Perioperative factors associated with survival following surgery for pancreatic cancer - a nationwide analysis of 473 cases from Denmark.

BACKGROUND: Pancreatic ductal adenocarcinoma (PDAC) remains one of the most lethal cancers worldwide, with an overall 5-year survival rate of only 5%. The effect of perioperative treatment factors including duration of surgery, blood transfusions as well as choice of anesthesia and analgesia techniques on overall survival (OS) following pancreatic resections for PDAC, is currently not well known. We hypothesized that these perioperative factors might be associated with OS after pancreatic resections for PDAC. METHODS: This is a retrospective study from a nationwide cohort of patients who underwent surgery for PDAC in Denmark from 2011 to 2020. Kaplan-Meier 1, 2 and 5-year survival estimates were 73%, 49% and 22%, respectively. Data were obtained by joining the national Danish Pancreatic Cancer Database (DPCD) and the Danish Anaesthesia Database (DAD). Associations between the primary endpoint (OS) and perioperative factors including duration of surgery, type of anesthesia (intravenous, inhalation or mixed), use of epidural analgesia and perioperative blood transfusions were assessed using Hazard Ratios (HRs). These were calculated by Cox regression, controlling for relevant confounders identified through an assessment of the current literature. These included demographics, comorbidities, perioperative information, pre and postoperative chemotherapy, tumor staging and free resection margins. RESULTS: Overall, data from 473 resected PDAC patients were available. Multivariate Cox regression indicated that perioperative blood transfusions were associated with shorter OS (HR 2.53, p = 0.005), with survival estimates of 8.8% in transfused vs. 28.0% in non-transfused patients at 72 months after surgery. No statistically significant associations were identified for the duration of surgery or anesthesia/analgesia techniques. CONCLUSION: In this study, the use of perioperative blood transfusions was associated with shorter OS.

De novo EIF2AK1 and EIF2AK2 Variants Are Associated with Developmental Delay, Leukoencephalopathy, and Neurologic Decompensation.

EIF2AK1 and EIF2AK2 encode members of the eukaryotic translation initiation factor 2 alpha kinase (EIF2AK) family that inhibits protein synthesis in response to physiologic stress conditions. EIF2AK2 is also involved in innate immune response and the regulation of signal transduction, apoptosis, cell proliferation, and differentiation. Despite these findings, human disorders associated with deleterious variants in EIF2AK1 and EIF2AK2 have not been reported. Here, we describe the identification of nine unrelated individuals with heterozygous de novo missense variants in EIF2AK1 (1/9) or EIF2AK2 (8/9). Features seen in these nine individuals include white matter alterations (9/9), developmental delay (9/9), impaired language (9/9), cognitive impairment (8/9), ataxia (6/9), dysarthria in probands with verbal ability (6/9), hypotonia (7/9), hypertonia (6/9), and involuntary movements (3/9). Individuals with EIF2AK2 variants also exhibit neurological regression in the setting of febrile illness or infection. We use mammalian cell lines and proband-derived fibroblasts to further confirm the pathogenicity of variants in these genes and found reduced kinase activity. EIF2AKs phosphorylate eukaryotic translation initiation factor 2 subunit 1 (EIF2S1, also known as EIF2α), which then inhibits EIF2B activity. Deleterious variants in genes encoding EIF2B proteins cause childhood ataxia with central nervous system hypomyelination/vanishing white matter (CACH/VWM), a leukodystrophy characterized by neurologic regression in the setting of febrile illness and other stressors. Our findings indicate that EIF2AK2 missense variants cause a neurodevelopmental syndrome that may share phenotypic and pathogenic mechanisms with CACH/VWM.

Impact of para aortic lymph node removal on survival following resection for pancreatic adenocarcinoma.

