36 research outputs found
Predicting trajectories of behavioral adjustment in children diagnosed with acute lymphoblastic leukemia
Purpose
Previous research showed that children with cancer are at risk for developing behavioral adjustment problems after successful treatment; however, the course of adjustment remains unclear. This study focuses on adjustment trajectories of children during treatment for acute lymphoblastic leukemia (ALL) and aims to distinguish subgroups of patients showing different trajectories during active treatment, and to identify sociodemographic, medical, and psychosocial predictors of the distinct adjustment trajectories.
Methods
In a multicenter longitudinal study, 108 parents of a child (response rate 80 %) diagnosed with ALL were assessed during induction treatment (T0), after induction/consolidation treatment (T1), and after end of treatment (T2). Trajectories of child behavioral adjustment (Child Behavior Checklist; CBCL) were tested with latent class growth modeling (LCGM) analyses.
Results
For internalizing behavior, a three-trajectory model was found: a group that experienced no problems (60 %), a group that experienced only initial problems (30 %), and a group that experienced chronic problems (10 %). For externalizing behavior, a three-trajectory model was also found: a group that experienced no problems (83 %), a group that experienced chronic problems (12 %), and a group that experienced increasing problems (5 %). Only parenting stress and baseline QoL (cancer related) were found to contribute uniquely to adjustment trajectories.
Conclusions
The majority of the children (77 %) showed no or transient behavioral problems during the entire treatment as reported by parents. A substantial group (23 %) shows maladaptive trajectories of internalizing behavioral problems and/or externalizing behavioral problems. Screening for risk factors for developing problems might be helpful in early identification of these children
Measuring perceived benefit and disease-related burden in young cancer survivors: validation of the Benefit and Burden Scale for Children (BBSC) in the Netherlands
Item does not contain fulltextPURPOSE: Perceiving favourable changes from one's illness may go hand in hand with experiencing harmful psychosocial effects. Each of these constructs should be considered when examining children's levels of psychological adjustment following stressful life events. A paediatric instrument that accounts for both positive and negative impact of stressful events has not been investigated in The Netherlands before. The aim of the study was to investigate psychometric properties of the Dutch version of the Benefit and Burden Scale for Children (BBSC), a 20-item questionnaire that intends to measure potential benefit and burden of illness in children. METHODS: Dutch paediatric survivors of childhood cancer aged 8-18 (N = 77) completed the BBSC and other psychological questionnaires: Pediatric Quality of Life Inventory (health-related quality of life), State-Trait Anxiety Inventory for Children (anxiety), Children's Revised Impact of Event Scale (posttraumatic stress) and Strengths and Difficulties Questionnaire (behavioural functioning). Reliability and validity were evaluated. RESULTS: Internal consistency (Cronbach's alpha, benefit 0.84, burden 0.72), test-retest reliability (benefit r = 0.74, burden r = 0.78) and homogeneity (mean inter-item correlation, benefit r = 0.34, burden r = 0.22) were satisfactory. Burden was associated with HRQoL (-), anxiety (+), posttraumatic stress symptoms (+) and behavioural problems. Benefit did not correlate with the psychological outcomes. CONCLUSIONS: The Dutch version of the BBSC shows promising psychometric properties. Perceived benefit and disease-related burden are distinct constructs; both should be considered when examining children's psychological adjustment to potentially traumatic experiences. The BBSC may be useful as monitoring and screening instrument
Adverse drug events caused by three high-risk drug–drug interactions in patients admitted to intensive care units:A multicentre retrospective observational study
