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  1. Article ; Online: Assessing the utility of deep neural networks in detecting superficial surgical site infections from free text electronic health record data.

    Bonde, Alexander / Lorenzen, Stephan / Brixen, Gustav / Troelsen, Anders / Sillesen, Martin

    Frontiers in digital health

    2024  Volume 5, Page(s) 1249835

    Abstract: Background: High-quality outcomes data is crucial for continued surgical quality improvement. Outcomes are generally captured through structured administrative data or through manual curation of unstructured electronic health record (EHR) data. The aim ... ...

    Abstract Background: High-quality outcomes data is crucial for continued surgical quality improvement. Outcomes are generally captured through structured administrative data or through manual curation of unstructured electronic health record (EHR) data. The aim of this study was to apply natural language processing (NLP) to chart notes in the EHR to accurately capture postoperative superficial surgical site infections (SSSIs).
    Methods: Deep Learning (DL) NLP models were trained on data from 389,865 surgical cases across all 11 hospitals in the Capital Region of Denmark. Surgical cases in the training dataset were performed between January 01st, 2017, and October 30th, 2021. We trained a forward reading and a backward reading universal language model on unlabeled postoperative chart notes recorded within 30 days of a surgical procedure. The two language models were subsequently finetuned on labeled data for the classification of SSSIs. Validation and testing were performed on surgical cases performed during the month of November 2021. We propose two different use cases: a stand-alone machine learning (SAM) pipeline and a human-in-the-loop (HITL) pipeline. Performances of both pipelines were compared to administrative data and to manual curation.
    Results: The models were trained on 3,983,864 unlabeled chart notes and finetuned on 1,231,656 labeled notes. Models had a test area under the receiver operating characteristic curves (ROC AUC) of 0.989 on individual chart notes and 0.980 on an aggregated case level. The SAM pipeline had a sensitivity of 0.604, a specificity of 0.996, a positive predictive value (PPV) of 0.763, and a negative predictive value (NPV) of 0.991. Prior to human review, the HITL pipeline had a sensitivity of 0.854, a specificity of 0.987, a PPV of 0.603, and a NPV of 0.997.
    Conclusion: The performance of the SAM pipeline was superior to administrative data, and significantly outperformed previously published results. The performance of the HITL pipeline approached that of manual curation.
    Language English
    Publishing date 2024-01-08
    Publishing country Switzerland
    Document type Journal Article
    ISSN 2673-253X
    ISSN (online) 2673-253X
    DOI 10.3389/fdgth.2023.1249835
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  2. Article ; Online: Assessing the utility of natural language processing for detecting postoperative complications from free medical text.

    Dencker, Emilie Even / Bonde, Alexander / Troelsen, Anders / Sillesen, Martin

    BJS open

    2024  Volume 8, Issue 2

    Abstract: Background: Postoperative complication rates are often assessed through administrative data, although this method has proven to be imprecise. Recently, new developments in natural language processing have shown promise in detecting specific phenotypes ... ...