INTRODUCTION: For PDAC patients undergoing resection, it remains unclear whether metastases to the paraaortic lymph nodes (PALN+) have any prognostic significance and whether metastases should lead to the operation not being carried out. Our hypothesis is that PALN + status would be associated with short overall survival (OS) compared with PALN-, but longer OS compared with patients undergoing surgical exploration only (EXP). METHODS: Patients with registered PALN removal from the nationwide Danish Pancreatic Cancer Database (DPCD) from May 1st 2011 to December 31st 2020 were assessed. A cohort of PDAC patients who only had explorative laparotomy due to non-resectable tumors were also included (EXP group). Survival analysis between groups were performed with cox-regression in a multivariate approach including relevant confounders. RESULTS: A total of 1758 patients were assessed, including 424 (24.1%) patients who only underwent explorative surgery leaving 1334 (75.8%) patients for further assessment. Of these 158 patients (11.8%) had selective PALN removal, of whom 19 patients (12.0%) had PALN+. Survival analyses indicated that explorative surgery was associated with significantly shorter OS compared with resection and PALN + status (Hazard Ratio 2.36, p < 0.001). No difference between PALN + and PALN- status could be demonstrated in resected patients after controlling for confounders. CONCLUSION: PALN + status in patients undergoing resection offer improved survival compared with EXP. PALN + should not be seen as a contraindication for curative intended resection.

Pancreatic surgery during the COVID-19 pandemic 2020-2021: an observational cohort study from a third level referral center.

BACKGROUND: During the COVID pandemic there has been limited access to elective surgery including oncologic surgery in several countries world-wide. The aim of this study was to investigate if there was any lockdown effect on pancreatic surgery with special focus on malignant pancreatic and periampullary tumours. METHODS: Patients who underwent pancreatic surgery during the two Danish lockdown periods from 11. March 2020 and the following 12 months were compared with patients who were operated the preceding 3 years. Data on patients' characteristics, waiting time, operations, and clinical outcomes were evaluated. RESULTS: During lockdown and the previous three years the annual number of resections were 242, 232, 253, and 254, respectively (p = 0.851). Although the numbers were not significantly different, there were fluctuations in operations and waiting time during the lockdown. During the second outbreak of COVID October 2020 to March 2021 the overall median waiting time increased to 33 days (quartiles 26;39) compared to 23 (17;33) days during the first outbreak from March to May 2020 (p = 0.019). The same difference was seen for patients with malignant tumours, 30 (23;36) vs. 22 (18;30) months (p = 0.001). However, the fluctuations and waiting time during lockdown was like the preceding three years. Neither 30- nor 90-days mortality, length of stay, number of extended operations, and complications and tumour stage were significantly different from previous years. CONCLUSIONS: There were significant fluctuations in waiting time for operations during the lockdown, but these variations were not different from the preceding three years, wherefore other explanations than an impact from COVID are conceivable.

Postoperative complications: an observational study of trends in the United States from 2012 to 2018.

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.

Smoking and risk of surgical bleeding: nationwide analysis of 5,452,411 surgical cases.

BACKGROUND: Although smoking is associated with several postoperative complications, a possible association with surgical bleeding remains unclear. We examined if smoking is associated with a higher risk of surgical bleeding. STUDY DESIGN AND METHODS: We included patients from the American College of Surgeons National Surgical Quality Improvement Program 2007-2016 from 680 hospitals across the United States. Patients with information on age, sex, surgical specialty, and smoking status were included. Surgical bleeding was defined as 1 or more red blood cell (RBC) units transfused intraoperatively to 72 hours postoperatively. The association between smoking and surgical bleeding was examined using logistic regressions adjusted for age, sex, body mass index, ethnicity, comorbidities, laboratory values, American Society of Anesthesiologists score, type of anesthesia, duration of surgery, work relative value unit (surrogate for operative complexity), surgical specialty, and procedure year. RESULTS: A total of 5,452,411 cases were recorded, of whom 19% smoked and 6% received transfusion. Odds ratios for transfusion were 1.06 (95% confidence interval [CI], 1.05-1.07) for smokers versus nonsmokers and 1.06 (95% CI, 1.04-1.09) for current smokers versus never-smokers. Odds ratios for cumulative smoking were 0.97 (95% CI, 0.95-1.00) for greater than 0 to 20 versus 0 pack-years, 1.04 (95% CI, 1.01-1.07) for greater than 20 to 40, and 1.12 (95% CI, 1.09-1.15) for greater than 40 (p for trend < 0.001). Hazard ratios for reoperations due to any cause and to bleeding were 1.28 (95% CI, 1.27-1.31) and 0.99 (95% CI, 0.93-1.04). CONCLUSION: Smoking was associated with a higher risk of RBC transfusion as a proxy for surgical bleeding across all surgical specialties combined.

