99mTc-GSA scintigraphy and modified albumin–bilirubin score can be complementary to ICG for predicting posthepatectomy liver failure

99mTc-GSA scintigraphy and modified albumin–bilirubin score can be complementary to ICG for predicting posthepatectomy liver failure | 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 Research Article 99mTc-GSA scintigraphy and modified albumin–bilirubin score can be complementary to ICG for predicting posthepatectomy liver failure Satoshi Mii, Takeshi Takahara, Susumu Shibasaki, Takuma Ishihara, and 6 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3997930/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 01 Nov, 2024 Read the published version in BMC Surgery → Version 1 posted 17 You are reading this latest preprint version Abstract Background: Posthepatectomy liver failure (PHLF) remains a severe complication after liver resection. This retrospective study investigated the correlation of three hepatic functional tests and whether 99mTc-galactosyl human serum albumin (99mTc-GSA) scintigraphy and modified albumin–bilirubin (ALBI) score are useful for predicting PHLF. Methods: A total of 413 consecutivepatients undergoing hepatectomies between January 2017 and December 2020 at our institution were enrolled in this retrospective cohort study. To evaluate preoperative hepatic functional reserve, modified ALBI grade, indocyanine green clearance (ICG-R15), and 99mTc-GSA scintigraphy (LHL15) were routinely examined before the scheduled hepatectomy. Based on the retrospective chart review, multivariate logistic regression analysis adjusted for confounding factors was performed to confirm that ALBI, ICG-R15, and LHL15 are independent risk factors for PHLF. Results: ICG-R15 and LHL15 were moderately correlated ( r = −0.61). However, the correlation with LHL15 weakened when ICG-R15 was about ³20. Weak correlations were observed between LHL15 and ALBI score ( r = −0.269) and ALBI score and ICG-R15 ( r = 0.339). Of 413 patients, 66 (19%) developed PHLF (grade A: n = 20, grade B: n = 44, grade C: n = 2). Multivariable logistic regression analyses, mALBI grade ( P = .014) and ICG-R15 ( P < .001) were significant independent risk factors for PHLF. Subgroup analysis showed that ICG-R15 <19, major hepatectomy, and mALBI grade and ICG-R15 ³19, major hepatectomy, and LHL15 were significant independent risk factors for PHLF ( P =.036,.020,.043, and.013, respectively). Conclusion: LHL15 and mALBI grade would be complementary to ICG-R15 for predicting PHLF risk. 99mTc-GSA scintigraphy LHL15 modified ALBI grade hepatic functional reserve Figures Figure 1 Figure 2 Figure 3 Introduction For hepatic malignancies, surgical resection plays an essential role as a curative treatment option. 1–4 Although surgical outcomes of hepatectomy have improved recently due to the development of surgical devices and perioperative management, posthepatectomy liver failure (PHLF) remains a crucial complication after hepatectomy. 5–10 To prevent severe PHLF from potentially leading to lethal outcomes, it is important to accurately assess preoperative hepatic functional reserve. Several reports have demonstrated that the indocyanine green (ICG) clearance test, technetium-99m-diethylenetriaminepentaacetic acid-galactosyl human serum albumin (99mTc-GSA) scintigraphy, albumin–bilirubin (ALBI) score, and ALBI grade are useful hepatic function tests for predicting PHLF. 10–13 Although the ICG retention rate at 15 minutes (ICG-R15) has been widely used, especially in Eastern countries, to assess preoperative hepatic functional reserve, 14–16 there is sometimes a discrepancy between its value and the actual hepatic function in patients with hyperbilirubinemia and intrahepatic shunts. 14,17,18 In addition, the ICG test cannot be performed for patients allergic to this fluorescent cyanine dye. 19–22 As an alternative to the ICG test, the ALBI score, a parameter calculated from albumin and total bilirubin in the blood; the ALBI grade; 13 and the modified ALBI (mALBI) grade 23 are also available as preoperative hepatic function tests. In contrast, liver activity at 15 minutes as assessed by 99mTc-GSA scintigraphy (LHL15) has not been used as commonly as ICG-R15 or ALBI due to its high cost and requirement for radioactive agents. 11,24 We have routinely measured both LHL15 and ICG-R15 and used the mALBI grade, ICG-R15, and LHL15 to evaluate preoperative hepatic functional reserve and determine the extent of hepatectomy. Although ICG-R15 and LHL15 are well correlated in most patients, a discrepancy is sometimes observed, especially in patients with deteriorated ICG-R15 values. It is difficult to interpret the hepatic functional reserve in such patients and thus to determine the appropriate procedure. However, a few reports have been published on the usefulness of measuring LHL15 in combination with ICG-R15 for predicting PHLF. In this study, we investigated the correlation of three hepatic functional tests (mALBI grade, ICG-R15, and LHL15) and evaluate whether LHL15 and ALBI are useful for predicting PHLF. Methods Patients This was a single-center, retrospective cohort study. Between January 2017 and December 2020, 501 consecutive patients underwent hepatectomy in our department. After excluding 17 patients who were living liver transplant donors with normal hepatic function, 16 patients who were living liver transplant recipients with end-stage liver failure at the time of surgery, 4 patients who underwent only liver bed resection for early-stage gallbladder cancer with negligible extent of liver resection, 10 patients who had neither preoperative ICG test nor 99mTc-GSAS, and 41 patients who underwent hepatectomy combined with bile duct resections, a total of 413 patients were enrolled in this study (Fig. 1 ). Preoperative physical assessment We obtained study data through a review of our prospectively maintained database. The American Society of Anesthesiologists physical status (ASA-PS) was used to assess the general status of surgical tolerance. 25 Preoperative hepatic functional reserve For patients at our institute who were scheduled to undergo hepatic resection, preoperative hepatic functional reserve was evaluated using the ALBI score, modified ALBI grade, ICG-R15, and LHL15, except for those with an ICG allergy or who had little time before surgery. The ALBI score was calculated as − 0.085 × (albumin [g/L]) + 0.66 × log10(− total bilirubin [µmol/L]), and was further categorized into three different grades as the modified ALBI grade: grade 1 ( − 2.60 to − 1.39). 23 The ICG-R15 was the serum ICG level measured 5 minutes after injection of 0.5 mg/kg of ICG. The LHL15 was calculated by [(L15; the radioactivity of the liver at 15 minutes after 99mTc-GSA injection)] / [L15 + (H15; the radioactivity of the heart at 15 minutes after injection)]. We also calculated the count ratio of the liver to the sum of the counts and the blood disappearance rate (HH15) = [H15]/[H3; the counts of the heart at 3 minutes after injection]. 12 Surgical procedure We conducted hepatectomy using Makuuchi’s criteria. 26 The extent of hepatectomy was classified according to the Japanese general rules for the clinical pathological study of primary liver cancer. 27 Hr1, 2, and 3 were classified as major hepatectomy. Laparoscopic surgery has been the first choice at our institution. Open surgery is selected for cases requiring vascular reconstruction, cases in which a high degree of adhesion is expected after multiple liver resections, or when the patient’s general condition is not good. In addition, in cases of laparoscopic surgery, robot-assisted surgery was performed if the patient strongly desired it and certain conditions were met, as previously described. 28–30 Details of the surgical procedures, including anatomical or nonanatomical liver resection, and open, laparoscopic, or robotic surgery were performed according to the previous reports. 28–30 PHLF and postoperative complications Using the criteria of the International Study Group of Liver Surgery, we defined PHLF as an increase in the international normalized ratio of prothrombin time and concomitant hyperbilirubinemia (according to the normal limits of the local laboratory) on or after postoperative day 5. 31 PHLF severity was classified as grade A, grade B, or grade C based on its impact on clinical management. 24,31 We dichotomized liver failure into no failure and grade A/B/C failure. Complications after surgery during the same hospital stay were categorized according to Dindo and colleagues. 