Effectiveness of immunoglobulin replacement therapy in preventing infections in patients with chronic obstructive pulmonary disease: a systematic review
Bibliographic record
Abstract
PURPOSE: Immunoglobulin replacement therapy is a standard treatment for patients with antibody production deficiencies, which is of interest in patients with chronic obstructive pulmonary disease (COPD). This systematic review, registered with PROSPERO (CRD42021281118), assessed the current literature regarding immunoglobulin replacement therapy on COPD clinical outcomes in patients with low immunoglobulin G (IgG) serum concentrations. METHODS: Literature searches conducted from inception to August 23, 2021, in databases including MEDLINE, EMBASE, and CINAHL. Population (sex, age, comorbidities), baseline clinical characteristics (pulmonary function testing results, IgG levels), and outcome (hospitalizations, emergency department visits) were extracted after title/abstract and full text screening. The Cochrane risk of bias assessment form was used for risk of bias assessment of randomized controlled trials and the National Heart, Lung, and Blood Institute (NHLBI) assessment was used for pre and post studies. RESULTS: A total of 1381 studies were identified in the preliminary search, and 874 records were screened after duplicates were removed. Screening 77 full texts yielded four studies that were included in the review. CONCLUSION: It is unclear whether immune globulin replacement therapy reduces acute exacerbation frequency and severity in COPD. Current evidence suggests that it is worth considering, but better developed protocols for administration of immune globulin supplementation is required for future randomized controlled trials.
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 | 0.005 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.007 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".