THE MULTIPLE REGRESSION MODEL WITH DICHOTOMOUS VARIABLES IN ANALYSIS OF MULTI-SECTIONAL DEMAND FOR CONNECTIVITY SERVICES – APPROACH BASED ON PER SECOND BILLING

The article presents the results of comparative research of the effectiveness of two types of models in terms of approximation and short-term forecasting of the multi-sectional demand for connectivity services. The presented results of the analyses are related to the selection of an appropriate forecasting method as an element of the Prediction System dedicated to telecommunications operators. The first tested model was a multiple regression model with dichotomous explanatory variables. The second model was a multiple regression model with dichotomous explanatory variables and autoregression. In both models, the dependent variable was the hourly counted seconds of outgoing calls within the network of the selected operator. Telephone calls were analysed in terms of such classification factors as: type of day, category of call, group of subscribers. Taking into account all levels of classification factors of the explanatory variable, 35 dichotomous explanatory variables were specified. The defined set of dichotomous explanatory variables was used in the estimation process of both compared regression models. However, in the second model, first-order autoregression was additionally applied. The second model (multiple regression model with dichotomous explanatory variables with first-order autoregression) was found to have higher approximation and predictive capabilities than the first model (multiple regression model with dichotomous explanatory variables without autoregression).

Simple Coagulation Profile as Predictor of Mortality in Adults Admitted with COVID-19: A Meta-Analysis

Context: COVID-19 severe manifestations must be detected as soon as possible. One of the essential poor characteristics is the involvement of coagulopathy. Simple coagulation parameters, including prothrombin time (PT), international normalized ratio (INR), activated partial thromboplastin time (aPTT), and platelet, are widely accessible in many health centers. Objectives: This meta-analysis aimed to determine the association between simple coagulation profiles and COVID-19 in-hospital mortality. Method: We systematically searched five databases for studies measuring simple coagulation parameters in COVID-19 on admission. The random-effects and inverse-variance weighting were used in the study, which used a standardized-mean difference of coagulation profile values. The odds ratios were computed using the Mantel-Haenszel formula for dichotomous variables. Results: This meta-analysis comprised a total of 30 studies (9,175 patients). In our meta-analysis, we found that non-survivors had a lower platelet count [SMD = -0.56 (95% CI: -0.79 to -0.33), P < 0.01; OR = 3.00 (95% CI: 1.66 to 5.41), P < 0.01], prolonged PT [SMD = 1.22 (95%CI: 0.71 to 1.72), P < 0.01; OR = 1.86 (95%CI: 1.43 to 2.43), P < 0.01], prolonged aPTT [SMD = 0.24 (95%CI: -0.04 to 0.52), P = 0.99], and increased INR [SMD = 2.21 (95%CI: 0.10 to 4.31), P = 0.04] than survivors. Conclusions: In COVID-19 patients, abnormal simple coagulation parameters on admission, such as platelet, PT, and INR, were associated with mortality outcomes.

Analysis of zero inflated dichotomous variables from a Bayesian perspective: application to occupational health

Background Zero-inflated models are generally aimed to addressing the problem that arises from having two different sources that generate the zero values observed in a distribution. In practice, this is due to the fact that the population studied actually consists of two subpopulations: one in which the value zero is by default (structural zero) and the other is circumstantial (sample zero). Methods This work proposes a new methodology to fit zero inflated Bernoulli data from a Bayesian approach, able to distinguish between two potential sources of zeros (structural and non-structural). Results The proposed methodology performance has been evaluated through a comprehensive simulation study, and it has been compiled as an R package freely available to the community. Its usage is illustrated by means of a real example from the field of occupational health as the phenomenon of sickness presenteeism, in which it is reasonable to think that some individuals will never be at risk of suffering it because they have not been sick in the period of study (structural zeros). Without separating structural and non-structural zeros one would be studying jointly the general health status and the presenteeism itself, and therefore obtaining potentially biased estimates as the phenomenon is being implicitly underestimated by diluting it into the general health status. Conclusions The proposed methodology is able to distinguish two different sources of zeros (structural and non-structural) from dichotomous data with or without covariates in a Bayesian framework, and has been made available to any interested researcher in the form of the bayesZIB R package (https://cran.r-project.org/package=bayesZIB).