32 Statistical analysis We present continuous data as the median and interquartile range. Categorical data are presented as count and proportion. We calculated Pearson’s correlation coefficients to determine the correlations between ALBI score, ICG-R15, and LHL15. Multivariate logistic regression analysis was performed to confirm whether ALBI score, ICG-R15, and LHL15 are independent risk factors for PHLF. Age and major hepatectomy, which are considered to be associated with PHLF, 33–35 and each factor (ALBI score, ICG-R15, and LHL15) were included in the model as adjusted factors. We also performed univariable logistic regression analysis to confirm the association between each factor and PHLF. The odds ratios are reported with 95% confidence intervals. A two-sided p value of < 0.05 was considered statistically significant. We identified 29 cases with missing values in ICG-R15 and 12 cases with missing values in LHL15. The exclusion of such patients might have biased our results, and missing values were complemented by multiple imputations. We performed the multiple imputation method based on the variables entered into a multivariable logistic regression model, and the results obtained through five interactions were integrated according to Rubin’s rule. To evaluate the predictive ability of PHLF by ICG-R15, we calculated the area under the curve (AUC) by the receiver-operating characteristic (ROC). The predictive ability of LHL15 was also evaluated by ROC and AUC in subgroups based on the cutoff point obtained by the Youden index. We also performed multivariable logistic regression for the ICG-R15 < 19 and ICG-R15 ≥19 subgroups. Statistical analyses were performed with R version 4.3.1 (The R Project for Statistical Computing, www.r-project.org ) and EZR version 1.52 (Saitama Medical Center, Jichi Medical University, Saitama, Japan). EZR is a graphical user interface for R version 4.02 (The R Foundation for Statistical Computing, Vienna, Austria) and is a modified version of R commander designed to add statistical functions frequently used in biostatistics. 36 Ethics All procedures were conducted according to the ethical standards of the responsible committee on human experimentation (institutional and national) and the Helsinki Declaration of 1964 and later version. This study protocol was approved by the institutional review board of Fujita Health University (approval No. HM19-064). Results Corelationship of the three hepatic functional tests Figure 2 shows the corelationship between the three hepatic functional tests. ICG-R15 and LHL15 were moderately correlated (correlation coefficients, r = − 0.61). However, the correlation with LHL15 weakened when the ICG-R15 was about 20 or higher. The correlations between LHL15 and ALBI score ( r = − 0.269) and between ALBI score and ICG-R15 ( r = 0.339) were weak. Clinical outcome and the relationship between perioperative factors and PHLF Table 1 shows the patients’ characteristics and perioperative outcomes. Of the 413 patients, 42 patients (10.2%) experienced complications of the Clavien–Dindo classification of IIIA or higher, 28 patients (6.8%) IIIA, 6 patients (1.5%) IIIB, 6 patients (1.5%) IV, and 2 patients (0.5%) V. PHLF occurred in 66 patients (16.0%): 20 patients (4.84%) in grade A, 44 patients (10.7%) in grade B, and 2 patients (0.48%) in grade C. Table 2 shows the summary results of the perioperative factors for each PHLF/nonPHLF. On univariable logistic regression analysis, several factors were noted to have a significant association with PHLF, including age, ALBI score, mALBI grade, ICG-R15, LHL15, major hepatectomy, operation time, and intraoperative blood loss. Multivariable regression analysis was performed using preoperative risk factors for PHLF. Table 3 shows the results of the univariable and multivariable logistic regression analysis evaluating the mALBI grade, ICG-R15, LHL15, and adjusted factor and PHLF. Multivariable logistic regression analysis identified mALBI grade (odds ratio [OR]: 1.57, 95% confidence interval [CI]: 1.09–2.24, P = 0.014), ICG-R15 (OR: 1.08, 95% CI: 1.04–1.12, P < 0.001), and major hepatectomy (OR: 2.52, 95% CI: 1.35–4.71, P = 0.004) as independent preoperative predictors of PHLF. The area under the receiver-operating characteristic curve (AUROC) of the ICG-R15 for PHLF was 0.716, and the optimal cutoff value was 19.2% (Fig. 3 ). Table 1 Patient characteristics and perioperative outcomes N 413 Preoperative factors Age, years* 69.0 [59.0, 75.0] Male, gender** 262 (63.4%) ASA-PS, n (1/2/3/4) 48/339/26/0 ALBI score* −2.52 [− 2.78, − 2.25] mALBI grade, n (1/2a/2b/3) 171/135/95/12 ICG-R15, %* 11.9 [7.8, 17.5] LHL15* 0.92 [0.90, 0.94] Intraoperative factors Approach** Open 125 (30.3) Laparoscopic 237 (57.4) Robotic 51 (12.3) Extent of hepatectomy** Hr0 188 (45.5) HrS 83 (20.1) Hr1 69 (16.7) Hr2 64 (15.5) Hr3 9 (2.2) Major hepatectomy** No 271 (65.6) Yes 142 (34.4) Operation time, min* 534.0 [360.0, 692.0] Blood loss, mL* 220.0 [75.0, 640.0] LOS, day* 15.0 [11.0, 20.0] Postoperative factors Morbidity** ⅢA > 371 (89.8) ⅢA ≤ 42 (10.2) PHLF** (+) 66 (16.0) A 20 (4.8) B 44 (10.7) C 2 (0.5) ASA-PS, American Society of Anesthesiologists physical status; ICG-R15, indocyanine green retention rate at 15 minutes; LHL15, radioactivity of the heart and liver after intravenous injection of 99mTc-GSA; Hr0, partial resection; HrS, subsegmentectomy; Hr1, segmentectomy; Hr2, lobectomy and central bisegmentectomy; Hr3, trisectomy and caudate lobectomy; LOS, length of hospital stay after surgery; PHLF, posthepatectomy liver failure. Continuous variables showed a nonnormal distribution and are presented as median and interquartile range. Hr1, 2, and 3 were classified as major hepatectomy. Morbidities after surgery during the same hospital stay were categorized according to Dindo and colleagues. *Values are presented as median (interquartile range). **Values are presented as number (%). Table 2 Relationship between perioperative factors and PHLF PHLF (−) PHLF (+) n (%) 347(84) 66 ( 16 ) Age, years* 69.0 [58.0, 75.0] 72.0 [63.3, 75.8] Gender** Male 212 (61.1) 50 (75.8) Female 135 (38.9) 16 (24.2) ASA-PS** 1 43 (12.4) 5 (7.6) 2 280 (80.7) 59 (89.7) 3 24 (6.9) 2 (3.0) Approach** Open 102 (29.4) 23 (34.8) Laparoscopic 201 (57.9) 36 (54.5) Robotic 44 (12.7) 7 (10.6) ALBI score* −2.57 [− 2.82, − 2.32] −2.28 [− 2.52, − 1.99] mALBI grade** 1 161 (46.4) 10 (15.2) 2a 112 (32.3) 23 (34.8) 2b 65 (18.7) 30 (45.5) 3 9 (2.6) 3 (4.5) ICG-R15,%* 11.4 [7.6, 16.0] 19.2 [10.4, 30.6] LHL15* 0.93 [0.90, 0.94] 0.91 [0.87, 0.93] Major hepatectomy No 235 (67.7) 36 (54.5) Yes 112 (32.3) 30 (45.5) Operation time, min** 510.0 [345.5, 641.5] 713.0 [ 491.3, 898.5] Blood loss, mL** 185.0 [61.0, 546.5] 639.0 [216.3, 1279.3] ASA-PS, American Society of Anesthesiologists physical status; ICG-R15, indocyanine green retention rate at 15 minutes; LHL15, radioactivity of the heart and liver after intravenous injection of 99mTc-GSA scintigraphy; Hr0, partial resection; HrS, subsegmentectomy; Hr1, segmentectomy, Hr2, lobectomy and central bisegmentectomy; Hr3, trisectomy and caudate lobectomy; PHLF, posthepatectomy liver failure. Continuous variables showed a nonnormal distribution and are presented as median and interquartile range. Hr1, 2, and 3 hepatectomy were classified as major hepatectomy. *Values are presented as median (interquartile range). **Values are presented as number (%). ***Univariable logistic regression analysis for the prediction of PHLF. Table 3 Logistic regression analysis for PHLF Univariable Multivariable Variables OR 95% CI P value OR 95% CI P value Age 1.03 1.00–1.05 0.0239 1.00 0.98–1.03 0.73 Major hepatectomy 1.75 1.02–2.98 0.04 2.52 1.35–4.71 0.004 mALBI grade 2.25 1.64–3.07 < 0.001 1.57 1.09–2.24 0.014 LHL15 0.86 0.81–0.93 < 0.001 0.98 0.89–1.08 0.67 ICG-R15 1.10 1.07–1.13 < 0.001 1.08 1.04–1.12 < 0.001 Multivariable logistic regression analysis by subgroup on ICG-R15 ICG-R15 < 19 ICG-R15 ≥19 Variable OR 95% CI P value OR 95% CI P value Age 1.03 0.99–1.07 0.108 0.97 0.92–1.02 0.215 Major hepatectomy 2.45 1.06–5.68 0.036 3.33 1.04–10.7 0.043 mALBI grade 1.73 1.09–2.76 0.020 1.84 0.88–3.84 0.104 LHL15 1.13 0.94–1.35 0.203 0.86 0.76–0.97 0.013 LHL15, radioactivity of the heart and liver after intravenous injection of 99mTc-GSA; ICG-R15, indocyanine green retention rate at 15 minutes; OR, odds ratio; 95% CI, 95% confidential interval; PHLF, posthepatectomy liver failure. Multivariable logistic regression analysis was conducted to reveal preoperative risk factors for PHLF. We divided the patients into subgroups with an ICG-R15 cutoff value of 19 and further examined the effect of LHL15 and ALBI on