Ketamine for rapid sequence intubation in adult trauma patients: A retrospective observational study.

BACKGROUND: In the trauma population, ketamine is commonly used during rapid sequence induction. However, as ketamine has been associated with important side effects, this study sought to compare in-hospital mortality in trauma patients after induction with ketamine versus other induction agents. METHODS: We retrospectively identified adult trauma patients intubated in the pre-hospital phase or initially in the trauma bay at two urban level-1 trauma centers during a 2-year period using local trauma registries and medical records. In-hospital mortality was compared for patients intubated with ketamine versus other agents using logistic regression with adjustment for age, gender, Injury Severity Score (ISS), systolic blood pressure (SBP) < 90 mm Hg, and pre-hospital Glasgow Coma Scale (GCS) score. RESULTS: A total of 343 trauma patients were included with a median ISS of 25 [17-34]. The most frequently used induction agents were ketamine (36%) and propofol (36%) followed by etomidate (9%) and midazolam (5%). There was no difference in ISS or the presence of SBP <90 mm Hg according to the agent of choice, but the pre-hospital GCS score was higher for patients intubated with ketamine (median 8 vs 5, P = .001). The mortality for patients intubated with ketamine was 18% vs 27% for patients intubated with other agents (P = .14). This remained statistically insignificant in the multivariable logistic regression analysis (odds ratio 0.68 [0.33-1.41], P = .30). CONCLUSIONS: We found no statistically significant difference in mortality among patients intubated in the initial phase post-trauma with the use of ketamine compared with other agents (propofol, etomidate, or midazolam).

Ketamine as a Rapid Sequence Induction Agent in the Trauma Population: A Systematic Review.

The choice of drug used to facilitate endotracheal intubation in trauma patients during rapid sequence induction (RSI) may have an impact on survival. Ketamine is commonly used in the hemodynamically unstable trauma patient although it has been associated with side effects. This review sought to investigate whether ketamine should be preferred over other induction agents for RSI in trauma patients. PubMed, Embase, and the Cochrane Library were systematically searched on September 19, 2016 for studies reporting RSI of adult trauma patients with ketamine compared with another induction agent (etomidate, propofol, thiopental, or midazolam). No language restrictions were applied. The primary outcome was 30-day mortality, and secondary outcomes included information on blood transfusions, length of hospital stay, and hospital mortality. Risk of bias was assessed using the Cochrane Risk of Bias assessment tool for randomized trials and the Risk of Bias in Non-Randomized Studies of Interventions for nonrandomized studies of intervention. A total of 4 studies were included. A cohort study from 1976 compared thiopental (n = 26) with ketamine (n = 14) for RSI in trauma patients. The primary outcome was number of blood transfusions, and no significant difference was found. Risk of bias was judged to be serious. A randomized controlled trial from 2009 compared etomidate (n = 57) with ketamine (n = 47) and found no significant difference in 28-day mortality (odds ratio [OR], 0.8 [0.4-2.0]). The trial was judged to have a low risk of bias. Two cohort studies from 2015 and 2017 also compared etomidate (n = 116 and n = 526) with ketamine (n = 145 and n = 442). No significant difference in hospital mortality between the groups was observed (OR, 1.11 [0.38-3.27] and OR, 1.41 [0.91-2.16], respectively). Both studies were judged to have a moderate risk of bias, thus excluding the possibility of a meaningful meta-analysis. The study from 2017 also reported number of units of blood transfused during the first 48 hours after trauma and length of hospital stay. No significant differences were observed (OR, 1.14 [0.87-1.49] and OR, 1.1 [0.95-1.27], respectively). Extremely few studies have compared induction agents for RSI in trauma patients. No significant differences have been found in mortality, length of hospital stay, or number of blood transfusions after induction with ketamine compared to other induction agents, but a clinically relevant benefit or harm cannot be excluded.

