The mNUTRIC Score as a Tool to Predict Mortality and Increased Resource Utilization in Intensive Care Patients with Sepsis.

Background: The mNUTRIC score is a nutrition risk assessment tool. The aim of this study was to evaluate mNUTRIC score ability to predict 28-mortality, icu resource utilization and nursing workload for patients with sepsis and septic shock. Methods: We performed a secondary analysis of prospectively collected data from a ICU sepsis registry database. The study included adults diagnosed with sepsis or septic shock, admitted from January to December 2014.Results: The study included 146 patients. In the ROC curve analysis the mNUTRIC score had the ability to predict 28-day mortality with an AUC of 0.833 (95% CI 0.76-0.89). Additionally group of patients with NUTRIC score ≥ 6 points more frequently required vasopressor infusion, mechanical ventilation, renal replacement therapy, thromboprophylaxis and blood products use. Nursing workload was also significantly higher in this group (TISS-28: 36 pts., IQR 33 – 40 vs. 31 pts, IQR 28 – 34, p<0.001).Conclusion: The mNUTRIC score obtained at admission to the ICU provided a good discriminative value for 28-mortality and makes it possible to identify patients who will ultimately require intense use of ICU resources with an associated increase in the nursing workload during ICU sepsis treatment.

A profile-based sentiment-aware approach for depression detection in social media

Depression is a severe mental health problem. Due to its relevance, the development of computational tools for its detection has attracted increasing attention in recent years. In this context, several research works have addressed the problem using word-based approaches (e.g., a bag of words). This type of representation has shown to be useful, indicating that words act as linguistic markers of depression. However, we believe that in addition to words, their contexts contain implicitly valuable information that could be inferred and exploited to enhance the detection of signs of depression. Specifically, we explore the use of user’s characteristics and the expressed sentiments in the messages as context insights. The main idea is that the words’ discriminative value depends on the characteristics of the person who is writing and on the polarity of the messages where they occur. Hence, this paper introduces a new approach based on specializing the framework of classification to profiles of users (e.g., males or women) and considering the sentiments expressed in the messages through a new text representation that captures their polarity (e.g., positive or negative). The proposed approach was evaluated on benchmark datasets from social media; the results achieved are encouraging, since they outperform those of state-of-the-art corresponding to computationally more expensive methods.

Gender and Stature Estimate Based on Facial Measurements: an Anthropometric Study in Southwest Iranian Population

This study was aimed to evaluate the facial dimensions and their relation with gender and stature in the Iranian southwest population. A cross-sectional study was conducted among 300 southwest Iranian cases age 20-50 years (150 males and 150 females). Studied variables through physical anthropometry in both genders were Upper facial height (UFH), Total facial height (TFH), Facial Height (FH), Facial Width (FW), and intercanthal width (IC) using a standard sliding caliper and Collis. Regarding the sex and age of the individuals, general descriptive analysis of facial dimensions was determined. All measurements, except TFH and FH, were different between men and women (p≤ 0.01). In male subjects, the Pearson’s correlation coefficient (r) revealed that IC (0.72 ⃰ ⃰ ), FW (0.58 ⃰ ⃰ ) and UFH (0.18 ⃰⃰ ⃰ ) parameters had a positive correlation with stature. In the female group, none of the facial parameters had a significant correlation with stature. Regarding the value of each facial diameter in discriminating male and female stature and gender, the highest discriminative value was specified to the FW (cutoff: 11.89, sensitivity: 89%, specificity: 11%) and IC (cutoff: 2.26, sensitivity: 98%, specificity: 0.04%) respectively. This study showed a significant association of some facial measurements with stature and gender in the southwest Iranian population. IC and FW had the most diagnostic value for gender and stature definition. It is shown a useful reference for the adult southwest Iranian population for facial recognition and that the subject’s sex should be considered during body identification procedures.

Severe aortic stenosis echocardiographic thresholds revisited

Background In view of inconsistencies in threshold values of severe aortic stenosis (AS) hemodynamic indices, it is unclear what is the relative contribution of each variable in a binary classification of AS based on aortic valve replacement (AVR) indication. Purpose Assess relative discriminative value and optimal threshold of each constituent hemodynamic parameter for this classification and confirm additional prognostic value. Methods Echocardiography studies of 168 patients with ≥ moderate AS were included. AS types were dichotomized based on intervention implication into two groups: Group-A, comprising moderate and Normal-Flow Low-Gradient (NFLG), and Group-B, comprising High-Gradient (HG), Low Ejection Fraction Low-Flow Low-Gradient (Low EF-LFLG), and Paradoxical Low-Flow Low-Gradient (PLFLG) AS. Aortic valve area (AVA), Doppler velocity index (DVI), peak aortic velocity, mean gradient and stroke volume index were assessed for A/B Group discrimination value and optimal thresholds were determined. Dichotomized values were assessed for predictive value for AVR or death. Results C-statistic values for binary AS classification was 0.74–0.9 for the tested variables. AVA and DVI featured the highest score, and SVI the lowest one. AVA≤0.81 cm2 and DVI≤0.249 had 87.6% and 86% respective sensitivity for Group B patients, and a similar specificity of 80.9%. During a mean follow-up of 9.1±10.1 months, each of the tested dichotomized variables except for SVI predicted AVR or death on multivariate analysis. Conclusion An AVA value ≤0.81 cm2 or a DVI ≤0.249 threshold carry the highest discriminative value for severe AS in patients with aortic stenosis, translating into an independent prognostic value, and should be considered in clinical decisions. FUNDunding Acknowledgement Type of funding sources: None. Echo variables correlation with Group B Survival curves for individual AS types