PHLF. Patients with ICG-R15 < 19 Major hepatectomy (OR: 2.45, 95% CI: 1.06–5.68, P = 0.036) and mALBI grade (OR: 1.73, 95% CI: 1.09–2.76, P = 0.02) were independent risk factors for PHLF (Table 3 ). Twenty-eight patients developed PHLF, 10 patients (35.7%) in grade A and 18 patients (64.3%) in grade B. Patients with ICG-R15 ≥19 Major hepatectomy (OR: 3.33, 95% CI: 1.04–10.7, P = 0.043) and LHL15 (OR: 0.86, 95% CI: 0.76–0.97, P = 0.013) were independent risk factors for PHLF (Table 3 ). Thirty-three patients developed PHLF, 6 patients (18.2%) in grade A, 25 patients (75.8%) in grade B, and 2 patients (6.1%) in grade C. Five patients with PHLF (4 patients in grade A, one patient in grade B) had missing ICG-R15 data. Discussion The current study showed that although LHL15 and ICG-R15 correlated well overall, the correlation weakened as hepatic function worsened. In patients with good hepatic function with low ICG-R15, the contribution of LHL15 to predicting PHLF is small, but as ICG-R15 increased, the impact of LHL15 on PHLF became larger. To our knowledge, this is the first study to identify patients for whom LHL15 should be measured in addition to ICG-R15 to increase the predictive accuracy for PHLF. Our study showed that LHL15 and ICG-R15 correlated well overall, but the correlation weakened as hepatic function worsened. As shown in Fig. 2 , LHL15 and ICG-R15 correlated well in all patients ( r = − 0.61, 95% CI: −0.67 to − 0.54), but the correlation weakened as ICG-R15 increased. Patients with poor hepatic function generally have elevated ICG-R15 (high ICG-R15), whereas patients with obstructive jaundice or intrahepatic shunts may have worse ICG-R15 than their actual hepatic function. In patients with high ICG-R15, additional hepatic function tests are needed to determine whether the hepatic function is truly worse or worse due to intrahepatic shunts or other factors. The usefulness of 99mTc-GSA scintigraphy as an alternative test to the ICG test has been reported in recent years. 24,37 Sumiyoshi et al. reported that there is a large discrepancy between ICG-R15 and actual hepatic function in patients with ICG-R15 > 40 and highly deteriorated ICG-R15 and that 99mTc-GSA scintigraphy assesses hepatic function more accurately than the ICG test does. 22 In patients with good hepatic function who have low ICG-R15, the contribution of LHL15 to the prediction of PHLF is small, but as ICG-R15 increases, the impact of LHL15 on PHLF becomes larger. Recently, researchers have reported the usefulness of the ALBI score and ALBI grade, calculated from serum albumin and bilirubin, in assessing hepatic function. 23,38,39 The greatest advantage of ALBI is that it can be obtained easily from routine blood test results. ALBI is worse in patients with hyperbilirubinemia, so as with ICG, it is useful for evaluating hepatic functional reserve in patients with low ICG-R15. On the other hand, its usefulness in patients with high bilirubin is unknown. We divided the patients into subgroups with an ICG-R15 cutoff value of 19 and further examined the effect of LHL15 and ALBI on PHLF. Table 3 shows the multivariable analysis of the preoperative risk factors of PHLF. For patients with ICG-R15 < 19, mALBI and major hepatectomy were independent risk factors for PHLF ( P = 0.036, P = 0.020). Our results indicate that in the group of patients with low ICG-R15, the mALBI grade was useful for assessing the risk of PHLF. Overall, the impact of LHL15 on the prediction of PHLF was not statistically significant. As for patients with ICG-R15 ≥19, LHL15 was an independent risk factor for PHLF ( P = 0.013). These results indicate that ALBI and ICG are useful for patients who have good hepatic function; on the other hand, for patients with poor hepatic function, the use of ICG only is not sufficient to predict the risk of PHLF, and LHL15 should also be measured. For patients for whom LHL15 should be measured, the cutoff value of ICG-R15 was 19. Table 4 shows the causes of PHLF, which were classified into the following three categories: intraoperative, postoperative morbidity, and hepatic functional factors. In both subgroups, major hepatectomy was a risk factor for PHLF. Table 4 shows that in patients with ICG-R15 < 19, 17 of 28 patients with PHLF underwent major hepatectomy. In this group, intraoperative factors were the most common factor for PHLF. This might be due to the increased intraoperative bleeding and longer operative time associated major hepatectomy. On the other hand, among patients with ICG-R15 ≥19, 12 of 33 patients with PHLF underwent major hepatectomy. Intraoperative factors were also common in this group; however, hepatic functional factors tended to be common as well (33.3% in 11 patients). The AUROC of the LHL15 for PHLF was 0.612, and the optimal cutoff value was 0.878 (Fig. 3 ). At our institution, the extent of hepatectomy was essentially determined using Makuuchi’s criteria. However, in some cases, surgeries deviating from Makuuchi’s criteria were performed for some patients who were deemed to be tolerable. In such cases, we thought that evaluating hepatic function using LHL15 might be useful. Our result indicates that LHL15 may be a useful test for assessing hepatic functional reserve when ICG-R15 does not accurately reflect hepatic function. Our result also indicates the reliability of LHL15 in the selection of hepatectomy candidates among the patient group with high ICG-R15. Table 4 Causes of PHLF ICG-R15 < 19 ICG-R15 ≥19 PHLF, n (%) 28 33 Grade A 10 (35.7) 6 (18.2) Grade B 18 (64.3) 25 (75.8) Grade C 0 2 (6.0) Major hepatectomy, n (%) 17 (60.7) 12 (36.4) Cause of PHLF, n (%) Intraoperative 17 (60.7) 21 (63.7) Morbidity 5 (17.9) 1 (3.0) Hepatic function 6 (21.4) 11 (33.3) ICG-R15, indocyanine green retention rate at 15 minutes; PHLF, posthepatectomy liver failure. The extent of hepatectomy was classified according to the Japanese general rules for the clinical pathological study of primary liver cancer. 27 Hr1, 2, and 3 were classified as major hepatectomy. Cause of PHLF; Intraoperative factors mean PHLF caused by a prolonged operation time (≥713 minutes) or intraoperative massive bleeding (≥639 mL). Morbidity factors mean PHLF caused by postoperative complex. Hepatic functional factors mean PHLF caused by impaired hepatic function (PHLF except for intraoperative factors and morbidity factors). There are several limitations to this study. First, this was a single-center, retrospective study, which might bias the demographics of the patients. Second, 99mTc-GSA scintigraphy is relatively widespread in Japan, but is not yet widely used in European countries; thus, it might be difficult to extrapolate this result to European countries. Third, this study included only patients who had received hepatectomy; patients who did not have received hepatectomy due to impaired hepatic function. As mentioned in previous reports, 40 this might imply that we excluded from this analysis patients with low LHL15 values for whom hepatectomy would not be safely performed due to impaired hepatic function. Conclusions Although LHL15 and ICG-R15 correlated well overall, the correlation weakened as hepatic function worsened. In patients with good hepatic function, the contribution of LHL15 to the prediction of PHLF is small, but as ICG-R15 increased, the impact of LHL15 on PHLF became larger. In patients with low ICG-R15, assessing hepatic function by mALBI grade would be useful. In patients with high ICG-R15, evaluating hepatic function using LHL15 would be useful for predicting the risk of PHLF. For predicting PHLF, 99mTc-GSA scintigraphy and modified ALBI score can complement ICG. Abbreviations AUC: area under the curve AUROC: area under the receiver-operating characteristic curve ISGLS: international study group of liver surgery ROC: receiver-operating characteristic Declarations Acknowledgments: The authors would like to thank Maruzen-Yushodo Co., Ltd. (https://kw.maruzen.co.jp/kousei-honyaku/) for the English language editing. Availability of data and material: The datasets used and/or analyses during the current study are available from the corresponding author upon reasonable request. Data is provided within supplementary information as supplementary files. The file name is "data file (supplementary material).csv". Funding: This work was not supported by any grants or funding. Competing interests : Mii Satoshi, Takeshi Takahara, Susumu Shibasaki, Yutaro Kato, and Koichi Suda have no commercial association or financial involvement that might be construed as a conflict of interest in connection with the submitted article. Koichi