scholarly journals Predictive determinants of overall survival among re-infected COVID-19 patients using the elastic-net regularized Cox proportional hazards model: a machine-learning algorithm

2021 ◽  
Author(s):  
Vahid Ebrahimi ◽  
Mehrdad Sharifi ◽  
Razieh Sadat Mousavi-Roknabadi ◽  
Robab Sadegh ◽  
Mohammad Hossein Khademian ◽  
...  
Keyword(s):  
Machine Learning ◽  
Overall Survival ◽  
Mortality Rate ◽  
Serum Creatinine ◽  
Hospital Mortality ◽  
Proportional Hazards ◽  
Cox Proportional Hazards ◽  
Elastic Net ◽  
Hospital Death ◽  
Wbc Count

Abstract Background: Narrowing a large set of features to a smaller one can improve our understanding of the main risk factors for in-hospital mortality in patients with COVID-19. This study aimed to derive a parsimonious model for predicting overall survival (OS) among re-infected COVID-19 patients using machine-learning (ML) algorithms.Methods: The retrospective data of 283 re-infected COVID-19 patients admitted to twenty-six medical centers (affiliated with Shiraz University of Medical Sciences) from 10 June to 26 December 2020 were reviewed and analyzed. An elastic-net regularized Cox proportional hazards (PH) regression and model approximation via backward elimination were utilized to optimize a predictive model of time to in-hospital death. Then, the model was reduced to its core features to maximize simplicity and generalizability.Results: The empirical in-hospital mortality rate among the re-infected COVID-19 patients was obtained as 9.5%. In addition, the mortality rate among the intubated patients was 83.5%. Using the Kaplan-Meier approach, the OS (95% CI) rates for days 7, 14, and 21 were 87.5% (81.6-91.6%), 78.3% (65.0-87.0%), and 52.2% (20.3-76.7%), respectively. The elastic-net Cox PH regression retained 8 out of 35 candidate features of death. Transfer by Emergency Medical Services (EMS) (HR=3.90, 95% CI: 1.63-9.48), SpO2≤85% (HR=8.10, 95% CI: 2.97-22.00), increased serum creatinine (HR=1.85, 95% CI: 1.48-2.30), and increased white blood cells (WBC) count (HR=1.10, 95% CI: 1.03-1.15) were associated with higher in-hospital mortality rates in the re-infected COVID-19 patients.Conclusion: The results of the ML analysis demonstrated that transfer by EMS, profound hypoxemia (SpO2≤85%), increased serum creatinine (more than 1.6 mg/dL), and increased WBC count (more than 8.5 (×109 cells/L)) reduced the OS of the re-infected COVID-19 patients.

scholarly journals Predictive determinants of overall survival among re-infected COVID-19 patients using the elastic-net regularized Cox proportional hazards model: a machine-learning algorithm

2022 ◽  
Vol 22 (1) ◽  
Author(s):  
Vahid Ebrahimi ◽  
Mehrdad Sharifi ◽  
Razieh Sadat Mousavi-Roknabadi ◽  
Robab Sadegh ◽  
Mohammad Hossein Khademian ◽  
...  
Keyword(s):  
Machine Learning ◽  
Overall Survival ◽  
Mortality Rate ◽  
Serum Creatinine ◽  
Hospital Mortality ◽  
Proportional Hazards ◽  
Cox Proportional Hazards ◽  
Elastic Net ◽  
Hospital Death ◽  
Wbc Count