Genotype-Phenotype Correlations in PMM2-CDG

PMM2-CDG is a rare disease, causing hypoglycosylation of multiple proteins, hence preventing full functionality. So far, no direct genotype–phenotype correlations have been identified. We carried out a retrospective cohort study on 26 PMM2-CDG patients. We collected the identified genotype, as well as continuous variables indicating the disease severity (based on Nijmegen Pediatric CDG Rating Score or NPCRS) and dichotomous variables reflecting the patients’ phenotype. The phenotypic effects of patients’ genotype were studied using non-parametric and Chi-Square tests. Seventeen different pathogenic variants have been studied. Variants with zero enzyme activity had no significant impact on the Nijmegen score. Pathogenic variants involving the stabilization/folding domain have a significantly lower total NPCRS (p = 0.017): presence of the p.Cys241Ser mutation had a significantly lower subscore 1,3 and NPCRS (p = 0.04) and thus result in a less severe phenotype. On the other hand, variants involving the dimerization domain, p.Pro113Leu and p.Phe119Leu, resulted in a significantly higher NPCRS score (p = 0.002), which indicates a worse clinical course. These concepts give a better insight in the phenotypic prognosis of PMM2-CDG, according to their molecular base.

The Performance of Sepsis-3 Criteria to Predict Mortality among patients with hematologic malignancy and post-transplant who have Suspected Infection

Background Sepsis is a leading cause of death, particularly in immunocompromised people. The revised definition of sepsis (Sepsis-3) uses Sequential Organ Failure Assessment (SOFA) and quick SOFA (qSOFA) to identify patients with sepsis. The aim of this study was to evaluate the performance of SOFA, qSOFA and SIRS (systemic inflammatory response syndrome) in immunocompromised patients. Methods Adult immunocompromised patients admitted to Michigan Medicine between 2012-2018 with suspected infection were included based on criteria adopted from the Sepsis-3 study. Each clinical score (SOFA≥2, qSOFA≥2, SIRS≥2) was added to the baseline risk model as an ordinal as well as dichotomous variables and AUROC values were calculated. In addition, breakpoints of SOFA between 2-10 were assessed to identify the breakpoints with the highest sensitivity and specificity for hospital mortality. The analysis was stratified for intensive care unit (ICU) status. Results Of 2822 immunocompromised patients with a mean age of 56.8±15.6, 213 (7.5%) died during hospitalization. When added to the baseline risk model, SOFA score had the greatest predictive validity for hospital mortality [AUROC=0.802 (95%CI: 0.771-0.832)], followed by qSOFA (AUROC=0.783 (0.754-0.812) and SIRS (AUROC=0.741 (0.708-0.774]). Among SOFA breakpoints that were evaluated, SOFA≥6 had the greatest predictive validity and moderate positive likelihood ratio (2.75) for hospital mortality. Conclusion The predictive validity for hospital mortality of qSOFA was similar among immunocompromised patients to that reported in the Sepsis-3 study. The sensitivity of qSOFA≥2 for hospital mortality was low. SOFA≥6 might be an effective tool to identify immunocompromised patients with suspected infection at high risk for clinical deterioration.

Updated Evaluation of Laparoscopic vs. Open Appendicectomy During Pregnancy: A Systematic Review and Meta-Analysis

