Duration of life in the three common variants of primary progressive aphasia: A retrospective study in a tertiary memory clinic
Bibliographic record
Abstract
Abstract Background Primary progressive aphasias (PPAs) are a group of neurodegenerative disorders characterized by an insidious and progressive language impairment. Clinical expression and underlying pathology remain highly heterogeneous. To date, there is a lack of knowledge on the natural history of each of the three main variants, particularly mortality. Moreover, advanced stages and end of life issues are rarely discussed with caregivers and families at diagnosis. In turn, this can cause additional psychological distress.We studied the natural history of the three main variants of PPA. More specifically, we focused on mortality and end of life issues in an attempt to better prepare patients and their families. Method We retrospectively studied all deceased patients with a diagnosis of PPA that had been followed at our tertiary memory clinic over the past twenty years (n=83). Clinical data included age of onset of symptoms, duration of illness, age at death and specific cause of death. Result Age at death was similar across all three PPA variants but there was less variability in the non‐fluent variant (nfvPPA) group (M=76.6, SD=6.2) than in the semantic variant (svPPA; M=74.1, SD=8.5) or the logopenic variant (lvPPA; M=76.1, SD=9.1) groups. Age at onset of symptoms was earlier for svPPA participants (M=64.5, SD=8.3) then for the two other variants (lvPPA: M=69.3, SD= 10.7; nfvPPA: M=70.4, SD=6.3). Consequently, duration of the disease (number of years between symptoms’ onset and death) was longer for svPPA participants (M=9.6, SD=3.0) than for nfvPPA and lvPPA participants (respectively M=6.2, SD=2.1 and M=7.0, SD=2.9). Surprisingly, cause of death was unknown for most of the participants. When available (n=15), it included sepsis (n=6), respiratory failure (n=4), neoplasia (n=3) and stroke (n=2), and. There were no differences in causes of death among PPA variants. Conclusion Despite similar age of death across PPA variants, disease duration was longer in the svPPA. Causes of death per se were similar among PPAs. Future studies should include more participants with better emphasis on causes of death. Nonetheless, our study provides useful information about the natural history of the common variants of PPA.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
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".