Abstract Background Narrowing a large set of features to a smaller one can improve our understanding of the main risk factors for in-hospital mortality in patients with COVID-19. This study aimed to derive a parsimonious model for predicting overall survival (OS) among re-infected COVID-19 patients using machine-learning algorithms. Methods The retrospective data of 283 re-infected COVID-19 patients admitted to twenty-six medical centers (affiliated with Shiraz University of Medical Sciences) from 10 June to 26 December 2020 were reviewed and analyzed. An elastic-net regularized Cox proportional hazards (PH) regression and model approximation via backward elimination were utilized to optimize a predictive model of time to in-hospital death. The model was further reduced to its core features to maximize simplicity and generalizability. Results The empirical in-hospital mortality rate among the re-infected COVID-19 patients was 9.5%. In addition, the mortality rate among the intubated patients was 83.5%. Using the Kaplan-Meier approach, the OS (95% CI) rates for days 7, 14, and 21 were 87.5% (81.6-91.6%), 78.3% (65.0-87.0%), and 52.2% (20.3-76.7%), respectively. The elastic-net Cox PH regression retained 8 out of 35 candidate features of death. Transfer by Emergency Medical Services (EMS) (HR=3.90, 95% CI: 1.63-9.48), SpO2≤85% (HR=8.10, 95% CI: 2.97-22.00), increased serum creatinine (HR=1.85, 95% CI: 1.48-2.30), and increased white blood cells (WBC) count (HR=1.10, 95% CI: 1.03-1.15) were associated with higher in-hospital mortality rates in the re-infected COVID-19 patients. Conclusion The results of the machine-learning analysis demonstrated that transfer by EMS, profound hypoxemia (SpO2≤85%), increased serum creatinine (more than 1.6 mg/dL), and increased WBC count (more than 8.5 (×109 cells/L)) reduced the OS of the re-infected COVID-19 patients. We recommend that future machine-learning studies should further investigate these relationships and the associated factors in these patients for a better prediction of OS.

scholarly journals Sodium Fluctuations and Mortality in a General Hospitalized Population

2019 ◽  
Vol 44 (4) ◽  
pp. 604-614 ◽  
Author(s):  
Gianmarco Lombardi ◽  
Pietro Manuel Ferraro ◽  
Luca Calvaruso ◽  
Alessandro Naticchia ◽  
Silvia D’Alonzo ◽  
...  
Keyword(s):  
Hospital Mortality ◽  
Hospital Admission ◽  
Hospital Stay ◽  
Proportional Hazards ◽  
Medical Center ◽  
Cerebrovascular Diseases ◽  
Linear Increase ◽  
Cox Proportional Hazards ◽  
Hospital Death ◽  
Cox Proportional Hazards Models

Background/Aims: Aim of our study was to describe the association between natremia (Na) fluctuation and hospital mortality in a general population admitted to a tertiary medical center. Methods: We performed a retrospective observational cohort study on the patient population admitted to the Fondazione Policlinico A. Gemelli IRCCS Hospital between January 2010 and December 2014 with inclusion of adult patients with at least 2 Na values available and with a normonatremic condition at hospital admission. Patients were categorized according to all Na values recorded during hospital stay in the following groups: normonatremia, hyponatremia, hypernatremia, and mixed dysnatremia. The difference between the highest or the lowest Na value reached during hospital stay and the Na value read at hospital admission was used to identify the maximum Na fluctuation. Cox proportional hazards models were used to estimate hazard ratios (HRs) for in-hospital death in the groups with dysnatremias and across quartiles of Na fluctuation. Covariates assessed were age, sex, highest and lowest Na level, Charlson/Deyo score, cardiovascular diseases, cerebrovascular diseases, dementia, congestive heart failure, severe kidney disease, estimated glomerular filtration rate, and number of Na measurements during hospital stay. Results: 46,634 admissions matched inclusion criteria. Incident dysnatremia was independently associated with in-hospital mortality (hyponatremia: HR 3.11, 95% CI 2.53, 3.84, p < 0.001; hypernatremia: HR 5.12, 95% CI 3.94, 6.65, p < 0.001; mixed-dysnatremia: HR 4.94, 95% CI 3.08, 7.92, p < 0.001). We found a higher risk of in-hospital death by linear increase of quartile of Na fluctuation (p trend <0.001) irrespective of severity of dysnatremia (HR 2.34, 95% CI 1.55, 3.54, p < 0.001, for the highest quartile of Na fluctuation compared with the lowest). Conclusions: Incident dysnatremia is associated with higher hospital mortality. Fluctuation of Na during hospital stay is a prognostic marker for hospital death independent of dysnatremia severity.

