Objective: Up to 50% of psychotherapeutic treatments end without significant improvements. While there is first evidence about predictors of nonresponse in outpatient psychotherapy, there are currently no studies investigating predictors of nonresponse in inpatient settings. Based upon a previous systematic literature review, we analyzed the predictive value of initial patient characteristics on nonresponse in symptom distress.
Methods: Treatment episodes from 546 patients, treated for at least 4 weeks, were assessed under naturalistic conditions. Nonresponse status (i.e., lack of a reliable improvement in symptom distress) was investigated at four different time points: at week 4, at discharge, and at a two follow-ups (3 and 12 months after discharge). Hierarchical binary logistic regression models were used to predict nonresponse. Sociodemographic data, clinical variables, and the previous response status were entered subsequently in the model.
Results: A moderate or functional level of initial symptom distress, a comorbid personality disorder, and previous nonresponse were the most consistent predictors of nonresponse.
Conclusions: The results point to the importance of early outcome assessment and suggest the implementation of more symptom-specific treatments.
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http://dx.doi.org/10.1080/10503307.2015.1030471 | DOI Listing |
Eur Radiol
December 2024
Department of Radiology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, State Key Laboratory of Druggability Evaluation and Systematic Translational Medicine, Tianjin Key Laboratory of Digestive Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, China.
Objectives: To establish a spectral CT-based nomogram for predicting the response to neoadjuvant chemotherapy (NAC) in patients with locally advanced esophageal squamous cell carcinoma (ESCC).
Methods: This retrospective study included 172 patients with ESCC who underwent spectral CT scans before NAC followed by resection. Based on postoperative tumor regression grades (TRG), 34% (58) of patients were responsive (TRG1) and 66% (114) were non-responsive (TRG2-3).
Objective: Machine learning has a great potential for prospectively forecasting individual patient response to mental health care (MHC), thereby enabling treatment personalization. However, previous efforts have been limited to populations living in predominantly higher income, developed countries. This study aimed to extend the reach of precision MHC systems by developing and testing a feasible and readily implementable algorithm for identifying patients at risk of nonresponse to routinely delivered psychotherapy in Chile, a developing country in Latin America.
View Article and Find Full Text PDFReady-to-use supplemental foods (RUSF) are energy-dense meals formulated to prevent and treat moderate and severe childhood acute malnutrition (MAM and SAM) in high-risk settings. Although lifesaving, the degree and durability of weight recovery with RUSF is unpredictable. We examined whether environmental enteric dysfunction (EED) and gut microbiota perturbations are risk factors for RUSF failure in a birth cohort of 416 rural Pakistani children followed for growth, common childhood illnesses, and biomarkers from blood, urine, and stool.
View Article and Find Full Text PDFEur J Heart Fail
December 2024
Université Paris Cité, INSERM UMR-S 942 (MASCOT), Paris, France.
Aims: We sought to characterize the clinical course of patients following worsening heart failure (WHF) treated in an outpatient setting and to identify factors associated with a poor response to standard of care with loop diuretics.
Methods And Results: Between September 2022 and March 2023, 44 eligible patients (mean age 66.3 years, 84% male) with ejection fraction <50% and with WHF symptoms in the preceding week treated in an outpatient setting were enrolled.
Cells
December 2024
Departments of Cutaneous Oncology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL 33612, USA.
Solid tumors vary by the immunogenic potential of the tumor microenvironment (TME) and the likelihood of response to immunotherapy. The emerging literature has identified key immune cell populations that significantly impact immune activation or suppression within the TME. This study investigated candidate T-cell populations and their differential infiltration within different tumor types as estimated from mRNA co-expression levels of the corresponding cellular markers.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!