Quality-of-life among women with breast cancer: application of the international classification of functioning, disability and health model

Background

This study aimed to identify the factors that influence Breast Cancer (BC) women's quality of life (QoL) based on the International Classification of Functioning, Disability and Health (ICF) framework.

Method

A cross-sectional study was conducted among 188 women with BC. The dependent variable, QoL, was measured using the Quality of Life Index (QLI-c). The independent variables were measured using the following Arabic-validated questionnaires: Pittsburgh Sleep Quality Index (PSQI), Female Sexual Function Index (FSFI), Modified Fatigue Impact Scale (MFIS), Hospital Anxiety and Depression Scale (HADS), and the International Physical Activity Questionnaire (IPAQ).

Results

There was a significant positive correlation between monthly income (r = 0.17, p = 0.016) and QoL, and significant negative correlation between the stage of disease (r = -0.221, p = 0.002) and duration of first diagnosis (r = -0.280, p = 0.004) with QoL. Poor sleep quality, sexual dysfunction, fatigue, depression, and anxiety had significant negative correlations with QoL (p < 0.01). Multiple regression analysis revealed that among the various factors that might affect QoL, sexual dysfunction, poor sleep quality, depression, and anxiety were significant predictors of QoL (p ≤ 0.05).

Conclusion

The ICF provided an excellent framework to explore the factors influencing QoL among women with BC. This study has given evidence for the relationship of demographic, clinical, and body functional factors with QoL among women with BC. Interestingly, sexual dysfunction, poor sleep quality, depression, and anxiety factors are predictors of QoL. Awareness of these factors that predict QoL will guide healthcare professionals to improve the health and QoL of BC women.

Healthcare Workers' Vulnerability to SARS-CoV-2 in Western Romania: A Study on Incidence and Risk Factors for Non-Vaccination and Reinfection

Purpose

The COVID-19 pandemic has severely impacted healthcare workers, a professional category at risk of infection in both hospital and community settings. The aim of the study was to compare morbidity among hospital staff and that in general population, as well as the factors predicting non-vaccination and reinfection.

Patients and Methods

The present study is a retrospective, cross-sectional study. It was conducted by including all the confirmed COVID-19 infection cases in medical staff members during the period 01.01.2021-31.03.2022 that were reported to the Public Health Authority of Timis County, Timisoara, Western Romania.

Results

Direct, strong, statistically significant correlations were found between the incidence of COVID-19 recorded in all categories of medical personnel and the community pandemic trend, with maximum values for auxiliary and medium medical staff (rho = 0.852/0.821, p < 0.001). The high socio-economic level, as well as the advanced medical education level, were predictor factors for anti-SARS-COV-2 vaccination among the personnel. The non-vaccinated status as well as incomplete vaccination or even the 2-dose vaccination represented independent risk factors for reinfection in 2022. Conversely, receiving a higher number of vaccine doses emerged as the primary protective factor. Notably, reduced adherence to the administration of the following doses was observed particularly among medium and auxiliary staff, leading to additional risks of infection with the Omicron variant.

Conclusion

Despite over 70% vaccination coverage among all studied medical personnel categories, there was low adherence to repeat doses of vaccination, particularly among medium and auxiliary staff. The study highlighted a distinct necessity for enhanced training on preventive behaviours and targeted prevention/control strategies for all professional groups interacting with patients, including caretakers, ambulance workers, receptionists, physiotherapists, and psychologists.

Predictors and efficacy of surgical treatment for consecutive exotropia

PURPOSE

To study the surgical outcomes of consecutive exotropia and predictive factors, and to compare the medial rectus (MR) advancement, lateral rectus (LR) recession, or a combination of both procedures.

METHODS

A retrospective study of patients diagnosed with consecutive exotropia that were operated on (2000-2020) were included. The convergence was classified from 0 to +++, with good: ++/+++ and poor: 0/+. A good outcome was considered when the final horizontal deviation was < 10 prism diopters (pd). Follow-up since the surgery and the number of reoperations were registered.

RESULTS

A total of 88 cases were analyzed, mean age: 33.98 ± 17.68 years (57.95%: women). The near and distance horizontal deviation mean (±SD) was 34.3 pd (±16.45) and 34.36 pd (±16.33), respectively. MR advancement was performed in 36.36%, LR recession in 27.27%, and a combination of both in 36.36%. Surgery was unilateral in 65.91% (bilateral in 34.09%). A good outcome was obtained in 69.32% and reoperations in 11.36%. The insufficiency convergence was associated with a bad outcome. The near horizontal deviation (P = .006), the vertical deviation (VD) association (P = .036) and the combination of both MR advancement and LR recession (P = .017) were predictors of a bad result. The mean follow-up was 56.5 months ± 57.65.

CONCLUSION

A long-term good surgical result was obtained in most patients. The greatest near deviation, the VD association, and the combination of MR advancement and the LR recession were predictive factors for bad results.

