Oral cavity squamous cell carcinoma and readmission: rates, causes, and risk factors

Oral cavity squamous cell carcinoma and readmission: rates, causes, and risk factors | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Short Report Oral cavity squamous cell carcinoma and readmission: rates, causes, and risk factors Almoaidbellah Rammal, Abdulsalam Alqutub, Omar Alsulami, Naif Mozahim, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3946396/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 Oral cancer is a prevalent form of cancer worldwide. Unplanned readmission exposes patients to hospital-acquired complications. The readmission rate is a metric for quality of care. We aimed to identify the rate, causes, and predictors of hospital readmission within 60 days after discharge following oral cancer surgery. Methods This 15-year retrospective study included all patients who underwent oral oncologic surgery at a single tertiary center between 2008 and 2023. Patient charts were reviewed for demographic information, comorbidities, and causes for readmission. Results Of the 93 patients who underwent oral oncologic surgery, nine (9.70%) were readmitted within 60 days after discharge. The most common reason for readmission was surgical site infection (33.33%), followed by wound bleeding (25%). The significant predictors were unmarried status (P = 0.003), T4 disease status (P = 0.004), a higher cumulative illness rating scale (CIRS) (P = 0.011), radical excisions (P = 0.028), a higher American Society of Anesthesiology (ASA) score (P = 0.029), a lower preoperative serum albumin (P = 0.028), and a greater neutrophil count (P = 0.03). Conclusion One in every ten patients was readmitted following oral cancer surgery. The most common cause is surgical site infection. Significant predictors included T4 disease, preoperative hypoalbuminemia, higher neutrophil counts, unmarried status, extensive surgery, and higher baseline comorbidity indices. Future guidelines to lower readmission rates should focus on high-risk patients and involve earlier follow-up, more rigorous postdischarge monitoring, and delayed discharge. Oral cancer Hypoalbuminemia Laryngectomy Patient readmission Retrospective studies Surgical wound infection Introduction Oral cancer is a prevalent form of cancer found worldwide ( 1 ). In 2015, 1.6% of total cancer cases were female, and 1.9% were male in Saudi Arabia ( 2 ). Oral cavity malignancies encompass a domain within the head and neck oncology field characterized by intriguing facets in terms of their management. Despite witnessing a substantial shift in the therapeutic approach for various head and neck neoplasms, wherein primary chemoradiation has gained prominence, its utilization in the context of oral cavity cancers remains relatively infrequent ( 3 ). Despite the use of proficient surgical methodologies in oral oncologic surgeries and the presence of highly skilled surgeons, the occurrence of postoperative complications can notably influence the overall outcome of surgical interventions. Importantly, from a surgical standpoint, the preoperative condition of patients, in conjunction with the selected operative approach, significantly contributes to the likelihood of encountering these complications. These complications include surgical site bleeding, infections, pain, and wound dehiscence ( 4 , 5 ). These complications can adversely influence patient quality of life, result in the postponement of adjuvant therapy, and increase the need for hospital readmission, resulting in an increased rate of subsequent mortality. The published material regarding the rate of readmission after oral oncologic surgery ranged from 3.2-5%, with postoperative flap-related issues and percutaneous fistula and wound infection as the most common causes of readmission ( 6 , 7 ). Because of the lack of similar reports, the rates and risk factors for readmission after oral oncologic surgery need to be clearly described in the Saudi population. This study aimed to determine the incidence, risk factors, and most likely complications that cause readmission following oral oncologic surgery within 60 days of hospital discharge at a tertiary academic care center in Jeddah, Saudi Arabia. Methodology After receiving ethical approval from the Institutional Review Board (IRB), we reviewed the records of patients who underwent oral oncologic surgery between 2008 and 2023. The causes of readmission were extracted as the final diagnosis from the medical records system. Only the first episode of unplanned returns was acquired if more than one episode was identified within the first 60 days after discharge. We included all patients who underwent oral oncologic surgery for squamous cell carcinoma at our center between 2008 and 2023. Patients with multiple malignant primary tumors, undocumented or unknown causes of readmission, or who did not undergo surgery or who underwent local tumor destruction alone were excluded from the analysis. Readmissions within 60 days for planned interventions, including adjuvant therapies, were not counted as readmissions in this analysis. Demographic data such as age, sex, race, marital status, date of first admission, date of discharge, and date of return were also gathered. We also reviewed the records for any history of chemotherapy or radiotherapy. Preoperative serum albumin levels, white blood cell counts, platelet counts, and hemoglobin levels were also collected. Moreover, procedure types included local excisions; wide excisions (including hemiglossectomies and partial glossectomies); and radical excisions (including total glossectomies and any resections in continuity with the maxilla, mandible, or other adjacent structures). The need for dissection, pathological T and N classifications, tumor grade, and primary tumor site were included in the analysis. Neck dissection was reported as “performed” or “not performed”. Tumor stage was determined by an attending physician at the reporting institution by the American Joint Committee on Cancer Eighth edition guidelines for pathological staging; T4, T4A, and T4B were combined into “T4”, and the N classification was divided into N0, N1, and N2+. The primary site of a tumor was identified using the International Classification of Diseases for Oncology, Third Edition topography codes. The primary site was classified into the tongue (codes C020–9), lip (C000–9), floor of mouth (C040–9), gum and hard palate (C030–9 and C050), retromolar trigone (C062), buccal mucosa (C060), and other parts of the mouth, such as the vestibule of the mouth and tumors of multiple or unknown sites. The Cumulative Illness Rating Scale (CIRS) and the American Society of Anesthesiology (ASA) score were used to assess the patients’ comorbidities. The CIRS is a comorbidity scale that analyzes the disease burden across 13 body systems ( 8 ). The data were subsequently entered into Google Forms and subsequently exported to Excel 16.0. Statistical analysis was performed using the Statistical Package for the Social Sciences for Windows version 21.0 (IBM SPSS Statistics), with P < 0.05 indicating statistical significance. Continuous variables are expressed as the means and standard deviations (SDs) or medians with interquartile ranges (IQRs) depending on the distribution. Categorical variables are summarized using numbers and frequencies. Student's t tests were performed to compare means. The Mann‒Whitney U test was used to compare medians, while the chi-square test was used to compare frequencies. Variables with significant relationships according to univariate analysis were included in multivariate analysis. Results The characteristics of the 93 patients who met the study criteria are summarized in Table 1 . Nine patients (9.70%) were readmitted within 60 days after discharge. The mean time to hospital readmission was 22.11 ± 11.65 days (range 6–56 days). Table 2 shows the causes of readmission; the most common reason was surgical site infection (33.33%), followed by wound bleeding (25%). Table 1 Patients, disease, and treatment baseline characteristics. Variable Included (n = 93) Age in years Mean ± SD 48.21 ± 15.41 Gender (n, %) Male 53, 56.99% Female 40, 43.01% Marital status (n, %) Married 86, 92.47% Unmarried 7, 7.53% Ethnicity (n, %) Arab 27, 29.03% Asian 36, 38.71% African 30, 32.26% Length of primary stay in days Median, IQR 12, (5–17) Time to readmission in days Mean ± SD 22.11 ± 11.65 CIRS Mean ± SD 3.57 ± 3.23 ASA Mean ± SD 2.18 ± 0.83 Chemotherapy and/or radiotherapy (n, %) Chemotherapy 9, 9.70% Radiotherapy 14, 15.10% Chemoradiotherapy 19, 20.40% Neither 51, 54.80% T classification (n, %) T1 40, 43.01% T2 28, 29.03% T3 7, 7.53% T4 18, 19.35% N classification (n, %) N0 58, 62.37% N1 11, 11.83% N2+ 24, 25.81% Site (n, %) Tongue 36, 38.71% Lip 9, 9.68% Floor of mouth 18, 19.35% Gum/hard palate 11, 11.83% Retromolar trigone 5, 5.38% Buccal mucosa 7, 7.53% Other mouth 7, 7.53% Procedure type Local excision 37, 39.78% Wide excision 40, 43.01% Radical excision 16, 17.20% Neck dissection Performed 37, 39.78% Not performed 56, 60.22% Duration of surgery in minutes Mean ± SD 365.33 ± 290.24 Table 2 Causes of readmission causes Numbers Rates (%) Surgical site infection 3 33.33 Wound bleeding 2 22.22 Gastrointestinal: nausea, vomiting 1 11.11 Equipment issues: tracheostomy, surgical drain 1 11.11 Decreased oral intake 1 11.11 Wound dehiscence 1 11.11 According to the univariate analysis (Table 3 ), patients with the highest risk of unplanned readmission were unmarried (P < 