Different resuscitation strategies and novel pharmacologic treatment with valproic acid in traumatic brain injury.

Traumatic brain injury (TBI) is a leading cause of death in young adults, and effective treatment strategies have the potential to save many lives. TBI results in coagulopathy, endothelial dysfunction, inflammation, cell death, and impaired epigenetic homeostasis, ultimately leading to morbidity and/or mortality. Commonly used resuscitation fluids such as crystalloids or colloids have several disadvantages and might even be harmful when administered in large quantities. There is a need for next-generation treatment strategies (especially in the prehospital setting) that minimize cellular damage, improve survival, and enhance neurological recovery. Pharmacologic treatment with histone deacetylase inhibitors, such as valproic acid, has shown promising results in animal studies of TBI and may therefore be an excellent example of next-generation therapy. This review briefly describes traditional resuscitation strategies for TBI combined with hemorrhagic shock and describes preclinical studies on valproic acid as a new pharmacologic agent in the treatment of TBI. It finally discusses limitations and future directions on the use of histone deacetylase inhibitors for the treatment of TBI.

The effect of fluid resuscitation strategy on monocyte and T-cell surface markers.

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 × 10-9) and positively associated with the transfused volume of FFP (q = 0.022). Platelets and crystalloid transfusion volumes were not associated with any surface marker trajectories. 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.

Effect of Transfusion Strategy in Acute Non-variceal Upper Gastrointestinal Bleeding: A Nationwide Study of 5861 Hospital Admissions in Denmark.

BACKGROUND: Acute non-variceal upper gastrointestinal bleeding (NVUGIB) is a common cause of admissions as well as aggressive transfusion of blood products. Whether the transfusion strategy in NVUGIB impacts on hemostasis is unknown and constitutes the focus of this study. METHOD: Retrospective analysis of all hospital admissions in Denmark between 2011 and 2013 where hemostatic endoscopic interventions in either the stomach or duodenum had been employed. Regression modeling was used to predict the effect of units transfused of packed red blood cells (PRBC), fresh frozen plasma (FFP), and platelets (PLT) on primary outcome 30-day mortality as well as secondary hemostasis-related outcomes and need for re-endoscopy and conversion to surgery. The model was corrected for confounders, including transfusion of other blood products (PRBC, FFP, and PLT, respectively), patient age as well as pre-existing medical conditions. RESULTS: 5107 patients received 10783 therapeutic endoscopic interventions. Units of PRBC transfused were identified as a predictor of re-endoscopy, surgery, and 30-day mortality with odds ratio (OR) 1.08 (1.06-1.09, p < 0.01), 1.05 (1.03-1.07, p < 0.01), and 1.04 (1.01-1.06, p < 0.01), respectively. Units of FFP transfused were associated with a higher risk of surgery and 30-day mortality with OR 1.05 (1.02-1.08, p < 0.01) and 1.04 (1.02-1.07, p < 0.01), respectively. Units of PLTs transfused were independently associated with a reduction in risk of re-endoscopy 0.93 (0.87-0.98, p = 0.02). A high ratio of PRBC:FFP:PLT (1:1:1) was associated with reduced need for re-endoscopy OR 0.23 (0.06-0.67, p = 0.01) but increased mortality with OR 3.60 (1.34-11.38, p = 0.02). CONCLUSION: PRBC transfusion was associated with adverse events, including 30-day mortality and failure of hemostasis. In contrast, transfusion of PLT was associated with a reduction in need for re-endoscopy.

Treatment with a histone deacetylase inhibitor, valproic acid, is associated with increased platelet activation in a large animal model of traumatic brain injury and hemorrhagic shock.

