Predictive Value of Antithrombin III and d -Dimer in the Development of Moderate-To-Severe Acute Pancreatitis : A Prospective, Observational Study (AT-PROPANC).

OBJECTIVES: To analyze if antithrombin III (AT-III) and d -dimer levels at admission and at 24 hours can predict acute pancreatitis (AP) progression to moderately severe AP (MSAP) to severe AP (SAP) and to determine their predictive value on the development of necrosis, infected necrosis, organ failure, and mortality. METHODS: Prospective observational study conducted in patients with mild AP in 2 tertiary hospitals (2015-2017). RESULTS: Three hundred forty-six patients with mild AP were included. Forty-four patients (12.7%) evolved to MSAP/SAP. Necrosis was detected in 36 patients (10.4%); in 10 (2.9%), infection was confirmed. Organ failure was recorded in 9 patients (2.6%), all of whom died. Those who progressed to MSAP/SAP showed lower AT-III levels; d -dimer and C-reactive protein (CRP) levels increased. The best individual marker for MSAP/SAP at 24 hours is CRP (area under the curve [AUC], 0.839). Antithrombin III (AUC, 0.641), d -dimer (AUC, 0.783), and creatinine added no benefit compared with CRP alone. Similar results were observed for patients who progressed to necrosis, infected necrosis, and organ failure/death. CONCLUSION: Low AT-III and high d -dimer plasma levels at 24 hours after admission were significantly associated with MSAP/SAP, although their predictive ability was low. C-reactive protein was the best marker tested. CLINICAL STUDY IDENTIFIER: ClinicalTrials.gov NCT02373293.

Predictors of the Use of a Mental Health-Focused eHealth System in Patients With Breast and Prostate Cancer: Bayesian Structural Equation Modeling Analysis of a Prospective Study.

BACKGROUND: eHealth systems have been increasingly used to manage depressive symptoms in patients with somatic illnesses. However, understanding the factors that drive their use, particularly among patients with breast and prostate cancer, remains a critical area of research. OBJECTIVE: This study aimed to determine the factors influencing use of the NEVERMIND eHealth system among patients with breast and prostate cancer over 12 weeks, with a focus on the Technology Acceptance Model. METHODS: Data from the NEVERMIND trial, which included 129 patients with breast and prostate cancer, were retrieved. At baseline, participants completed questionnaires detailing demographic data and measuring depressive and stress symptoms using the Beck Depression Inventory-II and the Depression, Anxiety, and Stress Scale-21, respectively. Over a 12-week period, patients engaged with the NEVERMIND system, with follow-up questionnaires administered at 4 weeks and after 12 weeks assessing the system's perceived ease of use and usefulness. Use log data were collected at the 2- and 12-week marks. The relationships among sex, education, baseline depressive and stress symptoms, perceived ease of use, perceived usefulness (PU), and system use at various stages were examined using Bayesian structural equation modeling in a path analysis, a technique that differs from traditional frequentist methods. RESULTS: The path analysis was conducted among 100 patients with breast and prostate cancer, with 66% (n=66) being female and 81% (n=81) having a college education. Patients reported good mental health scores, with low levels of depression and stress at baseline. System use was approximately 6 days in the initial 2 weeks and 45 days over the 12-week study period. The results revealed that PU was the strongest predictor of system use at 12 weeks (ßuse at 12 weeks is predicted by PU at 12 weeks=.384), whereas system use at 2 weeks moderately predicted system use at 12 weeks (ßuse at 12 weeks is predicted by use at 2 weeks=.239). Notably, there were uncertain associations between baseline variables (education, sex, and mental health symptoms) and system use at 2 weeks, indicating a need for better predictors for early system use. CONCLUSIONS: This study underscores the importance of PU and early engagement in patient engagement with eHealth systems such as NEVERMIND. This suggests that, in general eHealth implementations, caregivers should educate patients about the benefits and functionalities of such systems, thus enhancing their understanding of potential health impacts. Concentrating resources on promoting early engagement is also essential given its influence on sustained use. Further research is necessary to clarify the remaining uncertainties, enabling us to refine our strategies and maximize the benefits of eHealth systems in health care settings.

The NEVERMIND e-health system in the treatment of depressive symptoms among patients with severe somatic conditions: A multicentre, pragmatic randomised controlled trial.

