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Record W4388119983 · doi:10.1212/wnl.0000000000207858

Nationwide Retrospective Analysis of Combinations of Advanced Therapies in Patients With Parkinson Disease

2023· article· en· W4388119983 on OpenAlexaboutno aff
Dominik Pürner, Mohammad Ali Hormozi, Daniel Weiß, Michael T. Barbe, Hannah Jergas, Tino Prell, Eileen Gülke, Monika Pötter‐Nerger, Björn Falkenburger, Lisa Klingelhöfer, Bernhard Haslinger, Angela Jochim, Andreas Wolff, Nils Schröter, Michel Rijntjes, Christoph van Riesen, Ute Scheller, Martin Wolz, Ali Amouzandeh, Georg Ebersbach, Doreen Gruber, Zacharias Kohl, Walter Maetzler, Steffen Paschen, Pablo G. Pérez‐González, Verena Rozanski, Johannes Schwarz, Martin Südmeyer, Elisabeth Torka, Simone Wesbuer, Sarah Bornmann, Agnes Flöel, Chi Wang Ip, Patricia Krause, Andrea A. Kühn, Ilona Csóti, Birgit Herting, Simone van de Loo, Aniz Ahammed Basheer, Robert Liszka, Wolfgang H. Jost, Jiri Koschel, Bernhard Haller, Paul Lingor

Bibliographic record

VenueNeurology · 2023
Typearticle
Languageen
FieldMedicine
TopicNeurological disorders and treatments
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineRating scaleDeep brain stimulationParkinson's diseaseLevodopaDiseaseRetrospective cohort studyMedical recordPhysical therapyInternal medicinePsychology

Abstract

fetched live from OpenAlex

BACKGROUND AND OBJECTIVES: Advanced therapies (ATs; deep brain stimulation [DBS] or pump therapies: continuous subcutaneous apomorphine infusion [CSAI], levodopa/carbidopa intestinal gel [LCIG]) are used in later stages of Parkinson disease (PD). However, decreasing efficacy over time and/or side effects may require an AT change or combination in individual patients. Current knowledge about changing or combining ATs is limited to mostly retrospective and small-scale studies. The nationwide case collection Combinations of Advanced Therapies in PD assessed simultaneous or sequential AT combinations in Germany since 2005 to analyze their clinical outcome, their side effects, and the reasons for AT modifications. METHODS: Data were acquired retrospectively by modular questionnaires in 22 PD centers throughout Germany based on clinical records and comprised general information about the centers/patients, clinical (Mini-Mental Status Test/Montréal Cognitive Assessment, Movement Disorder Society-Sponsored Revision of the Unified Parkinson's Disease Rating Scale [MDS-UPDRS], side effects, reasons for AT modification), and therapeutical (ATs with specifications, oral medication) data. Data assessment started with initiation of the second AT. RESULTS: < 0.001]) and subjective clinical outcome and decreasing side effect rates. Main reasons for an AT modification were insufficient symptom control and side effects of the previous therapy. Subgroup analyses suggest addition of DBS in AT patients with leading dyskinesia, addition of LCIG for leading other cardinal motor symptoms, and addition of LCIG or CSAI for dominant off-time. The most long-lasting therapy-until requiring a modification-was DBS. DISCUSSION: Changing or combining ATs may be beneficial when 1 AT is insufficient in efficacy or side effects. The outcome of an AT combination is comparable with the clinical benefit by introducing the first AT. The added AT should be chosen dependent on dominant clinical symptoms and adverse effects. Furthermore, prospective trials are needed to confirm the results of this exploratory case collection. CLASSIFICATION OF EVIDENCE: This study provides Class IV evidence that, in patients with PD, changing or combining ATs is associated with an improvement in the MDS-UPDRS or subjective symptom reporting.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.008
GPT teacher head0.252
Teacher spread0.244 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations13
Published2023
Admission routes1
Has abstractyes

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