Pulmonary complications and mortality among COVID-19 patients undergoing a surgery: a multicenter cohort study

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Couture, and 8 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3959683/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Managing COVID-19-positive patients requiring surgery is complex due to perceived heightened perioperative risks. However, Canadian data in this context remains scarce. To address this gap, we conducted a multicenter cohort study in the province of Québec, the Canadian province most affected during the initial waves of the pandemic, to comprehensively assess the impact of COVID-19 symptoms, and recovery time, on postoperative outcomes in surgical patients. Methods We included adult surgical patients with either active COVID-19 at time of surgery or those who had recovered from the disease, from March 13, 2020, to April 30, 2021. We evaluated the association between symptoms or recovery time and postoperative pulmonary complications and hospital mortality using multivariable logistic regression and Cox models. Results We included 105 patients with an active infection (47 were symptomatic and 58 were asymptomatic) and 206 who had healed from COVID-19 in seven hospitals. Among patients with an active infection, those who were symptomatic had a higher risk of pulmonary complications (odds ratio = 3.19; 95% CI, from 1.12 to 9.68; p = 0.03) and hospital mortality (hazard ratio = 3.67; 95% CI, from 1.19 to 11.32; p = 0.02). We did not observe any significant effect of the duration of recovery prior to surgery on patients who had healed from their infection. Their postoperative outcomes were also similar to those observed in asymptomatic patients. Interpretation Symptomatic status should be considered in the decision to proceed with surgery in COVID-19-positive patients. Our results may help optimize surgical care in this patient population. Trial registration: ClinicalTrials.gov Identifier: NCT04458337, Registration Date: July 7, 2020. Background The COVID-19 pandemic has ushered in unparalleled challenges for healthcare systems globally, not least in the realm of surgical care for patients afflicted with the virus. An urgent concern in this context is the heightened risk of perioperative complications and potential virus transmission to healthcare workers and other patients [ 1 , 2 ]. During the earlier stages of the pandemic, the absence of comprehensive knowledge both in mainstream and scientific circles further compounded these difficulties. Recently, there has been a gradual evolution in the scientific literature, focusing on the complex relationship between COVID-19 and postoperative complications [ 3 ]. Initial data from Europe and the Middle East hinted at alarming postoperative 30-day mortality rates of 19–24%, and more than half of the patients experiencing postoperative pulmonary complications [ 4 – 7 ]. A key aspect in this emerging field has been the distinction between symptomatic and asymptomatic carriers of the virus [ 8 ]. Symptomatic patients, characterized by potential pulmonary involvement, significant systemic inflammation, and higher viral loads, have been shown to incur a greater risk of perioperative complications [ 9 ]. In contrast, the perceived lower risks associated with surgery in asymptomatic carriers contribute to the multifaceted challenges in perioperative management [ 10 ]. Emphasizing the need for detailed investigation into these complexities, research efforts must focus on the comprehensive documentation of surgical needs and an array of procedures, and their related outcomes among COVID-19 positive patients. Such studies have provided valuable insights into the effects of an active infection on surgical outcomes and the varying risk factors among symptomatic and asymptomatic patients [ 2 – 4 ]. Despite burgeoning global research, Canadian data has remained conspicuously sparse. To contend with this, we launched an observational cohort study in Québec, one of the most severely affected Canadian province during the pandemic [ 11 , 12 ]. Our primary objective was to investigate the association between the presence of COVID-19-related symptoms among patients with COVID-19 infection at time of surgery and postoperative pulmonary complications and mortality. Our second objective was to describe the postoperative outcomes of patients who underwent a surgical procedure after recovering from COVID-19 based on the time elapsed between the first positive test and the surgery and to compare them with those of asymptomatic COVID-19 patients. Our hypothesis was that the presence of symptoms would be associated with an increased risk of pulmonary complications, while asymptomatic patients would have similar outcomes to patients who had recovered [ 13 ]. Methods Design and setting We conducted a multicenter observational cohort study at seven university hospitals situated in the Province of Québec from March 13, 2020, through April 30, 2021. During the study period, the prevalent strains of the virus were the initial strain, along with the Alpha, Beta and Gamma variants [ 14 ]. Prompted by the urgency engendered early in the pandemic, we had previously published preliminary data focusing on postoperative mortality from this study [ 15 ]. The current study, however, boasts a larger sample size and shifts its focus to postoperative pulmonary complications. Our findings are reported in accordance with the STROBE guidelines for transparent reporting of observational studies [ 16 ]. Approval from the Research Ethics Board was obtained at all participating sites. Research Ethics Boards waived the need for written informed consent. Study participants We included all adult patients undergoing surgery who tested positive for COVID-19 and those who had recovered from COVID-19. COVID-19 patients were diagnosed through a positive polymerase chain reaction (PCR) test, conducted either before surgery or within 72 hours after. This testing used either oro-nasopharyngeal swabs or endotracheal aspirates. Patients were identified through the electronic medical data system or the operating room database at each site. Patients who had recovered from COVID-19 were those who had a positive test at least 10 days prior to surgery and one of the following three scenarios: 1) the presence of two consecutive negative SARS-CoV-2 PCR tests following the last positive test and preceding the surgery; 2) the presence of a single negative test along with a clinically substantial period without symptoms between the last positive test and the negative one; 3) no negative test available, but the patient was considered as having recovered based on the complete resolution of symptoms. This comprehensive definition was aligned with protocols applied in the hospital network of the province of Québec and became less restrictive in November 2020 (see table S1). Exposure variables To address our first objective, our exposure was the presence of symptoms at the time of the surgery based on patient-reported COVID-19 symptoms such as fever or respiratory failure, among others, as assessed by the attending clinicians (see table S2). For our secondary objective, our exposures were the time elapsed from the initial positive COVID-19 test to surgery in patients who had recovered and the infection status, categorized as either “recovered” and “active and asymptomatic”. Outcomes Our primary outcome was any postoperative pulmonary complication. We used a definition of postoperative pulmonary complications, informed by an established one, we believed better adapted to our population [ 17 ]. Our primary outcome included atelectasis, pneumonia, acute respiratory distress syndrome (ARDS) and pneumothorax. We substituted, from the original definition, the incidence of pulmonary aspiration for pneumothorax since we believed there might not be any causal relationship between active COVID and pulmonary aspiration, while the reported incidence of pneumothorax is high in this population [ 18 ] Our secondary outcome was hospital survival, assessed from the date of surgery up to hospital discharge. Our exploratory outcomes were the incidence of postoperative non-pulmonary infectious complications, acute kidney injury, thromboembolic events such as myocardial infarction and stroke, surgical reinterventions, need for new postoperative intensive care unit (ICU) admission, the length of hospital stay, any requirement for postoperative mechanical ventilation, and the number of organ dysfunction-free days within 30 days. Non-pulmonary infectious complications were defined as infections requiring antibiotics for more than 72 hours. Acute kidney injury was classified following the KDIGO-AKI criteria [ 19 ]. Myocardial infarction and stroke were based on physician reporting. Mechanical ventilation included both non-invasive and invasive modalities. For all 30-day outcomes, we considered each day on which the outcome occurred. Additionally, our 30-day organ dysfunction-free days adhered to established definitions [ 20 ]. Covariables We collected characteristics related to the COVID-19 presentation, including factors such as demographic variables, pre-existing comorbidities, surgical and anesthetic characteristics, the level of urgency for the surgery, baseline laboratory measurements, the preoperative Sequential Organ Failure Assessment (SOFA), the requirement for oxygen supplementation or invasive mechanical ventilation prior to surgery, and the administered treatments (e.g., antiviral medications, steroids, and antibiotics). Moreover, multiple intraoperative variables were documented. The characterization of surgical disease was based on surgeon's reporting and classified into distinct categories. Surgeries categorized as neurosurgical, cardiac, thoracic, major vascular, or non-vascular abdominal were defined as major surgeries. Minimally invasive surgery was characterized as those that avoided anatomical cavity opening (laparoscopy, thoracoscopy, endoluminal procedures). The urgency of surgery was classified into two categories: emergent or urgent surgeries that necessitated completion within 24 hours, and non-urgent surgeries that could be deferred beyond 24 hours. Data sources and management Research staff collected data prospectively up to hospital discharge or retrospectively as reported in the electronic medical records. We ascertained survival up to hospital discharge. Each site entered the data into a centralized electronic database (REDCap ™ electronic data capture tools hosted at the Centre hospitalier de l’Université de Montréal ), adhering to a manual of standardized operating procedures following necessary training [ 21 ]. Statistical analyses We sampled all eligible patients over the recruitment period. We used descriptive statistics (means (SD), medians (IQR) or proportions, as appropriate) to summarize baseline characteristics and the outcomes of COVID-19 patients, stratified based on the presence of symptoms, and for those who had recovered from COVID-19. For the primary objective, we fitted a multivariable mixed-effect logistic regression model to estimate the association between the prevalence of any symptom before the surgery and the incidence of postoperative pulmonary complications in COVID-19 patients who underwent surgery, adjusted for the following potential confounders: preoperative hospitalization, preoperative requirement for oxygen support, urgency of surgery and categorization of surgery as either “major” or “minor”. We also fitted a multivariable Cox proportional hazard model to estimate the association between presence of symptoms and time to in-hospital mortality among COVID-19 patients adjusted for the same potential confounders but stratified for preoperative requirement for oxygen. We used random effects and frailty factors to account for the clustered nature of the data within the same site. However, since the logistic mixed-effect model showed singularity with a null variance of the random effect, we reported estimates from a model without random effects. We