Background: This study assessed the effectiveness of the NEVERMIND e-health system, consisting of a smart shirt and a mobile application with lifestyle behavioural advice, mindfulness-based therapy, and cognitive behavioural therapy, in reducing depressive symptoms among patients diagnosed with severe somatic conditions. Our hypothesis was that the system would significantly decrease the level of depressive symptoms in the intervention group compared to the control group. Methods: This pragmatic, randomised controlled trial included 425 patients diagnosed with myocardial infarction, breast cancer, prostate cancer, kidney failure, or lower limb amputation. Participants were recruited from hospitals in Turin and Pisa (Italy), and Lisbon (Portugal), and were randomly assigned to either the NEVERMIND intervention or to the control group. Clinical interviews and structured questionnaires were administered at baseline, 12 weeks, and 24 weeks. The primary outcome was depressive symptoms at 12 weeks measured by the Beck Depression Inventory II (BDI-II). Intention-to-treat analyses included 425 participants, while the per-protocol analyses included 333 participants. This trial is registered in the German Clinical Trials Register, DRKS00013391. Findings: Patients were recruited between Dec 4, 2017, and Dec 31, 2019, with 213 assigned to the intervention and 212 to the control group. The sample had a mean age of 59·41 years (SD=10·70), with 44·24% women. Those who used the NEVERMIND system had statistically significant lower depressive symptoms at the 12-week follow-up (mean difference=-3·03, p<0·001; 95% CI -4·45 to -1·62) compared with controls, with a clinically relevant effect size (Cohen's d=0·39). Interpretation: The results of this study show that the NEVERMIND system is superior to standard care in reducing and preventing depressive symptoms among patients with the studied somatic conditions. Funding: The NEVERMIND project received funding from the European Union's Horizon 2020 Research and Innovation Programme under grant agreement No. 689691.

Left hepatic lobe agenesis, a rare anatomical condition.

Left hepatic lobe agenesis is a rare congenital disorder, first reported by Wakefield in 1898. Since then, less than 40 cases have been described in the literature. We present the case of a man with a left hepatic lobe agenesis diagnosed during the study of obstructive jaundice.

A protocol for a multicentre, parallel-group, pragmatic randomised controlled trial to evaluate the NEVERMIND system in preventing and treating depression in patients with severe somatic conditions.

BACKGROUND: Depressive symptoms are common in individuals suffering from severe somatic conditions. There is a lack of interventions and evidence-based interventions aiming to reduce depressive symptoms in patients with severe somatic conditions. The aim of the NEVERMIND project is to address these issues and provide evidence by testing the NEVERMIND system, designed to reduce and prevent depressive symptoms in comparison to treatment as usual. METHODS: The NEVERMIND study is a parallel-groups, pragmatic randomised controlled trial to assess the effectiveness of the NEVERMIND system in reducing depressive symptoms among individuals with severe somatic conditions. The NEVERMIND system comprises a smart shirt and a user interface, in the form of a mobile application. The system is a real-time decision support system, aiming to predict the severity and onset of depressive symptoms by modelling the well-being condition of patients based on physiological data, body movement, and the recurrence of social interactions. The study includes 330 patients who have a diagnosis of myocardial infarction, breast cancer, prostate cancer, kidney failure, or lower limb amputation. Participants are randomised in blocks of ten to either the NEVERMIND intervention or treatment as usual as the control group. Clinical interviews and structured questionnaires are administered at baseline, at 12 weeks, and 24 weeks to assess whether the NEVERMIND system is superior to treatment as usual. The endpoint of primary interest is Beck Depression Inventory II (BDI-II) at 12 weeks defined as (i) the severity of depressive symptoms as measured by the BDI-II. Secondary outcomes include prevention of the onset of depressive symptoms, changes in quality of life, perceived stigma, and self-efficacy. DISCUSSION: There is a lack of evidence-based interventions aiming to reduce and prevent depressive symptoms in patients with severe somatic conditions. If the NEVERMIND system is effective, it will provide healthcare systems with a novel and innovative method to attend to depressive symptoms in patients with severe somatic conditions. TRIAL REGISTRATION: DRKS00013391. Registered 23 November 2017.