scholarly journals Using Elastic Net Penalized Cox Proportional Hazards Regression to Identify Predictors of Imminent Smoking Lapse

2017 ◽  
Vol 21 (2) ◽  
pp. 173-179 ◽  
Author(s):  
Robert Suchting ◽  
Emily T Hébert ◽  
Ping Ma ◽  
Darla E Kendzor ◽  
Michael S Businelle
Keyword(s):  
Machine Learning ◽  
Proportional Hazards ◽  
Learning Algorithms ◽  
Cox Proportional Hazards ◽  
Elastic Net ◽  
Machine Learning Algorithms ◽  
Cox Proportional Hazards Regression ◽  
Backward Elimination ◽  
Proportional Hazards Regression ◽  
Smoking Lapse

Abstract Introduction Machine learning algorithms such as elastic net regression and backward selection provide a unique and powerful approach to model building given a set of psychosocial predictors of smoking lapse measured repeatedly via ecological momentary assessment (EMA). Understanding these predictors may aid in developing interventions for smoking lapse prevention. Methods In a randomized-controlled smoking cessation trial, smartphone-based EMAs were collected from 92 participants following a scheduled quit date. This secondary analysis utilized elastic net-penalized cox proportional hazards regression and model approximation via backward elimination to (1) optimize a predictive model of time to first lapse and (2) simplify that model to its core constituent predictors to maximize parsimony and generalizability. Results Elastic net proportional hazards regression selected 17 of 26 possible predictors from 2065 EMAs to model time to first lapse. The predictors with the highest magnitude regression coefficients were having consumed alcohol in the past hour, being around and interacting with a smoker, and having cigarettes easily available. This model was reduced using backward elimination, retaining five predictors and approximating to 93.9% of model fit. The retained predictors included those mentioned above as well as feeling irritable and being in areas where smoking is either discouraged or allowed (as opposed to not permitted). Conclusions The strongest predictors of smoking lapse were environmental in nature (e.g., being in smoking-permitted areas) as opposed to internal factors such as psychological affect. Interventions may be improved by a renewed focus of interventions on these predictors. Implications The present study demonstrated the utility of machine learning algorithms to optimize the prediction of time to smoking lapse using EMA data. The two models generated by the present analysis found that environmental factors were most strongly related to smoking lapse. The results support the use of machine learning algorithms to investigate intensive longitudinal data, and provide a foundation for the development of highly tailored, just-in-time interventions that can target on multiple antecedents of smoking lapse.

scholarly journals Serum sodium on admission affects postoperative in-hospital mortality in acute aortic dissection patients

PLoS ONE ◽  
2021 ◽  
Vol 16 (12) ◽  
pp. e0261168
Author(s):  
Pengfei Huang ◽  
Hongyan Wang ◽  
Dong Ma ◽  
Yongbo Zhao ◽  
Xiao Liu ◽  
...  
Keyword(s):  
Aortic Dissection ◽  
Hospital Mortality ◽  
Serum Sodium ◽  
Proportional Hazards ◽  
Acute Aortic Dissection ◽  
Proportional Hazards Model ◽  
Cox Proportional Hazards ◽  
Cox Proportional Hazards Model ◽  
Hospital Death ◽  
Hazards Model

Background Acute aortic dissection (AAD) is very fatal without surgical treatment. Higher serum sodium can increase in-hospital mortality of many diseases; however, the effect of serum sodium on postoperative in-hospital mortality in AAD patients remains unknown. Methods We collected a total of 415 AAD patients from January 2015 to December 2019. Patients were classified into four categories (Q1-Q4) according to the admission serum sodium quartile. The cox proportional hazards model evaluated the association between serum sodium and in-hospital mortality. All-cause in-hospital mortality was set as the endpoint. Results By adjusting many covariates, cox proportional hazards model revealed the in-hospital mortality risk of both Q3 and Q4 groups was 3.086 (1.242–7.671, P = 0.015) and 3.370 (1.384–8.204, P = 0.007) respectively, whereas the risk of Q2 group was not significantly increased. Univariate and multiple Cox analysis revealed that Stanford type A, serum glucose, α-hydroxybutyrate dehydrogenase and serum sodium were risk factors correlated with in-hospital death in AAD patients. Conclusion The study indicates that the admission serum sodium of AAD patients has a vital impact on postoperative hospital mortality.