BACKGROUND: We have previously shown that resuscitation with fresh frozen plasma (FFP) in a large animal model of traumatic brain injury (TBI) and hemorrhagic shock (HS) decreases the size of the brain lesion, and that addition of a histone deacetylase inhibitor, valproic acid (VPA), provides synergistic benefits. In this study, we hypothesized that VPA administration would be associated with a conservation of platelet function as measured by increased platelet activation after resuscitation. MATERIALS AND METHODS: Ten swine (42-50 kg) were subjected to TBI and HS (40% blood loss). Animals were left in shock for 2 h before resuscitation with either FFP or FFP+VPA (300 mg/kg). Serum levels of platelet activation markers transforming growth factor beta, CD40 L, P-selectin, and platelet endothelial cell adhesion molecule (PECAM) 1 were measured at baseline, postresuscitation, and after a 6-h observation period. Platelet activation markers were also measured in the brain whole cell lysates and immunohistochemistry. RESULTS: Circulating P-selectin levels were significantly higher in the FFP+VPA group compared with the FFP alone group (70.85±4.70 versus 48.44±7.28 ng/mL; P<0.01). Likewise, immunohistochemistry data showed elevated P-selectin in the VPA treatment group (22.30±10.39% versus 8.125±3.94%, P<0.01). Serum sCD40L levels were also higher in the FFP+VPA group (3.21±0.124 versus 2.38±0.124 ng/mL; P<0.01), as was brain sCD40L levels (1.41±0.15 versus 1.22±0.12 ng/mL; P=0.05). Circulating transforming growth factor beta levels were elevated in the FFP+VPA group, but this did not reach statistical significance (11.20±1.46 versus 8.09±1.41 ng/mL; P=0.17). Brain platelet endothelial cell adhesion molecule 1 levels were significantly lower in the FFP+VPA group compared with the FFP group (5.22±2.00 pg/mL versus 7.99±1.13 pg/mL; P=0.03). CONCLUSIONS: In this clinically relevant large animal model of combined TBI+HS, the addition of VPA to FFP resuscitation results in an early upregulation of platelet activation in the circulation and the brain. The previously observed neuroprotective effects of VPA may be due to a conservation of platelet function as measured by a higher platelet activation response after resuscitation.

Assessing the utility of natural language processing for detecting postoperative complications from free medical text.

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.

An assessment of the value of deep neural networks in genetic risk prediction for surgically relevant outcomes.

INTRODUCTION: Postoperative complications affect up to 15% of surgical patients constituting a major part of the overall disease burden in a modern healthcare system. While several surgical risk calculators have been developed, none have so far been shown to decrease the associated mortality and morbidity. Combining deep neural networks and genomics with the already established clinical predictors may hold promise for improvement. METHODS: The UK Biobank was utilized to build linear and deep learning models for the prediction of surgery relevant outcomes. An initial GWAS for the relevant outcomes was initially conducted to select the Single Nucleotide Polymorphisms for inclusion in the models. Model performance was assessed with Receiver Operator Characteristics of the Area Under the Curve and optimum precision and recall. Feature importance was assessed with SHapley Additive exPlanations. RESULTS: Models were generated for atrial fibrillation, venous thromboembolism and pneumonia as genetics only, clinical features only and a combined model. For venous thromboembolism, the ROC-AUCs were 60.1% [59.6%-60.4%], 63.4% [63.2%-63.4%] and 66.6% [66.2%-66.9%] for the linear models and 51.5% [49.4%-53.4%], 63.2% [61.2%-65.0%] and 62.6% [60.7%-64.5%] for the deep learning SNP, clinical and combined models, respectively. For atrial fibrillation, the ROC-AUCs were 60.3% [60.0%-60.4%], 78.7% [78.7%-78.7%] and 80.0% [79.9%-80.0%] for the linear models and 59.4% [58.2%-60.9%], 78.8% [77.8%-79.8%] and 79.8% [78.8%-80.9%] for the deep learning SNP, clinical and combined models, respectively. For pneumonia, the ROC-AUCs were 50.1% [49.6%-50.6%], 69.2% [69.1%-69.2%] and 68.4% [68.0%-68.5%] for the linear models and 51.0% [49.7%-52.4%], 69.7% [.5%-70.8%] and 69.7% [68.6%-70.8%] for the deep learning SNP, clinical and combined models, respectively. CONCLUSION: In this report we presented linear and deep learning predictive models for surgery relevant outcomes. Overall, predictability was similar between linear and deep learning models and inclusion of genetics seemed to improve accuracy.

Have a vital end-user been overlooked? Developing a shared decision intervention for patients with potential pancreatic cancer regarding the choice of surgery.