conducted post hoc sensitivity analyses for each outcome by estimating the same models, first by excluding patients who had a tracheotomy as their index surgery or had preoperative respiratory failure, and then by excluding only those who had a tracheotomy as their surgery. Finally, we reported an unadjusted Kaplan-Meier survival curve with 95% confidence bands. For our secondary objective, we estimated the association between the recovery duration from COVID-19 to the surgery on the incidence of postoperative pulmonary complications and hospital survival. We also compared both outcomes between patients who recovered from COVID-19 to those with an active asymptomatic infection. We used mixed-effect logistic regression models and Cox proportional hazard models with a frailty factor adjusted for the same confounders. The statistical significance level was set at 0.05. For all analyses, we reported odds ratios (OR) and hazard ratios (HR) with 95% confidence intervals (CI). All analyses were performed using R statistical software (R Foundation for Statistical Computing, Vienna, Austria, version 4.2.3). Results Between March 13, 2020, and April 30, 2021, we included 105 COVID-19 patients who underwent a surgical procedure and 206 patients who had recovered from COVID-19 at the time of surgery for our secondary objective. Symptomatic versus asymptomatic COVID-19 patients Among patients with confirmed COVID-19 at time of surgery, 47 (45%) exhibited symptoms and 58 (55%) were asymptomatic carriers. The baseline characteristics of these patients are presented in Tables 1 , S2 & S3 . Both groups displayed similar baseline characteristics in terms of sex distribution, but symptomatic patients were older, had a higher body mass index (BMI), and a greater prevalence of diabetes (Table 1 ). The presence of pulmonary infiltrates, as determined by the radiologist’s chest X-ray report, was more common among symptomatic patients and these patients were more likely to receive steroids before surgery and require preoperative respiratory support (Table 1 ). Interestingly, both groups showed a balanced distribution in terms of major and minor surgeries, urgency, and duration of surgery (Table 1 ). Out of 47 patients who had symptoms at time of surgery, 13 (28%) had a tracheotomy as their surgery and 25 (53%) had either a tracheotomy as their surgery or preoperative respiratory failure (not in tables). Table 1 Characteristics of COVID-19 patients Symptomatic status at time of surgery Variable Asymptomatic (N = 58) Symptomatic (N = 47) Baseline characteristics Age (years) 57.5 [36.5–74.8] 66.0 [52.5–72.5] Sex (female) 30 (52%) 25 (53%) BMI 1 (kg/m 2 ) 27.4 ± 7.4 30.8 ± 6.0 Diabetes 14 (24%) 15 (32%) Hypertension 11 (19%) 6 (13%) White blood cell count 2 (*10 9 /L) 8.8 [6.9–13.0] 9.5 [6.6–12.5] Hemoglobin 2 (g/L) 117.0 [104.0–133.0] 101.0 [81.0–122.5] Creatinine 3 (µmol/L) 77.0 [56.3–96.0] 83.0 [56.0–131.5] COVID characteristics Days from first positive COVID test to surgery 4.0 [1.0–9.8] 10.0 [3.0–22.5] Pulmonary infiltrates 12 (21%) 28 (60%) Steroid 14 (24%) 20 (43%) Antibiotic 16 (28%) 33 (70%) Preoperative respiratory support No oxygen 45 (78%) 17 (36%) Oxygen only 4 (7%) 7 (15%) Non-invasive mechanical ventilation 0 (0%) 1 (2%) Invasive ventilation 9 (16%) 22 (47%) Surgical characteristics Preoperative location Home 15 (26%) 7 (15%) Emergency department 14 (24%) 7 (15%) Ward 23 (40%) 10 (21%) Intensive care unit 6 (10%) 23 (49%) Urgent surgery (≤ 24 hours) 24 (41%) 22 (47%) Major surgery 21 (36%) 17 (36%) Duration of surgery (minutes) 60.0 [40.3–97.3] 47.0 [27.5–98.5] Categorical variables are presented as frequency (proportion). Continuous variables are presented as mean ± standard deviation or as median [1st quartile − 3rd quartile]. 1 Missing value for 28 and 17 patients respectively 2 1 missing value in the asymptomatic group 3 3 missing values in the asymptomatic group The postoperative outcomes of COVID-19 patients are summarized in Table 2 . Thirty symptomatic patients (64%) experienced at least one postoperative complication compared to 19 asymptomatic patients (33%) (Table 2 ). Symptomatic patients had a higher incidence of pneumonia, ARDS, and pneumothorax and a higher requirement for postoperative ICU admission and persistent postoperative mechanical ventilation (Table 2 ). Mortality was higher among symptomatic patients, with 15 deaths (32%) during hospitalization in the symptomatic group compared to 6 deaths (10%) in the asymptomatic group (Table 2 ). Table 2 Postoperative outcomes of COVID-19 confirmed patients Symptomatic status at time of surgery Variable Asymptomatic (N = 58) Symptomatic (N = 47) Postoperative complications Any complication 19 (33%) 30 (64%) Any pulmonary complications 8 (14%) 16 (34%) Atelectasis 1 (2%) 4 (9%) Pneumonia 6 (10%) 11 (23%) ARDS 2 (3%) 4 (9%) Pneumothorax 1 (2%) 3 (6%) Acute kidney injury 6 (10%) 9 (19%) New postoperative renal replacement therapy 0 (0%) 1 (2%) Myocardial infarction 0 (0%) 2 (4%) Stroke 0 (0%) 1 (2%) Non-pulmonary infection 6 (10%) 6 (13%) Surgical reintervention 4 (7%) 10 (21%) Resource utilization and mortality Need for a new postoperative ICU admission 10 (17%) 20 (43%) Hospital length of stay (days) 8.0 [3.0–31] 13.0 [7.5–31.5] One or more days on postoperative mechanically ventilated 17 (29%) 26 (55%) 30-day organ dysfunction free days 27.7 ± 6.8 19.9 ± 11.9 Hospital mortality 6 (10%) 15 (32%) Status at hospital discharge among living patients Discharged at home 40 (69%) 25 (53%) Transferred to another acute care setting 7 (12%) 3 (6%) Transferred to another long-term care setting 5 (9%) 4 (9%) Categorical variables are presented as frequency (proportion). Continuous variables are presented as mean ± standard deviation or as median [1st quartile − 3rd quartile]. ARDS = acute respiratory distress syndrome Patients with COVID-19 symptoms were found to have a higher risk of developing pulmonary complications compared to asymptomatic patients (OR = 3.19, 95% CI, from 1.12 to 9.68, p = 0.03) (Table 3 ). These patients also faced significantly higher hazard of in-hospital mortality compared to asymptomatic patients (HR = 3.67, 95% CI, from 1.19 to 11.32, p = 0.02) (Table 4 ). From our sensitivity analyses, after excluding 13 symptomatic patients who underwent a tracheotomy, we observed a weaker and non-significant effect between the presence of symptoms and the incidence of postoperative pulmonary complications (OR = 2.89 (95% CI from 0.94 to 9.31) (Table S4). A similar pattern was noted when excluding 25 symptomatic patients who either had a tracheotomy or preoperative respiratory failure (OR = 2.45 (95% CI from 0.67 to 8.89), see Table S5). The presence of symptoms on hospital mortality also showed a weaker, non-significant association in these analyses (HR = 2.60 (95% CI from 0.75 to 8.99) and HR = 1.35 (95% CI from 0.32 to 5.76) respectively) (Tables S6 & S7). Table 3 Association between the presence of symptoms and the incidence of postoperative pulmonary complications in patients with COVID-19 at time of surgery Variable Odds Ratio (95% CI) P value Presence of symptoms 3.19 [1.12; 9.68] 0.03 Preoperative hospitalization 0.91 [0.26; 3.72] 0.89 Preoperative oxygen requirement 1.30 [0.45; 3.72] 0.62 Urgent surgery 0.45 [0.15; 1.21] 0.12 Major surgery 2.45 [0.91; 6.77] 0.08 CI = Confidence interval No random effect Table 4 Association between the presence of symptoms and hospital mortality in patients with COVID-19 at time of surgery Variable Hazard Ratio (95% CI) P value Presence of symptoms 3.67 (1.19; 11.32) 0.02 Preoperative hospitalization 1.46 (0.33; 6.48) 0.62 Urgent surgery 0.92 (0.34; 2.52) 0.88 Major surgery 3.42 (1.25; 9.34) 0.02 CI = Confidence interval This model is stratified for preoperative oxygen requirement and has center as a frailty effect. Number of events = 21 (N = 105). Patients who recovered from COVID-19 Tables S8, S9, and S10 provide the baseline characteristics and postoperative outcomes of patients (N = 206) who had recovered from COVID-19 at the time of surgery, categorized on the number of weeks elapsed since their initial positive COVID-19 test. The time elapsed since the initial positive COVID-19 test in these patients was not associated with a higher risk of pulmonary complications (OR = 1.00, 95% CI from 0.99 to 1.00, p-value = 0.47, see Table 5 ) or mortality (HR = 1.00, 95% CI from 0.99 to 1.01, p-value = 0.70) (Table S11). Patients who had recovered from COVID-19 did not have a higher risk of postoperative pulmonary complications or hospital mortality when compared to asymptomatic carriers (Tables S12 & S13). Table 5 Association between the elapsed time between first positive test and surgery and postoperative pulmonary complications in patients who had recovered from COVID-19 at time of surgery Variable Odds Ratio (95% CI) P value Time from first positive COVID test 1.00 [0.99, 1.00] 0.47 Preoperative hospitalization 3.87 [1.08, 13.82] 0.04 Preoperative oxygen need 2.69 [0.84, 8.61] 0.09 Urgent surgery 0.42 [0.14,1.24] 0.12 Major surgery 2.51 [0.95, 6.65] 0.06 CI: Confidence Interval This logistic regression model has center as a random effect. Intracluster correlation = 0.076 Discussion In this study, we included 105 surgical patients with active COVID-19 and 206 who had recovered from the virus. We observed an important difference between symptomatic and asymptomatic COVID-19 patients undergoing surgery regarding the risk of adverse postoperative outcomes. The presence of an active symptomatic disease was associated with an increased risk of developing postoperative pulmonary complications and an increased mortality. Within this cohort, symptomatic patients who underwent a tracheotomy and those with preoperative respiratory failure encompassed half of the sample. However, even when excluding these cases, point estimates suggested an association between symptoms and postoperative pulmonary complications. Patients who had recovered from the infection at time of surgery and asymptomatic carriers had a similar risk of adverse postoperative outcomes. Interestingly, the length of the recovery period prior to surgery did not appear to influence the incidence of postoperative pulmonary complications and mortality in those who had recovered from the infection. The current study enhances our understanding of surgical care in the COVID-19 era, with a particular focus on assessing the risk of postoperative pulmonary complications and in-hospital mortality associated with COVID-19 symptoms prior to surgery. It builds upon prior research conducted by our group, which was spurred by the urgency of the pandemic and, as result, reported preliminary data that focused primarily on postoperative mortality [ 15 ]. Other studies have suggested that preoperative COVID-19 is associated with an increased risk of postoperative pulmonary or cardiovascular complications, and mortality [ 22 – 25 ]. Interestingly, a more recent study has not observed the same association [ 26 ]. While the primary focus of these studies was not specifically on this aspect, it appears that the presence of symptoms at time of surgery may account for the observed effect of preoperative COVID-19 on postoperative outcomes. Our findings are consistent with these results. Symptomatic patients are possibly more likely to exhibit severe pulmonary involvement, systemic inflammation, and higher viral loads. These factors collectively contribute to an escalated risk of perioperative complications [ 22 , 23 ]. Moreover, the markedly higher hazard of in-hospital mortality among symptomatic patients emphasizes the significant impact that active disease can have on postoperative patient survival [ 5 , 15 , 22 , 27 – 30 ]. Our results underscore the necessity of considering the symptomatic status of patients when assessing their suitability for surgery and evaluating the risk of postoperative complications. Our study's analyses of patients who had fully recovered from COVID-19 prior to surgery offer additional insights into the dynamic relationship between infection and surgical outcomes. Contrary to