Abdominal adiposity as a prognosis biomarker of clinical outcome in metastatic colorectal cancer.

OBJECTIVES: Adipose tissue distribution and radiodensity are associated with prognosis in many types of cancer. However, the roles of adipose tissue distribution and radiodensity in patients with metastatic colorectal cancer (mCRC) remain unclear. The aim of this study was to assess the prognostic effect of adiposity and adipose tissue radiodensities in patients with mCRC. METHODS: Patients with mCRC who received first-line palliative chemotherapy and had a computed tomography (CT) scan at the third lumbar vertebra (L3) level, admitted between January 2010 and December 2018, were sequentially enrolled. Body composition was assessed using CT-derived measurements. Univariate and multivariate logistic regression analyses and Kaplan-Meier curves were used to determine prognostic values. RESULTS: The study included 237 patients. Cox analyses demonstrated that high subcutaneous adipose tissue (SAT) index was associated with a lower risk for death (hazard ratio [HR], 0.51; 95% confidence interval [CI], 0.29-0.88; Ptrend < 0.025). There was no significant association between visceral adipose tissue (VAT) index tertiles and overall survival. However, high VAT and SAT radiodensities were significantly associated with increased mortality (HR, 1.80; 95% CI, 1.12-2.89; Ptrend < 0.030 and HR, 1.85; 95% CI, 1.19-2.86; Ptrend < 0.021, respectively). CONCLUSIONS: A higher SAT index in patients with mCRC was associated with a favorable overall survival outcome, whereas higher SAT and VAT radiodensities were associated with an increased risk for death, supporting that early nutritional intervention may improve mCRC prognosis.

Construction of a nomogram for predicting COVID-19 in-hospital mortality: A machine learning analysis.

Background and objectives: We aim to verify the use of ML algorithms to predict patient outcome using a relatively small dataset and to create a nomogram to assess in-hospital mortality of patients with COVID-19. Methods: A database of 200 COVID-19 patients admitted to the Clinical Hospital of State University of Campinas (UNICAMP) was used in this analysis. Patient features were divided into three categories: clinical, chest abnormalities, and body composition characteristics acquired by computerized tomography. These features were evaluated independently and combined to predict patient outcomes. To minimize performance fluctuations due to low sample number, reduce possible bias related to outliers, and evaluate the uncertainties generated by the small dataset, we developed a shuffling technique, a modified version of the Monte Carlo Cross Validation, creating several subgroups for training the algorithm and complementary testing subgroups. The following ML algorithms were tested: random forest, boosted decision trees, logistic regression, support vector machines, and neural networks. Performance was evaluated by analyzing Receiver operating characteristic (ROC) curves. The importance of each feature in the determination of the outcome predictability was also studied and a nomogram was created based on the most important features selected by the exclusion test. Results: Among the different sets of features, clinical variables age, lymphocyte number and weight were the most valuable features for prognosis prediction. However, we observed that skeletal muscle radiodensity and presence of pleural effusion were also important for outcome determination. Integrating these independent predictors was successfully developed to accurately predict mortality in COVID-19 in hospital patients. A nomogram based on these five features was created to predict COVID-19 mortality in hospitalized patients. The area under the ROC curve was 0.86 ± 0.04. Conclusion: ML algorithms can be reliable for the prediction of COVID-19-related in-hospital mortality, even when using a relatively small dataset. The success of ML techniques in smaller datasets broadens the applicability of these methods in several problems in the medical area. In addition, feature importance analysis allowed us to determine the most important variables for the prediction tasks resulting in a nomogram with good accuracy and clinical utility in predicting COVID-19 in-hospital mortality.

Low skeletal muscle radiodensity and neutrophil-to-lymphocyte ratio as predictors of poor outcome in patients with COVID-19.

Inflammatory states and body composition changes are associated with a poor prognosis in many diseases, but their role in coronavirus disease 2019 (COVID-19) is not fully understood. To assess the impact of low skeletal muscle radiodensity (SMD), high neutrophil-to-lymphocyte ratio (NLR) and a composite score based on both variables, on complications, use of ventilatory support, and survival in patients with COVID-19. Medical records of patients hospitalized between May 1, 2020, and July 31, 2020, with a laboratory diagnosis of COVID-19 who underwent computed tomography (CT) were retrospectively reviewed. CT-derived body composition measurements assessed at the first lumbar vertebra level, and laboratory tests performed at diagnosis, were used to calculate SMD and NLR. Prognostic values were estimated via univariate and multivariate logistic regression analyses and the Kaplan-Meier curve. The study was approved by the local Institutional Review Board (CAAE 36276620.2.0000.5404). A total of 200 patients were included. Among the patients assessed, median age was 59 years, 58% were men and 45% required ICU care. A total of 45 (22.5%) patients died. Multivariate logistic analysis demonstrated that a low SMD (OR 2.94; 95% CI 1.13-7.66, P = 0.027), high NLR (OR 3.96; 95% CI 1.24-12.69, P = 0.021) and both low SMD and high NLR (OR 25.58; 95% CI 2.37-276.71, P = 0.008) combined, were associated with an increased risk of death. Patients who had both low SMD and high NLR required more mechanical ventilation (P < 0.001) and were hospitalized for a longer period (P < 0.001). Low SMD, high NLR and the composite score can predict poor prognosis in patients with COVID-19, and can be used as a tool for early identification of patients at risk. Systemic inflammation and low muscle radiodensity are useful predictors of poor prognosis, and the assessment of these factors in clinical practice should be considered.

