Register study on neuroprognostics in patients with neurological / neurosurgical diseases in intensive care unit

Register study on neuroprognostics in patients with neurological / neurosurgical diseases in intensive care unit - NeuProg

Status

Recruiting

Phases

Unknown

Study type

Observational

Source

DRKS

Registry ID

DRKS00025259

Enrollment

1700

Registered

2021-05-06

Start date

2021-03-12

Completion date

Unknown

Last updated

2025-04-07

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

I63 I61 I67 I60 S06 D33 D43 C71 G00 G01 G02 G03 A87 A32 B05 G09 A17 B00 B01 B02 B45 G04 G05 A81 A83 A84 A85 A86 A39 G60 G61 G92 G70 G73 G35 G36 G60 G61 G62 G63 G64 G71 G72 M60 M63 M33 E88 G31 G40 G93 G92 E72 G41 G12 G20 G21 G23 G10 F02 F00 F01 F03 F04 F05 F10 F13 T65

Interventions

Group 1: Patients with neurointensive medical conditions that require monitoring in the neurointensive care unit or stroke unit are examined or interviewed once 6 months and / or 12 months after hospi

Eligibility

Sex/Gender

All

Age

18 Years to No maximum

Inclusion criteria

Inclusion criteria: - 18 years and older - Neurointensive medical condition requiring monitoring in the neurointensive care unit or stroke unit. This applies to patients with the following diagnoses: ischaemic stroke, intracerebral haemorrhage, subarachnoid haemorrhages, neurovascular malformations, craniocerebral trauma, brain tumours, Infectious diseases of the nervous system (pathogen-induced meningitis/encephalitis), neuromuscular diseases (e.g. myastenia grasvis, Lambert-Eaton syndrome), Various autoimmune neurological diseases (e.g. autoimmune encephalitis, multiple sclerosis, myelitis, neuromyelitis optica, inflammatory neuropathies (GBS, CIDP), myopathies/myositis), Metabolic or genetic neurological diseases, Hypoxic-ischaemic encephalopathies after cardiac arrest, Metabolic encephalopathies, Seizure disorders (status epilepticus, other epileptic seizures), Neurodegenerative diseases (e.g. ALS, Parkinson's disease, multisystem atrophies, Huntington's disease), Quantitative and qualitative disorders of consciousness (e.g. delirium), Intoxications - Consent by the patient or the patient's legal representative

Exclusion criteria

Exclusion criteria: - Simultaneous participation in an interventional drug or medical device study. - Known contraindications to MRI (pacemakers, neurostimulators, metal splinters, cochlear implant, claustrophobia)

Design outcomes

Primary

Measure	Time frame
The primary aim of the planned study is to use machine learning models (deep learning; "artificial intelligence") based on high-volume monitoring data [routinely collected via the Data Warehouse Connect (DWC) system of Philips] to better predict the long-term outcome of patients with neurological and neurosurgical diseases in acute care (e.g. Unresponsive Wakefulness Syndrome (UWS); Minimal Conscious State (MCS) or an outcome above MCS) 6 to 12 months after the onset of the disease. The aim is to be able to better predict the long-term outcome of patients with neurological and neurosurgical diseases in acute care (e.g. unresponsive wakefulness syndrome (UWS); minimal conscious state (MCS) or an outcome above the MCS) 6 to 12 months after the onset of the disease than is currently possible using disease-specific prognosis parameters (e.g. MRI (DWI, DTI)/ PET-CT in hypoxic-ischaemic encephalopathy). For this purpose, corresponding influencing factors or parameters are to be identified and evaluated with regard to their predictive value for long-term prognosis.	—

Measure

Time frame

The primary aim of the planned study is to use machine learning models (deep learning; "artificial intelligence") based on high-volume monitoring data [routinely collected via the Data Warehouse Connect (DWC) system of Philips] to better predict the long-term outcome of patients with neurological and neurosurgical diseases in acute care (e.g. Unresponsive Wakefulness Syndrome (UWS); Minimal Conscious State (MCS) or an outcome above MCS) 6 to 12 months after the onset of the disease. The aim is to be able to better predict the long-term outcome of patients with neurological and neurosurgical diseases in acute care (e.g. unresponsive wakefulness syndrome (UWS); minimal conscious state (MCS) or an outcome above the MCS) 6 to 12 months after the onset of the disease than is currently possible using disease-specific prognosis parameters (e.g. MRI (DWI, DTI)/ PET-CT in hypoxic-ischaemic encephalopathy). For this purpose, corresponding influencing factors or parameters are to be identified and evaluated with regard to their predictive value for long-term prognosis.

—

Secondary

Measure	Time frame
Furthermore, data from structural and functional MRI imaging in combination with EEG and possibly PET-CT data will be fused and analysed using the neuroinformatics platform The Virtual Brain (TVB) in order to better predict the long-term prognosis of patients with neurological and neurosurgical diseases in acute care (e.g. UWS; MCS or an outcome above the MCS) 6 to 12 months after the onset of the disease than was previously possible with disease-specific prognosis parameters (e.g. MCS). e.g. UWS; MCS or an outcome above the MCS) 6 to 12 months after the onset of the disease better than is currently possible with disease-specific prognostic parameters (e.g. MRI (DWI, DTI)/PET-CT in hypoxic-ischaemic encephalopathy, etc.). A further aim of the study is to obtain a better understanding of the sensitivity of diagnostic procedures used in acute care, such as the collection of clinical scores, MRI, PET-CT electrophysiology (SSEP, EEG, ENG, EMG/NLG) and laboratory (concerns e.g. analyses of blood, cerebrospinal fluid and biopsies) and, if necessary, to establish new procedures such as transcriptome analyses.	—

Measure

Time frame

Furthermore, data from structural and functional MRI imaging in combination with EEG and possibly PET-CT data will be fused and analysed using the neuroinformatics platform The Virtual Brain (TVB) in order to better predict the long-term prognosis of patients with neurological and neurosurgical diseases in acute care (e.g. UWS; MCS or an outcome above the MCS) 6 to 12 months after the onset of the disease than was previously possible with disease-specific prognosis parameters (e.g. MCS). e.g. UWS; MCS or an outcome above the MCS) 6 to 12 months after the onset of the disease better than is currently possible with disease-specific prognostic parameters (e.g. MRI (DWI, DTI)/PET-CT in hypoxic-ischaemic encephalopathy, etc.). A further aim of the study is to obtain a better understanding of the sensitivity of diagnostic procedures used in acute care, such as the collection of clinical scores, MRI, PET-CT electrophysiology (SSEP, EEG, ENG, EMG/NLG) and laboratory (concerns e.g. analyses of blood, cerebrospinal fluid and biopsies) and, if necessary, to establish new procedures such as transcriptome analyses.

—

Countries

Germany

Contacts

Public ContactFranziska Scheibe

NeuroCure Clinical Research Center (NCRC) der Charité - Universitätsmedizin Berlin

franziska.scheibe@charite.de030 450 639 057

Outcome results

None listed

Source: DRKS (via WHO ICTRP) · Data processed: Feb 4, 2026