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Record W4390099149 · doi:10.1097/md.0000000000036654

Risk factors of systemic lupus erythematosus patients with pulmonary arterial hypertension: A systematic review and meta-analysis

2023· review· en· W4390099149 on OpenAlexaboutno aff
Xueping Lun, Jianguo Yang, Ying Liu, Fuyu Zhao, Zhiliang Wei, Yuying Sun, Xinpeng Zhou

Bibliographic record

VenueMedicine · 2023
Typereview
Languageen
FieldMedicine
TopicPulmonary Hypertension Research and Treatments
Canadian institutionsnot available
FundersState Administration of Traditional Chinese Medicine of the People's Republic of China
KeywordsMedicineInternal medicineCochrane LibraryInterstitial lung diseasePulmonary hypertensionCohort studyCohortMeta-analysisLung

Abstract

fetched live from OpenAlex

BACKGROUND: To investigate the risk factors for the development of pulmonary arterial hypertension (PAH) in patients with systemic lupus erythematosus (SLE). METHODS: The literature related to risk factors for the development of PAH in SLE patients was searched by the computer on China national knowledge infrastructure (CNKI), PubMed, and Embase, and the literature search was limited to the period of library construction to October 2022. Two researchers independently performed literature screening and literature information extracting, including first author, publication time, case collection time, sample size, and study factors, and used the Newcastle-Ottawa Scale (NOS) to evaluate the quality of the literature. The relationship between each clinical manifestation and laboratory index and the occurrence of PAH in SLE patients was evaluated based on the ratio (OR value) and its 95% CI. RESULTS: A total of 24 publications were included, including 23 case-control studies and 1 cohort study with NOS ≥ 6, and the overall quality of the literature was high. The risk of PAH was higher in SLE patients who developed Raynaud phenomenon than in those who did not [OR = 2.39, 95% CI (1.91, 2.99), P < .05]; the risk of PAH was higher in SLE patients who were positive for anti-RNP antibodies than in those who were negative for anti-RNP antibodies [OR = 1.77, 95% CI (1.17, 3.2.65), P < .05]; the risk of PAH was higher in SLE patients with interstitial lung lesions than in those without combined interstitial lung lesions [OR = 3.28, 95% CI (2.37, 4.53), P < .05]; the risk of PAH was higher in SLE patients with combined serositis than in those without serositis [OR = 2.28, 95% CI (1.83, 2.84), P < .05]. The risk of PAH was higher in SLE patients with combined pericardial effusion than in those without pericardial effusion [OR = 2.97, 95% CI (2.37, 3.72), P < .05]; the risk of PAH was higher in SLE patients with combined vasculitis than in those without vasculitis [OR = 1.50, 95% CI (1.08, 2.07), P < .05]; rheumatoid factor-positive SLE patients had a higher risk of PAH than those with rheumatoid factor-negative [OR = 1.66, 95% CI (1.24, 2.24), P < .05]. CONCLUSION: Raynaud phenomenon, vasculitis, anti-RNP antibodies, serositis, interstitial lung lesions, rheumatoid factor, and pericardial effusion are risk factors for the development of PAH in patients with SLE.

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)0.009
metaresearch head score (Gemma)0.019
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.014
Threshold uncertainty score0.046

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.019
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0140.026
Bibliometrics0.0060.008
Science and technology studies0.0010.001
Scholarly communication0.0030.001
Open science0.0020.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.095
GPT teacher head0.330
Teacher spread0.235 · 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 designMeta-analysis
Domainnot available
GenreReview

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

Citations5
Published2023
Admission routes1
Has abstractyes

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