Modeling intra-abdominal volume and respiratory driving pressure during pneumoperitoneum insufflation - a patient-level data meta-analysis

2020 ◽  
Author(s):  
Guido Mazzinari ◽  
Oscar Diaz-Cambronero ◽  
Ary Serpa Neto ◽  
Antonio Cañada Martinez ◽  
Lucas Rovira ◽  
...  
Keyword(s):  
Meta Analysis ◽  
Postoperative Recovery ◽  
Bayesian Regression ◽  
Driving Pressure ◽  
Rate Of Change ◽  
Abdominal Pressure ◽  
Mathematical Function ◽  
Patient Level ◽  
Level Data ◽  
Pressure Changes

During pneumoperitoneum, intra-abdominal pressure (IAP) is usually kept at 12-14 mmHg. There is no clinical benefit in IAP increments if they do not increase intra-abdominal volume IAV. We aimed to estimate IAV (ΔIAV) and respiratory driving pressure changes (ΔPRS) in relation to changes in IAP (ΔIAP). We carried out a patient-level meta-analysis of 204 adult patients with available data on IAV and ΔPRS during pneumoperitoneum from three trials assessing the effect of IAP on postoperative recovery and airway pressure during laparoscopic surgery under general anesthesia. The primary endpoint was ΔIAV, and the secondary endpoint was ΔPRS. The endpoints' response to ΔIAP was modeled using mixed multivariable Bayesian regression to estimate which mathematical function best fitted it. IAP values on the pressure-volume (PV) curve where the endpoint rate of change according to IAP decreased were identified. Abdomino-thoracic transmission (ATT) rate, i.e., the rate ΔPRS change to ΔIAP, was also estimated. The best-fitting function was sigmoid logistic and linear for IAV and ΔPRS response, respectively. Increments in IAV reached a plateau at 6.0 [95%CI 5.9 to 6.2] L. ΔIAV for each ΔIAP decreased at IAP ranging from 9.8 [95%CI 9.7 to 9.9], to 12.2 [12.0 to12.3] mmHg. ATT rate was 0.65 [95%CI 0.62 to 0.68]. One mmHg of IAP raised ΔPRS 0.88 cmH2O. During pneumoperitoneum, IAP has a non-linear relationship with IAV and a linear one with ΔPRS. IAP should be set below the point where IAV gains diminish.

scholarly journals ODACH: A One-shot Distributed Algorithm for Cox model with Heterogeneous Multi-center Data

2021 ◽  
Author(s):  
Chongliang Luo ◽  
Rui Duan ◽  
Yong Chen
Keyword(s):  
Likelihood Function ◽  
Cox Model ◽  
Meta Analysis ◽  
Event Data ◽  
Time To Event ◽  
Hazard Functions ◽  
Patient Level ◽  
Time To Event Data ◽  
Level Data ◽  
Center Time

Objective: We developed and evaluated a privacy-preserving One-shot Distributed Algorithm for Cox model to analyze multi-center time-to-event data without sharing patient-level information across sites, while accounting for heterogeneity across sites by allowing site-specific baseline hazard functions and feature distributions. Materials and Methods: We constructed a surrogate likelihood function to approximate the Cox log partial likelihood function which is stratified by site, using patient-level data from a single site and aggregated information from other sites. The ODAC estimator was obtained by maximizing the surrogate likelihood function. We evaluated and compare the performance of ODACH with meta-analysis by extensive numerical studies. Results: The simulation study showed that ODACH provided estimates close to the pooled estimator, which is obtained by directly analyzing patient-level data from all sites via a stratified Cox model. The relative bias was <1% across all scenarios. As a comparison, the meta-analysis estimator, which was obtained by the inverse variance weighted average of the site-specific estimates, had substantial bias when the event rate is <5%, with the relative bias reaching 12% when the event rate is 1%. Conclusions: ODACH is a privacy-preserving and communication-efficient method for analyzing multi-center time-to-event data, which allows the baseline hazard functions as well as the distribution of covariate variables to vary across sites. It provides estimates that is close to the pooled estimator and substantially outperforms the meta-analysis estimator when the event is rare. It is thus extremely suitable for studying rare events with heterogeneous baseline hazards across sites in a distributed manner.