    Abstract Background: Postoperative complication rates are often assessed through administrative data, although this method has proven to be imprecise. Recently, new developments in natural language processing have shown promise in detecting specific phenotypes from free medical text. Using the clinical challenge of extracting four specific and frequently undercoded postoperative complications (pneumonia, urinary tract infection, sepsis, and septic shock), it was hypothesized that natural language processing would capture postoperative complications on a par with human-level curation from electronic health record free medical text.
    Methods: Electronic health record data were extracted for surgical cases (across 11 surgical sub-specialties) from 18 hospitals in the Capital and Zealand regions of Denmark that were performed between May 2016 and November 2021. The data set was split into training/validation/test sets (30.0%/48.0%/22.0%). Model performance was compared with administrative data and manual extraction of the test data set.
    Results: Data were obtained for 17 486 surgical cases. Natural language processing achieved a receiver operating characteristic area under the curve of 0.989 for urinary tract infection, 0.993 for pneumonia, 0.992 for sepsis, and 0.998 for septic shock, whereas administrative data achieved a receiver operating characteristic area under the curve of 0.595 for urinary tract infection, 0.624 for pneumonia, 0.571 for sepsis, and 0.625 for septic shock.
    Conclusion: The natural language processing approach was able to capture complications with acceptable performance, which was superior to administrative data. In addition, the model performance approached that of manual curation and thereby offers a potential pathway for complete real-time coverage of postoperative complications across surgical procedures based on natural language processing assessment of electronic health record free medical text.
    MeSH term(s) Humans ; Shock, Septic ; Natural Language Processing ; Postoperative Complications/epidemiology ; Sepsis/diagnosis ; Sepsis/epidemiology ; Urinary Tract Infections/diagnosis ; Pneumonia/diagnosis ; Pneumonia/epidemiology
    Language English
    Publishing date 2024-04-09
    Publishing country England
    Document type Journal Article
    ISSN 2474-9842
    ISSN (online) 2474-9842
    DOI 10.1093/bjsopen/zrae020
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  3. Article: Genetic risk factors for postoperative atrial fibrillation-a nationwide genome-wide association study (GWAS).

    Christensen, Mathias A / Bonde, Alexander / Sillesen, Martin

    Frontiers in cardiovascular medicine

    2023  Volume 10, Page(s) 1040757

    Abstract: Background: Atrial fibrillation (AF) is a major cause of morbidity with a high prevalence among the elderly and has an established genetic disposition. Surgery is a well-known risk factor for AF; however, it is currently not recognized how much common ... ...

    Abstract Background: Atrial fibrillation (AF) is a major cause of morbidity with a high prevalence among the elderly and has an established genetic disposition. Surgery is a well-known risk factor for AF; however, it is currently not recognized how much common genetic variants influence the postoperative risk. The purpose of this study was to identify Single Nucleotide Polymorphisms associated with postoperative AF.
    Methods: The UK Biobank was utilized to conduct a Genome-Wide Association Study (GWAS) to identify variants associated with AF after surgery. An initial discovery GWAS was performed in patients that had undergone surgery with subsequent replication in a unique non-surgical cohort. In the surgical cohort, cases were defined as newly diagnosed AF within 30 days after surgery. The threshold for significance was set at 5 × 10
    Results: After quality control, 144,196 surgical patients with 254,068 SNPs were left for analysis. Two variants (rs17042171 (
    Conclusion: In this GWAS-analysis of a large national biobank, we identified 2 variants that were significantly associated with postoperative AF. These variants were subsequently replicated in a unique non-surgical cohort. These findings bring new insight in the genetics of postoperative AF and may help identify at-risk patients and guide management.
    Language English
    Publishing date 2023-06-19
    Publishing country Switzerland
    Document type Journal Article
    ZDB-ID 2781496-8
    ISSN 2297-055X
    ISSN 2297-055X
    DOI 10.3389/fcvm.2023.1040757
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  4. Article ; Online: Assessing the utility of a sliding-windows deep neural network approach for risk prediction of trauma patients.

    Bonde, Alexander / Bonde, Mikkel / Troelsen, Anders / Sillesen, Martin

    Scientific reports

    2023  Volume 13, Issue 1, Page(s) 5176

    Abstract: The risks of post trauma complications are regulated by the injury, comorbidities, and the clinical trajectories, yet prediction models are often limited to single time-point data. We hypothesize that deep learning prediction models can be used for risk ... ...

