pre- en postoperatieve complicatie na hoog risico chirurgie clinical deterioration Pre and postoperative complications
Conditions
Interventions
None listed
Sponsors
Ziekenhuisgroep Twente
Eligibility
Age
18 Years to 99 Years
Inclusion criteria
Inclusion criteria: The study population includes two patient groups: 1. Patients aged > 18 years undergoing elective oesophageal and gastric resection admitted to the gastrointestinal surgical ward for postoperative care 2. Patients aged > 70 undergoing hip fracture surgery acutely admitted to the geriatric-trauma ward for pre- and postoperative care
Exclusion criteria
Exclusion criteria: 1. Contraindications for use of vital sign sensor patch (i.e. skin allergy, implanted medical devices, contact isolation, etc.) 2. Diagnosed or suspected delirium, cognitive impairment, or dementia
Design outcomes
Primary
| Measure | Time frame |
|---|---|
| The primary endpoint includes the time to detect adverse events. Adverse events of interest include pre- and postoperative complications with a Clavien Dindo class of II or higher, diagnosed according to standard guidelines. A predefined Continuous Early warning score (CEWS) is used to assess presence of abnormalities in continuous vital signs where detection is defined as CEWS*3. Detection of complications by the MEWS method is defined as MEWS*3. Event detection by nurse observations is defined by annotation of nurse worry in the nurse checklists. In patients where adverse events are diagnosed, the time to detect adverse events is calculated as the time difference between event identification and the moment that therapeutic actions targeting the event are started. The time to detect adverse events of the CEWS is compared with 1) MEWS, 2) nurse observations, and 3) the combination of MEWS and nurse observations. | — |
Secondary
| Measure | Time frame |
|---|---|
| The quality and availability of vital sign data and robustness of the wireless connection is verified to investigate the technical feasibility of remote vital sign monitoring. The practical feasibility of mobile monitoring system and use of the patient diary and nurse checklist for routine care is explored using the patient and nurse evaluations. This evaluation includes user comfort, user friendliness, time consumption, adherence, applicability, difficulty, and meaningfulness of the methods. To explore potential decision support methods, we will investigate which vital sign patterns (i.e. absolute values, time trends and shapes) are related with adverse events using visual inspection and regression analysis. From this knowledge, various statistical models predicting adverse events serving will be tested as novel continuous warning score. To verify whether clinical context information improves detection of adverse events, the accelerometry data, patient symptoms and nurse worry indicators will be integrated in the prediction models. | — |
Countries
Netherlands
Outcome results
None listed