scholarly journals Outcome following postneurosurgical Acinetobacter meningitis: an institutional experience of 72 cases

2019 ◽  
Vol 47 (2) ◽  
pp. E8 ◽  
Author(s):  
Ravi Sharma ◽  
Revanth Goda ◽  
Sachin Anil Borkar ◽  
Varidh Katiyar ◽  
Samagra Agarwal ◽  
...  
Keyword(s):  
Risk Factors ◽  
Hospital Mortality ◽  
Proportional Hazards ◽  
External Ventricular Drain ◽  
Univariate Analysis ◽  
Significant Risk ◽  
Case Series ◽  
Cox Proportional Hazards ◽  
Wbc Count ◽  
Gcs Score

OBJECTIVEThe authors aimed to evaluate the antimicrobial susceptibility pattern of Acinetobacter isolates responsible for nosocomial meningitis/ventriculitis in the neurosurgical ICU. The authors also sought to identify the risk factors for mortality following Acinetobacter meningitis/ventriculitis.METHODSThis was a retrospective study of 72 patients admitted to the neurosurgical ICU between January 2014 and December 2018 with clinical and microbiological diagnosis of nosocomial postneurosurgical Acinetobacter baumanii meningitis/ventriculitis. Electronic medical data on clinical characteristics, underlying pathology, CSF cytology, antibiotic susceptibilities, and mortality were recorded. To evaluate the outcome following nosocomial postneurosurgical Acinetobacter meningitis/ventriculitis, patients were followed up until discharge or death in the hospital. Kaplan-Meier survival analysis and multivariable Cox proportional hazards models were used to compute factors affecting survival.RESULTSThe study population was divided into two groups depending on the final outcome of whether the patient died or survived. Forty-three patients (59.7%) were included in the survivor group and 29 patients (40.3%) were included in the nonsurvivor group. Total in-hospital mortality due to Acinetobacter meningitis/ventriculitis was 40.3% (29 cases), with a 14-day mortality of 15.3% and a 30-day mortality of 25%. The 43 (59.7%) patients who survived had a mean length of hospital stay of 44 ± 4 days with a median Glasgow Outcome Scale–Extended score at discharge of 6. On univariate analysis, age > 40 years (p = 0.078), admission Glasgow Coma Scale (GCS) score ≤ 8 (p = 0.003), presence of septic shock (p = 0.011), presence of external ventricular drain (EVD) (p = 0.03), CSF white blood cell (WBC) count > 200 cells/mm3 (p = 0.084), and comorbidities (diabetes, p = 0.036; hypertension, p = 0.01) were associated with poor outcome. Carbapenem resistance was not a risk factor for mortality. According to a multivariable Cox proportional hazards model, age cutoff of 40 years (p = 0.016, HR 3.21), GCS score cutoff of 8 (p = 0.006, HR 0.29), CSF WBC count > 200 cells/mm3 (p = 0.01, HR 2.76), presence of EVD (p = 0.001, HR 5.42), and comorbidities (p = 0.017, HR 2.8) were found to be significant risk factors for mortality.CONCLUSIONSThis study is the largest case series reported to date of postneurosurgical Acinetobacter meningitis/ventriculitis. In-hospital mortality due to Acinetobacter meningitis/ventriculitis was high. Age older than 40 years, GCS score less than 8, presence of EVD, raised CSF WBC count, and presence of comorbidities were risk factors for mortality.