A Prospective Cohort Study

Introduction

The aim of the present study was to assess the dropout rate at 2, 6, and 12 months after an inpatient multidisciplinary residential program (MRP) for the treatment of obesity. Furthermore, this study assessed anthropometric and biochemical predictors associated with the dropout.

Methods

Adult and elderly patients (age 59 ± 14 years) with obesity had undergone an MRP, were followed up from 2 to 12 months. Biochemical and anthropometric markers have been assessed at the beginning of the follow-up period after the MRP.

Results

The study enrolled 178 subjects, 117 women and 61 men. The overall dropout rate at 2 months was 21.3%, after 6 months was 44.4%, and after 1 year was 68.5%. There was no difference by gender recorded. Furthermore, patients under medical treatment with psychiatric disorders did not show an association with the dropout rate. Patients with a higher level of body mass index (BMI) at the discharge of MRP showed +48% of dropout at 6 months. After the MRP, the baseline values of uricemia and white blood cells (WBCs) resulted as predictors of dropout at 2 months (p > 0.05). Furthermore, the excess percentage of fat mass lost during the MRP was associated with the risk of dropout at 2, 6, and 12 months (p > 0.05).

Conclusion

The MRP for obesity is an opportunity for losing weight for patients with established criteria. The future challenge will be addressing the best strategic plans in order to reduce the dropout rate after this intervention. Investigating deeply the main predictors could be an opportunity to improve the long-term efficacy of MRP.

Analysis of malaria clinical-epidemiological predictors in individuals from Brazilian Amazon

This research aims to determine whether the combination of epidemiological and clinical features can predict malaria. Diagnostic investigation detected 22.3% of individuals with Plasmodium vivax (P. vivax) malaria, with significant predominance of the male gender. The malaria triad (fever, chills and headache) had a more expressive frequency (81.1%) in individuals with positive thick blood than those with negative thick blood smear (65.1%), although there was no statistical significance. Among the variables analysed as predictive for positive thick blood smear, it was observed that personal history of travel to an endemic malaria area and past malaria infection (PMI) were significantly associated with malaria, even in multiple logistic regression. Fever had the higher sensitivity (94.6%) and past malaria history had the greater specificity (68.2%), with accuracy of 23.5% and 67.5%, respectively. In combined analysis, fever with chills had the highest sensitivity (91.9%), but low accuracy (38.5%). High specificity (91.5%) was found in the association of malaria triad, PMI and history of travel to endemic malaria area (which along with anorexia, was higher 94.6%), with good accuracy (80.7%), suggesting that the screening of patients for performing thick blood smear can be based on these data. The epidemiological features and the malaria triad (fever, chills and headache) can be predictors for identification of malaria patients, concurring to precocious diagnosis and immediate treatment of individuals with malaria.

A Machine Learning Predictive Model for Post-Ureteroscopy Urosepsis Needing Intensive Care Unit Admission: A Case-Control YAU Endourology Study from Nine European Centres

Introduction: With the rise in the use of ureteroscopy and laser stone lithotripsy (URSL), a proportionate increase in the risk of post-procedural urosepsis has also been observed. The aims of our paper were to analyse the predictors for severe urosepsis using a machine learning model (ML) in patients that needed intensive care unit (ICU) admission and to make comparisons with a matched cohort. Methods: A retrospective study was conducted across nine high-volume endourology European centres for all patients who underwent URSL and subsequently needed ICU admission for urosepsis (Group A). This was matched by patients with URSL without urosepsis (Group B). Statistical analysis was performed with ‘R statistical software’ using the ‘randomforests’ package. The data were segregated at random into a 70% training set and a 30% test set using the ‘sample’ command. A random forests ML model was then built with n = 300 trees, with the test set used for internal validation. Diagnostic accuracy statistics were generated using the ‘caret’ package. Results: A total of 114 patients were included (57 in each group) with a mean age of 60 ± 16 years and a male:female ratio of 1:1.19. The ML model correctly predicted risk of sepsis in 14/17 (82%) cases (Group A) and predicted those without urosepsis for 12/15 (80%) controls (Group B), whilst overall it also discriminated between the two groups predicting both those with and without sepsis. Our model accuracy was 81.3% (95%, CI: 63.7–92.8%), sensitivity = 0.80, specificity = 0.82 and area under the curve = 0.89. Predictive values most commonly accounting for nodal points in the trees were a large proximal stone location, long stent time, large stone size and long operative time. Conclusion: Urosepsis after endourological procedures remains one of the main reasons for ICU admission. Risk factors for urosepsis are reasonably accurately predicted by our innovative ML model. Focusing on these risk factors can allow one to create predictive strategies to minimise post-operative morbidity.