Suda was funded by Medicaroid, Inc., in relation to the Collaborative Laboratory for Research and Development in Advanced Surgical Intelligence, Fujita Health University, and has also received advisory fees from Medicaroid, Inc., outside the submitted work. Ethical approval and consent to participate statement: This study was approved by the institutional review board of Fujita Health University (HM19-064) and other participating hospitals. This study was also performed in accordance with the ethical standards laid down in the 1964 Declaration of Helsinki and its later amendments. Informed consent for this study was obtained through an opt-out method. Consent for publication: Authors’ contributions: All authors have fully satisfied the ICMJE authorship criteria as follows: study design: Satoshi Mii, Takeshi Takahara, Susumu Shibasaki, and Koichi Suda; data collection: Satoshi Mii and Yutaro Kato; statistical analysis and interpretation of results: Satoshi Mii, Takuma Ishihara, Takeshi Takahara, Susumu Shibasaki, and Koichi Suda; drafting of the manuscript: Satoshi Mii, Takuma Ishihara, Takeshi Takahara, Susumu Shibasaki, and Koichi Suda; and critical revision of the manuscript for important intellectual content: Takeshi Takahara, Susumu Shibasaki, Yutaro Kato, and Koichi Suda. 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AJR Am J Roentgenol. 2018;210:158-65. Zhang ZQ, Xiong L, Zhou JJ, Miao XY, Li QL, Wen Y, et al. Ability of the ALBI grade to predict posthepatectomy liver failure and long-term survival after liver resection for different BCLC stages of HCC. World J Surg Oncol. 2018;16:208. Imamura H, Sano K, Sugawara Y, Kokudo N, Makuuchi M. Assessment of hepatic reserve for indication of hepatic resection: decision tree incorporating indocyanine green test. J Hepato-Bil Pancreat Surg//. 2005 February;12:16-22. Lisotti A, Azzaroli F, Buonfiglioli F, Montagnani M, Cecinato P, Turco L, et al. Indocyanine green retention test as a noninvasive marker of portal hypertension and esophageal varices in compensated liver cirrhosis. Hepatology. 2014;59:643-50. Ohwada S, Kawate S, Hamada K, Yamada T, Sunose Y, Tsutsumi H, et al. Perioperative real-time monitoring of indocyanine green clearance by pulse spectrophotometry predicts remnant liver functional reserve in resection of hepatocellular carcinoma. Br J Surg. 2006;93:339-46. de Graaf W, Häusler S, Heger M, van Ginhoven TM, van Cappellen G, Bennink RJ, et al. Transporters involved in the hepatic uptake of (99m)Tc-mebrofenin and indocyanine green. J Hepatol. 2011 April;54:738-45. Cui Y, König J, Leier I, Buchholz U, Keppler D. Hepatic uptake of bilirubin and its conjugates by the human organic anion transporter SLC21A6. J Biol Chem. 2001;276:9626–30. Kwon AH, Ha‐Kawa SK, Uetsuji S, Inoue T, Matsui Y, Kamiyama Y. Preoperative determination of the surgical procedure for hepatectomy using technetium‐99m‐galactosyl human serum albumin (99mTc‐GSA) liver scintigraphy. Hepatology. 1997;25:426-9. Maeda H, Okabayashi T, Kobayashi M, Sugimoto T, Namikawa T, Okamoto K, et al. Hepatectomy for hepatocellular carcinoma with indocyanine green excretory defect: a case report. Hepato-Gastroenterology. 2007;54:1810-2. Sumiyoshi T, Shima Y, Okabayashi T, Kozuki A, Hata Y, Noda Y, et al. Liver function assessment using 99mTc-GSA single-photon emission computed tomography (SPECT)/CT fusion imaging in hilar bile duct cancer: a retrospective study. Surgery. 2016;160:118-26. Sumiyoshi T, Okabayashi T, Negoro Y, Hata Y, Noda Y, Sui K, et al. 99mTc-GSA SPECT/CT fusion imaging for hepatectomy candidates with extremely deteriorated ICG value. Jpn J Radiol. 2018;36:537-43. Hiraoka A, Kumada T. Clinical role of newly developed ALBI and mALBI grades for treatment of hepatocellular carcinoma. Appl Sci. 2020;10:7178. Nakamura I, Iimuro Y, Hai S, Kondo Y, Hatano E, Fujimoto J. Impaired value of 99m Tc-GSA scintigraphy as an independent risk factor for posthepatectomy liver failure in patients with hepatocellular carcinoma. Eur Surg Res. 2018;59:12-22. Hackett NJ, De Oliveira GS, Jain UK, Kim JY. ASA class is a reliable independent predictor of medical complications and mortality following surgery. Int J Surg. 2015;18:184-90. Imamura H, Seyama Y, Kokudo N, Maema A, Sugawara Y, Sano K, et al. One thousand fifty-six hepatectomies without mortality in 8 years. Arch Surg. 2003;138:1198-206; discussion 1206. Kudo M, Kitano M, Sakurai T, Nishida N. General rules for the clinical and pathological study of primary liver cancer, nationwide follow-up survey and clinical practice guidelines: the outstanding achievements of the Liver Cancer Study Group of Japan. Dig Dis. 2015;33:765-70. Kato Y, Sugioka A, Kojima M, Kiguchi G, Mii S, Uchida Y, et al. Initial experience with robotic liver resection: audit of 120 consecutive cases at a single center and comparison with open and laparoscopic approaches. J Hepato‐Bil Pancreat Sci. 2023;30:72-90. Kato Y, Sugioka A, Kojima M, Mii S, Uchida Y, Iwama H, et al. Minimally invasive anatomic liver resection for hepatocellular carcinoma using the extrahepatic Glissonian approach: surgical techniques and comparison of outcomes with the open approach and between the laparoscopic and robotic approaches. Cancers. 2023;15:2219. Kato Y, Sugioka A, Uyama I. Robotic liver resection for hepatocellular carcinoma: A focus on anatomic resection. HR. 2021;10. Rahbari NN, Garden OJ, Padbury R, Brooke-Smith M, Crawford M, Adam R, et al. Posthepatectomy liver failure: a definition and grading by the international study group of liver surgery (ISGLS). Surgery. 2011;149:713-24. Dindo D, Demartines N, Clavien PA. Classification of surgical complications: a new proposal with evaluation in a cohort of 6336 patients and results of a survey. Ann Surg. 2004;240:205-13. Lei Z, Cheng N, Si A, Yang P, Guo G, Ma W, et al. A novel nomogram for predicting postoperative liver failure after major hepatectomy for hepatocellular carcinoma. Front Oncol. 2022;12:817895. Søreide JA, Deshpande R. Post hepatectomy liver failure (PHLF) - recent advances in prevention and clinical management. Eur J Surg Oncol. 2021;47:216-24. Guglielmi A, Ruzzenente A, Conci S, Valdegamberi A, Iacono C. How much remnant is enough in liver resection? Dig Surg. 2012;29:6-17. Kanda Y. Investigation of the freely available easy-to-use software ‘EZR’ for medical statistics. Bone Marrow Transplant. 2013;48:452-8. Hayashi H, Beppu T, Okabe H, Kuroki H, Nakagawa S, Imai K, et al. Functional assessment versus conventional volumetric assessment in the prediction of operative outcomes after major hepatectomy. Surgery. 2015;157:20-6. Hiraoka A, Michitaka K, Kumada T, Izumi N, Kadoya M, Kokudo N, et al. Validation and potential of albumin-bilirubin grade and prognostication in a nationwide survey of 46,681 hepatocellular carcinoma patients in Japan: the need for a more detailed evaluation of hepatic function. Liver Cancer. 2017;6:325-36. Aida T, Haruki K, Akaoka M, Furukawa K, Onda S, Shirai Y, et al. A novel combined C-reactive protein‐albumin ratio and modified albumin‐bilirubin score can predict long‐term outcomes in patients with hepatocellular carcinoma after hepatic resection. Anna Gastroenterol Surg. 2023. Tomimaru Y, Eguchi H, Gotoh K, Kawamoto K, Wada H, Asaoka T, et al. Platelet count is more useful for predicting posthepatectomy liver failure at surgery for hepatocellular carcinoma than indocyanine green clearance test. J Surg Oncol. 2016;113:565-9. Additional Declarations No competing interests reported. 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1","display":"","copyAsset":false,"role":"figure","size":47973,"visible":true,"origin":"","legend":"\u003cp\u003ePatient selection\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3997930/v1/d21a6ef0ee08487d7c4bda7e.jpg"},{"id":53180528,"identity":"b2c9ea52-4d75-4f1a-8820-e51e135897a6","added_by":"auto","created_at":"2024-03-21 15:34:00","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":73465,"visible":true,"origin":"","legend":"\u003cp\u003eCorrelation of the three hepatic functional tests\u003c/p\u003e","description":"","filename":"2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3997930/v1/9b5dc50415c8f6d74f60f284.jpg"},{"id":53180529,"identity":"acb262e2-90dd-47fc-8f63-85038d1ff92e","added_by":"auto","created_at":"2024-03-21 15:34:00","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":74219,"visible":true,"origin":"","legend":"\u003cp\u003eArea under curve the receiver-operating characteristic curve (AUROC) for PHLF\u003c/p\u003e","description":"","filename":"3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3997930/v1/24513728de654880daf0d897.jpg"},{"id":68206599,"identity":"618891bf-07cf-48ad-8b3f-13d18c1473db","added_by":"auto","created_at":"2024-11-04 16:32:59","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":866677,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3997930/v1/e8b77faa-2fc2-4bc9-99ec-4adacf4ae528.pdf"},{"id":53180531,"identity":"6883ad08-7456-4661-96cc-d3059685980d","added_by":"auto","created_at":"2024-03-21 15:34:01","extension":"csv","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":101163,"visible":true,"origin":"","legend":"","description":"","filename":"datafilesupplementarymaterial.csv","url":"https://assets-eu.researchsquare.com/files/rs-3997930/v1/af1ce3516db2726611f6d347.csv"}],"financialInterests":"No competing interests reported.","formattedTitle":"99mTc-GSA scintigraphy and modified albumin–bilirubin score can be complementary to ICG for predicting posthepatectomy liver failure","fulltext":[{"header":"Introduction","content":"\u003cp\u003eFor hepatic malignancies, surgical resection plays an essential role as a curative treatment option.