    Abstract The risks of post trauma complications are regulated by the injury, comorbidities, and the clinical trajectories, yet prediction models are often limited to single time-point data. We hypothesize that deep learning prediction models can be used for risk prediction using additive data after trauma using a sliding windows approach. Using the American College of Surgeons Trauma Quality Improvement Program (ACS TQIP) database, we developed three deep neural network models, for sliding-windows risk prediction. Output variables included early- and late mortality and any of 17 complications. As patients moved through the treatment trajectories, performance metrics increased. Models predicted early- and late mortality with ROC AUCs ranging from 0.980 to 0.994 and 0.910 to 0.972, respectively. For the remaining 17 complications, the mean performance ranged from 0.829 to 0.912. In summary, the deep neural networks achieved excellent performance in the sliding windows risk stratification of trauma patients.
    MeSH term(s) Humans ; Neural Networks, Computer ; Benchmarking ; Comorbidity ; Quality Improvement ; Area Under Curve
    Language English
    Publishing date 2023-03-30
    Publishing country England
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 2615211-3
    ISSN 2045-2322 ; 2045-2322
    ISSN (online) 2045-2322
    ISSN 2045-2322
    DOI 10.1038/s41598-023-32453-3
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  5. Article: An assessment of the effect of the genotype on postoperative venous thromboembolism risk in 140,831 surgical patients.

    A Christensen, Mathias / Bonde, Alexander / Sillesen, Martin

    Annals of medicine and surgery (2012)

    2021  Volume 71, Page(s) 102938

    Abstract: Background: Postoperative Venous Thromboembolism Events (VTE) constitute a major source of morbidity and mortality after surgery. The aim of this study was to investigate whether commonly occurring Single Nucleotide Polymorphisms (SNPs) are associated ... ...

    Abstract Background: Postoperative Venous Thromboembolism Events (VTE) constitute a major source of morbidity and mortality after surgery. The aim of this study was to investigate whether commonly occurring Single Nucleotide Polymorphisms (SNPs) are associated with VTE in the surgical setting.
    Methods: Retrospective study using data from the United Kingdom (UK) biobank, a genome biobank containing healthcare and genotyping data from more than 500.000 individuals. A cohort of 140,831patients with a registered surgical procedure was identified and used for a discovery genome wide association study (GWAS), with the remainder of the cohort (305,349 non-surgical patients) used as a replication cohort. Primary outcome was associations between SNPs and VTE within 30 days after a surgical procedure. Genome wide significance was set at p = 5 × 10
    Results: In the surgical (discovery) cohort, no SNPs reached genome wide significance. The VTE association of the top candidate SNP in the
    Conclusions: and Relevance: This study did not identify associations between SNPs and postoperative VTE events reaching genome-wide significance, although the VTE relevance of top candidates were demonstrated.
    Language English
    Publishing date 2021-10-13
    Publishing country England
    Document type Journal Article
    ZDB-ID 2745440-X
    ISSN 2049-0801
    ISSN 2049-0801
    DOI 10.1016/j.amsu.2021.102938
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  6. Article ; Online: Assessment of post-trauma complications in eight million trauma cases over a decade in the USA.

    Jakobsen, Rasmus Kirial / Bonde, Alexander / Sillesen, Martin

    Trauma surgery & acute care open

    2021  Volume 6, Issue 1, Page(s) e000667

    Abstract: Background: Trauma is associated with a significant risk of post-trauma complications (PTCs). These include thromboembolic events, strokes, infections, and failure of organ systems (eg, kidney failure). Although care of the trauma patient has evolved ... ...