0.0001), of African ethnicity (P = 0.009), and with T4 disease (P < 0.0001). Patients who underwent radical excision (P = 0.002) or radiotherapy (P = 0.033) were more likely to be readmitted. A higher ASA score (P = 0.005) and CIRS score (P = 0.028), lower preoperative serum albumin (P = 0.005), and greater neutrophil count were significant risk factors (P = 0.029). Table 3 Univariate analysis of factors associated with 60-day readmission. Variable Readmitted Nonreadmitted P value Age in years Mean ± SD 50.56 ± 10.57 48.95 ± 17.42 0.779 Gender (n, %) Male 8, 88.90% 50, 59.50% 0.171 Female 1, 11.10% 34, 40.50% Marital status (n, %) Married 2, 22.20% 84, 100% < 0.0001 Unmarried 7, 77.80% 0, 0% Ethnicity (n, %) Arab 1, 11.10% 26, 31% 0.009 Asian 1, 11.10% 35, 41.7% African 7, 77.80% 23, 27.4% Length of primary stay in days Mean ± SD 16.56 ± 3.63 11.71 ± 1.40 0.242 CIRS Mean ± SD 7.22 ± 4.12 3.18 ± 2.88 ASA Mean ± SD 3 ± 0.71 2.10 ± 0.80 0.005 Preoperative serum albumin (g/L) Mean ± SD 20.5 ± 7.88 33.92 (9.15) 0.005 Preoperative white blood cell count (K/µL) Mean ± SD 8.21 ± 3.72 7.51 ± 3.67 0.606 Preoperative neutrophils (K/µL) Mean ± SD 4.79 ± 3.71 3.65 ± 2.13 0.029 Preoperative lymphocytes (K/µL) Mean ± SD 2.15 ± 0.79 2.31 ± 0.81 0.681 Preoperative platelets (K/µL) Mean ± SD 273.78 ± 52.15 276.02 ± 95.03 0.913 Preoperative hemoglobin (g/dL) Mean ± SD 12.71 ± 1.88 12.76 ± 1.63 0.937 Chemotherapy (n, %) Yes 0, 0% 14, 16.70% 0.401 No 9, 100% 70, 83.30% Radiotherapy Yes 4, 44.40% 13, 15.50% 0.033 No 5, 55.60% 71, 84.50% T classification (n, %) T1 0, 0% 40, 47.60% < 0.0001 T2 0, 0% 28, 33.30% T3 2, 22.20% 5, 6% T4 7, 77.80% 11, 13.10% N classification (n, %) N0 1, 11.10% 57, 67.90% 0.003 N1 3, 33.30% 8, 9.50% N2+ 5, 55.60% 19, 22.60% Site (n, %) Tongue 3, 33.33% 33, 39.29% 0.679 Lip 2, 22.22% 7, 8.33% Floor of mouth 2, 22.22% 16, 19.05% Gum/hard palate 1, 11.11% 10, 11.91% Retromolar trigone 0, 0% 5, 5.95% Buccal mucosa 1, 11.11% 6, 7.14% Other mouth 0, 0% 7, 8.33% Procedure type Local excision 0, 0% 37, 44% 0.002 Wide excision 4, 44.40% 36, 42.90% Radical excision 5, 55.60% 11, 13.10% Neck dissection Performed 6, 66.70% 31, 36.90% 0.083 Duration of surgery in minutes Mean ± SD 449.33 ± 388.14 356.33 ± 279.29 0.502 On multivariate regression analysis, significant predictors were being unmarried [odds ratio (OR) = 0.24; 95% confidence interval (CI): 0.08–0.39; P = 0.003]; having T4 disease (OR = 0.14; 95% CI: 0.05–0.23; P = 0.004); having a higher CIRS (OR = 0.83; 95% CI: 0.71–0.96; P = 0.011); having radical excisions (OR = 0.11; 95% CI: 0.05–0.16; P = 0.028); having a higher ASA (OR = 0.02; 95% CI: 0.002–0.03; P = 0.029); having a lower preoperative serum albumin concentration (OR = 0.11; 95% CI: 0.05–0.16; P = 0.028); and having higher neutrophil counts (OR = 0.05; 95% CI: 0.01–0.10; P = 0.03). Discussion Enhancing postoperative outcomes is a crucial objective in all surgical fields to achieve efficient oncologic outcomes ( 9 ). To the authors’ knowledge, this is the first paper that describes the 60-day readmission rate after surgery for oral cancer in the Middle East. The overall unplanned readmission rate in our sample was 9.70%, comparable to the readmission rates following most head and neck surgeries. Graboyes et al. reported a readmission rate of 7.30% for all otolaryngological procedures ( 10 ). Chaudhary et al. reported a rate of 14.10% after laryngeal and oropharyngeal cancer surgery ( 11 ). Factors associated with unplanned readmission after oral cavity squamous cell carcinoma surgery included divorce, radical surgery, and T4 disease. However, patients with these risk factors could benefit from additional monitoring. The methods of preventing postoperative readmission may be complex, even with targeted interventions. Notably, advanced T classification was linked to higher rates of readmission. N classification, however, was not. This finding suggested that the T classification might be more helpful in stratifying risk in the early postoperative phase than in terms of the overall stage. African ethnicity was associated with readmission in univariate analysis but not multivariate analysis. This implies that relationships with other covariates linked to readmission may cause higher readmission rates in this group. For example, African patients may be more likely to present with more advanced disease with more comorbidities and less access to healthcare, leading to poorer outcomes and unplanned readmissions. Several studies have proposed comprehensive approaches to lower surgical readmission rates in all surgical specialties. These approaches include preventing surgical site infections and providing appropriate discharge planning, follow-up care, and communication between hospital-based care teams and outpatient providers ( 12 – 15 ). However, practices for immediate postoperative care differ greatly depending on the surgical procedure, and there are no specific guidelines for the postoperative management of patients with oral cancer ( 16 , 17 ). Our findings suggest that patients with stage T4 oral cavity tumors who are receiving radiotherapy or radical surgery may be more susceptible to readmission and could thus benefit from targeted delayed discharge, extensive postdischarge observation, and early follow-up. To lower the readmission rate, these focused interventions may be included in future guidelines for the postoperative management of patients with cancers of the oral cavity. Additionally, individual facilities may benefit from monitoring readmissions and creating policies that eliminate the leading causes of these incidents at the institutional level. Preoperative lower serum albumin concentrations and higher neutrophil counts significantly predict hospital return. Other studies have shown that preoperative hypoalbuminemia and neutrophilia are associated with increased morbidity, mortality, and postoperative complications, especially infections ( 18 – 21 ). Our study showed consistent results, as surgical site infection was the most common cause of hospital readmission after oral SCC surgery. In acute illness and injury, albumin levels decrease as the liver shifts protein synthesis from visceral proteins to acute-phase reactant proteins ( 22 – 25 ). Thus, these markers may serve as diagnostic tools for underlying systemic inflammation. The comorbidities of the patients and their predictive value for readmission following oral cancer surgery were assessed in this study using two validated comorbidity indices. Within 60 days of discharge, both scores were highly predictive of readmission. Earlier studies have established that the ASA score is positively correlated with higher readmission rates and strongly predicts readmission ( 26 – 28 ). Higher scores indicate declining baseline health. The CIRS comorbidity score has also been applied to patients with head and neck cancer in the past ( 8 , 26 , 29 ). It is common knowledge that long-term exposure to risk factors such as tobacco use contributes to an increased number of comorbidities in patients with head and neck cancer ( 30 , 31 ). Unplanned readmissions may be decreased in patients with high baseline health burdens by more thorough and attentive postsurgery follow-ups. Based on our findings, patients who were widowed, separated, or single had higher readmission rates. This result is consistent with prior research showing a link between acute care requirements and social support. In contrast to other family members, marital support has been shown by Wachtel et al. to be a substantial protective factor against unanticipated hospital return following discharge ( 32 ). Separation or divorce has been demonstrated to be an independent risk factor for hospital readmission in another study involving patients receiving surgery for laryngeal and oropharyngeal cancer ( 11 ). These results imply that treatments aimed at preventing unanticipated readmission following hospital discharge should focus on a high-risk population. By extending the analysis period from the customary 30 days following surgery to 60 days, we present unique and exclusive data regarding the causes of unexpected hospital readmission. The study was conducted in a tertiary referral center in the western region of Saudi Arabia. The hospital receives many cases from remote areas, which could hinder early follow-up due to transportation and referral issues. Therefore, we would be better able to comprehend the actual rate of unanticipated hospital readmission following oral cancer surgery if the study period was extended to 60 days after discharge. Limitations Nonetheless, several limitations of this study should be kept in mind when interpreting its results. We may not be able to generalize our results as much because our study was restricted to one region. Although this retrospective analysis can identify patients targeted for interventions to lower mortality and early readmission, prospective trials are needed to ascertain whether these interventions will improve outcomes. Moreover, retrospective studies risk inaccuracies during data collection due to missing significant data, such as simple demographic data. Furthermore, the diversity of surgeons and varied expertise can impact the accuracy of our results. Conclusions One in every ten patients will be readmitted following oral cancer surgery. The most common cause is surgical site infection. Significant predictors included T4 disease, preoperative hypoalbuminemia, higher neutrophil counts, unmarried status, extensive surgery, and higher