previous research on COVID-19 positive patients, we did not observe any effect of the time elapsed from COVID-19 diagnosis to surgery on postoperative outcomes in patients who had recovered from COVID-19 [ 24 , 31 , 32 ]. Notably, in a recent study, an increased mortality risk was observed in patients who had recovered from COVID-19 undergoing surgery within two weeks of a positive test compared to longer recovery time [ 33 ]. Beyond this period, the mortality risk aligns closely between patients with and without prior COVID-19. Our research diverges as it does not explore the timing between COVID-19 diagnosis and surgery in a categorized fashion, nor does it compare our cohort to non-COVID patients. Furthermore, these studies often overlook the distinction between patients who had fully recovered at the time of surgery and those with persistent symptoms. Our results support the fact that patients who have fully recovered and those with an active asymptomatic disease tend to have similar postoperative outcomes. “Post-COVID syndrome” is an entity that describes patients who, despite no longer having an active viral infection, continue to experience residual effects of the illness such as deconditioning, inflammation, fatigue, headaches, memory disturbances, difficulty with concentration, and depression [ 34 ]. Given the potential complications associated with post-COVID syndrome, the importance of thoroughly assessing a patient’s suitability for surgery, especially in the context of ongoing recovery from COVID, cannot be overstated. Recovery timelines remain uncertain, and parallels from current literature emphasize the need for complete clinical recovery from major medical events before proceeding with non-emergent surgery. While our study sheds valuable light on the association between COVID-19 status and postoperative outcomes, there are several limitations that should be acknowledged. First and foremost, patient data was sourced from electronic medical records and operating room databases, which may lead to incomplete or inconsistent information. The reliance on these sources could result in missing or inaccurately recorded data, potentially impacting the validity of our findings. Furthermore, the relatively modest sample size of our cohort, particularly in specific subgroups, such as patients who were symptomatic prior to surgery, limited the power of our analyses. Mostly, 24% of the sample of COVID-19 patients were symptomatic patients who either had a tracheotomy as their surgery or respiratory failure prior to surgery. This composition limits the inference that can be drawn from our results in relation to a more general surgical population. Also, the cohort's composition primarily consists of patients from the Province of Québec, which could potentially limit the external validity of our results to other geographic regions or healthcare systems, despite acknowledging that this province was among the ones most impacted by the pandemic. Also, our study was conducted during a period of the pandemic featuring different variants than the more contemporary ones. Moreover, the assessment of symptoms and COVID-19 recovery was reliant on the accuracy of medical documentation and clinical judgment. Variability in symptom reporting, diagnostic methods, and the interpretation of recovery criteria could introduce bias and imprecision in patient categorization. The comprehensive definition of recovery we employed aims to account for the diverse presentations of COVID-19 patients, but it is inherently subjective and could lead to misclassification. Finally, the potential influence of vaccination status on postoperative outcomes would have merited consideration, though it was not specifically analyzed in our study since most of it was conducted prior to the availability of vaccines [ 23 ]. Our study possesses several strengths that contribute to a comprehensive understanding of the relationship between COVID-19 status, surgical outcomes, and recovery and inform clinical practice and decision-making. One of the primary strengths of our study is its multicenter design. Conducted across seven academic hospitals within the Province of Québec, the study benefits from a diverse patient population and surgical practices, enhancing the generalizability of our results. This diversity in healthcare settings reduces the potential for single-center biases and increases the likelihood of capturing a broader spectrum of COVID-19 patients undergoing surgery. We documented various aspects of patient characteristics, COVID-19 status, surgical procedures, and postoperative outcomes. This detailed information allows for more robust analyses, including adjustments for potential confounding variables, contributing to the reliability of our results. We also conducted sensitivity analyses, which provided a more nuanced understanding of how preoperative respiratory failure can potentially affect postoperative results. The study's inclusion of both symptomatic and asymptomatic COVID-19 patients, as well as those who had recovered from the infection, further adds to its strength. By comparing these distinct patient groups, we were able to identify specific trends and associations that might otherwise have been overlooked. In addition, our study benefited from a relatively long observation period, spanning from March 2020 to April 2021, thus capturing various phases of the pandemic. Lastly, our study fills a crucial gap in the literature by providing data on Canadian surgical patients either infected with COVID-19 or having recently recovered. The COVID-19 pandemic has profoundly transformed surgical care, introducing complex challenges in managing patients with COVID-19 or those who recovered from the infection. As one of the few studies conducted within a Canadian perioperative context, our findings contribute to a comprehensive understanding of the complex interplay between COVID-19 status and postoperative outcomes in this patient population. These insights hold vital implications for patient management and care decisions, as they provide crucial guidance to healthcare professionals in optimizing postoperative care and mitigating risks for patients with COVID-19 undergoing surgery. Our results highlight important trends, suggesting the need for further investigation with larger sample sizes to draw more conclusive insights regarding the impact of these factors on in-hospital mortality, especially in patients without preoperative respiratory failure. Declarations Funding sources This work was financially supported by the Fonds de développement du département d’anesthésiologie et de médecine de la douleur de l’Université de Montréal and by the Fondation d’Anesthésie-Réanimation du Québec . Dr. D’Aragon and Dr. Carrier are recipients of a career research award from the Fonds de Recherche du Québec - Santé (FRQS). Dr. Turgeon is the holder of the Canada Research Chair in Critical Care Neurology and Trauma. Dr. D’Aragon is the holder of the « Chaire de recherche Justin Lefebvre en don d’organes de l’Université de Sherbrooke ». Dr. Carrier is the holder of the « Chaire de médecine transfusionnelle Fondation Héma-Québec-Bayer de l’Université de Montréal ». Conflict of interest The authors have no conflict of interest to declare. Data availability statement The datasets generated and analyzed during the current study are not publicly available due to legal restrictions but may be available from the corresponding author on reasonable written request and after local REB approval. The Province of Quebec does not allow public patient data sharing. The dataset is held on a secured server at the CHUM Research Center. Ethics approval This study was centrally approved by the “Research Ethics Board (REB) of the Centre hospitalier de l’Université de Montréal” (#19.386) that waived the need for informed consent. The study was subsequently approved by all local REB from each institution. All methods were carried out in accordance with relevant guidelines and regulations. Acknowledgements We want to thank Dr Siamak Mohammadi from the Institut universitaire de cardiologie et de pneumologie de Québec - Université Laval , Dr Olivier Verdonck from CIUSSS de l’Est de l’île de Montréal, Hôpital Maisonneuve-Rosemont and Dre Sophie Lena Discepola from the Medical School of the Université de Montréal for their help with study procedures and local data collection. We also extend our sincerest gratitude to all the anesthesiologists across every center for their invaluable assistance in data collection and the dedicated students and research assistants who played an active role in facilitating the study's initiation and diligent data collection. References COVIDSurg Collaborative, Global Guidance for Surgical Care During the COVID-19 Pandemic . British Journal of Surgery, 2020. Soni, K., et al., Cancer surgery during COVID increased the patient mortality and the transmission risk to healthcare workers: results from a retrospective cohort study (NCT05240378) . 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Les variants du SRAS-CoV-2 . 2023 November 23, 2023; Available from: https://www.inspq.qc.ca/covid-19/labo/variants . Carrier, F.M., et al., Postoperative outcomes in surgical COVID-19 patients: a multicenter cohort study . BMC Anesthesiol, 2021. 21(1): p. 15. von Elm, E., et al., The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies . J Clin Epidemiol, 2008. 61(4): p. 344–9. Abbott, T.E.F., et al., A systematic review and consensus definitions for standardised end-points in perioperative medicine: pulmonary complications . Br J Anaesth, 2018. 120(5): p. 1066–1079. Ide, Y., et al., Clinical characteristics of pneumothorax and pneumomediastinum in mechanical ventilated patients with coronavirus disease 2019: a case series . J Med Case Rep, 2024. 18(1): p. 7. Acute Kidney Injury Work Group, Kidney Disease: Improving Global Outcomes (KDIGO). KDIGO Clinical Practice Guideline for Acute Kidney Injury . 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COVIDSurg Collaborative GlobalSurg Collaborative, Timing of surgery following SARS-CoV-2 infection: an international prospective cohort study . Anaesthesia, 2021. 76(6): p. 748–758. O'Brien, W.J., K. Gupta, and K.M.F. Itani, Estimated Risk of Adverse Surgical Outcomes Among Patients With Recent COVID-19 Infection Using Target Trial Emulation Methods . JAMA Netw Open, 2023. 6(3): p. e234876. Knisely, A., et al., Perioperative Morbidity and Mortality of Patients With COVID-19 Who Undergo Urgent and Emergent Surgical Procedures . Ann Surg, 2021. 273(1): p. 34–40. Isla, A., et al., Postoperative mortality in the COVID-positive hip fracture patient, a systematic review and meta-analysis . Eur J Orthop Surg Traumatol, 2023. 33(4): p. 927–935. Shao, C.C., et al., Increased Risk of Postoperative Mortality Associated With Prior COVID-19 Infection . Am J Prev Med, 2022. 63(1 Suppl 1): p. S75-S82. Bozada-Gutierrez, K., M. Trejo-Avila, and M. Moreno-Portillo, Postoperative complications and predictors of mortality in patients with COVID-19 . Cir Cir, 2023. 91(3): p. 344–353. Deng, J.Z., et al., The Risk of Postoperative Complications After Major Elective Surgery in Active or Resolved COVID-19 in the United States . Annals of Surgery, 2021. Neumaier, M., et al., Heightened 30-Day Postoperative Complication Risk Persists After COVID-19 Infection . World J Surg, 2023. 47(1): p. 40–49. Aziz, M.F., et al., Perioperative Mortality of the COVID-19 Recovered Patient Compared to a Matched Control: A Multicenter Retrospective Cohort Study . Anesthesiology, 2024. 140(2): p. 195–206. Bui, N., et al., Preparing previously COVID-19-positive patients for elective surgery: a framework for preoperative evaluation . Perioper Med (Lond), 2021. 10(1): p. 1. Additional Declarations No competing interests reported. 