\u003csup\u003e1\u0026ndash;4\u003c/sup\u003e Although surgical outcomes of hepatectomy have improved recently due to the development of surgical devices and perioperative management, posthepatectomy liver failure (PHLF) remains a crucial complication after hepatectomy.\u003csup\u003e5\u0026ndash;10\u003c/sup\u003e To prevent severe PHLF from potentially leading to lethal outcomes, it is important to accurately assess preoperative hepatic functional reserve. Several reports have demonstrated that the indocyanine green (ICG) clearance test, technetium-99m-diethylenetriaminepentaacetic acid-galactosyl human serum albumin (99mTc-GSA) scintigraphy, albumin\u0026ndash;bilirubin (ALBI) score, and ALBI grade are useful hepatic function tests for predicting PHLF.\u003csup\u003e10\u0026ndash;13\u003c/sup\u003e Although the ICG retention rate at 15 minutes (ICG-R15) has been widely used, especially in Eastern countries, to assess preoperative hepatic functional reserve,\u003csup\u003e14\u0026ndash;16\u003c/sup\u003e there is sometimes a discrepancy between its value and the actual hepatic function in patients with hyperbilirubinemia and intrahepatic shunts.\u003csup\u003e14,17,18\u003c/sup\u003e In addition, the ICG test cannot be performed for patients allergic to this fluorescent cyanine dye.\u003csup\u003e19\u0026ndash;22\u003c/sup\u003e As an alternative to the ICG test, the ALBI score, a parameter calculated from albumin and total bilirubin in the blood; the ALBI grade;\u003csup\u003e13\u003c/sup\u003e and the modified ALBI (mALBI) grade\u003csup\u003e23\u003c/sup\u003e are also available as preoperative hepatic function tests. In contrast, liver activity at 15 minutes as assessed by 99mTc-GSA scintigraphy (LHL15) has not been used as commonly as ICG-R15 or ALBI due to its high cost and requirement for radioactive agents.\u003csup\u003e11,24\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eWe have routinely measured both LHL15 and ICG-R15 and used the mALBI grade, ICG-R15, and LHL15 to evaluate preoperative hepatic functional reserve and determine the extent of hepatectomy. Although ICG-R15 and LHL15 are well correlated in most patients, a discrepancy is sometimes observed, especially in patients with deteriorated ICG-R15 values. It is difficult to interpret the hepatic functional reserve in such patients and thus to determine the appropriate procedure. However, a few reports have been published on the usefulness of measuring LHL15 in combination with ICG-R15 for predicting PHLF. In this study, we investigated the correlation of three hepatic functional tests (mALBI grade, ICG-R15, and LHL15) and evaluate whether LHL15 and ALBI are useful for predicting PHLF.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003ePatients\u003c/h2\u003e \u003cp\u003eThis was a single-center, retrospective cohort study. Between January 2017 and December 2020, 501 consecutive patients underwent hepatectomy in our department. After excluding 17 patients who were living liver transplant donors with normal hepatic function, 16 patients who were living liver transplant recipients with end-stage liver failure at the time of surgery, 4 patients who underwent only liver bed resection for early-stage gallbladder cancer with negligible extent of liver resection, 10 patients who had neither preoperative ICG test nor 99mTc-GSAS, and 41 patients who underwent hepatectomy combined with bile duct resections, a total of 413 patients were enrolled in this study (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003ePreoperative physical assessment\u003c/h2\u003e \u003cp\u003e We obtained study data through a review of our prospectively maintained database. The American Society of Anesthesiologists physical status (ASA-PS) was used to assess the general status of surgical tolerance.\u003csup\u003e25\u003c/sup\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003ePreoperative hepatic functional reserve\u003c/h2\u003e \u003cp\u003eFor patients at our institute who were scheduled to undergo hepatic resection, preoperative hepatic functional reserve was evaluated using the ALBI score, modified ALBI grade, ICG-R15, and LHL15, except for those with an ICG allergy or who had little time before surgery. The ALBI score was calculated as \u0026minus;\u0026thinsp;0.085 \u0026times; (albumin [g/L])\u0026thinsp;+\u0026thinsp;0.66 \u0026times; log10(\u0026minus;\u0026thinsp;total bilirubin [\u0026micro;mol/L]), and was further categorized into three different grades as the modified ALBI grade: grade 1 (\u0026thinsp;\u0026lt;\u0026thinsp;\u0026minus;\u0026thinsp;2.60), grade 2a (\u0026thinsp;\u0026gt;\u0026thinsp;\u0026minus;\u0026thinsp;2.60 to \u0026lt;\u0026thinsp;\u0026minus;\u0026thinsp;2.27), grade 2b (\u0026ge;\u0026minus;\u0026thinsp;2.27 to \u0026le;\u0026minus;\u0026thinsp;1.39), and grade 3 (\u0026thinsp;\u0026gt;\u0026thinsp;\u0026minus;\u0026thinsp;1.39).\u003csup\u003e23\u003c/sup\u003e The ICG-R15 was the serum ICG level measured 5 minutes after injection of 0.5 mg/kg of ICG. The LHL15 was calculated by [(L15; the radioactivity of the liver at 15 minutes after 99mTc-GSA injection)] / [L15 + (H15; the radioactivity of the heart at 15 minutes after injection)]. We also calculated the count ratio of the liver to the sum of the counts and the blood disappearance rate (HH15) = [H15]/[H3; the counts of the heart at 3 minutes after injection].\u003csup\u003e12\u003c/sup\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eSurgical procedure\u003c/h2\u003e \u003cp\u003eWe conducted hepatectomy using Makuuchi\u0026rsquo;s criteria.\u003csup\u003e26\u003c/sup\u003e The extent of hepatectomy was classified according to the Japanese general rules for the clinical pathological study of primary liver cancer.\u003csup\u003e27\u003c/sup\u003e Hr1, 2, and 3 were classified as major hepatectomy. Laparoscopic surgery has been the first choice at our institution. Open surgery is selected for cases requiring vascular reconstruction, cases in which a high degree of adhesion is expected after multiple liver resections, or when the patient\u0026rsquo;s general condition is not good. In addition, in cases of laparoscopic surgery, robot-assisted surgery was performed if the patient strongly desired it and certain conditions were met, as previously described.\u003csup\u003e28\u0026ndash;30\u003c/sup\u003e Details of the surgical procedures, including anatomical or nonanatomical liver resection, and open, laparoscopic, or robotic surgery were performed according to the previous reports.\u003csup\u003e28\u0026ndash;30\u003c/sup\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003ePHLF and postoperative complications\u003c/h2\u003e \u003cp\u003eUsing the criteria of the International Study Group of Liver Surgery, we defined PHLF as an increase in the international normalized ratio of prothrombin time and concomitant hyperbilirubinemia (according to the normal limits of the local laboratory) on or after postoperative day 5.\u003csup\u003e31\u003c/sup\u003e PHLF severity was classified as grade A, grade B, or grade C based on its impact on clinical management.\u003csup\u003e24,31\u003c/sup\u003e We dichotomized liver failure into no failure and grade A/B/C failure. Complications after surgery during the same hospital stay were categorized according to Dindo and colleagues.