baseline comorbidity indices. Future initiatives and guidelines to lower readmission rates might focus on high-risk patients and involve earlier follow-up, more rigorous postdischarge monitoring, and delayed discharge. Abbreviations ASA American Society of Anesthesiology CIRS Cumulative Illness Rating Scale SD Standard deviation IQR Interquartile range IRB Institutional Review Board Declarations Acknowledgments: The authors acknowledge the permission granted by the other consultants to enroll their patients in the study. Funding: This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors. Contributions: Conceptualization: AR, AA and SA; methodology: AA, NM, and OA; software: SM, NM, SA, and MA; validation: AA, AR, and SA; formal analysis: AA, NM, and OA; investigation: MA and SA; resources: SM and NM; data curation: OA; writing—original draft preparation: AA, NM, SM, OA, AR, and MA; writing—review and editing: AA and AR; visualization: SM; supervision: AR and SA; project administration: AR and SA. All the authors have read and agreed to publish the current version of the manuscript. Ethics declarations: All patients signed an informed written consent for their contribution to the research (collecting and publishing data) prior to any data collection. The study was approved by the Biomedical Ethics Research Committee at King Abdulaziz University, Jeddah, Saudi Arabia, and was conducted in accordance with the ethical standards of the Declaration of Helsinki. Consent for publication: Not applicable. Availability of data and materials: The data were collected throughout 2023 from the hospital’s Phoenix system and patients’ paper-based records and can be provided upon request for appropriate reasons. Competing interests: The authors declare no competing interests. References Ferlay J, Colombet M, Soerjomataram I, Mathers C, Parkin DM, Piñeros M, et al. Estimating the global cancer incidence and mortality in 2018: GLOBOCAN sources and methods. Int J Cancer. 2019;144(8):1941–53. Alshehri BM. Trends in the incidence of oral cancer in Saudi Arabia from 1994 to 2015. World J Surg Oncol. 2020;18(1):217. Campana JP, Meyers AD. The surgical management of oral cancer. Otolaryngol Clin North Am. 2006;39(2):331–48. Katta P, Agarwal A, Saifi AM, Yadav A. Analysis of postoperative complications of oral cavity cancer: A cohort study. Oral Oncol Rep. 2023;6:100038. Schwam ZG, Sosa JA, Roman S, Judson BL. Complications and mortality following surgery for oral cavity cancer: analysis of 408 cases. Laryngoscope. 2015;125(8):1869–73. Luryi AL, Chen MM, Mehra S, Roman SA, Sosa JA, Judson BL. Hospital readmission and 30-day mortality after surgery for oral cavity cancer: Analysis of 21,681 cases. Head Neck. 2016;38(S1):E221–E6. Thiagarajan S, Sawhney S, Jain S, Chakraborthy A, Menon N, Gupta A, et al. Factors predisposing to the Unplanned Hospital Readmission (UHR) in patients undergoing surgery for Oral Cavity Squamous Cell Carcinoma (OSCC): Experience from a tertiary cancer centre. Indian J Surg Oncol. 2020;11:475–81. Linn BS, Linn MW, Gurel L. Cumulative illness rating scale. J Am Geriatr Soc. 1968;16(5):622–6. Hansen LO, Young RS, Hinami K, Leung A, Williams MV. Interventions to reduce 30-day rehospitalization: a systematic review. Ann Intern Med. 2011;155(8):520–8. Graboyes EM, Liou T-N, Kallogjeri D, Nussenbaum B, Diaz JA. Risk factors for unplanned hospital readmission in otolaryngology patients. Otolaryngology–Head Neck Surg. 2013;149(4):562–71. Chaudhary H, Stewart CM, Webster K, Herbert RJ, Frick KD, Eisele DW, et al. Readmission following primary surgery for larynx and oropharynx cancer in the elderly. Laryngoscope. 2017;127(3):631–41. Brooke BS, De Martino RR, Girotti M, Dimick JB, Goodney PP. Developing strategies for predicting and preventing readmissions in vascular surgery. J Vasc Surg. 2012;56(2):556–62. Giordano A, Scalvini S, Zanelli E, Corrà U, Longobardi GL, Ricci VA, et al. Multicenter randomised trial on home-based telemanagement to prevent hospital readmission of patients with chronic heart failure. Int J Cardiol. 2009;131(2):192–9. Bratzler DW, Hunt DR. The surgical infection prevention and surgical care improvement projects: national initiatives to improve outcomes for patients having surgery. Clin Infect Dis. 2006;43(3):322–30. Hansen LO, Greenwald JL, Budnitz T, Howell E, Halasyamani L, Maynard G, et al. Project BOOST: effectiveness of a multihospital effort to reduce rehospitalization. J Hosp Med. 2013;8(8):421–7. Luryi AL, Chen MM, Mehra S, Roman SA, Sosa JA, Judson BL. Hospital readmission and 30-day mortality after surgery for oral cavity cancer: Analysis of 21,681 cases. Head Neck. 2016;38(Suppl 1):E221–6. Dimick JB, Pronovost PJ, Cowan JA Jr., Lipsett PA, Stanley JC, Upchurch GR. Jr. Variation in postoperative complication rates after high-risk surgery in the United States. Surgery. 2003;134(4):534–40. discussion 40 – 1. Bone RC, Sibbald WJ, Sprung CL. The ACCP-SCCM consensus conference on sepsis and organ failure. Chest. 1992;101(6):1481-3. Gibbs J, Cull W, Henderson W, Daley J, Hur K, Khuri SF. Preoperative serum albumin level as a predictor of operative mortality and morbidity: results from the National VA Surgical Risk Study. Arch Surg. 1999;134(1):36–42. Aizenshtein A, Kachel E, Liza GR, Hijazi B, Blum A. Effects of Preoperative WBC Count on Post-CABG Surgery Clinical Outcome. South Med J. 2020;113(6):305–10. Jamali SA, Turnbull MT, Kanekiyo T, Vishnu P, Zubair AC, Raper CC, et al. Elevated Neutrophil-Lymphocyte Ratio is Predictive of Poor Outcomes Following Aneurysmal Subarachnoid Hemorrhage. J Stroke Cerebrovasc Dis. 2020;29(4):104631. Phillips A, Shaper AG, Whincup PH. Association between serum albumin and mortality from cardiovascular disease, cancer, and other causes. Lancet. 1989;2(8677):1434–6. Sganga G, Siegel JH, Brown G, Coleman B, Wiles CE 3rd, Belzberg H, et al. Reprioritization of hepatic plasma protein release in trauma and sepsis. Arch Surg. 1985;120(2):187–99. Dowd PS, Heatley RV. The influence of undernutrition on immunity. Clin Sci (Lond). 1984;66(3):241–8. Rammal A, Alqutub A, Alsulami O, Mozahim N, Mozahim S, Awadh M, et al. Total laryngectomy and readmission: causes, rates and predictors. BMC Res Notes. 2023;16(1):377. Wu V, Hall SF. Rates and causes of 30-day readmission and emergency room utilization following head and neck surgery. J Otolaryngol - Head Neck Surg. 2018;47(1):36. Merkow RP, Ju MH, Chung JW, Hall BL, Cohen ME, Williams MV, et al. Underlying reasons associated with hospital readmission following surgery in the United States. JAMA. 2015;313(5):483–95. AlDardeir N, Alzhrani G, Alqutub A, Kabli R, Sait D, Alsaeed R, et al. Rates and Causes of Readmission Within 60 Days Following Hysterectomy in a Tertiary Care Center in Saudi Arabia. Cureus. 2023;15(3):e36500. Castro MA, Dedivitis RA, Ribeiro KC. Comorbidity measurement in patients with laryngeal squamous cell carcinoma. ORL. 2007;69(3):146–52. Hashibe M, Brennan P, Benhamou S, Castellsague X, Chen C, Curado MP, et al. Alcohol drinking in never users of tobacco, cigarette smoking in never drinkers, and the risk of head and neck cancer: pooled analysis in the International Head and Neck Cancer Epidemiology Consortium. J Natl Cancer Inst. 2007;99(10):777–89. Blot WJ, McLaughlin JK, Winn DM, Austin DF, Greenberg RS, Preston-Martin S, et al. Smoking and drinking in relation to oral and pharyngeal cancer. Cancer Res. 1988;48(11):3282–7. Wachtel TJ, Derby C, Fulton JP. Predicting the outcome of hospitalization for elderly persons: home versus nursing home. South Med J. 1984;77(10):1283–5. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-3946396","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Short Report","associatedPublications":[],"authors":[{"id":272599195,"identity":"9f40d1b4-cb95-4473-853b-88cc68b1ff5a","order_by":0,"name":"Almoaidbellah Rammal","email":"","orcid":"","institution":"King Abdulaziz University","correspondingAuthor":false,"prefix":"","firstName":"Almoaidbellah","middleName":"","lastName":"Rammal","suffix":""},{"id":272599196,"identity":"995f39e3-582c-46b1-99f8-134401055c2d","order_by":1,"name":"Abdulsalam Alqutub","email":"data:image/png;base64,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","orcid":"","institution":"King Abdulaziz University","correspondingAuthor":true,"prefix":"","firstName":"Abdulsalam","middleName":"","lastName":"Alqutub","suffix":""},{"id":272599197,"identity":"1f6c26dc-8e89-445b-bcd7-4a5429bdb687","order_by":2,"name":"Omar Alsulami","email":"","orcid":"","institution":"King Abdulaziz University","correspondingAuthor":false,"prefix":"","firstName":"Omar","middleName":"","lastName":"Alsulami","suffix":""},{"id":272599198,"identity":"734854ce-0b37-4a60-a478-c8f27f145a9f","order_by":3,"name":"Naif Mozahim","email":"","orcid":"","institution":"King Abdulaziz University","correspondingAuthor":false,"prefix":"","firstName":"Naif","middleName":"","lastName":"Mozahim","suffix":""},{"id":272599199,"identity":"da83cda9-fc96-4a81-a974-359a4b547400","order_by":4,"name":"Sarah Mozahim","email":"","orcid":"","institution":"King Abdulaziz University","correspondingAuthor":false,"prefix":"","firstName":"Sarah","middleName":"","lastName":"Mozahim","suffix":""},{"id":272599200,"identity":"005a3b91-6e69-47ee-8be5-b28621b86d48","order_by":5,"name":"Mohammed Awadh","email":"","orcid":"","institution":"King Abdulaziz University","correspondingAuthor":false,"prefix":"","firstName":"Mohammed","middleName":"","lastName":"Awadh","suffix":""},{"id":272599201,"identity":"8cfbdcda-f3ca-488c-b4b1-5b50b22616ad","order_by":6,"name":"Sadiq Alqutub","email":"","orcid":"","institution":"King Abdulaziz University","correspondingAuthor":false,"prefix":"","firstName":"Sadiq","middleName":"","lastName":"Alqutub","suffix":""}],"badges":[],"createdAt":"2024-02-10 17:16:40","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3946396/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3946396/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":55615229,"identity":"a9107133-84c2-4ed3-b709-73d4dc99d2bb","added_by":"auto","created_at":"2024-04-30 15:15:21","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":553711,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3946396/v1/97857b11-6e53-4c77-9b36-5ad12cd620ab.