To explore the updated evaluation about the obstetrical and perioperative outcomes of laparoscopic appendicectomy (LA) for pregnancy appendicitis compared with open appendicectomy (OA). Two reviewers independently searched the PubMed, the Cochrane Central Register of Controlled Trials, EMBASE, and Web of Science databases to screen eligible studies up to December 2020. Only clinical researches, no &lt; 10 cases for LA and OA group were included. Twenty retrospective studies with 7,248 pregnant women, evaluating LA and OA in surgical and obstetrical outcomes, were included. The weighted mean difference (WMD) with 95% CI and odds ratio (OR) was used to compare continuous and dichotomous variables. It seems LA was connected with significantly shorter hospital time and lower wound infection [mean difference (MD), −0.57 days; 95% CI, −0.96 to −0.18; p = 0.004 and OR, 0.34; 95% CI, 0.18 to 0.62; p = 0.0005, respectively]. The incidence of fetal loss after LA was higher than OA (OR,1.93; 95% CI, 1.39–2.69; p &lt; 0.0001). It was almost similar in the rate of preterm delivery (OR, 0.80; 95% CI, 0.48 to 1.34; p = 0.40) and other perioperative and obstetrical complications (p &gt; 0.05). Our results indicated that the occurrence of fetal loss after LA should not be ignored. Caution, skillful operation, and thoroughly informed consent about the advantages and disadvantages of laparoscopy are necessary.Systematic Review Registration:https://www.crd.york.ac.uk/PROSPERO/#recordDetails, identifier: CRD42021233150.

Drug Intolerance: Age Related Aspects

Aim: Identification of age-specific drug intolerance. Materials and methods: The study was conducted over the period from 2017 to 2020 and included 200 outpatient medical history forms of people diagnosed as having an unspecified pathological reaction to a drug or medication. All drug reactions are reported by patients own statements and were allocated to dichotomous variables. The results were analyzed by nonparametric statistics. Results: Three groups of patients: 18-44 years (n=49); 45-60 years (n=60); 61 and over (n=91). The odds of incomprehensible reactions were 2.2 times higher in patients in group 3 than in patients in the other groups. Group 3 patients were 12 times more likely to have an itchy reaction to medications than patients in the other groups. Group 1 patients were 3 times more likely to have urticaria than patients in groups 2 and 3. The odds of drug intolerance to ACE inhibitors were 2.6 times higher in group 3 patients than in patients in other groups. When comparing clinical manifestations of drug intolerance to penicillin- and cephalosporin-type antibiotics, no significant differences were found in all patients. The presence of allergies and somatic pathology of 3 or more systems did not significantly affect the possibility of reactions of varying severity to 3 or more drugs in these groups. Conclusions: Patients age has no effect on the possibility of reactions to certain groups of drugs. The exception was ACE inhibitors, which is most likely due to the higher frequency of prescribing antihypertensive therapy in patients in this age group. The aggravation of clinical manifestations and the occurrence of polypharmacy are not associated with age and comorbid background. It should be noted that correlation between age and non-life-threatening clinical manifestations of drug intolerance was revealed, which indicates the absence of reliable effect of age on the possibility of anaphylactic shock or angioedema.

Metabolic syndrome among Nigerians with type 2 diabetes mellitus: a comparative study of the diagnostic criteria.

BackgroundMetabolic syndrome is associated with increased cardiovascular death. The objectives of this study were to find the frequency of metabolic syndrome among Nigerians with type 2 diabetes and to compare the modified NCEP ATP III criteria and the IDF criteria MethodsThe study involved 134 participants. Sixty-seven were cases with type 2 diabetes while the rest were the controls without type 2 diabetes. Ethical approval was granted by the institution’s ethics review committee. Anthropometric, clinical and laboratory parameters were obtained using standard protocols. Data were analyzed with SPSS version 22. Means were compared with Student’s t test while proportions were compared with the Pearson’s chi square. Point biserial correlation was used to determine the association between the dichotomous variables and interval variables. Agreement between the criteria was tested with the Cohen’s kappa test.ResultsType 2 diabetes was associated with a higher prevalence of hypertension and truncal obesity. The frequency of metabolic syndrome was lower with the IDF criteria compared with the modified NCEP criteria (65.7% vs 71.6%). Although there was a strong agreement between the IDF and the modified NCEP criteria (κ=0.862; p<0.0001) yet, the IDF criteria missed 8.3% of diabetic individuals diagnosed with metabolic syndrome by the modified NCEP criteria. Cardiovascular risk is better predicted when the modified NCEP criteria were used to diagnose metabolic syndrome.ConclusionMetabolic syndrome is very common among Nigerians with type 2 diabetes and it is better diagnosed with the modified NCEP ATP III criteria.