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Couture","email":"","orcid":"","institution":"Université Laval","correspondingAuthor":false,"prefix":"","firstName":"Etienne","middleName":"J.","lastName":"Couture","suffix":""},{"id":273832692,"identity":"8d64fa87-2ead-4820-af54-3d30db1a25bf","order_by":4,"name":"Frédérick D’Aragon","email":"","orcid":"","institution":"Université de Sherbrooke","correspondingAuthor":false,"prefix":"","firstName":"Frédérick","middleName":"","lastName":"D’Aragon","suffix":""},{"id":273832693,"identity":"aab09da5-907e-4924-8198-be1b53f42ace","order_by":5,"name":"Stanislas Kandelman","email":"","orcid":"","institution":"McGill University Health Centre","correspondingAuthor":false,"prefix":"","firstName":"Stanislas","middleName":"","lastName":"Kandelman","suffix":""},{"id":273832694,"identity":"a1d894e9-2c18-4937-b7f3-d70215e1e365","order_by":6,"name":"Alexis F. Turgeon","email":"","orcid":"","institution":"Université Laval","correspondingAuthor":false,"prefix":"","firstName":"Alexis","middleName":"F.","lastName":"Turgeon","suffix":""},{"id":273832695,"identity":"2c429d46-0f94-4e45-8ae0-ea3678825ea6","order_by":7,"name":"Caroline Jodoin","email":"","orcid":"","institution":"University of Montreal","correspondingAuthor":false,"prefix":"","firstName":"Caroline","middleName":"","lastName":"Jodoin","suffix":""},{"id":273832696,"identity":"6797d200-407e-4a5b-8508-0a737fe7bbbc","order_by":8,"name":"Martin Girard","email":"","orcid":"","institution":"Centre Hospitalier de l’Université de Montréal","correspondingAuthor":false,"prefix":"","firstName":"Martin","middleName":"","lastName":"Girard","suffix":""},{"id":273832697,"identity":"7ce84e4e-5759-4e4e-b35e-75179af20238","order_by":9,"name":"Pierre Beaulieu","email":"","orcid":"","institution":"University of Montreal","correspondingAuthor":false,"prefix":"","firstName":"Pierre","middleName":"","lastName":"Beaulieu","suffix":""},{"id":273832698,"identity":"0fd1bb73-fe76-4f11-a887-91f1eeafb5d7","order_by":10,"name":"Philippe Richebé","email":"","orcid":"","institution":"University of Montreal","correspondingAuthor":false,"prefix":"","firstName":"Philippe","middleName":"","lastName":"Richebé","suffix":""},{"id":273832699,"identity":"6d9474b3-9283-45e0-b17f-b12cf63ff01c","order_by":11,"name":"François Martin Carrier","email":"data:image/png;base64,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","orcid":"","institution":"University of Montreal","correspondingAuthor":true,"prefix":"","firstName":"François","middleName":"Martin","lastName":"Carrier","suffix":""}],"badges":[],"createdAt":"2024-02-15 20:47:10","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3959683/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3959683/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":57145971,"identity":"37bb1daa-3583-435f-8a63-dfb7c8b9daf3","added_by":"auto","created_at":"2024-05-25 20:01:36","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":882970,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3959683/v1/ee4e7946-b9f8-48c8-ad38-8cbc52d1093a.pdf"},{"id":51460833,"identity":"6e2bf5e4-28bf-4717-b1f8-09dcf332d09e","added_by":"auto","created_at":"2024-02-22 04:16:34","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":148075,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementarymaterial.docx","url":"https://assets-eu.researchsquare.com/files/rs-3959683/v1/24488a3070aa4ce82867fc57.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Pulmonary complications and mortality among COVID-19 patients undergoing a surgery: a multicenter cohort study","fulltext":[{"header":"Background","content":"\u003cp\u003eThe COVID-19 pandemic has ushered in unparalleled challenges for healthcare systems globally, not least in the realm of surgical care for patients afflicted with the virus. An urgent concern in this context is the heightened risk of perioperative complications and potential virus transmission to healthcare workers and other patients [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eDuring the earlier stages of the pandemic, the absence of comprehensive knowledge both in mainstream and scientific circles further compounded these difficulties. Recently, there has been a gradual evolution in the scientific literature, focusing on the complex relationship between COVID-19 and postoperative complications [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Initial data from Europe and the Middle East hinted at alarming postoperative 30-day mortality rates of 19\u0026ndash;24%, and more than half of the patients experiencing postoperative pulmonary complications [\u003cspan additionalcitationids=\"CR5 CR6\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eA key aspect in this emerging field has been the distinction between symptomatic and asymptomatic carriers of the virus [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Symptomatic patients, characterized by potential pulmonary involvement, significant systemic inflammation, and higher viral loads, have been shown to incur a greater risk of perioperative complications [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. In contrast, the perceived lower risks associated with surgery in asymptomatic carriers contribute to the multifaceted challenges in perioperative management [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Emphasizing the need for detailed investigation into these complexities, research efforts must focus on the comprehensive documentation of surgical needs and an array of procedures, and their related outcomes among COVID-19 positive patients. Such studies have provided valuable insights into the effects of an active infection on surgical outcomes and the varying risk factors among symptomatic and asymptomatic patients [\u003cspan additionalcitationids=\"CR3\" citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Despite burgeoning global research, Canadian data has remained conspicuously sparse.\u003c/p\u003e \u003cp\u003eTo contend with this, we launched an observational cohort study in Qu\u0026eacute;bec, one of the most severely affected Canadian province during the pandemic [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Our primary objective was to investigate the association between the presence of COVID-19-related symptoms among patients with COVID-19 infection at time of surgery and postoperative pulmonary complications and mortality. Our second objective was to describe the postoperative outcomes of patients who underwent a surgical procedure after recovering from COVID-19 based on the time elapsed between the first positive test and the surgery and to compare them with those of asymptomatic COVID-19 patients. Our hypothesis was that the presence of symptoms would be associated with an increased risk of pulmonary complications, while asymptomatic patients would have similar outcomes to patients who had recovered [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e].\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eDesign and setting\u003c/h2\u003e \u003cp\u003eWe conducted a multicenter observational cohort study at seven university hospitals situated in the Province of Qu\u0026eacute;bec from March 13, 2020, through April 30, 2021. During the study period, the prevalent strains of the virus were the initial strain, along with the Alpha, Beta and Gamma variants [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Prompted by the urgency engendered early in the pandemic, we had previously published preliminary data focusing on postoperative mortality from this study [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. The current study, however, boasts a larger sample size and shifts its focus to postoperative pulmonary complications. Our findings are reported in accordance with the STROBE guidelines for transparent reporting of observational studies [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Approval from the Research Ethics Board was obtained at all participating sites. Research Ethics Boards waived the need for written informed consent.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eStudy participants\u003c/h2\u003e \u003cp\u003eWe included all adult patients undergoing surgery who tested positive for COVID-19 and those who had recovered from COVID-19. COVID-19 patients were diagnosed through a positive polymerase chain reaction (PCR) test, conducted either before surgery or within 72 hours after. This testing used either oro-nasopharyngeal swabs or endotracheal aspirates. Patients were identified through the electronic medical data system or the operating room database at each site.\u003c/p\u003e \u003cp\u003ePatients who had recovered from COVID-19 were those who had a positive test at least 10 days prior to surgery and one of the following three scenarios: 1) the presence of two consecutive negative SARS-CoV-2 PCR tests following the last positive test and preceding the surgery; 2) the presence of a single negative test along with a clinically substantial period without symptoms between the last positive test and the negative one; 3) no negative test available, but the patient was considered as having recovered based on the complete resolution of symptoms. This comprehensive definition was aligned with protocols applied in the hospital network of the province of Qu\u0026eacute;bec and became less restrictive in November 2020 (see table S1).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eExposure variables\u003c/h2\u003e \u003cp\u003eTo address our first objective, our exposure was the presence of symptoms at the time of the surgery based on patient-reported COVID-19 symptoms such as fever or respiratory failure, among others, as assessed by the attending clinicians (see table S2). For our secondary objective, our exposures were the time elapsed from the initial positive COVID-19 test to surgery in patients who had recovered and the infection status, categorized as either \u0026ldquo;recovered\u0026rdquo; and \u0026ldquo;active and asymptomatic\u0026rdquo;.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eOutcomes\u003c/h2\u003e \u003cp\u003eOur primary outcome was any postoperative pulmonary complication. We used a definition of postoperative pulmonary complications, informed by an established one, we believed better adapted to our population [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Our primary outcome included atelectasis, pneumonia, acute respiratory distress syndrome (ARDS) and pneumothorax. We substituted, from the original definition, the incidence of pulmonary aspiration for pneumothorax since we believed there might not be any causal relationship between active COVID and pulmonary aspiration, while the reported incidence of pneumothorax is high in this population [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e] Our secondary outcome was hospital survival, assessed from the date of surgery up to hospital discharge. Our exploratory outcomes were the incidence of postoperative non-pulmonary infectious complications, acute kidney injury, thromboembolic events such as myocardial infarction and stroke, surgical reinterventions, need for new postoperative intensive care unit (ICU) admission, the length of hospital stay, any requirement for postoperative mechanical ventilation, and the number of organ dysfunction-free days within 30 days. Non-pulmonary infectious complications were defined as infections requiring antibiotics for more than 72 hours. Acute kidney injury was classified following the KDIGO-AKI criteria [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Myocardial infarction and stroke were based on physician reporting. Mechanical ventilation included both non-invasive and invasive modalities. For all 30-day outcomes, we considered each day on which the outcome occurred. Additionally, our 30-day organ dysfunction-free days adhered to established definitions [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eCovariables\u003c/h2\u003e \u003cp\u003eWe collected characteristics related to the COVID-19 presentation, including factors such as demographic variables, pre-existing comorbidities, surgical and anesthetic characteristics, the level of urgency for the surgery, baseline laboratory measurements, the preoperative Sequential Organ Failure Assessment (SOFA), the requirement for oxygen supplementation or invasive mechanical ventilation prior to surgery, and the administered treatments (e.g., antiviral medications, steroids, and antibiotics). Moreover, multiple intraoperative variables were documented. The characterization of surgical disease was based on surgeon's reporting and classified into distinct categories. Surgeries categorized as neurosurgical, cardiac, thoracic, major vascular, or non-vascular abdominal were defined as major surgeries. Minimally invasive surgery was characterized as those that avoided anatomical cavity opening (laparoscopy, thoracoscopy, endoluminal procedures). The urgency of surgery was classified into two categories: emergent or urgent surgeries that necessitated completion within 24 hours, and non-urgent surgeries that could be deferred beyond 24 hours.