Background
Postoperative pericardial adhesions have been associated with increased morbidity, mortality, and surgical difficulty. Barriers exist to limit adhesion formation, yet little is known about their use in cardiac surgery. The study presented here provides the first major systematic review of adhesion barriers in cardiac surgery.
Methods
Scopus and PubMed were assessed on November 20, 2020. Inclusion criteria were clinical studies on human subjects, and exclusion criteria were studies not published in English and case reports. Risk of bias was evaluated with the Cochrane Risk of Bias Tool. Barrier efficacy data was assessed with Excel and GraphPad Prism 5.
Results
Twenty‐five studies were identified with a total of 13 barriers and 2928 patients. Polytetrafluoroethylene (PTFE) was the most frequently evaluated barrier (13 studies, 67% of patients) with adhesion formation rate of 37.31% and standardized tenacity score of 26.50. Several barriers had improved efficacy. In particular, Cova CARD had a standardized tenacity score of 15.00.
Conclusions
Overall, the data varied considerably in terms of study design and reporting bias. The amount of data was also limited for the non‐PTFE studies. PTFE has historically been effective in preventing adhesions. More recent barriers may be superior, yet the current data is nonconfirmatory. No ideal adhesion barrier currently exists, and future barriers must focus on the requirements unique to operating in and around the heart.
Background
Airspace disease as seen on chest X-rays is an important point in triage for patients initially presenting to the emergency department with suspected COVID-19 infection. The purpose of this study is to evaluate a previously trained interpretable deep learning algorithm for the diagnosis and prognosis of COVID-19 pneumonia from chest X-rays obtained in the ED.
Methods
This retrospective study included 2456 (50% RT-PCR positive for COVID-19) adult patients who received both a chest X-ray and SARS-CoV-2 RT-PCR test from January 2020 to March of 2021 in the emergency department at a single U.S. institution. A total of 2000 patients were included as an additional training cohort and 456 patients in the randomized internal holdout testing cohort for a previously trained Siemens AI-Radiology Companion deep learning convolutional neural network algorithm. Three cardiothoracic fellowship-trained radiologists systematically evaluated each chest X-ray and generated an airspace disease area-based severity score which was compared against the same score produced by artificial intelligence. The interobserver agreement, diagnostic accuracy, and predictive capability for inpatient outcomes were assessed. Principal statistical tests used in this study include both univariate and multivariate logistic regression.
Results
Overall ICC was 0.820 (95% CI 0.790–0.840). The diagnostic AUC for SARS-CoV-2 RT-PCR positivity was 0.890 (95% CI 0.861–0.920) for the neural network and 0.936 (95% CI 0.918–0.960) for radiologists. Airspace opacities score by AI alone predicted ICU admission (AUC = 0.870) and mortality (0.829) in all patients. Addition of age and BMI into a multivariate log model improved mortality prediction (AUC = 0.906).
Conclusion
The deep learning algorithm provides an accurate and interpretable assessment of the disease burden in COVID-19 pneumonia on chest radiographs. The reported severity scores correlate with expert assessment and accurately predicts important clinical outcomes. The algorithm contributes additional prognostic information not currently incorporated into patient management.
BACKGROUND: Postoperative pericardial adhesions have been associated
with increased morbidity, mortality, and surgical difficulty. Barriers
exist to limit adhesion formation, yet little is known about their use
in cardiac surgery. The study presented here provides the first major
systematic review of adhesion barriers in cardiac surgery. METHODS:
Scopus and PubMed were assessed on November 20, 2020. Inclusion criteria
were clinical studies on human subjects, and exclusion criteria were
studies not published in English and case reports. Risk of bias was
evaluated with the Cochrane Risk of Bias Tool. Barrier safety and
efficacy data were assessed with Excel and GraphPad Prism 5. RESULTS: 25
studies were identified with a total of 13 barriers and 2,928 patients.
Polytetrafluoroethylene (PTFE) was the most frequently evaluated barrier
(13 studies, 67% of patients) with an infection rate of 1.14%,
bleeding event rate of 0.75%, mortality rate of 1.22%, adhesion
formation rate of 37.31%, and standardized tenacity score of 26.50.
Several barriers had improved safety and efficacy. In particular, Cova
CARD had an infection rate of 0.00%, a bleeding event rate of 0.00%,
and a tenacity score of 15.00. CONCLUSIONS: Overall, the data varied
considerably in terms of study design and reporting bias. The amount of
data was also limited for the non-PTFE studies. PTFE has historically
been effective in preventing adhesions. More recent barriers may be
superior, yet the current data is non-confirmatory. No ideal adhesion
barrier currently exists, and future barriers must focus on the
requirements unique to operating in and around the heart.
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