Internal and emergency medicine
-
Pain is a multidimensional experience, potentially rendering unidimensional pain scales inappropriate for assessment. Prior research highlighted their inadequacy as reliable indicators of analgesic requirement. This systematic review aimed to compare multidimensional with unidimensional pain scales in assessing analgesic requirements in the emergency department (ED). ⋯ Limited heterogenous literature suggests that in the ED, a multidimensional pain scale (DVPRS), may better discriminate moderate and severe pain compared to a unidimensional pain scale (NRS). This potentially impacts analgesia, particularly when analgesic interventions rely on pain scores. Patients might prefer multidimensional pain scales (BPI-SF, MPQ-SF) over NRS or VAS for assessing their pain experience.
-
Review Observational Study
Renal function-adapted D-dimer cutoffs in combination with a clinical prediction rule to exclude pulmonary embolism in patients presenting to the emergency department.
D-dimer levels significantly increase with declining renal function and hence, renal function-adjusted D-dimer cutoffs to rule out pulmonary embolism were suggested. Aim of this study was to "post hoc" validate previously defined renal function-adjusted D-dimer levels to safely rule out pulmonary embolism in patients presenting to the emergency department. In this retrospective, observational analysis, all patients with low to intermediate pre-test probability receiving D-dimer measurement and computed tomography angiography (CTA) to rule out pulmonary embolism between January 2017 and December 2020 were included. ⋯ The findings of this study underline that application of renal function-adapted D-dimer levels in combination with a clinical prediction rule appears feasible to rule out pulmonary embolism. Out of the current dataset, renal function-adjusted D-dimer cutoffs to rule out pulmonary embolism were slightly different compared to previously defined cutoffs. Further studies on a larger scale are needed to validate possible renal function-adjusted D-dimer cutoffs.
-
Randomized Controlled Trial
Real-time machine learning-assisted sepsis alert enhances the timeliness of antibiotic administration and diagnostic accuracy in emergency department patients with sepsis: a cluster-randomized trial.
Machine learning (ML) has been applied in sepsis recognition across different healthcare settings with outstanding diagnostic accuracy. However, the advantage of ML-assisted sepsis alert in expediting clinical decisions leading to enhanced quality for emergency department (ED) patients remains unclear. A cluster-randomized trial was conducted in a tertiary-care hospital. ⋯ The diagnostic performance of ML in prompt sepsis detection was superior to that of the rule-based system. Trial registration Thai Clinical Trials Registry TCTR20230120001. Registered 16 January 2023-Retrospectively registered, https://www.thaiclinicaltrials.org/show/TCTR20230120001 .
-
Observational Study
Site and duration of abdominal pain discriminate symptomatic uncomplicated diverticular disease from previous diverticulitis patients.
Abdominal pain in patients with diverticular disease (DD) can be challenging in clinical practice. Patients with symptomatic uncomplicated diverticular disease (SUDD) and patients with a previous acute diverticulitis (PD) may share a similar clinical pattern, difficult to differentiate from irritable bowel syndrome (IBS). We used standardized questionnaires for DD (short and long lasting abdominal pain) and IBS (following Rome III Criteria) to assess clinical features of abdominal pain, in terms of presence, severity and length, in SUDD and PD patients. ⋯ SUDD and PD patients presented different pattern of abdominal pain (length, number of long lasting episodes, site and associated features), with a third reporting overlap with IBS. Further observational studies are needed to better characterize abdominal symptoms in DD patients, especially in those not fulfilling IBS criteria. Trial registration: The REMAD Registry is registered as an observational study in ClinicalTrial.gov (ID: NCT03325829).