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eData sources and management\u003c/h2\u003e \u003cp\u003eResearch staff collected data prospectively up to hospital discharge or retrospectively as reported in the electronic medical records. We ascertained survival up to hospital discharge. Each site entered the data into a centralized electronic database (REDCap\u003csup\u003e\u0026trade;\u003c/sup\u003e electronic data capture tools hosted at the \u003cem\u003eCentre hospitalier de l\u0026rsquo;Universit\u0026eacute; de Montr\u0026eacute;al\u003c/em\u003e), adhering to a manual of standardized operating procedures following necessary training [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analyses\u003c/h2\u003e \u003cp\u003eWe sampled all eligible patients over the recruitment period. We used descriptive statistics (means (SD), medians (IQR) or proportions, as appropriate) to summarize baseline characteristics and the outcomes of COVID-19 patients, stratified based on the presence of symptoms, and for those who had recovered from COVID-19. For the primary objective, we fitted a multivariable mixed-effect logistic regression model to estimate the association between the prevalence of any symptom before the surgery and the incidence of postoperative pulmonary complications in COVID-19 patients who underwent surgery, adjusted for the following potential confounders: preoperative hospitalization, preoperative requirement for oxygen support, urgency of surgery and categorization of surgery as either \u0026ldquo;major\u0026rdquo; or \u0026ldquo;minor\u0026rdquo;. We also fitted a multivariable Cox proportional hazard model to estimate the association between presence of symptoms and time to in-hospital mortality among COVID-19 patients adjusted for the same potential confounders but stratified for preoperative requirement for oxygen. We used random effects and frailty factors to account for the clustered nature of the data within the same site. However, since the logistic mixed-effect model showed singularity with a null variance of the random effect, we reported estimates from a model without random effects. We conducted post hoc sensitivity analyses for each outcome by estimating the same models, first by excluding patients who had a tracheotomy as their index surgery or had preoperative respiratory failure, and then by excluding only those who had a tracheotomy as their surgery. Finally, we reported an unadjusted Kaplan-Meier survival curve with 95% confidence bands.\u003c/p\u003e \u003cp\u003eFor our secondary objective, we estimated the association between the recovery duration from COVID-19 to the surgery on the incidence of postoperative pulmonary complications and hospital survival. We also compared both outcomes between patients who recovered from COVID-19 to those with an active asymptomatic infection. We used mixed-effect logistic regression models and Cox proportional hazard models with a frailty factor adjusted for the same confounders. The statistical significance level was set at 0.05. For all analyses, we reported odds ratios (OR) and hazard ratios (HR) with 95% confidence intervals (CI). All analyses were performed using R statistical software (R Foundation for Statistical Computing, Vienna, Austria, version 4.2.3).\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eBetween March 13, 2020, and April 30, 2021, we included 105 COVID-19 patients who underwent a surgical procedure and 206 patients who had recovered from COVID-19 at the time of surgery for our secondary objective.\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eSymptomatic versus asymptomatic COVID-19 patients\u003c/h2\u003e \u003cp\u003eAmong patients with confirmed COVID-19 at time of surgery, 47 (45%) exhibited symptoms and 58 (55%) were asymptomatic carriers. The baseline characteristics of these patients are presented in Tables \u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, \u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003eS2\u003c/span\u003e \u0026amp; \u003cspan refid=\"Tab8\" class=\"InternalRef\"\u003eS3\u003c/span\u003e. Both groups displayed similar baseline characteristics in terms of sex distribution, but symptomatic patients were older, had a higher body mass index (BMI), and a greater prevalence of diabetes (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The presence of pulmonary infiltrates, as determined by the radiologist\u0026rsquo;s chest X-ray report, was more common among symptomatic patients and these patients were more likely to receive steroids before surgery and require preoperative respiratory support (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Interestingly, both groups showed a balanced distribution in terms of major and minor surgeries, urgency, and duration of surgery (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Out of 47 patients who had symptoms at time of surgery, 13 (28%) had a tracheotomy as their surgery and 25 (53%) had either a tracheotomy as their surgery or preoperative respiratory failure (not in tables).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCharacteristics of COVID-19 patients\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eSymptomatic status at time of surgery\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eVariable\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eAsymptomatic\u003c/b\u003e\u003c/p\u003e \u003cp\u003e(N\u0026thinsp;=\u0026thinsp;58)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eSymptomatic\u003c/b\u003e\u003c/p\u003e \u003cp\u003e(N\u0026thinsp;=\u0026thinsp;47)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBaseline characteristics\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge (years)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e57.5 [36.5\u0026ndash;74.8]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e66.0 [52.5\u0026ndash;72.5]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSex (female)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30 (52%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25 (53%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBMI\u003c/b\u003e\u003csup\u003e\u003cb\u003e1\u003c/b\u003e\u003c/sup\u003e \u003cb\u003e(kg/m\u003c/b\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u003cb\u003e)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e27.4\u0026thinsp;\u0026plusmn;\u0026thinsp;7.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30.8\u0026thinsp;\u0026plusmn;\u0026thinsp;6.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDiabetes\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14 (24%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15 (32%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHypertension\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11 (19%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6 (13%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eWhite blood cell count\u003c/b\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e \u003cb\u003e(*10\u003c/b\u003e\u003csup\u003e\u003cb\u003e9\u003c/b\u003e\u003c/sup\u003e\u003cb\u003e/L)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.8 [6.9\u0026ndash;13.0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9.5 [6.6\u0026ndash;12.5]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHemoglobin\u003c/b\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e \u003cb\u003e(g/L)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e117.0 [104.0\u0026ndash;133.0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e101.0 [81.0\u0026ndash;122.5]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCreatinine\u003c/b\u003e\u003csup\u003e\u003cb\u003e3\u003c/b\u003e\u003c/sup\u003e \u003cb\u003e(\u0026micro;mol/L)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e77.0 [56.3\u0026ndash;96.0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e83.0 [56.0\u0026ndash;131.5]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCOVID characteristics\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDays from first positive COVID test to surgery\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.0 [1.0\u0026ndash;9.8]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10.0 [3.0\u0026ndash;22.5]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePulmonary infiltrates\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12 (21%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e28 (60%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSteroid\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14 (24%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20 (43%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAntibiotic\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16 (28%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e33 (70%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePreoperative respiratory support\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eNo oxygen\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e45 (78%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17 (36%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eOxygen only\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4 (7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7 (15%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eNon-invasive mechanical ventilation\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eInvasive ventilation\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9 (16%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22 (47%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSurgical characteristics\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePreoperative location\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eHome\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15 (26%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7 (15%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eEmergency department\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14 (24%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7 (15%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eWard\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e23 (40%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10 (21%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eIntensive care unit\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6 (10%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23 (49%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eUrgent surgery (\u0026le;\u0026thinsp;24 hours)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e24 (41%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22 (47%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMajor surgery\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21 (36%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17 (36%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDuration of surgery (minutes)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e60.0 [40.3\u0026ndash;97.3]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e47.0 [27.5\u0026ndash;98.5]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003eCategorical variables are presented as frequency (proportion).\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003eContinuous variables are presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation or as median [1st quartile \u0026minus;\u0026thinsp;3rd quartile].