\u003csup\u003e32\u003c/sup\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eWe present continuous data as the median and interquartile range. Categorical data are presented as count and proportion. We calculated Pearson\u0026rsquo;s correlation coefficients to determine the correlations between ALBI score, ICG-R15, and LHL15. Multivariate logistic regression analysis was performed to confirm whether ALBI score, ICG-R15, and LHL15 are independent risk factors for PHLF. Age and major hepatectomy, which are considered to be associated with PHLF,\u003csup\u003e33\u0026ndash;35\u003c/sup\u003e and each factor (ALBI score, ICG-R15, and LHL15) were included in the model as adjusted factors. We also performed univariable logistic regression analysis to confirm the association between each factor and PHLF. The odds ratios are reported with 95% confidence intervals. A two-sided \u003cem\u003ep\u003c/em\u003e value of \u0026lt;\u0026thinsp;0.05 was considered statistically significant. We identified 29 cases with missing values in ICG-R15 and 12 cases with missing values in LHL15. The exclusion of such patients might have biased our results, and missing values were complemented by multiple imputations. We performed the multiple imputation method based on the variables entered into a multivariable logistic regression model, and the results obtained through five interactions were integrated according to Rubin\u0026rsquo;s rule. To evaluate the predictive ability of PHLF by ICG-R15, we calculated the area under the curve (AUC) by the receiver-operating characteristic (ROC). The predictive ability of LHL15 was also evaluated by ROC and AUC in subgroups based on the cutoff point obtained by the Youden index. We also performed multivariable logistic regression for the ICG-R15\u0026thinsp;\u0026lt;\u0026thinsp;19 and ICG-R15 \u0026ge;19 subgroups. Statistical analyses were performed with R version 4.3.1 (The R Project for Statistical Computing, \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e\u003ca href=\"https://kw.maruzen.co.jp/kousei-honyaku/\" target=\"_blank\"\u003ewww.r-project.org\u003c/a\u003e\u003c/span\u003e\u003cspan address=\"http://www.r-project.org\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) and EZR version 1.52 (Saitama Medical Center, Jichi Medical University, Saitama, Japan). EZR is a graphical user interface for R version 4.02 (The R Foundation for Statistical Computing, Vienna, Austria) and is a modified version of R commander designed to add statistical functions frequently used in biostatistics.\u003csup\u003e36\u003c/sup\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eEthics\u003c/h2\u003e \u003cp\u003e All procedures were conducted according to the ethical standards of the responsible committee on human experimentation (institutional and national) and the Helsinki Declaration of 1964 and later version. This study protocol was approved by the institutional review board of Fujita Health University (approval No. HM19-064).\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eCorelationship of the three hepatic functional tests\u003c/h2\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e shows the corelationship between the three hepatic functional tests. ICG-R15 and LHL15 were moderately correlated (correlation coefficients, \u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;0.61). However, the correlation with LHL15 weakened when the ICG-R15 was about 20 or higher. The correlations between LHL15 and ALBI score (\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;0.269) and between ALBI score and ICG-R15 (\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.339) were weak.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eClinical outcome and the relationship between perioperative factors and PHLF\u003c/h2\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e shows the patients\u0026rsquo; characteristics and perioperative outcomes. Of the 413 patients, 42 patients (10.2%) experienced complications of the Clavien\u0026ndash;Dindo classification of IIIA or higher, 28 patients (6.8%) IIIA, 6 patients (1.5%) IIIB, 6 patients (1.5%) IV, and 2 patients (0.5%) V. PHLF occurred in 66 patients (16.0%): 20 patients (4.84%) in grade A, 44 patients (10.7%) in grade B, and 2 patients (0.48%) in grade C. Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e shows the summary results of the perioperative factors for each PHLF/nonPHLF. On univariable logistic regression analysis, several factors were noted to have a significant association with PHLF, including age, ALBI score, mALBI grade, ICG-R15, LHL15, major hepatectomy, operation time, and intraoperative blood loss. Multivariable regression analysis was performed using preoperative risk factors for PHLF. Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e shows the results of the univariable and multivariable logistic regression analysis evaluating the mALBI grade, ICG-R15, LHL15, and adjusted factor and PHLF. Multivariable logistic regression analysis identified mALBI grade (odds ratio [OR]: 1.57, 95% confidence interval [CI]: 1.09\u0026ndash;2.24, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.014), ICG-R15 (OR: 1.08, 95% CI: 1.04\u0026ndash;1.12, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and major hepatectomy (OR: 2.52, 95% CI: 1.35\u0026ndash;4.71, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.004) as independent preoperative predictors of PHLF. The area under the receiver-operating characteristic curve (AUROC) of the ICG-R15 for PHLF was 0.716, and the optimal cutoff value was 19.2% (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\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\u003ePatient characteristics and perioperative outcomes\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\u003eN\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e413\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePreoperative factors\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\u003eAge, years*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e69.0 [59.0, 75.0]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale, gender**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e262 (63.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eASA-PS, n (1/2/3/4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e48/339/26/0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eALBI score*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;2.52 [\u0026minus;\u0026thinsp;2.78, \u0026minus;\u0026thinsp;2.25]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003emALBI grade, n (1/2a/2b/3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e171/135/95/12\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eICG-R15, %*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11.9 [7.8, 17.5]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLHL15*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.92 [0.90, 0.94]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIntraoperative factors\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\u003eApproach**\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\u003eOpen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e125 (30.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLaparoscopic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e237 (57.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRobotic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e51 (12.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eExtent of hepatectomy**\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\u003eHr0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e188 (45.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHrS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e83 (20.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHr1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e69 (16.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHr2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e64 (15.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHr3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9 (2.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMajor hepatectomy**\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\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e271 (65.6)\u003c/p\u003e \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\u003e142 (34.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOperation time, min*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e534.0 [360.0, 692.0]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBlood loss, mL*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e220.0 [75.0, 640.0]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLOS, day*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15.0 [11.0, 20.0]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePostoperative factors\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\u003eMorbidity**\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\u003eⅢA \u0026gt;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e371 (89.