Predictor factors of prism effectiveness in young adults with convergence insufficiency

Clinical relevance: The findings of this study can be useful in the process of patient selection as well as in optimising the prescription of the prism in patients with convergence insufficiency.Background: To determine the relationship between the demographic variables and baseline clinical characteristics with the prism effectiveness in young adults with convergence insufficiency.Methods: Sixty-four young adults with convergence insufficiency entered a randomised clinical trial and were randomly assigned to either treatment or placebo groups. For participants in the treatment group, the near optical correction containing base-in prism was determined based on the Sheard's criterion. Participants in the placebo group received near optical correction. After three months of using the assigned correction, the outcome examinations were performed.Results: In the univariate analysis, a remote near point of convergence, a higher baseline symptoms score, and a higher prescribed prism power showed a significant relationship with the increase in prism effectiveness. A significant inverse relationship was found between the near positive fusional vergence, vergence facility, and prism adaptation rate with the prism effectiveness. Based on the results of the multiple regression, the prism adaptation rate was the only independent predictor factor of prism effectiveness, so that the prism effectiveness increased by 0.60 for each per cent reduction in prism adaptation rate.Conclusion: Prism adaptation is the only independent predictive factor of prism effectiveness in young adults with convergence insufficiency. Based on the findings of the present study, it is recommended that careful assessment of prism adaptation be considered before considering prism prescription.

The Impact of Medical Complications in Predicting the Rehabilitation Outcome of Patients With Disorders of Consciousness After Severe Traumatic Brain Injury

In this study, we sought to assess the predictors of outcome in patients with disorders of consciousness (DOC) after severe traumatic brain injury (TBI) during neurorehabilitation stay. In total, 96 patients with DOC (vegetative state, minimally conscious state, or emergence from minimally conscious state) were enrolled (69 males; mean age 43.6 ± 20.8 years) and the improvement of the degree of disability, as assessed by the Disability Rating Scale, was considered the main outcome measure. To define the best predictor, a series of demographical and clinical factors were modeled using a twofold approach: (1) logistic regression to evaluate a possible causal effect among variables; and (2) machine learning algorithms (ML), to define the best predictive model. Univariate analysis demonstrated that disability in DOC patients statistically decreased at the discharge with respect to admission. Genitourinary was the most frequent medical complication (MC) emerging during the neurorehabilitation period. The logistic model revealed that the total amount of MCs is a risk factor for lack of functional improvement. ML discloses that the most important prognostic factors are the respiratory and hepatic complications together with the presence of the upper gastrointestinal comorbidities. Our study provides new evidence on the most adverse short-term factors predicting a functional recovery in DOC patients after severe TBI. The occurrence of medical complications during neurorehabilitation stay should be considered to avoid poor outcomes.

Radiation-induced nausea and vomiting in head and neck cancer: Is it something worth considering in the intensity modulated radiotherapy era? "A narrative review"

Radiation therapy is one of the cornerstones in the treatment of head and neck squamous cell carcinomas (HNSCC), alone or in combination with chemotherapy or surgery. Technological advances which occurred over the last few decades have increased the efficacy of radiotherapy (RT), particularly, intensity-modulated RT (IMRT). IMRT can deliver treatments on complex tumoral targets with dose escalation while sparing organs at risk; anyway IMRT deposits dose in unpredictable patterns outside of the target volume with the purpose of improving conformality. Radiation-induced nausea and vomiting (RINV) is a frequent albeit neglected side effect of RT that can lead to delays in treatment with serious consequences on cure rates. According to several guidelines (MASCC 2016, NCCN 2018), RT for HNSCC has traditionally been regarded as a low emetic risk treatment. Nevertheless, several works suggest that IMRT could increase RINV. Further studies are needed to define the exact incidence and the detailed pathophysiology of RINV in patients with HNSCC treated with state of art IMRT techniques, with and without concurrent chemotherapy.

Predictors of time to sputum smear conversion in patients with pulmonary tuberculosis under treatment

Sputum acid-fast bacilli smear conversion is a fundamental index of treatment response and reduced infectivity in patients with pulmonary tuberculosis (P-TB). To date, there are no models to predict the time to sputum conversion based on patient characteristics. This study aims to ascertain the time to sputum conversion in patients with smear-positive P-TB under treatment, and the variables associated with time to smear conversion. We retrospectively evaluated the time to sputum smear conversion of 89 patients with smear-positive P-TB undergoing treatment at the S. Orsola-Malpighi University Hospital, Bologna (Italy), a referral centre for the diagnosis of TB. Multivariate Cox regression analysis was performed to document variables independently associated with time to conversion. Median time to sputum smear conversion was 24 days (IQR 12-54); the sputum smear converted within the first 2 months of treatment in 78.7% patients. Multivariate Cox regression analysis showed that older age, high baseline mycobacterial load detected by Xpert MTB/RIF, and severity of lung involvement are predictors of persistent smear positivity. The identification of risk factors delaying smear conversion allowed us to develop predictive models that may greatly facilitate the management of smear-positive patients in terms of the duration of respiratory isolation and treatment.