\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003e\u003csup\u003e1\u003c/sup\u003e Missing value for 28 and 17 patients respectively\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003e\u003csup\u003e2\u003c/sup\u003e 1 missing value in the asymptomatic group\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003e\u003csup\u003e3\u003c/sup\u003e 3 missing values in the asymptomatic group\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe postoperative outcomes of COVID-19 patients are summarized in Table \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. Thirty symptomatic patients (64%) experienced at least one postoperative complication compared to 19 asymptomatic patients (33%) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Symptomatic patients had a higher incidence of pneumonia, ARDS, and pneumothorax and a higher requirement for postoperative ICU admission and persistent postoperative mechanical ventilation (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Mortality was higher among symptomatic patients, with 15 deaths (32%) during hospitalization in the symptomatic group compared to 6 deaths (10%) in the asymptomatic group (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePostoperative outcomes of COVID-19 confirmed patients\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eSymptomatic status at time of surgery\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eVariable\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eAsymptomatic\u003c/b\u003e\u003c/p\u003e \u003cp\u003e(N\u0026thinsp;=\u0026thinsp;58)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eSymptomatic\u003c/b\u003e\u003c/p\u003e \u003cp\u003e(N\u0026thinsp;=\u0026thinsp;47)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePostoperative complications\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAny complication\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e19 (33%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30 (64%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAny pulmonary complications\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8 (14%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16 (34%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eAtelectasis\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4 (9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003ePneumonia\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6 (10%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11 (23%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eARDS\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 (3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4 (9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003ePneumothorax\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 (6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAcute kidney injury\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6 (10%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9 (19%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNew postoperative renal replacement therapy\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMyocardial infarction\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eStroke\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNon-pulmonary infection\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6 (10%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6 (13%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSurgical reintervention\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4 (7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10 (21%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eResource utilization and mortality\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNeed for a new postoperative ICU admission\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10 (17%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20 (43%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHospital length of stay (days)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.0 [3.0\u0026ndash;31]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13.0 [7.5\u0026ndash;31.5]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eOne or more days on postoperative mechanically ventilated\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17 (29%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26 (55%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e30-day organ dysfunction free days\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e27.7\u0026thinsp;\u0026plusmn;\u0026thinsp;6.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19.9\u0026thinsp;\u0026plusmn;\u0026thinsp;11.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHospital mortality\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6 (10%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15 (32%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eStatus at hospital discharge among living patients\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eDischarged at home\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e40 (69%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25 (53%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eTransferred to another acute care setting\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7 (12%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 (6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eTransferred to another long-term care setting\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5 (9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4 (9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003eCategorical variables are presented as frequency (proportion).\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003eContinuous variables are presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation or as median [1st quartile \u0026minus;\u0026thinsp;3rd quartile].\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003eARDS\u0026thinsp;=\u0026thinsp;acute respiratory distress syndrome\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003ePatients with COVID-19 symptoms were found to have a higher risk of developing pulmonary complications compared to asymptomatic patients (OR\u0026thinsp;=\u0026thinsp;3.19, 95% CI, from 1.12 to 9.68, p\u0026thinsp;=\u0026thinsp;0.03) (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). These patients also faced significantly higher hazard of in-hospital mortality compared to asymptomatic patients (HR\u0026thinsp;=\u0026thinsp;3.67, 95% CI, from 1.19 to 11.32, p\u0026thinsp;=\u0026thinsp;0.02) (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). From our sensitivity analyses, after excluding 13 symptomatic patients who underwent a tracheotomy, we observed a weaker and non-significant effect between the presence of symptoms and the incidence of postoperative pulmonary complications (OR\u0026thinsp;=\u0026thinsp;2.89 (95% CI from 0.94 to 9.31) (Table S4). A similar pattern was noted when excluding 25 symptomatic patients who either had a tracheotomy or preoperative respiratory failure (OR\u0026thinsp;=\u0026thinsp;2.45 (95% CI from 0.67 to 8.89), see Table S5). The presence of symptoms on hospital mortality also showed a weaker, non-significant association in these analyses (HR\u0026thinsp;=\u0026thinsp;2.60 (95% CI from 0.75 to 8.99) and HR\u0026thinsp;=\u0026thinsp;1.35 (95% CI from 0.32 to 5.76) respectively) (Tables S6 \u0026amp; S7).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAssociation between the presence of symptoms and the incidence of postoperative pulmonary complications in patients with COVID-19 at time of surgery\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOdds Ratio (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePresence of symptoms\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.19 [1.12; 9.68]\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePreoperative hospitalization\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.91 [0.26; 3.72]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.89\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePreoperative oxygen requirement\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.30 [0.45; 3.72]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.62\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUrgent surgery\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.45 [0.15; 1.21]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.12\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMajor surgery\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.45 [0.91; 6.77]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.08\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003e\u003cem\u003eCI\u0026thinsp;=\u0026thinsp;Confidence interval\u003c/em\u003e\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003e\u003cem\u003eNo random effect\u003c/em\u003e\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAssociation between the presence of symptoms and hospital mortality in patients with COVID-19 at time of surgery\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHazard Ratio (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePresence of symptoms\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.67 (1.19; 11.32)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePreoperative hospitalization\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.46 (0.33; 6.48)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.62\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUrgent surgery\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.92 (0.34; 2.52)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.88\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMajor surgery\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.42 (1.25; 9.34)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003e\u003cem\u003eCI\u0026thinsp;=\u0026thinsp;Confidence interval\u003c/em\u003e\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003e\u003cem\u003eThis model is stratified for preoperative oxygen requirement and has center as a frailty effect. Number of events\u0026thinsp;=\u0026thinsp;21 (N\u0026thinsp;=\u0026thinsp;105).\u003c/em\u003e\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003ePatients who recovered from COVID-19\u003c/h2\u003e \u003cp\u003eTables S8, S9, and S10 provide the baseline characteristics and postoperative outcomes of patients (N\u0026thinsp;=\u0026thinsp;206) who had recovered from COVID-19 at the time of surgery, categorized on the number of weeks elapsed since their initial positive COVID-19 test. The time elapsed since the initial positive COVID-19 test in these patients was not associated with a higher risk of pulmonary complications (OR\u0026thinsp;=\u0026thinsp;1.00, 95% CI from 0.99 to 1.00, p-value\u0026thinsp;=\u0026thinsp;0.47, see Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e) or mortality (HR\u0026thinsp;=\u0026thinsp;1.00, 95% CI from 0.99 to 1.01, p-value\u0026thinsp;=\u0026thinsp;0.70) (Table S11). Patients who had recovered from COVID-19 did not have a higher risk of postoperative pulmonary complications or hospital mortality when compared to asymptomatic carriers (Tables S12 \u0026amp; S13).