Aims: Knowledge about adverse drug events caused by drug–drug interactions (DDI-ADEs) is limited. We aimed to provide detailed insights about DDI-ADEs related to three frequent, high-risk potential DDIs (pDDIs) in the critical care setting: pDDIs with international normalized ratio increase (INR+) potential, pDDIs with acute kidney injury (AKI) potential, and pDDIs with QTc prolongation potential. Methods: We extracted routinely collected retrospective data from electronic health records of intensive care units (ICUs) patients (≥18 years), admitted to ten hospitals in the Netherlands between January 2010 and September 2019. We used computerized triggers (e-triggers) to preselect patients with potential DDI-ADEs. Between September 2020 and October 2021, clinical experts conducted a retrospective manual patient chart review on a subset of preselected patients, and assessed causality, severity, preventability, and contribution to ICU length of stay of DDI-ADEs using internationally prevailing standards. Results: In total 85 422 patients with ≥1 pDDI were included. Of these patients, 32 820 (38.4%) have been exposed to one of the three pDDIs. In the exposed group, 1141 (3.5%) patients were preselected using e-triggers. Of 237 patients (21%) assessed, 155 (65.4%) experienced an actual DDI-ADE; 52.9% had severity level of serious or higher, 75.5% were preventable, and 19.3% contributed to a longer ICU length of stay. The positive predictive value was the highest for DDI-INR+ e-trigger (0.76), followed by DDI-AKI e-trigger (0.57). Conclusion: The highly preventable nature and severity of DDI-ADEs, calls for action to optimize ICU patient safety. Use of e-triggers proved to be a promising preselection strategy.</p
Adverse drug events caused by three high-risk drug–drug interactions in patients admitted to intensive care units:A multicentre retrospective observational study
Aims: Knowledge about adverse drug events caused by drug–drug interactions (DDI-ADEs) is limited. We aimed to provide detailed insights about DDI-ADEs related to three frequent, high-risk potential DDIs (pDDIs) in the critical care setting: pDDIs with international normalized ratio increase (INR+) potential, pDDIs with acute kidney injury (AKI) potential, and pDDIs with QTc prolongation potential. Methods: We extracted routinely collected retrospective data from electronic health records of intensive care units (ICUs) patients (≥18 years), admitted to ten hospitals in the Netherlands between January 2010 and September 2019. We used computerized triggers (e-triggers) to preselect patients with potential DDI-ADEs. Between September 2020 and October 2021, clinical experts conducted a retrospective manual patient chart review on a subset of preselected patients, and assessed causality, severity, preventability, and contribution to ICU length of stay of DDI-ADEs using internationally prevailing standards. Results: In total 85 422 patients with ≥1 pDDI were included. Of these patients, 32 820 (38.4%) have been exposed to one of the three pDDIs. In the exposed group, 1141 (3.5%) patients were preselected using e-triggers. Of 237 patients (21%) assessed, 155 (65.4%) experienced an actual DDI-ADE; 52.9% had severity level of serious or higher, 75.5% were preventable, and 19.3% contributed to a longer ICU length of stay. The positive predictive value was the highest for DDI-INR+ e-trigger (0.76), followed by DDI-AKI e-trigger (0.57). Conclusion: The highly preventable nature and severity of DDI-ADEs, calls for action to optimize ICU patient safety. Use of e-triggers proved to be a promising preselection strategy.</p
Study protocol: population screening for colorectal cancer by colonoscopy or CT colonography: a randomized controlled trial
<p>Abstract</p> <p>Background</p> <p>Colorectal cancer (CRC) is the second most prevalent type of cancer in Europe. Early detection and removal of CRC or its precursor lesions by population screening can reduce mortality. Colonoscopy and computed tomography colonography (CT colonography) are highly accurate exams and screening options that examine the entire colon. The success of screening depends on the participation rate. We designed a randomized trial to compare the uptake, yield and costs of direct colonoscopy population screening, using either a telephone consultation or a consultation at the outpatient clinic, versus CT colonography first, with colonoscopy in CT colonography positives.</p> <p>Methods and design</p> <p>7,500 persons between 50 and 75 years will be randomly selected from the electronic database of the municipal administration registration and will receive an invitation to participate in either CT colonography (2,500 persons) or colonoscopy (5,000 persons) screening. Those invited for colonoscopy screening will be randomized to a prior consultation either by telephone or a visit at the outpatient clinic. All CT colonography invitees will have a prior consultation by telephone. Invitees are instructed to consult their general practitioner and not to participate in screening if they have symptoms suggestive for CRC. After providing informed consent, participants will be scheduled for the screening procedure. The primary outcome measure of this study is the participation rate. Secondary outcomes are the diagnostic yield, the expected and perceived burden of the screening test, level of informed choice and cost-effectiveness of both screening methods.</p> <p>Discussion</p> <p>This study will provide further evidence to enable decision making in population screening for colorectal cancer.</p> <p>Trial registration</p> <p>Dutch trial register: NTR1829</p