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Oral cavity squamous cell carcinoma and readmission: rates, causes, and risk factors","fulltext":[{"header":"Introduction","content":"\u003cp\u003eOral cancer is a prevalent form of cancer found worldwide (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). In 2015, 1.6% of total cancer cases were female, and 1.9% were male in Saudi Arabia (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). Oral cavity malignancies encompass a domain within the head and neck oncology field characterized by intriguing facets in terms of their management. Despite witnessing a substantial shift in the therapeutic approach for various head and neck neoplasms, wherein primary chemoradiation has gained prominence, its utilization in the context of oral cavity cancers remains relatively infrequent (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). Despite the use of proficient surgical methodologies in oral oncologic surgeries and the presence of highly skilled surgeons, the occurrence of postoperative complications can notably influence the overall outcome of surgical interventions. Importantly, from a surgical standpoint, the preoperative condition of patients, in conjunction with the selected operative approach, significantly contributes to the likelihood of encountering these complications. These complications include surgical site bleeding, infections, pain, and wound dehiscence (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). These complications can adversely influence patient quality of life, result in the postponement of adjuvant therapy, and increase the need for hospital readmission, resulting in an increased rate of subsequent mortality.\u003c/p\u003e \u003cp\u003eThe published material regarding the rate of readmission after oral oncologic surgery ranged from 3.2-5%, with postoperative flap-related issues and percutaneous fistula and wound infection as the most common causes of readmission (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eBecause of the lack of similar reports, the rates and risk factors for readmission after oral oncologic surgery need to be clearly described in the Saudi population. This study aimed to determine the incidence, risk factors, and most likely complications that cause readmission following oral oncologic surgery within 60 days of hospital discharge at a tertiary academic care center in Jeddah, Saudi Arabia.\u003c/p\u003e"},{"header":"Methodology","content":"\u003cp\u003e After receiving ethical approval from the Institutional Review Board (IRB), we reviewed the records of patients who underwent oral oncologic surgery between 2008 and 2023.\u003c/p\u003e \u003cp\u003eThe causes of readmission were extracted as the final diagnosis from the medical records system. Only the first episode of unplanned returns was acquired if more than one episode was identified within the first 60 days after discharge.\u003c/p\u003e \u003cp\u003e We included all patients who underwent oral oncologic surgery for squamous cell carcinoma at our center between 2008 and 2023. Patients with multiple malignant primary tumors, undocumented or unknown causes of readmission, or who did not undergo surgery or who underwent local tumor destruction alone were excluded from the analysis. Readmissions within 60 days for planned interventions, including adjuvant therapies, were not counted as readmissions in this analysis.\u003c/p\u003e \u003cp\u003eDemographic data such as age, sex, race, marital status, date of first admission, date of discharge, and date of return were also gathered.\u003c/p\u003e \u003cp\u003eWe also reviewed the records for any history of chemotherapy or radiotherapy.\u003c/p\u003e \u003cp\u003ePreoperative serum albumin levels, white blood cell counts, platelet counts, and hemoglobin levels were also collected.\u003c/p\u003e \u003cp\u003eMoreover, procedure types included local excisions; wide excisions (including hemiglossectomies and partial glossectomies); and radical excisions (including total glossectomies and any resections in continuity with the maxilla, mandible, or other adjacent structures). The need for dissection, pathological T and N classifications, tumor grade, and primary tumor site were included in the analysis. Neck dissection was reported as \u0026ldquo;performed\u0026rdquo; or \u0026ldquo;not performed\u0026rdquo;. Tumor stage was determined by an attending physician at the reporting institution by the American Joint Committee on Cancer Eighth edition guidelines for pathological staging; T4, T4A, and T4B were combined into \u0026ldquo;T4\u0026rdquo;, and the N classification was divided into N0, N1, and N2+.\u003c/p\u003e \u003cp\u003eThe primary site of a tumor was identified using the International Classification of Diseases for Oncology, Third Edition topography codes. The primary site was classified into the tongue (codes C020\u0026ndash;9), lip (C000\u0026ndash;9), floor of mouth (C040\u0026ndash;9), gum and hard palate (C030\u0026ndash;9 and C050), retromolar trigone (C062), buccal mucosa (C060), and other parts of the mouth, such as the vestibule of the mouth and tumors of multiple or unknown sites.\u003c/p\u003e \u003cp\u003eThe Cumulative Illness Rating Scale (CIRS) and the American Society of Anesthesiology (ASA) score were used to assess the patients\u0026rsquo; comorbidities. The CIRS is a comorbidity scale that analyzes the disease burden across 13 body systems (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe data were subsequently entered into Google Forms and subsequently exported to Excel 16.0. Statistical analysis was performed using the Statistical Package for the Social Sciences for Windows version 21.0 (IBM SPSS Statistics), with P\u0026thinsp;\u0026lt;\u0026thinsp;0.05 indicating statistical significance. Continuous variables are expressed as the means and standard deviations (SDs) or medians with interquartile ranges (IQRs) depending on the distribution. Categorical variables are summarized using numbers and frequencies. Student's t tests were performed to compare means. The Mann‒Whitney U test was used to compare medians, while the chi-square test was used to compare frequencies. Variables with significant relationships according to univariate analysis were included in multivariate analysis.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eThe characteristics of the 93 patients who met the study criteria are summarized in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Nine patients (9.70%) were readmitted within 60 days after discharge. The mean time to hospital readmission was 22.11\u0026thinsp;\u0026plusmn;\u0026thinsp;11.65 days (range 6\u0026ndash;56 days). Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e shows the causes of readmission; the most common reason was surgical site infection (33.33%), followed by wound bleeding (25%).\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\u003ePatients, disease, and treatment baseline characteristics.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\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 \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\u003eIncluded (n\u0026thinsp;=\u0026thinsp;93)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge in years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e48.21\u0026thinsp;\u0026plusmn;\u0026thinsp;15.41\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender (n, %)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e53, 56.99%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e40, 43.01%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarital status (n, %)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarried\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e86, 92.47%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnmarried\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7, 7.53%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEthnicity (n, %)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eArab\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e27, 29.03%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAsian\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e36, 38.71%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAfrican\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30, 32.26%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLength of primary stay in days\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedian, IQR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12, (5\u0026ndash;17)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTime to readmission in