Ignite Creation Date:
2024-05-06 @ 8:21 PM
Last Modification Date:
2024-10-26 @ 3:26 PM
Study NCT ID:
NCT06352710
Status:
RECRUITING
Last Update Posted:
2024-04-08
First Post:
2024-04-02
Brief Title:
Determining Postoperative Recovery and the Impact of Adverse Events in Neurosurgery Based on Self-reported App-based Longitudinal Assessment - a Collaborative Observational Research Project
Sponsor:
Cantonal Hospital of St Gallen
Organization:
Cantonal Hospital of St Gallen
Study Overview
Official Title:
Determining Postoperative Recovery and the Impact of Adverse Events in Neurosurgery Based on Self-reported App-based Longitudinal Assessment - a Collaborative Observational Research Project
Status:
RECRUITING
Status Verified Date:
2024-04
Last Known Status:
None
Delayed Posting:
No
If Stopped, Why?:
Not Stopped
Has Expanded Access:
False
If Expanded Access, NCT#:
N/A
Has Expanded Access, NCT# Status:
N/A
Acronym:
None
Brief Summary:
Analyzing the impact of surgery and adverse events AEs on patients well-being is of paramount importance as it provides essential information for benefit-risk assessment Current methods in outcome research are static resource-intensive and subject to missing-data issues Moreover AEs are inconsistently reported using various grading systems that usually do not account for patients subjective well-being These are severe drawbacks for outcome research as it hinders monitoring comparison and improvement of treatment quality
The increasing use of smartphones offers unprecedented opportunities for data collection We developed a free smartphone application to assess fluctuations of patients well-being as a result of surgical treatment and possible AEs The application is installed on each patients smartphone and collects standardized data at defined timepoints before and after surgery well-being AE description and severity
By acquiring longitudinal patient-reported outcome before and after neurosurgical interventions we aim to determine the regular postoperative course for specific surgical procedures as well as any deviation thereof depending on the occurrence and severity of AEs We will evaluate the validity of existing AE classifications and if necessary propose a new patient-centered scheme We hope that this will result in an increase in standardized reporting of patient outcome and ultimately allow for evidence-based patient information and decision-making
The increasing use of smartphones offers unprecedented opportunities for data collection We developed a free smartphone application to assess fluctuations of patients well-being as a result of surgical treatment and possible AEs The application is installed on each patients smartphone and collects standardized data at defined timepoints before and after surgery well-being AE description and severity
By acquiring longitudinal patient-reported outcome before and after neurosurgical interventions we aim to determine the regular postoperative course for specific surgical procedures as well as any deviation thereof depending on the occurrence and severity of AEs We will evaluate the validity of existing AE classifications and if necessary propose a new patient-centered scheme We hope that this will result in an increase in standardized reporting of patient outcome and ultimately allow for evidence-based patient information and decision-making
Detailed Description:
Understanding and analyzing the impact of surgery and adverse events AEs on the subjective well-being of patients is of paramount importance as it provides objective information that may be useful in a risk-benefit discussion Current methods in outcome research are static resource-intensive and subject to missing-data issues This results in a poor understanding of the normal postoperative course which in turn prevents consistent reporting of AEs as they are usually defined as a deviation thereof As an additional challenge and because there is no consensus andor recommendation on this subject AEs are graded using various classifications that neglect the impact of AEs on the subjective well-being of patients For example the most used AE grading system is the therapy-based Clavien-Dindo-Grading system CDG doi10109701sla000013308354934ae which fails to detect the severity of AE that are not treated by means of pharmacotherapy andor surgery This is an important limitation as new neurologic deficits are frequent AEs that may imply dramatic consequences on quality of life but are considered as low grade in therapy-based grading systems such as the CDG Other classifications were developed specifically for neurosurgery but they suffer the same limitations Recently our group proposed the Therapy-Disability-Neurology Grade TDN doi101093neurosnyab121 to address this problem The TDN grade takes into account the therapy used to counteract AEs as does the CDG the associated neurologic deficits and the resulting disability but currently lacks widespread use and validation These are severe drawbacks for outcome research as it hinders monitoring comparison and improvement of quality of the treatment delivered
The increasing use of smartphones across all age groups offers unprecedented opportunities for data collection We have created a smartphone application app to assess patient well-being in a standardized and longitudinal fashion The app named Op-tracker app It collects longitudinal self-reported data subjective well-being rated from 0 to 10 at fixed time points before and after surgery Additional information such as type of disease type of surgery currently four categories AE description and severity according to the CDG and TDN grade is also recorded along with a standardized quality of life QoL questionnaire EQ-5D-5L A simplified version recently described in a feasibility study showed good acceptance and no major technical issues doi101007s00701-021-04967-0 With this innovative technique of data acquisition we will gather a higher density of data using less resources than traditional methods
In a prospective observational pilot study without intervention using the op-tracker app to acquire longitudinal patient reported outcome measures the subjective well-being index SWI before and after surgery we aim to determine the regular postoperative course for certain surgical procedures as well as the deviation thereof depending on the severity of specific AEs We will evaluate the validity of existing AE severity grading systems and if necessary propose a classification more consistent with the subjective well-being of patients This will greatly benefit patient information by providing essential insight about standard and complicated postoperative course Beyond the benefit this new data will add to the scientific literature we hope that the app will improve daily patient care by enabling early detection of and reaction to AEs in case of pathological decrease in self-reported well-being and QoL Should this be confirmed the app could be widely used and its scope could be extended to the whole neurosurgical spectrum or even to further surgical subspecialties We anticipate that this will result in an increase in standardized reporting of patient outcome and ultimately in a more evidence-based patient information and decision-making
The increasing use of smartphones across all age groups offers unprecedented opportunities for data collection We have created a smartphone application app to assess patient well-being in a standardized and longitudinal fashion The app named Op-tracker app It collects longitudinal self-reported data subjective well-being rated from 0 to 10 at fixed time points before and after surgery Additional information such as type of disease type of surgery currently four categories AE description and severity according to the CDG and TDN grade is also recorded along with a standardized quality of life QoL questionnaire EQ-5D-5L A simplified version recently described in a feasibility study showed good acceptance and no major technical issues doi101007s00701-021-04967-0 With this innovative technique of data acquisition we will gather a higher density of data using less resources than traditional methods
In a prospective observational pilot study without intervention using the op-tracker app to acquire longitudinal patient reported outcome measures the subjective well-being index SWI before and after surgery we aim to determine the regular postoperative course for certain surgical procedures as well as the deviation thereof depending on the severity of specific AEs We will evaluate the validity of existing AE severity grading systems and if necessary propose a classification more consistent with the subjective well-being of patients This will greatly benefit patient information by providing essential insight about standard and complicated postoperative course Beyond the benefit this new data will add to the scientific literature we hope that the app will improve daily patient care by enabling early detection of and reaction to AEs in case of pathological decrease in self-reported well-being and QoL Should this be confirmed the app could be widely used and its scope could be extended to the whole neurosurgical spectrum or even to further surgical subspecialties We anticipate that this will result in an increase in standardized reporting of patient outcome and ultimately in a more evidence-based patient information and decision-making
Study Oversight
Has Oversight DMC:
None
Is a FDA Regulated Drug?:
False
Is a FDA Regulated Device?:
False
Is an Unapproved Device?:
None
Is a PPSD?:
None
Is a US Export?:
None
Is an FDA AA801 Violation?:
None