Adverse drug events caused by three high-risk drug-drug interactions in patients admitted to intensive care units: a multicentre retrospective observational study
Aims: Knowledge about adverse drug events caused by drug–drug interactions (DDI-ADEs) is limited. We aimed to provide detailed insights about DDI-ADEs related to three frequent, high-risk potential DDIs (pDDIs) in the critical care setting: pDDIs with international normalized ratio increase (INR+) potential, pDDIs with acute kidney injury (AKI) potential, and pDDIs with QTc prolongation potential. Methods: We extracted routinely collected retrospective data from electronic health records of intensive care units (ICUs) patients (≥18 years), admitted to ten hospitals in the Netherlands between January 2010 and September 2019. We used computerized triggers (e-triggers) to preselect patients with potential DDI-ADEs. Between September 2020 and October 2021, clinical experts conducted a retrospective manual patient chart review on a subset of preselected patients, and assessed causality, severity, preventability, and contribution to ICU length of stay of DDI-ADEs using internationally prevailing standards. Results: In total 85 422 patients with ≥1 pDDI were included. Of these patients, 32 820 (38.4%) have been exposed to one of the three pDDIs. In the exposed group, 1141 (3.5%) patients were preselected using e-triggers. Of 237 patients (21%) assessed, 155 (65.4%) experienced an actual DDI-ADE; 52.9% had severity level of serious or higher, 75.5% were preventable, and 19.3% contributed to a longer ICU length of stay. The positive predictive value was the highest for DDI-INR+ e-trigger (0.76), followed by DDI-AKI e-trigger (0.57). Conclusion: The highly preventable nature and severity of DDI-ADEs, calls for action to optimize ICU patient safety. Use of e-triggers proved to be a promising preselection strategy
Long COVID exhibits clinically distinct phenotypes at 3–6 months post-SARSCoV-2 infection: results from the P4O2 consortium
Background Four months after SARS-CoV-2 infection, 22%–50% of COVID-19 patients still experience complaints. Long COVID is a heterogeneous disease and finding subtypes could aid in optimising and developing treatment for the individual patient. Methods Data were collected from 95 patients in the P4O2 COVID-19 cohort at 3–6 months after infection. Unsupervised hierarchical clustering was performed on patient characteristics, characteristics from acute SARSCoV-2 infection, long COVID symptom data, lung function and questionnaires describing the impact and severity of long COVID. To assess robustness, partitioning around medoids was used as alternative clustering. Results Three distinct clusters of patients with long COVID were revealed. Cluster 1 (44%) represented predominantly female patients (93%) with pre-existing asthma and suffered from a median of four symptom categories, including fatigue and respiratory and neurological symptoms. They showed a milder SARS-CoV-2 infection. Cluster 2 (38%) consisted of predominantly male patients (83%) with cardiovascular disease (CVD) and suffered from a median of three symptom categories, most commonly respiratory and neurological symptoms. This cluster also showed a significantly lower forced expiratory volume within 1 s and diffusion capacity of the lung for carbon monoxide. Cluster 3 (18%) was predominantly male (88%) with pre-existing CVD and diabetes. This cluster showed the mildest long COVID, and suffered from symptoms in a median of one symptom category. Conclusions Long COVID patients can be clustered into three distinct phenotypes based on their clinical presentation and easily obtainable information. These clusters show distinction in patient characteristics, lung function, long COVID severity and acute SARS-CoV-2 infection severity. This clustering can help in selecting the most beneficial monitoring and/or treatment strategies for patients suffering from long COVID. Follow-up research is needed to reveal the underlying molecular mechanisms implicated in the different phenotypes and determine the efficacy of treatment