Effect of Anticoagulant Administration on the Mortality of Hospitalized Patients With COVID-19: An Updated Systematic Review and Meta-Analysis

Background: Anticoagulation is generally used in hospitalized patients with coronavirus disease 2019 (COVID-19) as thromboprophylaxis. However, results from different studies comparing the effect of anticoagulation on the mortality of COVID-19 patients with non-anticoagulation are inconclusive.Methods: Our systematic review included observational trials if they studied anticoagulant therapy in hospitalized patients with COVID-19 for mortality or bleeding events. Dichotomous variables from individual studies were pooled by risk ratio (RR) and their 95% confidence interval (95% CI) using the random-effects model. Grading of Recommendations Assessment, Development and Evaluation was used to assess the quality of evidence.Results: A total of 11 observational studies enrolling 20,748 hospitalized COVID-19 patients overall were included. A pooled meta-analysis of these studies showed that anticoagulation therapy, compared with non-anticoagulation therapy, was associated with lower mortality risk (RR 0.70, 95% CI 0.52–0.93, p = 0.01). The evidence of benefit was stronger among critically ill COVID-19 patients in the intensive care units (RR 0.59, 95% CI 0.43–0.83, p = 0.002). Additionally, severe bleeding events were not associated with the administration of anticoagulants (RR 0.93, 95% CI 0.71–1.23, p = 0.63).Conclusion: Among patients with COVID-19 admitted to hospital, the administration of anticoagulants was associated with a decreased mortality without increasing the incidence of bleeding events.

Comparison of Two Predictive Models of Sepsis in Critically Ill Patients Based on the Combined use of Inflammatory Markers

Background: Sepsis is considered to be a systemic inflammatory response due to infection, resulting in organ dysfunction. Timely targeted interventions can reduce mortality and improve prognosis. Therefore, it is important to identify potential sepsis in time. Inflammation plays a crucial role in the process of sepsis. We combined inflammatory markers to develop and validate a nomogram model and a simple risk scoring model for predicting sepsis in critically ill patients. Furthermore, comparing the prediction performance of the two models.Methods: The medical records of adult patients admitted to our intensive care unit (ICU) from August 2017 to December 2020 were analyzed. The finally included patients were randomly divided into training cohort (70%) and validation cohort (30%). A nomogram model for sepsis was developed through multivariate logistic regression analysis in the training cohort. The continuous variables included in nomogram model were transformed into dichotomous variables. Then a multivariable logistic regression analysis was performed based on these dichotomous variables and the odds ratio (OR) for each variable was used to construct a simple risk scoring model for predicting sepsis. The receiver operating characteristic curves (ROC) were constructed and the area under the curve (AUC) was calculated to evaluate the discrimination performance of the two models. Results: According to our inclusion and exclusion criteria, 2074 patients were included in study. Finally, white blood cell (WBC), C-reactive protein (CRP), interleukin-6 (IL-6), procalcitonin (PCT) and neutrophil-to-lymphocyte ratio (NLR) were included in our models. The AUC of the nomogram model was 0.854 (95%CI: 0.835-0.872). The AUC of the simple risk scoring model was 0.842 (95%CI: 0.822-0.861). When the cut-off value was 7.5 points, the sensitivity was 77.03% and the specificity was 75.75%. The prediction performance of the two models on sepsis is comparable (p=0.1298) and better than that of Sequential Organ Failure Assessment (SOFA) scores (AUC=0.759).Conclusions: This study combining five commonly available inflammatory markers (WBC, CRP, IL-6, PCT and NLR) developed a nomogram model and a simple risk scoring model to predict sepsis in critically ill patients. Although the prediction performance of the two models is comparable, the simple risk scoring model may be simpler and more practical for clinicians to identify potential sepsis in critically ill patients at an early stage and make treatment strategies.