days\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e22.11\u0026thinsp;\u0026plusmn;\u0026thinsp;11.65\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCIRS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.57\u0026thinsp;\u0026plusmn;\u0026thinsp;3.23\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eASA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.18\u0026thinsp;\u0026plusmn;\u0026thinsp;0.83\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChemotherapy and/or radiotherapy (n, %)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChemotherapy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9, 9.70%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRadiotherapy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14, 15.10%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChemoradiotherapy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e19, 20.40%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNeither\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e51, 54.80%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT classification (n,\u0026nbsp;%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e40, 43.01%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28, 29.03%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7, 7.53%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18, 19.35%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eN classification (n,\u0026nbsp;%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eN0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e58, 62.37%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eN1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11, 11.83%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eN2+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e24, 25.81%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSite (n, %)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTongue\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e36, 38.71%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLip\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9, 9.68%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFloor of mouth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18, 19.35%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGum/hard palate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11, 11.83%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRetromolar trigone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5, 5.38%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBuccal mucosa\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7, 7.53%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther mouth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7, 7.53%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProcedure type\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLocal excision\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e37, 39.78%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWide excision\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e40, 43.01%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRadical excision\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16, 17.20%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNeck dissection\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePerformed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e37, 39.78%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNot performed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e56, 60.22%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDuration of surgery in minutes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e365.33\u0026thinsp;\u0026plusmn;\u0026thinsp;290.24\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\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\u003eCauses of readmission\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\u003ecauses\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNumbers\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRates (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSurgical site infection\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e33.33\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWound bleeding\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e22.22\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGastrointestinal: nausea, vomiting\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11.11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEquipment issues: tracheostomy, surgical drain\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11.11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDecreased oral intake\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11.11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWound dehiscence\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11.11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eAccording to the univariate analysis (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e), patients with the highest risk of unplanned readmission were unmarried (P\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), of African ethnicity (P\u0026thinsp;=\u0026thinsp;0.009), and with T4 disease (P\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). Patients who underwent radical excision (P\u0026thinsp;=\u0026thinsp;0.002) or radiotherapy (P\u0026thinsp;=\u0026thinsp;0.033) were more likely to be readmitted. A higher ASA score (P\u0026thinsp;=\u0026thinsp;0.005) and CIRS score (P\u0026thinsp;=\u0026thinsp;0.028), lower preoperative serum albumin (P\u0026thinsp;=\u0026thinsp;0.005), and greater neutrophil count were significant risk factors (P\u0026thinsp;=\u0026thinsp;0.029).\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\u003eUnivariate analysis of factors associated with 60-day readmission.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\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 \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\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\u003eReadmitted\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNonreadmitted\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge in years\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 \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e50.56\u0026thinsp;\u0026plusmn;\u0026thinsp;10.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e48.95\u0026thinsp;\u0026plusmn;\u0026thinsp;17.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.779\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender (n, %)\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 \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8, 88.90%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e50, 59.50%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.171\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1, 11.10%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e34, 40.50%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarital status (n, %)\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 \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarried\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2, 22.20%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e84, 100%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnmarried\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7, 77.80%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0, 0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEthnicity (n, %)\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 \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eArab\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1, 11.10%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26, 31%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.009\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAsian\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1, 11.10%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e35, 41.7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAfrican\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7, 77.80%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23, 27.4%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLength of primary stay in days\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 \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16.56\u0026thinsp;\u0026plusmn;\u0026thinsp;3.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11.71\u0026thinsp;\u0026plusmn;\u0026thinsp;1.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.242\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCIRS\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 \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.22\u0026thinsp;\u0026plusmn;\u0026thinsp;4.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.18\u0026thinsp;\u0026plusmn;\u0026thinsp;2.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eASA\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 \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3\u0026thinsp;\u0026plusmn;\u0026thinsp;0.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.10\u0026thinsp;\u0026plusmn;\u0026thinsp;0.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePreoperative serum albumin (g/L)\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 \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20.5\u0026thinsp;\u0026plusmn;\u0026thinsp;7.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e33.92 (9.15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePreoperative white blood cell count (K/\u0026micro;L)\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 \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.21\u0026thinsp;\u0026plusmn;\u0026thinsp;3.