\u003c/p\u003e\u003ctable id=\"Tab9\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eAssociation between the elapsed time between first positive test and surgery and postoperative pulmonary complications in patients who had recovered from COVID-19 at time of surgery\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"3\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eVariable\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eOdds Ratio (95% CI)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eP value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eTime from first positive COVID test\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e1.00 [0.99, 1.00]\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e0.47\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePreoperative hospitalization\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3.87 [1.08, 13.82]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePreoperative oxygen need\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.69 [0.84, 8.61]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUrgent surgery\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.42 [0.14,1.24]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.12\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMajor surgery\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.51 [0.95, 6.65]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\"\u003e\u003cem\u003eCI: Confidence Interval\u003c/em\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\"\u003e\u003cem\u003eThis logistic regression model has center as a random effect. Intracluster correlation\u0026thinsp;=\u0026thinsp;0.076\u003c/em\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this study, we included 105 surgical patients with active COVID-19 and 206 who had recovered from the virus. We observed an important difference between symptomatic and asymptomatic COVID-19 patients undergoing surgery regarding the risk of adverse postoperative outcomes. The presence of an active symptomatic disease was associated with an increased risk of developing postoperative pulmonary complications and an increased mortality. Within this cohort, symptomatic patients who underwent a tracheotomy and those with preoperative respiratory failure encompassed half of the sample. However, even when excluding these cases, point estimates suggested an association between symptoms and postoperative pulmonary complications. Patients who had recovered from the infection at time of surgery and asymptomatic carriers had a similar risk of adverse postoperative outcomes. Interestingly, the length of the recovery period prior to surgery did not appear to influence the incidence of postoperative pulmonary complications and mortality in those who had recovered from the infection.\u003c/p\u003e \u003cp\u003eThe current study enhances our understanding of surgical care in the COVID-19 era, with a particular focus on assessing the risk of postoperative pulmonary complications and in-hospital mortality associated with COVID-19 symptoms prior to surgery. It builds upon prior research conducted by our group, which was spurred by the urgency of the pandemic and, as result, reported preliminary data that focused primarily on postoperative mortality [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Other studies have suggested that preoperative COVID-19 is associated with an increased risk of postoperative pulmonary or cardiovascular complications, and mortality [\u003cspan additionalcitationids=\"CR23 CR24\" citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Interestingly, a more recent study has not observed the same association [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. While the primary focus of these studies was not specifically on this aspect, it appears that the presence of symptoms at time of surgery may account for the observed effect of preoperative COVID-19 on postoperative outcomes. Our findings are consistent with these results. Symptomatic patients are possibly more likely to exhibit severe pulmonary involvement, systemic inflammation, and higher viral loads. These factors collectively contribute to an escalated risk of perioperative complications [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Moreover, the markedly higher hazard of in-hospital mortality among symptomatic patients emphasizes the significant impact that active disease can have on postoperative patient survival [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan additionalcitationids=\"CR28 CR29\" citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Our results underscore the necessity of considering the symptomatic status of patients when assessing their suitability for surgery and evaluating the risk of postoperative complications.\u003c/p\u003e \u003cp\u003eOur study's analyses of patients who had fully recovered from COVID-19 prior to surgery offer additional insights into the dynamic relationship between infection and surgical outcomes. Contrary to previous research on COVID-19 positive patients, we did not observe any effect of the time elapsed from COVID-19 diagnosis to surgery on postoperative outcomes in patients who had recovered from COVID-19 [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. Notably, in a recent study, an increased mortality risk was observed in patients who had recovered from COVID-19 undergoing surgery within two weeks of a positive test compared to longer recovery time [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. Beyond this period, the mortality risk aligns closely between patients with and without prior COVID-19. Our research diverges as it does not explore the timing between COVID-19 diagnosis and surgery in a categorized fashion, nor does it compare our cohort to non-COVID patients. Furthermore, these studies often overlook the distinction between patients who had fully recovered at the time of surgery and those with persistent symptoms. Our results support the fact that patients who have fully recovered and those with an active asymptomatic disease tend to have similar postoperative outcomes. \u0026ldquo;Post-COVID syndrome\u0026rdquo; is an entity that describes patients who, despite no longer having an active viral infection, continue to experience residual effects of the illness such as deconditioning, inflammation, fatigue, headaches, memory disturbances, difficulty with concentration, and depression [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. Given the potential complications associated with post-COVID syndrome, the importance of thoroughly assessing a patient\u0026rsquo;s suitability for surgery, especially in the context of ongoing recovery from COVID, cannot be overstated. Recovery timelines remain uncertain, and parallels from current literature emphasize the need for complete clinical recovery from major medical events before proceeding with non-emergent surgery.\u003c/p\u003e \u003cp\u003eWhile our study sheds valuable light on the association between COVID-19 status and postoperative outcomes, there are several limitations that should be acknowledged. First and foremost, patient data was sourced from electronic medical records and operating room databases, which may lead to incomplete or inconsistent information. The reliance on these sources could result in missing or inaccurately recorded data, potentially impacting the validity of our findings. Furthermore, the relatively modest sample size of our cohort, particularly in specific subgroups, such as patients who were symptomatic prior to surgery, limited the power of our analyses. Mostly, 24% of the sample of COVID-19 patients were symptomatic patients who either had a tracheotomy as their surgery or respiratory failure prior to surgery. This composition limits the inference that can be drawn from our results in relation to a more general surgical population. Also, the cohort's composition primarily consists of patients from the Province of Qu\u0026eacute;bec, which could potentially limit the external validity of our results to other geographic regions or healthcare systems, despite acknowledging that this province was among the ones most impacted by the pandemic. Also, our study was conducted during a period of the pandemic featuring different variants than the more contemporary ones. Moreover, the assessment of symptoms and COVID-19 recovery was reliant on the accuracy of medical documentation and clinical judgment. Variability in symptom reporting, diagnostic methods, and the interpretation of recovery criteria could introduce bias and imprecision in patient categorization. The comprehensive definition of recovery we employed aims to account for the diverse presentations of COVID-19 patients, but it is inherently subjective and could lead to misclassification. Finally, the potential influence of vaccination status on postoperative outcomes would have merited consideration, though it was not specifically analyzed in our study since most of it was conducted prior to the availability of vaccines [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eOur study possesses several strengths that contribute to a comprehensive understanding of the relationship between COVID-19 status, surgical outcomes, and recovery and inform clinical practice and decision-making. One of the primary strengths of our study is its multicenter design. Conducted across seven academic hospitals within the Province of Qu\u0026eacute;bec, the study benefits from a diverse patient population and surgical practices, enhancing the generalizability of our results. This diversity in healthcare settings reduces the potential for single-center biases and increases the likelihood of capturing a broader spectrum of COVID-19 patients undergoing surgery. We documented various aspects of patient characteristics, COVID-19 status, surgical procedures, and postoperative outcomes. This detailed information allows for more robust analyses, including adjustments for potential confounding variables, contributing to the reliability of our results. We also conducted sensitivity analyses, which provided a more nuanced understanding of how preoperative respiratory failure can potentially affect postoperative results. The study's inclusion of both symptomatic and asymptomatic COVID-19 patients, as well as those who had recovered from the infection, further adds to its strength. By comparing these distinct patient groups, we were able to identify specific trends and associations that might otherwise have been overlooked. In addition, our study benefited from a relatively long observation period, spanning from March 2020 to April 2021, thus capturing various phases of the pandemic. Lastly, our study fills a crucial gap in the literature by providing data on Canadian surgical patients either infected with COVID-19 or having recently recovered.\u003c/p\u003e \u003cp\u003eThe COVID-19 pandemic has profoundly transformed surgical care, introducing complex challenges in managing patients with COVID-19 or those who recovered from the infection. As one of the few studies conducted within a Canadian perioperative context, our findings contribute to a comprehensive understanding of the complex interplay between COVID-19 status and postoperative outcomes in this patient population. These insights hold vital implications for patient management and care decisions, as they provide crucial guidance to healthcare professionals in optimizing postoperative care and mitigating risks for patients with COVID-19 undergoing surgery. Our results highlight important trends, suggesting the need for further investigation with larger sample sizes to draw more conclusive insights regarding the impact of these factors on in-hospital mortality, especially in patients without preoperative respiratory failure.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cu\u003eFunding sources\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eThis work was financially supported by the \u003cem\u003eFonds de développement du département d’anesthésiologie et de médecine de la douleur de l’Université de Montréal\u003c/em\u003e and by the \u003cem\u003eFondation d’Anesthésie-Réanimation du Québec\u003c/em\u003e.\u0026nbsp;Dr. D’Aragon and Dr. Carrier are recipients of a career research award from the Fonds de Recherche du Québec - Santé (FRQS). Dr. Turgeon is the holder of the Canada Research Chair in Critical Care Neurology and Trauma.\u0026nbsp;Dr. D’Aragon is the holder of the\u0026nbsp;«\u003cem\u003e\u0026nbsp;Chaire de recherche Justin Lefebvre en don d’organes de l’Université de Sherbrooke ».\u0026nbsp;\u003c/em\u003eDr. Carrier is the holder of the « \u003cem\u003eChaire de médecine transfusionnelle Fondation Héma-Québec-Bayer de l’Université de Montréal\u003c/em\u003e ».\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eConflict of interest\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eThe authors have no conflict of interest to declare.