scholarly journals Survival rates and prognostic factors in right- and left-sided colon cancer stage I–IV: an unselected retrospective single-center trial

2021 ◽  
Author(s):  
Claudius E. Degro ◽  
Richard Strozynski ◽  
Florian N. Loch ◽  
Christian Schineis ◽  
Fiona Speichinger ◽  
...  
Keyword(s):  
Colon Cancer ◽  
Overall Survival ◽  
Blood Level ◽  
Proportional Hazards ◽  
Survival Rates ◽  
Cox Proportional Hazards ◽  
Stage I ◽  
Cancer Stage ◽  
Single Center ◽  
Significant Difference

Abstract Purpose Colorectal cancer revealed over the last decades a remarkable shift with an increasing proportion of a right- compared to a left-sided tumor location. In the current study, we aimed to disclose clinicopathological differences between right- and left-sided colon cancer (rCC and lCC) with respect to mortality and outcome predictors. Methods In total, 417 patients with colon cancer stage I–IV were analyzed in the present retrospective single-center study. Survival rates were assessed using the Kaplan–Meier method and uni/multivariate analyses were performed with a Cox proportional hazards regression model. Results Our study showed no significant difference of the overall survival between rCC and lCC stage I–IV (p = 0.354). Multivariate analysis revealed in the rCC cohort the worst outcome for ASA (American Society of Anesthesiologists) score IV patients (hazard ratio [HR]: 16.0; CI 95%: 2.1–123.5), CEA (carcinoembryonic antigen) blood level > 100 µg/l (HR: 3.3; CI 95%: 1.2–9.0), increased lymph node ratio of 0.6–1.0 (HR: 5.3; CI 95%: 1.7–16.1), and grade 4 tumors (G4) (HR: 120.6; CI 95%: 6.7–2179.6) whereas in the lCC population, ASA score IV (HR: 8.9; CI 95%: 0.9–91.9), CEA blood level 20.1–100 µg/l (HR: 5.4; CI 95%: 2.4–12.4), conversion to laparotomy (HR: 14.1; CI 95%: 4.0–49.0), and severe surgical complications (Clavien-Dindo III–IV) (HR: 2.9; CI 95%: 1.5–5.5) were identified as predictors of a diminished overall survival. Conclusion Laterality disclosed no significant effect on the overall prognosis of colon cancer patients. However, group differences and distinct survival predictors could be identified in rCC and lCC patients.

scholarly journals Quantitative assessment of erector spinae muscles and prognosis in elderly patients with pneumonia

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Hiroki Yoshikawa ◽  
Kosaku Komiya ◽  
Takashi Yamamoto ◽  
Naoko Fujita ◽  
Hiroaki Oka ◽  
...  
Keyword(s):  
Elderly Patients ◽  
Hospital Mortality ◽  
Regression Models ◽  
Proportional Hazards ◽  
Community Acquired Pneumonia ◽  
Cox Proportional Hazards ◽  
Erector Spinae ◽  
Cross Sectional ◽  
Proportional Hazards Regression ◽  
Survivor Group

AbstractErector spinae muscle (ESM) size has been reported as a predictor of prognosis in patients with some respiratory diseases. This study aimed to assess the association of ESM size on all-cause in-hospital mortality among elderly patients with pneumonia. We retrospectively included patients (age: ≥ 65 years) admitted to hospital from January 2015 to December 2017 for community-acquired pneumonia who underwent chest computed tomography (CT) on admission. The cross-sectional area of the ESM (ESMcsa) was measured on a single-slice CT image at the end of the 12th thoracic vertebra and adjusted by body surface area (BSA). Cox proportional hazards regression models were used to assess the influence of ESMcsa/BSA on in-hospital mortality. Among 736 patients who were admitted for pneumonia, 702 patients (95%) underwent chest CT. Of those, 689 patients (98%) for whom height and weight were measured to calculate BSA were included in this study. Patients in the non-survivor group were significantly older, had a greater frequency of respiratory failure, loss of consciousness, lower body mass index, hemoglobin, albumin, and ESMcsa/BSA. Multivariate analysis showed that a lower ESMcsa/BSA independently predicted in-hospital mortality after adjusting for these variables. In elderly patients with pneumonia, quantification of ESMcsa/BSA may be associated with in-hospital mortality.