    Abstract Background: Trauma is associated with a significant risk of post-trauma complications (PTCs). These include thromboembolic events, strokes, infections, and failure of organ systems (eg, kidney failure). Although care of the trauma patient has evolved during the last decade, whether this has resulted in a reduction in specific PTCs is unknown. We hypothesize that the incidence of PTCs has been decreasing during a 10-year period from 2007 to 2017.
    Methods: This is a descriptive study of trauma patients originating from level 1, 2, 3, and 4 trauma centers in the USA, obtained via the Trauma Quality Improvement Program (TQIP) database from 2007 to 2017. PTCs documented throughout the time frame were extracted along with demographic variables. Multiple regression modeling was used to associate admission year with PTCs, while controlling for age, gender, Glasgow Coma Scale score, and Injury Severity Score.
    Results: Data from 8 720 026 trauma patients were extracted from the TQIP database. A total of 366 768 patients experienced one or more PTCs. There was a general decrease in the incidence of PTCs during the study period, with the overall incidence dropping from 7.0% in 2007 to 2.8% in 2017. Multiple regression identified a slight decrease in incidence in all PTCs, although deep surgical site infection (SSI), deep venous thrombosis (DVT), and stroke incidences increased when controlled for confounders.
    Discussion: Overall the incidence of PTCs dropped during the 10-year study period, although deep SSI, DVT, stroke, and cardiac arrest increased during the study period. Better risk prediction tools, enabling a precision medicine approach, are warranted to identify at-risk patients.
    Level of evidence: III.
    Language English
    Publishing date 2021-03-26
    Publishing country England
    Document type Journal Article
    ISSN 2397-5776
    ISSN (online) 2397-5776
    DOI 10.1136/tsaco-2020-000667
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  7. Article ; Online: Assessing optimal methods for transferring machine learning models to low-volume and imbalanced clinical datasets: experiences from predicting outcomes of Danish trauma patients.

    Millarch, Andreas Skov / Bonde, Alexander / Bonde, Mikkel / Klein, Kiril Vadomovic / Folke, Fredrik / Rudolph, Søren Steemann / Sillesen, Martin

    Frontiers in digital health

    2023  Volume 5, Page(s) 1249258

    Abstract: Introduction: Accurately predicting patient outcomes is crucial for improving healthcare delivery, but large-scale risk prediction models are often developed and tested on specific datasets where clinical parameters and outcomes may not fully reflect ... ...

    Abstract Introduction: Accurately predicting patient outcomes is crucial for improving healthcare delivery, but large-scale risk prediction models are often developed and tested on specific datasets where clinical parameters and outcomes may not fully reflect local clinical settings. Where this is the case, whether to opt for de-novo training of prediction models on local datasets, direct porting of externally trained models, or a transfer learning approach is not well studied, and constitutes the focus of this study. Using the clinical challenge of predicting mortality and hospital length of stay on a Danish trauma dataset, we hypothesized that a transfer learning approach of models trained on large external datasets would provide optimal prediction results compared to de-novo training on sparse but local datasets or directly porting externally trained models.
    Methods: Using an external dataset of trauma patients from the US Trauma Quality Improvement Program (TQIP) and a local dataset aggregated from the Danish Trauma Database (DTD) enriched with Electronic Health Record data, we tested a range of model-level approaches focused on predicting trauma mortality and hospital length of stay on DTD data. Modeling approaches included de-novo training of models on DTD data, direct porting of models trained on TQIP data to the DTD, and a transfer learning approach by training a model on TQIP data with subsequent transfer and retraining on DTD data. Furthermore, data-level approaches, including mixed dataset training and methods countering imbalanced outcomes (e.g., low mortality rates), were also tested.
    Results: Using a neural network trained on a mixed dataset consisting of a subset of TQIP and DTD, with class weighting and transfer learning (retraining on DTD), we achieved excellent results in predicting mortality, with a ROC-AUC of 0.988 and an F2-score of 0.866. The best-performing models for predicting long-term hospitalization were trained only on local data, achieving an ROC-AUC of 0.890 and an F1-score of 0.897, although only marginally better than alternative approaches.
    Conclusion: Our results suggest that when assessing the optimal modeling approach, it is important to have domain knowledge of how incidence rates and workflows compare between hospital systems and datasets where models are trained. Including data from other health-care systems is particularly beneficial when outcomes are suffering from class imbalance and low incidence. Scenarios where outcomes are not directly comparable are best addressed through either de-novo local training or a transfer learning approach.
    Language English
    Publishing date 2023-11-02
    Publishing country Switzerland
    Document type Journal Article
    ISSN 2673-253X
    ISSN (online) 2673-253X
    DOI 10.3389/fdgth.2023.1249258
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  8. Article ; Online: [Lengthening temporalis myoplasty in treatment of chronic facial paralysis].