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eⅢA \u0026le;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e42 (10.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePHLF**\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\u003e(+)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e66 (16.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20 (4.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e44 (10.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 (0.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"2\"\u003eASA-PS, American Society of Anesthesiologists physical status; ICG-R15, indocyanine green retention rate at 15 minutes; LHL15, radioactivity of the heart and liver after intravenous injection of 99mTc-GSA; Hr0, partial resection; HrS, subsegmentectomy; Hr1, segmentectomy; Hr2, lobectomy and central bisegmentectomy; Hr3, trisectomy and caudate lobectomy; LOS, length of hospital stay after surgery; PHLF, posthepatectomy liver failure.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"2\"\u003eContinuous variables showed a nonnormal distribution and are presented as median and interquartile range. Hr1, 2, and 3 were classified as major hepatectomy.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"2\"\u003eMorbidities after surgery during the same hospital stay were categorized according to Dindo and colleagues.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"2\"\u003e*Values are presented as median (interquartile range).\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"2\"\u003e**Values are presented as number (%).\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eRelationship between perioperative factors and PHLF\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePHLF (\u0026minus;)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePHLF (+)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003en (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e347(84)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e66 (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge, years*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e69.0 [58.0, 75.0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e72.0 [63.3, 75.8]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e212 (61.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e50 (75.8)\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\u003e135 (38.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16 (24.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eASA-PS**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e43 (12.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 (7.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e280 (80.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e59 (89.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e24 (6.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (3.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eApproach**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOpen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e102 (29.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23 (34.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLaparoscopic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e201 (57.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e36 (54.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRobotic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e44 (12.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7 (10.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eALBI score*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;2.57 [\u0026minus;\u0026thinsp;2.82, \u0026minus;\u0026thinsp;2.32]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026minus;2.28 [\u0026minus;\u0026thinsp;2.52, \u0026minus;\u0026thinsp;1.99]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003emALBI grade**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e161 (46.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10 (15.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e112 (32.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23 (34.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e65 (18.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30 (45.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9 (2.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 (4.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eICG-R15,%*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11.4 [7.6, 16.0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19.2 [10.4, 30.6]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLHL15*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.93 [0.90, 0.94]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.91 [0.87, 0.93]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMajor hepatectomy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e235 (67.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e36 (54.5)\u003c/p\u003e \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\u003e112 (32.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30 (45.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOperation time, min**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e510.0 [345.5, 641.5]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e713.0 [ 491.3, 898.5]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBlood loss, mL**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e185.0 [61.0, 546.5]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e639.0 [216.3, 1279.3]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003eASA-PS, American Society of Anesthesiologists physical status; ICG-R15, indocyanine green retention rate at 15 minutes; LHL15, radioactivity of the heart and liver after intravenous injection of 99mTc-GSA scintigraphy; Hr0, partial resection; HrS, subsegmentectomy; Hr1, segmentectomy, Hr2, lobectomy and central bisegmentectomy; Hr3, trisectomy and caudate lobectomy; PHLF, posthepatectomy liver failure.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003eContinuous variables showed a nonnormal distribution and are presented as median and interquartile range. Hr1, 2, and 3 hepatectomy were classified as major hepatectomy.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003e*Values are presented as median (interquartile range).\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003e**Values are presented as number (%).\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003e***Univariable logistic regression analysis for the prediction of PHLF.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e\u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\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=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003eLogistic regression analysis for PHLF\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eUnivariable\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003eMultivariable\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eOR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.00\u0026ndash;1.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0239\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.98\u0026ndash;1.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.73\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMajor hepatectomy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.02\u0026ndash;2.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.35\u0026ndash;4.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003emALBI grade\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.64\u0026ndash;3.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.09\u0026ndash;2.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.014\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLHL15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.81\u0026ndash;0.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.89\u0026ndash;1.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.67\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eICG-R15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.07\u0026ndash;1.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.04\u0026ndash;1.