Symptomatic pharmacotherapy in ALS: data analysis from a platform-based medication management programme
Bibliographic record
Abstract
Although symptomatic medicines constitute an important intervention in amyotrophic lateral sclerosis (ALS), few systematic investigations into drug management have been reported so far.1 Furthermore, symptomatic pharmacotherapy is constantly evolving with an increasing number of drugs being used. Therefore, more detailed information on drug prescription must be obtained to monitor the current standards of care, identify potential shortcomings in drug management and elucidate progress in symptomatic pharmacotherapy. Thus, the aims of the present study were to (i) identify the spectrum of symptomatic drugs; (ii) rank symptomatic drugs according to their frequency of use; (iii) assign symptomatic drugs to pharmacological domains and (iv) determine the number of symptomatic drugs per patient. We hypothesised that the pharmacological spectrum and frequency of use range widely. Furthermore, we supposed that symptomatic drug treatment may vary substantially among patients with ALS and may be highly personalised. A prospective, multicentre, cross-sectional observational study was conducted. The participants met the following criteria: (1) diagnosis of ALS2; (2) one or more ALS-related drug prescriptions; (3) participation in a case management programme for ALS medication; (4) consent to data capture using a digital research platform.3 The cohort encompassed patients who had received treatment at nine specialised ALS centres in Germany between July 2013 and December 2019. Participant’s demographic and clinical data are summarised in figure 1A. Detailed methods and the setting of the study are listed in the online supplementary file 1. ### Supplementary data [jnnp-2020-322938supp001.pdf] Figure 1 (A) Characteristics of the study participants. (B) Assignment of symptomatic drugs to pharmacologic domains and ranking according to the frequency of use. The number and percentage of patients is shown who received the drug during the course of ALS treatment. Symptomatic drugs were assorted the leading domains of symptomatic drugs: (1) anticholinergic drugs: pirenzepine, ipratropium bromide, amitriptyline, atropine, scopolamine, bornaprine, …
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".