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.51\u0026thinsp;\u0026plusmn;\u0026thinsp;3.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.606\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePreoperative neutrophils (K/\u0026micro;L)\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 \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.79\u0026thinsp;\u0026plusmn;\u0026thinsp;3.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.65\u0026thinsp;\u0026plusmn;\u0026thinsp;2.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.029\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePreoperative lymphocytes (K/\u0026micro;L)\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 \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.15\u0026thinsp;\u0026plusmn;\u0026thinsp;0.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.31\u0026thinsp;\u0026plusmn;\u0026thinsp;0.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.681\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePreoperative platelets (K/\u0026micro;L)\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 \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e273.78\u0026thinsp;\u0026plusmn;\u0026thinsp;52.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e276.02\u0026thinsp;\u0026plusmn;\u0026thinsp;95.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.913\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePreoperative hemoglobin (g/dL)\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 \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12.71\u0026thinsp;\u0026plusmn;\u0026thinsp;1.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12.76\u0026thinsp;\u0026plusmn;\u0026thinsp;1.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.937\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChemotherapy (n, %)\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 \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\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\u003e14, 16.70%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.401\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9, 100%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e70, 83.30%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRadiotherapy\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 \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4, 44.40%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13, 15.50%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.033\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5, 55.60%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e71, 84.50%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT classification (n,\u0026nbsp;%)\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 \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT1\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\u003e40, 47.60%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT2\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\u003e28, 33.30%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2, 22.20%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5, 6%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7, 77.80%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11, 13.10%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eN classification (n,\u0026nbsp;%)\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 \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eN0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1, 11.10%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e57, 67.90%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eN1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3, 33.30%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8, 9.50%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eN2+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5, 55.60%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19, 22.60%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSite (n, %)\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 \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTongue\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3, 33.33%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e33, 39.29%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.679\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLip\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2, 22.22%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7, 8.33%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFloor of mouth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2, 22.22%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16, 19.05%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGum/hard palate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1, 11.11%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10, 11.91%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRetromolar trigone\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\u003e5, 5.95%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBuccal mucosa\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1, 11.11%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6, 7.14%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther mouth\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\u003e7, 8.33%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProcedure type\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 \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLocal excision\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\u003e37, 44%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWide excision\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4, 44.40%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e36, 42.90%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRadical excision\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5, 55.60%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11, 13.10%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNeck dissection\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 \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePerformed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6, 66.70%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31, 36.90%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.083\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDuration of surgery in minutes\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 \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e449.33\u0026thinsp;\u0026plusmn;\u0026thinsp;388.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e356.33\u0026thinsp;\u0026plusmn;\u0026thinsp;279.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.502\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eOn multivariate regression analysis, significant predictors were being unmarried [odds ratio (OR)\u0026thinsp;=\u0026thinsp;0.24; 95% confidence interval (CI): 0.08\u0026ndash;0.39; P\u0026thinsp;=\u0026thinsp;0.003]; having T4 disease (OR\u0026thinsp;=\u0026thinsp;0.14; 95% CI: 0.05\u0026ndash;0.23; P\u0026thinsp;=\u0026thinsp;0.004); having a higher CIRS (OR\u0026thinsp;=\u0026thinsp;0.83; 95% CI: 0.71\u0026ndash;0.96; P\u0026thinsp;=\u0026thinsp;0.011); having radical excisions (OR\u0026thinsp;=\u0026thinsp;0.11; 95% CI: 0.05\u0026ndash;0.16; P\u0026thinsp;=\u0026thinsp;0.028); having a higher ASA (OR\u0026thinsp;=\u0026thinsp;0.02; 95% CI: 0.002\u0026ndash;0.03; P\u0026thinsp;=\u0026thinsp;0.029); having a lower preoperative serum albumin concentration (OR\u0026thinsp;=\u0026thinsp;0.11; 95% CI: 0.05\u0026ndash;0.16; P\u0026thinsp;=\u0026thinsp;0.028); and having higher neutrophil counts (OR\u0026thinsp;=\u0026thinsp;0.05; 95% CI: 0.01\u0026ndash;0.10; P\u0026thinsp;=\u0026thinsp;0.03).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eEnhancing postoperative outcomes is a crucial objective in all surgical fields to achieve efficient oncologic outcomes (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). To the authors\u0026rsquo; knowledge, this is the first paper that describes the 60-day readmission rate after surgery for oral cancer in the Middle East. The overall unplanned readmission rate in our sample was 9.70%, comparable to the readmission rates following most head and neck surgeries. Graboyes et al. reported a readmission rate of 7.30% for all otolaryngological procedures (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). Chaudhary et al. reported a rate of 14.10% after laryngeal and oropharyngeal cancer surgery (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). Factors associated with unplanned readmission after oral cavity squamous cell carcinoma surgery included divorce, radical surgery, and T4 disease. However, patients with these risk factors could benefit from additional monitoring. The methods of preventing postoperative readmission may be complex, even with targeted interventions. Notably, advanced T classification was linked to higher rates of readmission. N classification, however, was not. This finding suggested that the T classification might be more helpful in stratifying risk in the early postoperative phase than in terms of the overall stage. African ethnicity was associated with readmission in univariate analysis but not multivariate analysis. This implies that relationships with other covariates linked to readmission may cause higher readmission rates in this group. For example, African patients may be more likely to present with more advanced disease with more comorbidities and less access to healthcare, leading to poorer outcomes and unplanned readmissions.