State-Level Examination of Clinical Outcomes and Costs for Robotic and Laparoscopic Approach to Diaphragmatic Hernia Repair

Kulshrestha, Sujay; Janjua, Haroon; Bunn, Corinne; Rogers, Michael P.; DuCoin, Christopher; Abdelsattar, Zaid M.; Luchette, Fred A.; Kuo, Paul C.; Baker, Marshall S.

doi:10.1016/j.jamcollsurg.2021.05.003

Cited by 5 publications

(4 citation statements)

References 13 publications

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“…Only O'Connor et [3][4][5]7,8,22]. (B) Meta-analysis of length of stay [4,5,[7][8][9][10]22,27,28]. (C) Meta-analysis of mean operation time [4,5,7,9,10,27].…”

Section: Resultsmentioning

confidence: 99%

“…Lekarczyk et al [ 27 ] found similar hospital profits for the robotic group despite higher supply costs and charges. However, Kulshrestha et al [ 28 ], in a study with more participants, reported that both open and robotic-assisted procedures had significantly higher median index hospitalization costs compared to laparoscopic ones. The most common reasons that increased the cost were upper endoscopy and reoperation, followed by emergent priority, increased comorbidity index, and LOS.…”

Section: Discussionmentioning

confidence: 99%

“…(A) Meta-analysis of overall postoperative complication rates[3][4][5]7,8,22]. (B) Meta-analysis of length of stay[4,5,[7][8][9][10]22,27,28]. (C) Meta-analysis of mean operation time[4,5,7,9,10,27].…”

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confidence: 99%

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Robotic-assisted versus laparoscopic paraesophageal hernia repair: a systematic review and meta-analysis

Elissavet,

Ioannis,

Panagiotis

et al. 2023

J Minim Invasive Surg

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Purpose The robotic approach offers improved visualization and maneuverability for surgeons. This systematic review aims to compare the outcomes of robotic-assisted and conventional laparoscopic approaches for paraesophageal hernia repair, specifically examining postoperative complications, operative time, hospital stay, and recurrence. Methods A systematic review including thorough research through PubMed, Scopus, and Cochrane, was performed and only comparative studies were included. Studies concerning other types of hiatal hernias or children were excluded. A meta-analysis was conducted to compare overall postoperative complications, hospital stay, and operation time. Results Ten comparative studies, with 186,259 participants in total, were included in the meta-analysis, but unfortunately, not all of them reported all the outcomes under question. It appeared that there is no statistically significant difference between the conventional laparoscopic and the robotic-assisted approach, regarding the overall postoperative complication rate (odds ratio [OR], 0.56, 95% confidence interval [CI], 0.28–1.11), the mean operation time (t = 1.41; 95% CI, –0.15–0.52; p = 0.22), and the hospital length of stay (t = –1.54; degree of freedom = 8; 95% CI, –0.53–0.11; p = 0.16). Only two studies reported evidence concerning the recurrence rates. Conclusion Overall, the robotic-assisted method did not demonstrate superiority over conventional laparoscopic paraesophageal hiatal hernia repair in terms of postoperative complications, operation time, or hospital stay. However, some studies focused on cost and patient characteristics of each group. Further comparative and randomized control studies with longer follow-up periods are needed for more accurate conclusions on short- and long-term outcomes.

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“…Only O'Connor et [3][4][5]7,8,22]. (B) Meta-analysis of length of stay [4,5,[7][8][9][10]22,27,28]. (C) Meta-analysis of mean operation time [4,5,7,9,10,27].…”

Section: Resultsmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

See 1 more Smart Citation

Robotic-assisted versus laparoscopic paraesophageal hernia repair: a systematic review and meta-analysis

Elissavet,

Ioannis,

Panagiotis

et al. 2023

J Minim Invasive Surg

View full text Add to dashboard Cite

show abstract

“…However, it still proves to be disadvantageous when it comes to costs. This was displayed by Kulshrestha’s et al , in which the authors reported robotic surgery having comparable clinical outcomes, but a higher index cost when compared to laparoscopic surgery ( 78 ). In another study, Kulshrestha et al described the existence of a 2-fold variation between diaphragmatic hernia repair costs between various hospitals ( 79 ).…”

