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Record W4220898850 · doi:10.3390/clinpract12020024

Prevalence, Trends, and Outcomes of Pulmonary Embolism Treated with Mechanical and Surgical Thrombectomy from a Nationwide Inpatient Sample

2022· article· en· W4220898850 on OpenAlexaff
Shalini Raghupathy, Achala Prashant Barigidad, Raydiene Doorgen, Shrestha Adak, Rohma Rafique Malik, Gaurav Parulekar, Jeet Janak Patel, Santh Prakash Lanka, George Mohan Varghese, Mohammed Rashid, Urvish Patel, Achint Patel, Ya‐Ching Hsieh

Bibliographic record

VenueClinics and Practice · 2022
Typearticle
Languageen
FieldMedicine
TopicVenous Thromboembolism Diagnosis and Management
Canadian institutionsYork University
Fundersnot available
KeywordsMedicinePulmonary embolismComorbidityHealthcare Cost and Utilization ProjectDiagnosis codeDemographicsRetrospective cohort studyEmergency medicineInternal medicineHealth carePopulationDemography

Abstract

fetched live from OpenAlex

Pulmonary embolism (PE) is the third most common vascular disease in the US, a frequently underdiagnosed and potentially fatal condition where embolic material blocks one or more pulmonary arteries impairing blood flow. In this study, we aim to describe the prevalence, outcomes, and predictors of mortality of PE patients treated with mechanical (MT) and surgical thrombectomy (ST). This is a retrospective study using the Agency for Healthcare Research and Quality’s HCUP NIS data from 2010−2018. We used the ninth and tenth revisions of the International Classification of Diseases clinical modification codes (ICD-9-CM and ICD-10-CM) to identify patients admitted with a primary diagnosis of PE (ICD-10-CM codes I26.02, I26.09, I26.92, I26.93, I26.94, and I26.99; ICD-9-CM codes 415.11, 415.13, and 415.19). We extracted demographics, hospital-level, and patient-level characteristics, and defined the severity of comorbid conditions using Deyo modification of the Elixhauser Comorbidity Index. The primary outcomes of interest were the utilization trends of PE (treated with MT and ST); the secondary outcomes were mortality, discharge to facility, peri-procedural complications, and length of hospital (LOS) stay; the tertiary outcome was to identify the predictors of in-hospital mortality. From 2010−2018, there were 1,627,718 hospitalizations for PE, of which 6531 (0.39%) underwent MT and 3465 (0.21%) underwent ST. The utilization trend of MT increased from 336 (0.20%) in 2010 to 1655 (0.87%) in 2018; the utilization trend of ST was 260 (0.15%) in 2010 and 430 (0.23%) in 2018. The unadjusted in-hospital mortality for MT was 9.1% with the mean LOS being 7(±0.3) days; for ST, mortality was 13.9% with a mean LOS of 13(±0.4) days. The occurrences of periprocedural complications for MT and ST were as follows: invasive mechanical ventilation was 13.8% and 32%; cardiopulmonary bypass was 3.3% and 68.3%; pulmonary embolectomy surgery was 1.7%; and bleeding complications were 1.4% and 3.4%. Predictors associated with in-hospital mortality for MT were: increasing age (OR 1.2, 95% CI 1.0−1.3, p < 0.026), female sex (OR 1.9, 95% CI 1.2−2.8, p < 0.004), large hospitals (OR 2.2, 95% 1.4−3.5, p < 0.001), and teaching hospitals (OR 1.8, 95% CI 1.1−3.1, p < 0.023). The predictor of in-hospital mortality for ST was increasing age (OR 1.2, 95% CI 1.0−1.4, p < 0.046). The number of MT procedures performed has rapidly increased over the past decade. Further studies are warranted to determine their rise and therapeutic use.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.159
Threshold uncertainty score0.421

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.025
GPT teacher head0.326
Teacher spread0.300 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations26
Published2022
Admission routes1
Has abstractyes

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