Diagnosis of early stage knee osteoarthritis based on early clinical course: data from the CHECK cohort

Background Early diagnosis of knee osteoarthritis (OA) is important in managing this disease, but such an early diagnostic tool is still lacking in clinical practice. The purpose of this study was to develop diagnostic models for early stage knee OA based on the first 2-year clinical course after the patient’s initial presentation in primary care and to identify whether these course factors had additive discriminative value over baseline factors. Methods We extracted eligible patients’ clinical and radiographic data from the CHECK cohort and formed the first 2-year course factors according to the factors’ changes over the 2 years. Clinical expert consensus-based diagnosis, which was made via evaluating patients’ 5- to 10-year follow-up data, was used as the outcome factor. Four models were developed: model 1, included clinical course factors only; model 2, included clinical and radiographic course factors; model 3, clinical baseline factors + clinical course factors; and model 4, clinical and radiographic baseline factors + clinical and radiographic course factors. All the models were built by a generalized estimating equation with a backward selection method. Area under the receiver operating characteristic curve (AUC) and its 95% confidence interval (CI) were calculated for assessing model discrimination. Delong’s method compared AUCs. Results Seven hundred sixty-one patients with 1185 symptomatic knees were included in this study. Thirty-seven percent knees were diagnosed as OA at follow-up. Model 1 contained 6 clinical course factors; model 2: 6 clinical and 3 radiographic course factors; model 3: 6 baseline clinical factors combined with 5 clinical course factors; and model 4: 4 clinical and 1 radiographic baseline factors combined with 5 clinical and 3 radiographic course factors. Model discriminations are as follows: model 1, AUC 0.70 (95% CI 0.67–0.74); model 2, 0.74 (95% CI 0.71–0.77); model 3, 0.77 (95% CI 0.74–0.80); and model 4, 0.80 (95% CI 0.77–0.82). AUCs of model 3 and model 4 were slightly but significantly higher than corresponding baseline-factor models (model 3 0.77 vs 0.75, p = 0.031; model 4 0.80 vs 0.76, p = 0.003). Conclusions Four diagnostic models were developed with “fair” to “good” discriminations. First 2-year course factors had additive discriminative value over baseline factors.

Strong associations and moderate predictive value of early symptoms for SARS-CoV-2 test positivity among healthcare workers, the Netherlands, March 2020

Healthcare workers (n = 803) with mild symptoms were tested for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) (n = 90 positive) and asked to complete a symptom questionnaire. Anosmia, muscle ache, ocular pain, general malaise, headache, extreme tiredness and fever were associated with positivity. A predictive model based on these symptoms showed moderate discriminative value (sensitivity: 91.2%; specificity: 55.6%). While our models would not justify presumptive SARS-CoV-2 diagnosis without molecular confirmation, it can contribute to targeted screening strategies.

Gender Identification Based on the Parameters of the Sternum Bone in the Cadavers

Background: Identifying identity in the absence of large bones becomes more difficult and complicated; accordingly, it is highly beneficial to use the features of the sternum. The present study aimed to evaluate the dimensions of the sternum and its relation with gender in the Iranian population.Methods: This cross-sectional study was conducted on 200 cadavers (100 men and 100 women). By performing an autopsy, the sternum bone was first cut in the midline using a vibrating saw, and the different dimensions were measured using a caliper.Results: Among different dimensions related to the sternum, the mean length of manubrium, mesosternum, the largest width of manubrium, and the shortest width of manubrium were significantly higher in men compared to women. Regarding the value of each sternal diameter in discriminating male and female gender, the highest discriminative value was specified to the shortest width of manubrium (cutoff: 26.75, sensitivity: 100%, specificity: 84.0%), followed by the length of sternebrae 1 (cutoff: 8.45, sensitivity: 76.0%, specificity: 21.0%).Conclusion: Measuring various indices of sternum bone, particularly the shortest width of the manubrium and the length of sternebrae 1, leads to gender identity accurately.