Empowering Citizens through Perceptual Sensing of Urban Environmental and Health Data Following a Participative Citizen Science Approach.

The growth of the urban population together with a high concentration of air pollution have important health impacts on citizens who are exposed to them, causing serious risks of the development and evolution of different chronic diseases. This paper presents the design and development of a novel participatory citizen science-based application and data ecosystem model. These developments are imperative and scientifically designed to gather and process perceptual sensing of urban, environmental, and health data. This data acquisition approach allows citizens to gather and generate environment- and health-related data through mobile devices. The sum of all citizens' data will continuously enrich and increase the volumes of data coming from the city sensors and sources across geographical locations. These scientifically generated data, coupled with data from the city sensors and sources, will enable specialized predictive analytic solutions to empower citizens with urban, environmental, and health recommendations, while enabling new data-driven policies. Although it is difficult for citizens to relate their personal behaviour to large-scale problems such as climate change, pollution, or public health, the developed ecosystem provides the necessary tools to enable a greener and healthier lifestyle, improve quality of life, and contribute towards a more sustainable local environment.

Comparison of the risk prediction systems POSSUM and P-POSSUM with the Surgical Risk Scale: A prospective cohort study of 721 patients.

INTRODUCTION: The outcomes of surgery are subject to variability and difficult to be accurately predicted. Different score systems have been developed to estimating the risk of undergoing a surgical procedure. The aim of this study was to assess the predictive ability of POSSUM and P-POSSUM scoring systems, compared to the Surgical Risk Scale (SRS), in Spanish patients undergoing general surgery. PATIENTS AND METHODS: In this prospective observational study, 721 consecutive patients needing a surgical procedure were included. Observed morbidity and mortality after surgery were compared to the expected ones obtained by applying POSSUM, P-POSSUM and SRS. RESULTS: Mean age was 59.2 years (standard deviation (SD): 17.4 years), 43.5% were women. 616 (85.5%) patients underwent elective general surgery and 105 (14.5%) emergency surgery. The 30-day morbidity was 15.4%. The reintervention rate was 2.1% and mortality was 2.1%. The discrimination ability was excellent in predicting mortality. The Area Under the Curve (AUC) values were: POSSUM: AUC = 0.97, C.I.95%: 0.948-0.992, p < 0.0001; P-POSSUM: AUC = 0.966, C.I.95%: 0.941-0.991, p < 0.0001; SRS: AUC = 0.91, C.I.95%:0.853-0.967, p < 0.0001. POSSUM was also discriminative in the prediction of morbidity (AUC = 0.772, C.I.95%: 0.719-0.826, p < 0.0001). POSSUM predicted morbidity and mortality were higher than the observed ones (p = 0.01 and p = 0.04). Predicted and observed mortality were very similar for P-POSSUM (p = 0.93) and SRS (p = 0.37). CONCLUSIONS: Expected morbidity and mortality determined by POSSUM score showed values significantly above the observed ones. P-POSSUM and SRS systems were effective in predicting mortality. The SRS application is simple and may contribute to appropriate medical decision making.

Proteínas mediadoras de la respuesta inflamatoria como predictores de resultados adversos postoperatorios en pacientes quirúrgicos octogenarios: estudio prospectivo observacional / Inflammatory markers as predictors of postoperative adverse outcome in octogenarian surgical patients: An observational prospective study