Section: Robotic Giant Paraesophageal Hernia (Peh) Repairmentioning

confidence: 95%

Tackling complex thoracic surgical operations with robotic solutions: a narrative review

Odeh,

Wyant,

Freeman

et al. 2024

J Thorac Dis

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Background and Objective The adoption of robotic surgery for general thoracic surgery has rapidly progressed over the last two decades from its application in basic operations to complex pathologies. As such, the purpose of this narrative review is to highlight the collective experience of tackling complex thoracic surgical operations with minimally invasive robotic solutions. Methods Electronic searches of PubMed were conducted for each subtopic, using specific keywords and inclusion criteria. Once identified, the articles were screened through the abstract, introduction, results and conclusion for relevancy, and included based on a standard narrative review inclusion criteria. Key Content and Findings The role of the robotic approach has increased in thoracic outlet syndrome, chest wall resection, tracheobronchomalacia, airway and sleeve lung surgery, lobectomy after neoadjuvant therapy, complex segmentectomy, giant paraesophageal hernia repair, esophagectomy and esophageal enucleation, mediastinal masses and thymectomy and lung transplantation. Robotic surgery has several advantages when compared to video-assisted and open thoracoscopic surgery. These include better pain control and aesthetic outcome, improved handling of complex anatomy, enhanced access to lymph nodes, and faster recovery rates. Although it is associated with longer operative time, robotic surgery has comparable morbidity rates. Conclusions The robotic approach to complex thoracic problems is safe, effective, and associated with improved patient outcomes. To encourage wider adoption of robotic technology, increased training and expanded research efforts are essential, alongside improved worldwide access to this technology.

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Machine Learning Refinement of the NSQIP Risk Calculator: Who Survives the “Hail Mary” Case?

Rogers

Janjua

DeSantis

et al. 2022

Journal of the American College of Surgeons

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BACKGROUND: The American College of Surgeons (ACS) NSQIP risk calculator helps guide operative decision making. In patients with significant surgical risk, it may be unclear whether to proceed with “Hail Mary”–type interventions. To refine predictions, a local interpretable model-agnostic explanations machine (LIME) learning algorithm was explored to determine weighted patient-specific factors’ contribution to mortality. STUDY DESIGN: The ACS-NSQIP database was queried for all surgical patients with mortality probability greater than 50% between 2012 and 2019. Preoperative factors (n = 38) were evaluated using stepwise logistic regression; 26 significant factors were used in gradient boosted machine (GBM) modeling. Data were divided into training and testing sets, and model performance was substantiated with 10-fold cross validation. LIME provided individual subject mortality. The GBM-trained model was interpolated to LIME, and predictions were made using the test dataset. RESULTS: There were 6,483 deaths (53%) among 12,248 admissions. GBM modeling displayed good performance (area under the curve = 0.65, 95% CI 0.636–0.671). The top 5 factors (% contribution) to mortality included: septic shock (27%), elevated International Normalized Ratio (22%), ventilator-dependence (14%), thrombocytopenia (14%), and elevated serum creatinine (5%). LIME modeling subset personalized patients by factors and weights on survival. In the entire cohort, mortality positive predictive value with 2 factor combinations was 53.5% (specificity 0.713), 3 combinations 64.2% (specificity 0.835), 4 combinations 72.1% (specificity 0.943), and all 5 combinations 77.9% (specificity 0.993). Conversely, mortality positive predictive value fell to 34% in the absence of 4 factors. CONCLUSIONS: Through the application of machine learning algorithms (GBM and LIME), our model individualized predicted mortality and contributing factors with substantial ACS-NSQIP predicted mortality. USE of machine learning techniques may better inform operative decisions and family conversations in cases of significant surgical risk.

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State-Level Examination of Clinical Outcomes and Costs for Robotic and Laparoscopic Approach to Diaphragmatic Hernia Repair

Cited by 5 publications

References 13 publications

Robotic-assisted versus laparoscopic paraesophageal hernia repair: a systematic review and meta-analysis

Robotic-assisted versus laparoscopic paraesophageal hernia repair: a systematic review and meta-analysis

Tackling complex thoracic surgical operations with robotic solutions: a narrative review

Machine Learning Refinement of the NSQIP Risk Calculator: Who Survives the “Hail Mary” Case?

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