Objective: To develop a patient decision aid facilitating shared decision making for patients with potential pancreatic cancer deciding about no treatment, surgical or medical treatment. Methods: Based on a user-centred design by Wittemann et al., we developed a shared decision making intervention in three phases: 1) Understanding decision needs 2) Development of a patient decision aid (PtDA) based on a generic template 3) Assessment of the intervention from interviews with patients (n = 11), relatives (n = 11), nurses (n = 4) and surgeons (n = 2) analysed with thematic analysis, and measuring patients' perceptions of choice of options with the Decisional Conflict Scale. Results: Results showed varying experiences with the use of the PtDA, with surgeons not finding PtDA useful as it was impractical and constraining with patients' conversations. There was no difference in patients' perceptions in choosing options for those being presented vs those patients not being presented for the PtDA. Conclusion: The format and structure of the PtDA was not feasible for the surgeons as fundamental users in the present clinic. Innovation: This study highlights the urgent need to consider clinical context before introducing a predefined tool and shows the importance of a multistakeholder approach. Research should focus on finding means to successful implement shared decision making.

Genetic risk factors for postoperative atrial fibrillation-a nationwide genome-wide association study (GWAS).

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 × 10-8. Results: After quality control, 144,196 surgical patients with 254,068 SNPs were left for analysis. Two variants (rs17042171 (p = 4.86 × 10-15) and rs17042081 (p = 7.12 × 10-15)) near the PITX2-gene reached statistical significance. These variants were replicated in the non-surgical cohort (1.39 × 10-101 and 1.27 × 10-93, respectively). Several other loci were significantly associated with AF in the non-surgical cohort. 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.

Assessing the utility of a sliding-windows deep neural network approach for risk prediction of trauma patients.

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.

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

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.

Association of Trauma With Long-Term Risk of Death and Immune-Mediated or Cancer Disease in Same-Sex Twins.

Importance: Immediate consequences of trauma include a rapid and immense activation of the immune system, whereas long-term outcomes include premature death, physical disability, and reduced workability. Objective: To investigate if moderate to severe trauma is associated with long-term increased risk of death or immune-mediated or cancer disease. Design, Setting, and Participants: This registry-based, matched, co-twin control cohort study linked the Danish Twin Registry and the Danish National Patient Registry to identify twin pairs in which 1 twin had been exposed to severe trauma and the other twin had not from 1994 to 2018. The co-twin control design allowed for matching on genetic and environmental factors shared within twin pairs. Exposure: Twin pairs were included if 1 twin had been exposed to moderate to severe trauma and the other twin had not (ie, co-twin). Only twin pairs where both twins were alive 6 months after the trauma event were included. Main Outcome and Measure: Twin pairs were followed up from 6 months after trauma until 1 twin experienced the primary composite outcome of death or 1 of 24 predefined immune-mediated or cancer diseases or end of follow-up. Cox proportional hazards regression was used for intrapair analyses of the association between trauma and the primary outcome. Results: A total of 3776 twin pairs were included, and 2290 (61%) were disease free prior to outcome analysis and were eligible for the analysis of the primary outcome. The median (IQR) age was 36.4 (25.7-50.2) years. The median (IQR) follow-up time was 8.6 (3.8-14.5) years. Overall, 1268 twin pairs (55%) reached the primary outcome; the twin exposed to trauma was first to experience the outcome in 724 pairs (32%), whereas the co-twin was first in 544 pairs (24%). The hazard ratio for reaching the composite outcome was 1.33 (95% CI, 1.19-1.49) for twins exposed to trauma. Analyses of death or immune-mediated or cancer disease as separate outcomes provided hazard ratios of 1.91 (95% CI, 1.68-2.18) and 1.28 (95% CI, 1.14-1.44), respectively. Conclusion and Relevance: In this study, twins exposed to moderate to severe trauma had significantly increased risk of death or immune-mediated or cancer disease several years after trauma compared with their co-twins.

Assessing optimal methods for transferring machine learning models to low-volume and imbalanced clinical datasets: experiences from predicting outcomes of Danish trauma patients.

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.