A Revisit of the Criteria To Define Remission in Patients with Idiopathic Thrombocytopenia Undergoing Splenectomy.
Bibliographic record
Abstract
Abstract Introduction In patient with immune thrombocytopenic purpura (ITP), the responses to splenectomy are traditionally categorized based on the platelet count. A platelet count of 150 x109/L is generally considered as complete remission. However, asplenic patients may have higher baseline platelet counts. To investigate whether the definition of the remission affects the interpretation of follow up data, we have studied patients with ITP undergoing splenectomy. The results were also compared with a meta-analysis of all the trials published in the past 30 years. Methods and Materials Phase I: A retrospective chart review was performed of all patients referred to a tertiary medical center before the splenectomy. The peak post-splenectomy count (PPSC) was defined as the platelet count within 100 days after splenectomy. The patients were followed for various durations. Long-term outcomes after splenectomy were categorized as remission or failure. A failure was defined as a platelet count of less than 30 x109/L after the first 100th post-operative day or the need for further long-term therapy to maintain the platelet count at a safe level. The clinical outcomes were independently assessed by two investigators. The relationship between PPSC and clinical outcome was assessed via logistic regression. Phase II: The published case series of patients with ITP were identified through MEDLINE® search. Study inclusion criteria were defined as cohort of adult patients with ITP or adult patients undergoing splenectomy. 2550 articles were found through MEDLINE® search. The results of the 51 publications involving 4198 patients were summarized. As the focus of this review is on the failure rates of splenectomy for patients with ITP, the published results were recalculated according to a set of pre-defined criteria with dichotomized variables (remission or failure). A failure was defined as a platelet count of less than 50 x109/L, 100 x109/L or 150 x109/L whatever the lowest platelet count used in the study or the need for further long term post-splenectomy therapy. Two reviewers extracted the information from the publications independently to ensure consistent reporting of the results. Results Phase I: There was a significant correlation between the PPSC and clinical outcome only when the PPSC was higher than 150 x109/L. Logistic regression indicated that for each increase in the PPSC of 10 x109/L there was a 5% risk reduction in the failure rate after splenectomy. Phase II: The long-term failure rates were extracted from published series. There has been no significant difference in the long-term failure rate of splenectomy when the initial remission criteria were defined as a post-splenectomized platelet count above 50 x109/L, 100 x109/L or 150 x109/L. Discussion The post-splenectomy platelet counts are determined by remaining platelet clearance mechanism(s); the perioperative medical treatments; and other concomitant medical conditions. The normal range of platelet count in asplenic population is poorly defined. As the consensus is not to treat asymptomatic ITP patients with a platelet count higher 30 x109/L, the parameter used to measure the long-term outcome of patients with ITP should derive from these clinical criteria. Simplified dichotomized variables (remission or failure) may provide a better description of the outcome of the treatments after splenectomy in patients with ITP.
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 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 | 0.037 | 0.054 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.009 | 0.010 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.001 | 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".