Longer duration of symptoms at the time of presentation is not associated with worse survival in primary bone sarcoma

2018 ◽  
Vol 100-B (5) ◽  
pp. 652-661 ◽  
Author(s):  
J. M. Lawrenz ◽  
J. F. Styron ◽  
M. Parry ◽  
R. J. Grimer ◽  
N. W. Mesko
Keyword(s):  
Overall Survival ◽  
Proportional Hazards ◽  
Bone Sarcoma ◽  
Axial Skeleton ◽  
Cox Proportional Hazards ◽  
Low Grade ◽  
Duration Of Symptoms ◽  
Negative Effect ◽  
Primary Bone Sarcoma ◽  
Primary Bone

Aims The primary aim of this study was to determine the effect of the duration of symptoms (DOS) prior to diagnosis on the overall survival in patients with a primary bone sarcoma. Patients and Methods In a retrospective analysis of a sarcoma database at a single institution between 1990 and 2014, we identified 1446 patients with non-metastatic and 346 with metastatic bone sarcoma. Low-grade types of tumour were excluded. Our data included the demographics of the patients, the characteristics of the tumour, and the survival outcome of patients. Cox proportional hazards analysis and Kaplan–Meier survival analysis were performed, and the survivorship of the non-metastatic and metastatic cohorts were compared. Results In the non-metastatic cohort, a longer DOS was associated with a slightly more favourable survival (hazard ratio (HR) 0.996, 95% confidence interval (CI) 0.994 to 0.998, p < 0.001). In all types of tumour, there was no difference in survival between patients with a DOS of greater than four months and those with a DOS of less than four months (p = 0.566). There was no correlation between the year of diagnosis and survival (p = 0.741). A diagnosis of chondrosarcoma (HR 0.636, 95% CI 0.474 to 0.854, p = 0.003) had the strongest positive effect on survival, while location in the axial skeleton (HR 1.76, 95% CI 1.36 to 2.29, p < 0.001) had the strongest negative effect on survival. Larger size of tumour (HR 1.05, 95% CI 1.03 to 1.06, p < 0.001) and increased age of the patient (HR 1.02, 95% CI 1.01 to 1.03, p < 0.001) had a slightly negative effect on survival. Metastatic and non-metastatic cohorts had similar median DOS (16 weeks, p = 0.277), although the median survival (15.5 months vs 41 months) and rates of survival at one year (69% vs 89%) and five years (20% vs 59%) were significantly shorter in the metastatic cohort. Conclusion A longer DOS prior to diagnosis is not associated with a poorer overall survival in patients with a primary bone sarcoma. Location in the axial skeleton remains the strongest predictor of a worse prognosis. This may be helpful in counselling patients referred for evaluation on a delayed basis. Cite this article: Bone Joint J 2018;100-B:652–61.

scholarly journals Eps15 Homology Domain-Containing Protein 3 Hypermethylation as a Prognostic and Predictive Marker for Colorectal Cancer

Biomedicines ◽  
2021 ◽  
Vol 9 (5) ◽  
pp. 453
Author(s):  
Yu-Han Wang ◽  
Shih-Ching Chang ◽  
Muhamad Ansar ◽  
Chin-Sheng Hung ◽  
Ruo-Kai Lin
Keyword(s):  
Colorectal Cancer ◽  
Overall Survival ◽  
Mrna Expression ◽  
Proportional Hazards ◽  
Uterine Cancer ◽  
Colonic Polyps ◽  
Predictive Marker ◽  
Cox Proportional Hazards ◽  
The Cancer Genome Atlas ◽  
Eps15 Homology Domain