INTRODUCCIÓN: La utilidad de proteínas mediadoras de la inflamación (alfa-1 glucoproteína e interleucina-6) en la predicción de complicaciones en personas mayores intervenidas quirúrgicamente no está suficientemente establecida. OBJETIVO: Determinar si los niveles preoperatorios de estos marcadores de inflamación se correlacionan con complicaciones postoperatorias en pacientes ancianos, obteniendo las bases para la elaboración de un sistema de predicción de riesgo quirúrgico. MÉTODOS: Estudio prospectivo observacional en pacientes mayores de 80 años, intervenidos quirúrgicamente de procedimientos de cirugía general. Se determinaron preoperatoriamente: edad, sexo, tipo de cirugía, existencia de malignidad, comorbilidades asociadas, el estado físico, mental y nutricional de los pacientes. También marcadores de inflamación: proteína C reactiva, interleucina-6, alfa-1-ácido glucoproteína. Se registraron las complicaciones postoperatorias. Se realizó un análisis multivariante para la obtención de un modelo de predicción de riesgo. RESULTADOS: Se incluyó Se incluyó a 225 pacientes. De ellos, 55 pacientes (24,4%) presentaron complicaciones, con una mortalidad del 5,3%. En el análisis multivariante, las variables interleucina-6, alfa-1-ácido glucoproteína y la presencia de malignidad se asociaron de forma independiente con la existencia de morbilidad. Se utilizaron estas variables para el cálculo de riesgo (R) de morbilidad postoperatoria ajustado por edad. El modelo mostró una sensibilidad del 22,2%, con 94,8% de especificidad, y un porcentaje de correctos clasificados del 78,3%. Área bajo la curva ROC: 0,781 (95% CI: 0,703-0,858). CONCLUSIONES: La valoración conjunta preoperatoria de la existencia de malignidad, niveles de alfa-1-ácido glucoproteína e interleucina-6 puede ser de utilidad en el cálculo del riesgo quirúrgico en ancianos

INTRODUCTION: The value of inflammatory proteins, interleukin-6 and alpha-1-acid glycoprotein as prognostic factors in elderly people undergoing surgery has not been determined yet. Objective To know whether preoperatively determined inflammatory markers may predict the postoperative outcome of elderly patients undergoing surgery. A scoring system for predicting postoperative morbidity was assessed. METHODS: Hospital-based observational prospective study, with geriatric surgical patients. Preoperative determination of following data: age, gender, scheduled or urgent operation, comorbid diseases, malignancy, physical, mental and nutritional profile. Biochemical markers of inflammation, C Reactive Protein, interleukin-6, and alpha-1-acid glycoprotein were also studied. Preoperative data and postoperative complications were recorded. Binary logistic regression analysis was used to obtain a morbidity risk prediction model. RESULTS: A total of 225 patients were included. Fifty-five patients (24.4%) had postoperative complications, with a mortality rate of 5.3%. Binary logistic regression analysis showed an independent relation between morbidity and the variables malignancy, alpha-1-acid glycoprotein and interleukin-6. The risk (R) of postoperative morbidity adjusted by age was calculated. The model showed a 22.2% sensitivity, 94.8% specificity, and a percentage of correct classification of 78.3%. The area under the ROC curve was 0.781 (95% CI: 0.703-0.858). CONCLUSIONS: An age-adjusted equation for predicting 30-day morbidity that included malignancy, serum IL-6 and alpha 1-acid glycoprotein levels may be useful for risk assessment in octogenarian surgical patients

Inflammatory markers as predictors of postoperative adverse outcome in octogenarian surgical patients: an observational prospective study.

INTRODUCTION: The value of inflammatory proteins, interleukin-6 and alpha-1-acid glycoprotein as prognostic factors in elderly people undergoing surgery has not been determined yet. OBJECTIVE: To know whether preoperatively determined inflammatory markers may predict the postoperative outcome of elderly patients undergoing surgery. A scoring system for predicting postoperative morbidity was assessed. METHODS: Hospital-based observational prospective study, with geriatric surgical patients. Preoperative determination of following data: age, gender, scheduled or urgent operation, comorbid diseases, malignancy, physical, mental and nutritional profile. Biochemical markers of inflammation, C Reactive Protein, interleukin-6, and alpha-1-acid glycoprotein were also studied. Preoperative data and postoperative complications were recorded. Binary logistic regression analysis was used to obtain a morbidity risk prediction model. RESULTS: A total of 225 patients were included. Fifty-five patients (24.4%) had postoperative complications, with a mortality rate of 5.3%. Binary logistic regression analysis showed an independent relation between morbidity and the variables malignancy, alpha-1-acid glycoprotein and interleukin-6. The risk (R) of postoperative morbidity adjusted by age was calculated. The model showed a 22.2% sensitivity, 94.8% specificity, and a percentage of correct classification of 78.3%. The area under the ROC curve was 0.781 (95% CI: 0.703-0.858). CONCLUSIONS: An age-adjusted equation for predicting 30-day morbidity that included malignancy, serum IL-6 and alpha 1-acid glycoprotein levels may be useful for risk assessment in octogenarian surgical patients.