\u003c/p\u003e \u003cp\u003eSeveral studies have proposed comprehensive approaches to lower surgical readmission rates in all surgical specialties. These approaches include preventing surgical site infections and providing appropriate discharge planning, follow-up care, and communication between hospital-based care teams and outpatient providers (\u003cspan additionalcitationids=\"CR13 CR14\" citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). However, practices for immediate postoperative care differ greatly depending on the surgical procedure, and there are no specific guidelines for the postoperative management of patients with oral cancer (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e). Our findings suggest that patients with stage T4 oral cavity tumors who are receiving radiotherapy or radical surgery may be more susceptible to readmission and could thus benefit from targeted delayed discharge, extensive postdischarge observation, and early follow-up. To lower the readmission rate, these focused interventions may be included in future guidelines for the postoperative management of patients with cancers of the oral cavity. Additionally, individual facilities may benefit from monitoring readmissions and creating policies that eliminate the leading causes of these incidents at the institutional level.\u003c/p\u003e \u003cp\u003ePreoperative lower serum albumin concentrations and higher neutrophil counts significantly predict hospital return. Other studies have shown that preoperative hypoalbuminemia and neutrophilia are associated with increased morbidity, mortality, and postoperative complications, especially infections (\u003cspan additionalcitationids=\"CR19 CR20\" citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e). Our study showed consistent results, as surgical site infection was the most common cause of hospital readmission after oral SCC surgery. In acute illness and injury, albumin levels decrease as the liver shifts protein synthesis from visceral proteins to acute-phase reactant proteins (\u003cspan additionalcitationids=\"CR23 CR24\" citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e). Thus, these markers may serve as diagnostic tools for underlying systemic inflammation.\u003c/p\u003e \u003cp\u003eThe comorbidities of the patients and their predictive value for readmission following oral cancer surgery were assessed in this study using two validated comorbidity indices. Within 60 days of discharge, both scores were highly predictive of readmission. Earlier studies have established that the ASA score is positively correlated with higher readmission rates and strongly predicts readmission (\u003cspan additionalcitationids=\"CR27\" citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e). Higher scores indicate declining baseline health. The CIRS comorbidity score has also been applied to patients with head and neck cancer in the past (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e). It is common knowledge that long-term exposure to risk factors such as tobacco use contributes to an increased number of comorbidities in patients with head and neck cancer (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e). Unplanned readmissions may be decreased in patients with high baseline health burdens by more thorough and attentive postsurgery follow-ups.\u003c/p\u003e \u003cp\u003eBased on our findings, patients who were widowed, separated, or single had higher readmission rates. This result is consistent with prior research showing a link between acute care requirements and social support. In contrast to other family members, marital support has been shown by Wachtel et al. to be a substantial protective factor against unanticipated hospital return following discharge (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e). Separation or divorce has been demonstrated to be an independent risk factor for hospital readmission in another study involving patients receiving surgery for laryngeal and oropharyngeal cancer (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). These results imply that treatments aimed at preventing unanticipated readmission following hospital discharge should focus on a high-risk population.\u003c/p\u003e \u003cp\u003eBy extending the analysis period from the customary 30 days following surgery to 60 days, we present unique and exclusive data regarding the causes of unexpected hospital readmission. The study was conducted in a tertiary referral center in the western region of Saudi Arabia. The hospital receives many cases from remote areas, which could hinder early follow-up due to transportation and referral issues. Therefore, we would be better able to comprehend the actual rate of unanticipated hospital readmission following oral cancer surgery if the study period was extended to 60 days after discharge.\u003c/p\u003e\n\u003ch3\u003eLimitations\u003c/h3\u003e\n\u003cp\u003eNonetheless, several limitations of this study should be kept in mind when interpreting its results. We may not be able to generalize our results as much because our study was restricted to one region. Although this retrospective analysis can identify patients targeted for interventions to lower mortality and early readmission, prospective trials are needed to ascertain whether these interventions will improve outcomes. Moreover, retrospective studies risk inaccuracies during data collection due to missing significant data, such as simple demographic data. Furthermore, the diversity of surgeons and varied expertise can impact the accuracy of our results.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eOne in every ten patients will be readmitted following oral cancer surgery. The most common cause is surgical site infection. Significant predictors included T4 disease, preoperative hypoalbuminemia, higher neutrophil counts, unmarried status, extensive surgery, and higher baseline comorbidity indices. Future initiatives and guidelines to lower readmission rates might focus on high-risk patients and involve earlier follow-up, more rigorous postdischarge monitoring, and delayed discharge.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eASA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAmerican Society of Anesthesiology\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCIRS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eCumulative Illness Rating Scale\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eStandard deviation\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eIQR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eInterquartile range\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eIRB\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eInstitutional Review Board\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors acknowledge the permission granted by\u0026nbsp;the\u0026nbsp;other consultants to enroll their patients\u0026nbsp;in\u0026nbsp;the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eContributions:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eConceptualization: AR, AA and SA; methodology: AA, NM, and OA; software: SM, NM, SA, and MA; validation: AA, AR, and SA; formal analysis: AA, NM, and OA; investigation: MA and SA; resources: SM and NM; data curation: OA; writing\u0026mdash;original draft preparation: AA, NM, SM, OA, AR, and MA; writing\u0026mdash;review and editing: AA and AR; visualization: SM; supervision: AR and SA; project administration:\u0026nbsp;AR and SA. All\u0026nbsp;the\u0026nbsp;authors have read and agreed to publish the current version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics declarations:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll patients signed an informed written consent for their contribution to\u0026nbsp;the\u0026nbsp;research (collecting and publishing data) prior to any data collection. The study was approved by the Biomedical Ethics Research Committee at King Abdulaziz University, Jeddah, Saudi Arabia, and was conducted in accordance with the ethical standards of the Declaration of Helsinki.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data\u0026nbsp;were collected throughout 2023 from the hospital\u0026rsquo;s Phoenix system and patients\u0026rsquo; paper-based records and can be provided upon request for appropriate reasons.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eFerlay J, Colombet M, Soerjomataram I, Mathers C, Parkin DM, Pi\u0026ntilde;eros M, et al. Estimating the global cancer incidence and mortality in 2018: GLOBOCAN sources and methods. Int J Cancer. 2019;144(8):1941\u0026ndash;53.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAlshehri BM. Trends in the incidence of oral cancer in Saudi Arabia from 1994 to 2015. World J Surg Oncol. 2020;18(1):217.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCampana JP, Meyers AD. The surgical management of oral cancer. Otolaryngol Clin North Am. 2006;39(2):331\u0026ndash;48.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKatta P, Agarwal A, Saifi AM, Yadav A. Analysis of postoperative complications of oral cavity cancer: A cohort study. Oral Oncol Rep. 2023;6:100038.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSchwam ZG, Sosa JA, Roman S, Judson BL. Complications and mortality following surgery for oral cavity cancer: analysis of 408 cases. Laryngoscope. 2015;125(8):1869\u0026ndash;73.