ArticleBMC neurology2022
Optimizing home-based long-term intensive care for neurological patients with neurorehabilitation outreach teams - protocol of a multicenter, parallel-group randomized controlled trial (OptiNIV-Study).
Article in BMC neurology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
5 citing papers in PubMed, 3 citations in OpenAlex.
- Long-term outcomes of community-based intensive care treatment following neurological early rehabilitation- results of a multicentric German study.Neurological research and practice · 2025Article
- Post-discharge "continuum of care" clinical pathway for persons with severe neurodisabilities-qualitative research to assess its concept and practicality after implementation.Frontiers in neurology · 2025Article
- Decannulation Potential After Acquired Brain Injury in Rehabilitation-Oriented Outpatient Intensive Care.Deutsches Arzteblatt international · 2023Article
- Article
- Characterization of individuals in home-based intensive care in Germany: data from a cross-sectional study.Frontiers in neurologyArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
19 authors at 8 institutions in 1 country.
Funding
Abstract
backgroundEven with high standards of acute care and neurological early rehabilitation (NER) a substantial number of patients with neurological conditions still need mechanical ventilation and/or airway protection by tracheal cannulas when discharged and hence home-based specialised intensive care nursing (HSICN). It may be possible to improve the home care situation with structured specialized long-term neurorehabilitation support and following up patients with neurorehabilitation teams. Consequently, more people might recover over an extended period to a degree that they were no longer dependent on HSICN.
methodsThis healthcare project and clinical trial implements a new specialised neurorehabilitation outreach service for people being discharged from NER with the need for HSICN. The multicentre, open, parallel-group RCT compares the effects of one year post-discharge specialized outpatient follow-up to usual care in people receiving HSICN. Participants will randomly be assigned to receive the new form of healthcare (intervention) or the standard healthcare (control) on a 2:1 basis. Primary outcome is the rate of weaning from mechanical ventilation and/or decannulation (primary outcome) after one year, secondary outcomes include both clinical and economic measures. 173 participants are required to corroborate a difference of 30 vs. 10% weaning success rate statistically with 80% power at a 5% significance level allowing for 15% attrition. DISCUSSION: The OptiNIV-Study will implement a new specialised neurorehabilitation outreach service and will determine its weaning success rates, other clinical outcomes, and cost-effectiveness compared to usual care for people in need for mechanical ventilation and/or tracheal cannula and hence HSICN after discharge from NER.
trial registrationThe trial OptiNIV has been registered in the German Clinical Trials Register (DRKS) since 18.01.2022 with the ID DRKS00027326 .
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.