    Bonde, Alexander / Wolthers, Mette Stueland

    Ugeskrift for laeger

    2017  Volume 179, Issue 45

    Abstract: Introducing the lengthening temporalis myoplasty (LTM), a newly implemented surgical treatment of chronic facial paralysis. LTM is a single-stage operation where the temporalis muscle is transposed for dynamic smile reconstruction, hereby serving as an ... ...

    Abstract Introducing the lengthening temporalis myoplasty (LTM), a newly implemented surgical treatment of chronic facial paralysis. LTM is a single-stage operation where the temporalis muscle is transposed for dynamic smile reconstruction, hereby serving as an alternative to the more complex two-stage microvascular functional muscle transplantation. This case report demonstrates how LTM can be used to treat patients, who are not motivated or suitable for extensive surgery. The introduction of this technique aims to help a larger number of patients with chronic facial paralysis.
    MeSH term(s) Chronic Disease ; Facial Paralysis/pathology ; Facial Paralysis/surgery ; Female ; Humans ; Middle Aged ; Reconstructive Surgical Procedures/methods ; Smiling ; Temporal Muscle/surgery
    Language Danish
    Publishing date 2017-11-01
    Publishing country Denmark
    Document type Case Reports
    ZDB-ID 124102-3
    ISSN 1603-6824 ; 0041-5782
    ISSN (online) 1603-6824
    ISSN 0041-5782
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  9. Article ; Online: Postoperative complications: an observational study of trends in the United States from 2012 to 2018.

    Dencker, Emilie Even / Bonde, Alexander / Troelsen, Anders / Varadarajan, Kartik Mangudi / Sillesen, Martin

    BMC surgery

    2021  Volume 21, Issue 1, Page(s) 393

    Abstract: Background: Postoperative complications continue to constitute a major issue for both the healthcare system and the individual patient and are associated with inferior outcomes and higher healthcare costs. The objective of this study was to evaluate the ...

    Abstract Background: Postoperative complications continue to constitute a major issue for both the healthcare system and the individual patient and are associated with inferior outcomes and higher healthcare costs. The objective of this study was to evaluate the trends of postoperative complication rates over a 7-year period.
    Methods: The NSQIP datasets from 2012 to 2018 were used to assess 30-day complication incidence rates including mortality rate following surgical procedures within ten surgical subspecialties. Multivariable logistic regression was used to associate complication rates with dataset year, while adjusting for relevant confounders.
    Results: A total of 5,880,829 patients undergoing major surgery were included. Particularly the incidence rates of four complications were found to be decreasing: superficial SSI (1.9 to 1.3%), deep SSI (0.6 to 0.4%), urinary tract infection (1.6 to 1.2%) and patient unplanned return to the operating room (3.1 to 2.7%). Incidence rate for organ/space SSI exhibited an increase (1.1 to 1.5%). When adjusted, regression analyses indicated decreased odds ratios (OR) through the study period years for particularly deep SSI OR 0.92 [0.92-0.93], superficial SSI OR 0.94 [0.94-0.94] and acute renal failure OR 0.96 [0.95-0.96] as the predictor variable (study year) increased (p < 0.01). However, OR's for organ/space SSI 1.05 [1.05-1.06], myocardial infarction 1.01 [1.01-1.02] and sepsis 1.01 [1.01-1.02] increased slightly over time (all p < 0.01).
    Conclusions: Incidence rates for the complications exhibited a stable trend over the study period, with minor in or decreases observed.
    MeSH term(s) Humans ; Incidence ; Logistic Models ; Postoperative Complications/epidemiology ; Postoperative Period ; Retrospective Studies ; Risk Factors ; Surgical Wound Infection ; United States/epidemiology
    Language English
    Publishing date 2021-11-06
    Publishing country England
    Document type Journal Article ; Observational Study
    ZDB-ID 2050442-1
    ISSN 1471-2482 ; 1471-2482
    ISSN (online) 1471-2482
    ISSN 1471-2482
    DOI 10.1186/s12893-021-01392-z
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  10. Article ; Online: The effect of fluid resuscitation strategy on monocyte and T-cell surface markers.