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLuryi AL, Chen MM, Mehra S, Roman SA, Sosa JA, Judson BL. Hospital readmission and 30-day mortality after surgery for oral cavity cancer: Analysis of 21,681 cases. Head Neck. 2016;38(S1):E221\u0026ndash;E6.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eThiagarajan S, Sawhney S, Jain S, Chakraborthy A, Menon N, Gupta A, et al. Factors predisposing to the Unplanned Hospital Readmission (UHR) in patients undergoing surgery for Oral Cavity Squamous Cell Carcinoma (OSCC): Experience from a tertiary cancer centre. Indian J Surg Oncol. 2020;11:475\u0026ndash;81.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLinn BS, Linn MW, Gurel L. Cumulative illness rating scale. J Am Geriatr Soc. 1968;16(5):622\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHansen LO, Young RS, Hinami K, Leung A, Williams MV. Interventions to reduce 30-day rehospitalization: a systematic review. Ann Intern Med. 2011;155(8):520\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGraboyes EM, Liou T-N, Kallogjeri D, Nussenbaum B, Diaz JA. Risk factors for unplanned hospital readmission in otolaryngology patients. Otolaryngology\u0026ndash;Head Neck Surg. 2013;149(4):562\u0026ndash;71.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChaudhary H, Stewart CM, Webster K, Herbert RJ, Frick KD, Eisele DW, et al. Readmission following primary surgery for larynx and oropharynx cancer in the elderly. Laryngoscope. 2017;127(3):631\u0026ndash;41.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBrooke BS, De Martino RR, Girotti M, Dimick JB, Goodney PP. Developing strategies for predicting and preventing readmissions in vascular surgery. J Vasc Surg. 2012;56(2):556\u0026ndash;62.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGiordano A, Scalvini S, Zanelli E, Corr\u0026agrave; U, Longobardi GL, Ricci VA, et al. Multicenter randomised trial on home-based telemanagement to prevent hospital readmission of patients with chronic heart failure. Int J Cardiol. 2009;131(2):192\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBratzler DW, Hunt DR. The surgical infection prevention and surgical care improvement projects: national initiatives to improve outcomes for patients having surgery. Clin Infect Dis. 2006;43(3):322\u0026ndash;30.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHansen LO, Greenwald JL, Budnitz T, Howell E, Halasyamani L, Maynard G, et al. Project BOOST: effectiveness of a multihospital effort to reduce rehospitalization. J Hosp Med. 2013;8(8):421\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLuryi AL, Chen MM, Mehra S, Roman SA, Sosa JA, Judson BL. Hospital readmission and 30-day mortality after surgery for oral cavity cancer: Analysis of 21,681 cases. Head Neck. 2016;38(Suppl 1):E221\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDimick JB, Pronovost PJ, Cowan JA Jr., Lipsett PA, Stanley JC, Upchurch GR. Jr. Variation in postoperative complication rates after high-risk surgery in the United States. Surgery. 2003;134(4):534\u0026ndash;40. discussion 40\u0026thinsp;\u0026ndash;\u0026thinsp;1.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBone RC, Sibbald WJ, Sprung CL. The ACCP-SCCM consensus conference on sepsis and organ failure. Chest. 1992;101(6):1481-3.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGibbs J, Cull W, Henderson W, Daley J, Hur K, Khuri SF. Preoperative serum albumin level as a predictor of operative mortality and morbidity: results from the National VA Surgical Risk Study. Arch Surg. 1999;134(1):36\u0026ndash;42.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAizenshtein A, Kachel E, Liza GR, Hijazi B, Blum A. Effects of Preoperative WBC Count on Post-CABG Surgery Clinical Outcome. South Med J. 2020;113(6):305\u0026ndash;10.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJamali SA, Turnbull MT, Kanekiyo T, Vishnu P, Zubair AC, Raper CC, et al. Elevated Neutrophil-Lymphocyte Ratio is Predictive of Poor Outcomes Following Aneurysmal Subarachnoid Hemorrhage. J Stroke Cerebrovasc Dis. 2020;29(4):104631.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePhillips A, Shaper AG, Whincup PH. Association between serum albumin and mortality from cardiovascular disease, cancer, and other causes. Lancet. 1989;2(8677):1434\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSganga G, Siegel JH, Brown G, Coleman B, Wiles CE 3rd, Belzberg H, et al. Reprioritization of hepatic plasma protein release in trauma and sepsis. Arch Surg. 1985;120(2):187\u0026ndash;99.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDowd PS, Heatley RV. The influence of undernutrition on immunity. Clin Sci (Lond). 1984;66(3):241\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRammal A, Alqutub A, Alsulami O, Mozahim N, Mozahim S, Awadh M, et al. Total laryngectomy and readmission: causes, rates and predictors. BMC Res Notes. 2023;16(1):377.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWu V, Hall SF. Rates and causes of 30-day readmission and emergency room utilization following head and neck surgery. J Otolaryngol - Head Neck Surg. 2018;47(1):36.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMerkow RP, Ju MH, Chung JW, Hall BL, Cohen ME, Williams MV, et al. Underlying reasons associated with hospital readmission following surgery in the United States. JAMA. 2015;313(5):483\u0026ndash;95.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAlDardeir N, Alzhrani G, Alqutub A, Kabli R, Sait D, Alsaeed R, et al. Rates and Causes of Readmission Within 60 Days Following Hysterectomy in a Tertiary Care Center in Saudi Arabia. Cureus. 2023;15(3):e36500.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCastro MA, Dedivitis RA, Ribeiro KC. Comorbidity measurement in patients with laryngeal squamous cell carcinoma. ORL. 2007;69(3):146\u0026ndash;52.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHashibe M, Brennan P, Benhamou S, Castellsague X, Chen C, Curado MP, et al. Alcohol drinking in never users of tobacco, cigarette smoking in never drinkers, and the risk of head and neck cancer: pooled analysis in the International Head and Neck Cancer Epidemiology Consortium. J Natl Cancer Inst. 2007;99(10):777\u0026ndash;89.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBlot WJ, McLaughlin JK, Winn DM, Austin DF, Greenberg RS, Preston-Martin S, et al. Smoking and drinking in relation to oral and pharyngeal cancer. Cancer Res. 1988;48(11):3282\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWachtel TJ, Derby C, Fulton JP. Predicting the outcome of hospitalization for elderly persons: home versus nursing home. South Med J. 1984;77(10):1283\u0026ndash;5.\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":"Oral cancer, Hypoalbuminemia, Laryngectomy, Patient readmission, Retrospective studies, Surgical wound infection","lastPublishedDoi":"10.21203/rs.3.rs-3946396/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3946396/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eOral cancer is a prevalent form of cancer worldwide. Unplanned readmission exposes patients to hospital-acquired complications. The readmission rate is a metric for quality of care. We aimed to identify the rate, causes, and predictors of hospital readmission within 60 days after discharge following oral cancer surgery.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003e This 15-year retrospective study included all patients who underwent oral oncologic surgery at a single tertiary center between 2008 and 2023. Patient charts were reviewed for demographic information, comorbidities, and causes for readmission.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eOf the 93 patients who underwent oral oncologic surgery, nine (9.70%) were readmitted within 60 days after discharge. The most common reason for readmission was surgical site infection (33.33%), followed by wound bleeding (25%). The significant predictors were unmarried status (P\u0026thinsp;=\u0026thinsp;0.003), T4 disease status (P\u0026thinsp;=\u0026thinsp;0.004), a higher cumulative illness rating scale (CIRS) (P\u0026thinsp;=\u0026thinsp;0.011), radical excisions (P\u0026thinsp;=\u0026thinsp;0.028), a higher American Society of Anesthesiology (ASA) score (P\u0026thinsp;=\u0026thinsp;0.029), a lower preoperative serum albumin (P\u0026thinsp;=\u0026thinsp;0.028), and a greater neutrophil count (P\u0026thinsp;=\u0026thinsp;0.03).\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eOne in every ten patients was readmitted following oral cancer surgery. The most common cause is surgical site infection. Significant predictors included T4 disease, preoperative hypoalbuminemia, higher neutrophil counts, unmarried status, extensive surgery, and higher baseline comorbidity indices. Future guidelines to lower readmission rates should focus on high-risk patients and involve earlier follow-up, more rigorous postdischarge monitoring, and delayed discharge.\u003c/p\u003e","manuscriptTitle":"Oral cavity squamous cell carcinoma and readmission: rates, causes, and risk factors","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-02-14 17:33:51","doi":"10.21203/rs.3.rs-3946396/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":"55d277aa-9500-4103-ab73-6fdae6cb519c","owner":[],"postedDate":"February 14th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-04-30T15:15:07+00:00","versionOfRecord":[],"versionCreatedAt":"2024-02-14 17:33:51","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-3946396","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3946396","identity":"rs-3946396","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}