Abstract 17059: Re-Use of Clinical Trial Data From the NHLBI Data Repository (BioLINCC) for Patient-Level Meta-Analyses of Cardiovascular Outcomes: Challenges and Opportunities

Circulation ◽  
2018 ◽  
Vol 138 (Suppl_1) ◽  
Author(s):  
Helena Sviglin ◽  
Gauri Dandi ◽  
Eileen Navarro Almario ◽  
Tejas Patel ◽  
Colin O Wu ◽  
...  
Keyword(s):  
Risk Factors ◽  
Meta Analysis ◽  
Cardiovascular Outcomes ◽  
Data Repository ◽  
Common Data Elements ◽  
Patient Level Data ◽  
Patient Level ◽  
Level Data ◽  
Data Elements ◽  
Meta Analyses

Introduction: An objective of the Meta-AnalyTical Interagency Group (MATIG) is to conduct patient-level meta-analyses of cardiovascular outcomes using data from publicly available repositories. We describe challenges with data re-use from a seminal trial, provide a systematic approach to identify and curate data elements for hypothesis generation, and establish stackable trials to support these analyses. Methods: We used data from the ACCORD trial to assess risk factors and their gender specific differences for the event of hospitalization or death due to heart failure (hdHF), in patients with type 2 diabetes*. We identified the data elements needed to answer the research questions, reviewed the trial protocol to verify definitions, extracted patient-level data, performed quality assessment and statistical analysis. The results showed a gender difference in the effect of intensive vs. standard glucose-lowering therapy on hdHF. To validate the findings, we sought additional trials in BioLINCC to develop a compendium for meta-analysis, and repeated these steps for each trial. Results: Challenges for reusing the ACCORD trial included access to complete patient-level data and metadata. The compendium, developed to evaluate the stackability** of data across trials, identified differences in trial designs, patient populations, study interventions, and data elements that may impact the feasibility and interpretation of meta-analysis. An example of compendium components is shown in Table 1. Conclusion: High-quality metadata facilitate re-use of trial repository data. This compendium standardizes common data elements for gender, racial and age-group specific outcome assessment in major clinical trials. It provides the framework to assess the fitness of trials for patient-level meta-analyses. Efforts are underway by MATIG to expand the compendium to include risk factors and major cardiovascular outcomes across multiple large trials for meta-analysis.

Type and intensity of FVIII exposure on inhibitor development in PUPs with haemophilia A

2015 ◽  
Vol 113 (05) ◽  
pp. 958-967 ◽  
Author(s):  
Maria Elisa Mancuso ◽  
Elena Santagostino ◽  
Gili Kenet ◽  
Mohssen Elalfy ◽  
Susanne Holzhauer ◽  
...  
Keyword(s):  
Cox Regression ◽  
Meta Analysis ◽  
Treatment Intensity ◽  
Haemophilia A ◽  
Related Factors ◽  
Inhibitor Development ◽  
Patient Level ◽  
Level Data ◽  
Statistical Approaches ◽  
The Impact

SummaryThe impact of treatment-related factors on inhibitor development in previously untreated patients (PUPs) with haemophilia A is still debated. We present the results of a collaborative, individual patient data meta-analytic project. Eligible data sources were published cohorts of PUPs for which patient-level data were available. The exposures of interest were factor (F)VIII type (recombinant [rFVIII] vs plasma-derived [pdFVIII]) and treatment intensity (≥ vs < 150 IU/kg/week) at first treatment. Family history of inhibitors, F8 mutations, age, treatment regimen (on-demand vs prophylaxis), secular trend and surgery were analysed as putative confounders using different statistical approaches (multivariable Cox regression, propensity score analyses, CART). Analyses accounted for the multi-centre origin of the data. We included 761 consecutive, unselected PUPs with moderate to severe haemophilia A from 10 centres in Egypt, Germany, Israel and Italy. A total of 27 % of patients developed inhibitors; 40 % and 22 % of patients treated with rFVIII and pdFVIII (unadjusted HR 2.2, 95 % CI 1.6–2.9), respectively; 51 % and 24 % of patients receiving high-and low-intensity treatment (unadjusted HR 2.9, 95 % CI 2.0–4.2), respectively. In adjusted analyses, only treatment intensity remained an independent predictor; the effect of FVIII type was largely due to confounding, but with a significant interaction between FVIII type and treatment intensity. This patient-level meta-analysis confirms, across different statistical approaches, that high-intensity treatment is a strong risk factor for inhibitor development. The possible role of FVIII type in subgroups is suggested by the test for interactions but could not be proven because of the limited subgroups sample sizes.

scholarly journals Forced vital capacity and cross-domain late-onset Pompe disease outcomes: an individual patient-level data meta-analysis

2019 ◽  
Vol 266 (9) ◽  
pp. 2312-2321
Author(s):  
Kenneth I. Berger ◽  
Steve Kanters ◽  
Jeroen P. Jansen ◽  
Andrew Stewart ◽  
Susan Sparks ◽  
...  
Keyword(s):  
Forced Vital Capacity ◽  
Vital Capacity ◽  
Late Onset ◽  
Meta Analysis ◽  
Patient Level Data ◽  
Individual Patient Level ◽  
Patient Level ◽  
Cross Domain ◽  
Disease Outcomes ◽  
Level Data
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