables, e.g. (X + Y) vs. X. Thus, RGR depends on what starting M(X) is used even within the same growth phase. Equally, RGR lacks independence from its derived components, net assimilation rate (NAR) and leaf mass ratio (LMR), as RGR = NAR × LMR, so that they cannot legitimately be compared by standard regression or correlation analysis.
The mathematical properties of RGR exemplify the general problem of \'spurious\' correlations that compare expressions derived from various combinations of the same component terms X and Y. This is particularly acute when X >> Y, the variance of X or Y is large, or there is little range overlap of X and Y values among datasets being compared. Relationships (direction, curvilinearity) between such confounded variables are essentially predetermined and so should not be reported as if they are a finding of the study. Standardizing by M rather than time does not solve the problem. We propose the inherent growth rate (IGR), lnΔM/lnM, as a simple, robust alternative to RGR that is independent of M within the same growth phase.
Although the preferred alternative is to avoid the practice altogether, we discuss cases where comparing expressions with components in common may still have utility. These may provide insights if (1) the regression slope between pairs yields a new variable of biological interest, (2) the statistical significance of the relationship remains supported using suitable methods, such as our specially devised randomization test, or (3) multiple datasets are compared and found to be statistically different. Distinguishing true biological relationships from spurious ones, which arise from comparing non-independent expressions, is essential when dealing with derived variables associated with plant growth analyses.