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eData availability statement\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated and analyzed during the current study are not publicly available due to legal restrictions but may be available from the corresponding author on reasonable written request and after local REB approval. The Province of Quebec does not allow public patient data sharing. The dataset is held on a secured server at the CHUM Research Center.\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eEthics approval\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eThis study was centrally approved by the “Research Ethics Board (REB) of the Centre hospitalier de l’Université de Montréal” (#19.386) that waived the need for informed consent. The study was subsequently approved by all local REB from each institution. All methods were carried out in accordance with relevant guidelines and regulations.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe want to thank Dr Siamak Mohammadi from the\u0026nbsp;\u003cem\u003eInstitut universitaire de cardiologie et de pneumologie de Qu\u0026eacute;bec - Universit\u0026eacute; Laval\u003c/em\u003e, Dr Olivier Verdonck from\u0026nbsp;\u003cem\u003eCIUSSS de l\u0026rsquo;Est de l\u0026rsquo;\u0026icirc;le de Montr\u0026eacute;al, H\u0026ocirc;pital Maisonneuve-Rosemont\u003c/em\u003e and Dre Sophie Lena Discepola from the \u003cem\u003eMedical School of the Universit\u0026eacute; de Montr\u0026eacute;al\u003c/em\u003e for their help with study procedures and local data collection. We also extend our sincerest gratitude to all the anesthesiologists across every center for their invaluable assistance in data collection and the dedicated students and research assistants who played an active role in facilitating the study\u0026apos;s initiation and diligent data collection.\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eCOVIDSurg Collaborative, \u003cem\u003eGlobal Guidance for Surgical Care During the COVID-19 Pandemic\u003c/em\u003e. British Journal of Surgery, 2020.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSoni, K., et al., \u003cem\u003eCancer surgery during COVID increased the patient mortality and the transmission risk to healthcare workers: results from a retrospective cohort study (NCT05240378)\u003c/em\u003e. World J Surg Oncol, 2022. 20(1): p. 302.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVerhagen, N.B., et al., \u003cem\u003eSeverity of Prior COVID-19 is Associated with Postoperative Outcomes Following Major Inpatient Surgery.\u003c/em\u003e Ann Surg, 2023.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCOVIDSurg Collaborative, \u003cem\u003eMortality and pulmonary complications in patients undergoing surgery with perioperative SARS-CoV-2 infection: an international cohort study\u003c/em\u003e. Lancet, 2020. 396(10243): p. 27\u0026ndash;38.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDoglietto, F., et al., \u003cem\u003eFactors Associated With Surgical Mortality and Complications Among Patients With and Without Coronavirus Disease 2019 (COVID-19) in Italy\u003c/em\u003e. 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Surgery, 2022. 171(6): p. 1500\u0026ndash;1504.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDadras, O., et al., \u003cem\u003eThe Relationship Between COVID-19 Viral Load and Disease Severity: A Systematic Review\u003c/em\u003e. Immunity Inflammation and Disease, 2021.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNahshon, C., et al., \u003cem\u003eHazardous Postoperative Outcomes of Unexpected COVID-19 Infected Patients: A Call for Global Consideration of Sampling All Asymptomatic Patients Before Surgical Treatment\u003c/em\u003e. World Journal of Surgery, 2020.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShim, E., \u003cem\u003eRegional Variability in COVID-19 Case Fatality Rate in Canada, February\u0026ndash;December 2020\u003c/em\u003e. International Journal of Environmental Research and Public Health, 2021.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDetsky, A.S. and I.I. 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BMC Anesthesiol, 2021. 21(1): p. 15.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003evon Elm, E., et al., \u003cem\u003eThe Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies\u003c/em\u003e. J Clin Epidemiol, 2008. 61(4): p. 344\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAbbott, T.E.F., et al., \u003cem\u003eA systematic review and consensus definitions for standardised end-points in perioperative medicine: pulmonary complications\u003c/em\u003e. Br J Anaesth, 2018. 120(5): p. 1066\u0026ndash;1079.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eIde, Y., et al., \u003cem\u003eClinical characteristics of pneumothorax and pneumomediastinum in mechanical ventilated patients with coronavirus disease 2019: a case series\u003c/em\u003e. J Med Case Rep, 2024. 18(1): p. 7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAcute Kidney Injury Work Group, \u003cem\u003eKidney Disease: Improving Global Outcomes (KDIGO). KDIGO Clinical Practice Guideline for Acute Kidney Injury\u003c/em\u003e. Kidney International Supplements, 2012. 2(1).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHeyland, D.K., et al., \u003cem\u003ePersistent organ dysfunction plus death: a novel, composite outcome measure for critical care trials\u003c/em\u003e. Crit Care, 2011. 15(2): p. R98.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHarris, P.A., et al., \u003cem\u003eThe REDCap consortium: Building an international community of software platform partners\u003c/em\u003e. J Biomed Inform, 2019. 95: p. 103208.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKiyatkin, M.E., et al., \u003cem\u003eIncreased incidence of post-operative respiratory failure in patients with pre-operative SARS-CoV-2 infection\u003c/em\u003e. J Clin Anesth, 2021. 74: p. 110409.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGarnier, M., et al., \u003cem\u003eAssociation of preoperative COVID-19 and postoperative respiratory morbidity during the Omicron epidemic wave: the DROMIS-22 multicentre prospective observational cohort study\u003c/em\u003e. EClinicalMedicine, 2023. 58: p. 101881.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBryant, J.M., et al., \u003cem\u003eAssociation of Time to Surgery After COVID-19 Infection With Risk of Postoperative Cardiovascular Morbidity\u003c/em\u003e. Jama Network Open, 2022.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCOVIDSurg Collaborative GlobalSurg Collaborative, \u003cem\u003eTiming of surgery following SARS-CoV-2 infection: an international prospective cohort study\u003c/em\u003e. Anaesthesia, 2021. 76(6): p. 748\u0026ndash;758.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eO'Brien, W.J., K. Gupta, and K.M.F. Itani, \u003cem\u003eEstimated Risk of Adverse Surgical Outcomes Among Patients With Recent COVID-19 Infection Using Target Trial Emulation Methods\u003c/em\u003e. JAMA Netw Open, 2023. 6(3): p. e234876.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKnisely, A., et al., \u003cem\u003ePerioperative Morbidity and Mortality of Patients With COVID-19 Who Undergo Urgent and Emergent Surgical Procedures\u003c/em\u003e. Ann Surg, 2021. 273(1): p. 34\u0026ndash;40.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eIsla, A., et al., \u003cem\u003ePostoperative mortality in the COVID-positive hip fracture patient, a systematic review and meta-analysis\u003c/em\u003e. Eur J Orthop Surg Traumatol, 2023. 33(4): p. 927\u0026ndash;935.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShao, C.C., et al., \u003cem\u003eIncreased Risk of Postoperative Mortality Associated With Prior COVID-19 Infection\u003c/em\u003e. Am J Prev Med, 2022. 63(1 Suppl 1): p. S75-S82.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBozada-Gutierrez, K., M. Trejo-Avila, and M. Moreno-Portillo, \u003cem\u003ePostoperative complications and predictors of mortality in patients with COVID-19\u003c/em\u003e. Cir Cir, 2023. 91(3): p. 344\u0026ndash;353.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDeng, J.Z., et al., \u003cem\u003eThe Risk of Postoperative Complications After Major Elective Surgery in Active or Resolved COVID-19 in the United States\u003c/em\u003e. Annals of Surgery, 2021.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNeumaier, M., et al., \u003cem\u003eHeightened 30-Day Postoperative Complication Risk Persists After COVID-19 Infection\u003c/em\u003e. World J Surg, 2023. 47(1): p. 40\u0026ndash;49.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAziz, M.F., et al., \u003cem\u003ePerioperative Mortality of the COVID-19 Recovered Patient Compared to a Matched Control: A Multicenter Retrospective Cohort Study\u003c/em\u003e. Anesthesiology, 2024. 140(2): p. 195\u0026ndash;206.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBui, N., et al., \u003cem\u003ePreparing previously COVID-19-positive patients for elective surgery: a framework for preoperative evaluation\u003c/em\u003e. Perioper Med (Lond), 2021. 10(1): p. 1.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-3959683/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3959683/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eManaging COVID-19-positive patients requiring surgery is complex due to perceived heightened perioperative risks. However, Canadian data in this context remains scarce. To address this gap, we conducted a multicenter cohort study in the province of Québec, the Canadian province most affected during the initial waves of the pandemic, to comprehensively assess the impact of COVID-19 symptoms, and recovery time, on postoperative outcomes in surgical patients.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe included adult surgical patients with either active COVID-19 at time of surgery or those who had recovered from the disease, from March 13, 2020, to April 30, 2021. We evaluated the association between symptoms or recovery time and postoperative pulmonary complications and hospital mortality using multivariable logistic regression and Cox models.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe included 105 patients with an active infection (47 were symptomatic and 58 were asymptomatic) and 206 who had healed from COVID-19 in seven hospitals. Among patients with an active infection, those who were symptomatic had a higher risk of pulmonary complications (odds ratio = 3.19; 95% CI, from 1.12 to 9.68; p = 0.03) and hospital mortality (hazard ratio = 3.67; 95% CI, from 1.19 to 11.32; p = 0.02). We did not observe any significant effect of the duration of recovery prior to surgery on patients who had healed from their infection. Their postoperative outcomes were also similar to those observed in asymptomatic patients.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInterpretation\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSymptomatic status should be considered in the decision to proceed with surgery in COVID-19-positive patients. Our results may help optimize surgical care in this patient population.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTrial registration:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eClinicalTrials.gov Identifier: NCT04458337, Registration Date: July 7, 2020.\u003c/p\u003e","manuscriptTitle":"Pulmonary complications and mortality among COVID-19 patients undergoing a surgery: a multicenter cohort study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-02-22 04:16:29","doi":"10.21203/rs.3.rs-3959683/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"c3e5c635-6c09-4f17-9bc2-277e000d4b64","owner":[],"postedDate":"February 22nd, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-05-25T19:53:29+00:00","versionOfRecord":[],"versionCreatedAt":"2024-02-22 04:16:29","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-3959683","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3959683","identity":"rs-3959683","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}