Colorectal cancer (CRC) arises from chromosomal instability, resulting from aberrant hypermethylation in tumor suppressor genes. This study identified hypermethylated genes in CRC and investigated how they affect clinical outcomes. Methylation levels of specific genes were analyzed from The Cancer Genome Atlas dataset and 20 breast cancer, 16 esophageal cancer, 33 lung cancer, 15 uterine cancer, 504 CRC, and 9 colon polyp tissues and 102 CRC plasma samples from a Taiwanese cohort. In the Asian cohort, Eps15 homology domain-containing protein 3 (EHD3) had twofold higher methylation in 44.4% of patients with colonic polyps, 37.3% of plasma from CRC patients, and 72.6% of CRC tissues, which was connected to vascular invasion and high microsatellite instability. Furthermore, EHD3 hypermethylation was detected in other gastrointestinal cancers. In the Asian CRC cohort, low EHD3 mRNA expression was found in 45.1% of patients and was connected to lymph node metastasis. Multivariate Cox proportional-hazards survival analysis revealed that hypermethylation in women and low mRNA expression were associated with overall survival. In the Western CRC cohort, EHD3 hypermethylation was also connected to overall survival and lower chemotherapy and antimetabolite response rates. In conclusion, EHD3 hypermethylation contributes to the development of CRC in both Asian and Western populations.

Abstract 3248: Is It Safe to Train Residents to Perform Cardiac Surgery? Intermediate Term Follow-up

Circulation ◽  
2007 ◽  
Vol 116 (suppl_16) ◽  
Author(s):  
Billie Jean Martin ◽  
Dimitri Kalavrouziotis ◽  
Roger Baskett
Keyword(s):  
Cardiac Surgery ◽  
Hospital Mortality ◽  
Proportional Hazards ◽  
Artery Bypass ◽  
Cox Proportional Hazards ◽  
Adverse Outcomes ◽  
Short Term ◽  
Term Outcome ◽  
Teaching Case ◽  
Teaching Cases

Introduction While there are rigourous assessments made of trainees’ knowledge through formal examinations, objective assessments of technical skills are not available. Little is known about the safety of allowing resident trainees to perform cardiac surgical operations. Methods Peri-operative date was prospectively collected on all patients who underwent coronary artery bypass grafting (CABG), aortic valve replacement (AVR) or a combined procedure between 1998 and 2005. Teaching-cases were identified by resident records and defined as cases which the resident performed skin to skin. Pre-operative characteristics were compared between teaching and non-teaching cases. Short-term adverse events were defined as a composite of: in-hospital mortality, stroke, intra- or post-operative intra-aortic balloon pump (IABP) insertion, myocardial infarction, renal failure, wound infection, sepsis or return to the operating room. Intermediate adverse outcomes were defined as hospital readmission for any cardiac disease or late mortality. Logistic regression and Cox proportional hazard models were used to adjust for differences in age, acuity, and medical co-morbidities. Outcomes were compared between teaching and non-teaching cases. Results 6929 cases were included, 895 of which were identified as teaching-cases. Teaching-cases were more likely to have an EF<40%, pre-operative IABP, CHF, combined CABG/AVRs or total arterial grafting cases (all p<0.01). However, a case being a teaching-case was not a predictor of in-hospital mortality (OR=1.02, 95%CI 0.67–1.55) or the composite short-term outcome (OR=0.97, 95%CI 0.75–1.24). The Kaplan-Meier event-free survival of staff and teaching-cases was equivalent at 1, 3, and 5 years: 80% vs. 78%, 67% vs. 66%, and 58% vs. 55% (log-rank p=0.06). Cox proportional hazards regression modeling did not demonstrate teaching-case to be a predictor of late death or re-hospitalization (HR=1.05, 95%CI 0.94 –1.18). Conclusions Teaching-cases were more likely to have greater acuity and complexity than non-teaching cases. Despite this, teaching cases did no worse than staff cases in the short or intermediate term. Allowing residents to perform cardiac surgery does not appear to adversely affect patient outcomes.

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