Association of Albumin-Corrected Serum Calcium Levels with Colorectal Cancer Survival Outcomes.

In epidemiological studies, higher calcium intake has been associated with decreased colorectal cancer (CRC) incidence. However, whether circulating calcium concentrations are associated with CRC prognosis is largely unknown. In this retrospective cohort analysis, we identified 498 patients diagnosed with stage I-IV CRC between the years of 2000 and 2018 in whom calcium and albumin level measurements within 3 months of diagnosis had been taken. We used the Kaplan-Meier method for survival analysis. We used multivariate Cox proportional hazards regression to identify associations between corrected calcium levels and CRC survival outcomes. Corrected calcium levels in the highest tertile were associated with significantly lower progression-free survival rates (hazard ratio (HR) 1.85; 95% confidence interval (CI) 1.28-2.69; p = 0.001) and overall survival (HR 1.86; 95% CI 1.26-2.74, p = 0.002) in patients with stage IV or recurrent CRC, and significantly lower disease-free survival rates (HR 1.44; 95% confidence interval (CI) 1.02-2.03; p = 0.040) and overall survival rates (HR 1.72; 95% CI 1.18-2.50; p = 0.004) in patients with stage I-III disease. In conclusion, higher corrected calcium levels after the diagnosis of CRC were significantly associated with decreased survival rates. Prospective trials are necessary to confirm this association.

Myosteatosis Differentially Affects the Prognosis of Non-Metastatic Colon and Rectal Cancer Patients: An Exploratory Study.

Body composition performed by computed tomography (CT) impacts on cancer patients' prognoses and responses to treatment. Myosteatosis has been related to overall survival (OS) and disease-specific survival in colorectal cancer (CRC); however, the independent impact of the association of myosteatosis with prognosis in colon cancer (CC) and rectal cancer (RC) is still unclear. CT was performed at the L3 level to assess body composition features in 227 patients with CRC. Clinical parameters were collected. Overall survival (OS) was the primary outcome, and the secondary outcome was disease-free survival (DFS). Skeletal muscle attenuation and intramuscular adipose tissue area were associated with DFS (p = 0.003 and p = 0.011, respectively) and OS (p < 0.001 and p < 0.001, respectively) in CC patients but not in RC patients. Only the skeletal muscle area was associated with better prognosis related to OS in RC patients (p = 0.009). When CC and RC were analyzed separately, myosteatosis influenced survival negatively in CC patients, worsening DFS survival (hazard ratio [HR], 2.70; 95% confidence interval [CI], 1.07-6.82; p = 0.035) and OS (HR, 5.76; 95% CI, 1.31-25.40; p = 0.021). By contrast, the presence of myosteatosis did not influence DFS (HR, 1.02; 95% CI, 0.52-2.03; p = 0.944) or OS (HR, 0.76; 95% CI, 0.33-1.77; p = 0.529) in RC patients. Our study revealed the interference of myosteatosis in the therapy and survival of patients with CC but not in those with RC, strengthening the value of grouping the two types of cancer in body composition analyses.

O trabalho de profissionais na residência multiprofissional em saúde / Work of professionals in health multiprofessional residency

Trata-se de um estudo de caso sobre a atuação interprofissional de residentes em saúde durante atendimentos de puericultura de uma criança com paralisia cerebral. Objetivou-se conhecer as rotinas de atendimento, as rotinas familiares, o processo saúde-doença e a compreensão da família sobre a doença da criança, buscando construir um plano terapêutico singular, capaz de identificar as necessidades de saúde do núcleo familiar, encorajar a verbalização de dificuldades, intermediar o acesso a serviços de atenção secundária e integrar as redes de apoio sociais. O projeto terapêutico singular envolvendo a enfermagem, a fonoaudiologia e a nutrição possibilitou intervenções que abrangeram a criança e seu núcleo familiar. É necessária uma maior atenção a esses casos devido a dificuldades em acessar os serviços de Atenção Primária à Saúde, buscando oferecer apoio às famílias, bem como atenção integral à saúde desses sujeitos.

The aim of this paper is to describe the activities of the Multiprofessional Residency in Child and Adolescent Health based on a case report in Primary Health Care. The preparation of the article is the result of experiences in the territory, in particular the development of child care appointment of children with cerebral palsy. Singular Therapeutic Project involving nursing, speech and language pathology and nutrition have allowed interventions that embraces the child and family context. It is necessary more attention to these cases due to difficulties to access the Primary Health Care, seeking to provide support to these families and integral attention to the health of these individuals.