    Bonde, Alexander / Kirial, Rasmus / Svenningsen, Peter / Sillesen, Martin

    The Journal of surgical research

    2018  Volume 230, Page(s) 20–27

    Abstract: Background: Despite initial lifesaving benefits, posttraumatic resuscitation strategies have been associated with immunologic complications leading to systemic inflammatory response syndrome, sepsis, multiple organ failure, and late trauma death. ... ...

    Abstract Background: Despite initial lifesaving benefits, posttraumatic resuscitation strategies have been associated with immunologic complications leading to systemic inflammatory response syndrome, sepsis, multiple organ failure, and late trauma death. Nevertheless, the direct effect on immunologic surface markers remains inadequately described. We hypothesized that changes in monocyte and T-cell surface markers were associated with initial posttraumatic fluid resuscitation.
    Materials and methods: Data were extracted from the inflammation and host response to injury (Glue Grant) study. Blood samples were drawn from 492 patients on days 0, 1, 4, 7, 14, and 28 and analyzed for 31 monocyte and T-cell surface markers. Resuscitation strategies during the initial 48 h were quantified, including transfusion of packed red blood cells (PRBCs), fresh frozen plasma (FFP), platelets, and crystalloids. Longitudinal surface marker concentration changes were quantified by the calculation of a within-patient signal intensity change and were associated with resuscitation strategy while controlling confounders. P-values were post hoc corrected using the false detection rate q-value.
    Results: The monocyte surface marker (CD83) trajectory (as measured by a within-patient signal intensity change) was found to be positively associated with volume of PRBCs transfused (q = 0.002) and negatively associated with the transfused volume of FFP (q = 0.004). T-cell surface marker (CD3) was found to be negatively associated with volume of PRBCs transfused (q = 854 × 10
    Conclusions: PRBC and FFP transfusion was associated with opposing effects on CD3 and CD83 trajectories, which may in part explain some of the protective effects of a high FFP:PRBC ratio in trauma-related resuscitation.
    MeSH term(s) Adult ; Antigens, CD/immunology ; Antigens, CD/metabolism ; Biomarkers/metabolism ; Blood Component Transfusion/adverse effects ; Blood Component Transfusion/methods ; Crystalloid Solutions/administration & dosage ; Crystalloid Solutions/adverse effects ; Female ; Humans ; Immunoglobulins/immunology ; Immunoglobulins/metabolism ; Inflammation/blood ; Inflammation/diagnosis ; Inflammation/etiology ; Inflammation/immunology ; Male ; Membrane Glycoproteins/immunology ; Membrane Glycoproteins/metabolism ; Middle Aged ; Monocytes/drug effects ; Monocytes/immunology ; Monocytes/metabolism ; Resuscitation/adverse effects ; Resuscitation/methods ; T-Lymphocytes/drug effects ; T-Lymphocytes/metabolism ; Wounds and Injuries/blood ; Wounds and Injuries/immunology ; Wounds and Injuries/therapy ; CD83 Antigen
    Chemical Substances Antigens, CD ; Biomarkers ; Crystalloid Solutions ; Immunoglobulins ; Membrane Glycoproteins
    Language English
    Publishing date 2018-05-12
    Publishing country United States
    Document type Journal Article
    ZDB-ID 80170-7
    ISSN 1095-8673 ; 0022-4804
    ISSN (online) 1095-8673
    ISSN 0022-4804
    DOI 10.1016/j.jss.2018.04.029
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