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c7\" namest=\"c2\"\u003e \u003cp\u003eMultivariable logistic regression analysis by subgroup on ICG-R15\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eICG-R15\u0026thinsp;\u0026lt;\u0026thinsp;19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003eICG-R15 \u0026ge;19\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eOR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.99\u0026ndash;1.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.108\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.92\u0026ndash;1.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.215\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMajor hepatectomy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.06\u0026ndash;5.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.036\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.04\u0026ndash;10.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.043\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003emALBI grade\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.09\u0026ndash;2.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.88\u0026ndash;3.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.104\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLHL15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.94\u0026ndash;1.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.203\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.76\u0026ndash;0.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.013\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eLHL15, radioactivity of the heart and liver after intravenous injection of 99mTc-GSA; ICG-R15, indocyanine green retention rate at 15 minutes; OR, odds ratio; 95% CI, 95% confidential interval; PHLF, posthepatectomy liver failure.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eMultivariable logistic regression analysis was conducted to reveal preoperative risk factors for PHLF.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eWe divided the patients into subgroups with an ICG-R15 cutoff value of 19 and further examined the effect of LHL15 and ALBI on PHLF.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003ePatients with ICG-R15\u0026thinsp;\u0026lt;\u0026thinsp;19\u003c/h2\u003e \u003cp\u003eMajor hepatectomy (OR: 2.45, 95% CI: 1.06\u0026ndash;5.68, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.036) and mALBI grade (OR: 1.73, 95% CI: 1.09\u0026ndash;2.76, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.02) were independent risk factors for PHLF (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Twenty-eight patients developed PHLF, 10 patients (35.7%) in grade A and 18 patients (64.3%) in grade B.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003ePatients with ICG-R15 \u0026ge;19\u003c/h2\u003e \u003cp\u003eMajor hepatectomy (OR: 3.33, 95% CI: 1.04\u0026ndash;10.7, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.043) and LHL15 (OR: 0.86, 95% CI: 0.76\u0026ndash;0.97, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.013) were independent risk factors for PHLF (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Thirty-three patients developed PHLF, 6 patients (18.2%) in grade A, 25 patients (75.8%) in grade B, and 2 patients (6.1%) in grade C. Five patients with PHLF (4 patients in grade A, one patient in grade B) had missing ICG-R15 data.\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe current study showed that although LHL15 and ICG-R15 correlated well overall, the correlation weakened as hepatic function worsened. In patients with good hepatic function with low ICG-R15, the contribution of LHL15 to predicting PHLF is small, but as ICG-R15 increased, the impact of LHL15 on PHLF became larger. To our knowledge, this is the first study to identify patients for whom LHL15 should be measured in addition to ICG-R15 to increase the predictive accuracy for PHLF.\u003c/p\u003e \u003cp\u003eOur study showed that LHL15 and ICG-R15 correlated well overall, but the correlation weakened as hepatic function worsened. As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, LHL15 and ICG-R15 correlated well in all patients (\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;0.61, 95% CI: \u0026minus;0.67 to \u0026minus;\u0026thinsp;0.54), but the correlation weakened as ICG-R15 increased. Patients with poor hepatic function generally have elevated ICG-R15 (high ICG-R15), whereas patients with obstructive jaundice or intrahepatic shunts may have worse ICG-R15 than their actual hepatic function. In patients with high ICG-R15, additional hepatic function tests are needed to determine whether the hepatic function is truly worse or worse due to intrahepatic shunts or other factors. The usefulness of 99mTc-GSA scintigraphy as an alternative test to the ICG test has been reported in recent years.\u003csup\u003e24,37\u003c/sup\u003e Sumiyoshi et al. reported that there is a large discrepancy between ICG-R15 and actual hepatic function in patients with ICG-R15\u0026thinsp;\u0026gt;\u0026thinsp;40 and highly deteriorated ICG-R15 and that 99mTc-GSA scintigraphy assesses hepatic function more accurately than the ICG test does.\u003csup\u003e22\u003c/sup\u003e In patients with good hepatic function who have low ICG-R15, the contribution of LHL15 to the prediction of PHLF is small, but as ICG-R15 increases, the impact of LHL15 on PHLF becomes larger. Recently, researchers have reported the usefulness of the ALBI score and ALBI grade, calculated from serum albumin and bilirubin, in assessing hepatic function.\u003csup\u003e23,38,39\u003c/sup\u003e The greatest advantage of ALBI is that it can be obtained easily from routine blood test results. ALBI is worse in patients with hyperbilirubinemia, so as with ICG, it is useful for evaluating hepatic functional reserve in patients with low ICG-R15. On the other hand, its usefulness in patients with high bilirubin is unknown.\u003c/p\u003e \u003cp\u003eWe divided the patients into subgroups with an ICG-R15 cutoff value of 19 and further examined the effect of LHL15 and ALBI on PHLF. Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e shows the multivariable analysis of the preoperative risk factors of PHLF. For patients with ICG-R15\u0026thinsp;\u0026lt;\u0026thinsp;19, mALBI and major hepatectomy were independent risk factors for PHLF (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.036, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.020). Our results indicate that in the group of patients with low ICG-R15, the mALBI grade was useful for assessing the risk of PHLF. Overall, the impact of LHL15 on the prediction of PHLF was not statistically significant. As for patients with ICG-R15 \u0026ge;19, LHL15 was an independent risk factor for PHLF (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.013). These results indicate that ALBI and ICG are useful for patients who have good hepatic function; on the other hand, for patients with poor hepatic function, the use of ICG only is not sufficient to predict the risk of PHLF, and LHL15 should also be measured. For patients for whom LHL15 should be measured, the cutoff value of ICG-R15 was 19.\u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e shows the causes of PHLF, which were classified into the following three categories: intraoperative, postoperative morbidity, and hepatic functional factors. In both subgroups, major hepatectomy was a risk factor for PHLF. Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e shows that in patients with ICG-R15\u0026thinsp;\u0026lt;\u0026thinsp;19, 17 of 28 patients with PHLF underwent major hepatectomy. In this group, intraoperative factors were the most common factor for PHLF. This might be due to the increased intraoperative bleeding and longer operative time associated major hepatectomy. On the other hand, among patients with ICG-R15 \u0026ge;19, 12 of 33 patients with PHLF underwent major hepatectomy. Intraoperative factors were also common in this group; however, hepatic functional factors tended to be common as well (33.3% in 11 patients). The AUROC of the LHL15 for PHLF was 0.612, and the optimal cutoff value was 0.878 (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). At our institution, the extent of hepatectomy was essentially determined using Makuuchi\u0026rsquo;s criteria. However, in some cases, surgeries deviating from Makuuchi\u0026rsquo;s criteria were performed for some patients who were deemed to be tolerable. In such cases, we thought that evaluating hepatic function using LHL15 might be useful. Our result indicates that LHL15 may be a useful test for assessing hepatic functional reserve when ICG-R15 does not accurately reflect hepatic function. Our result also indicates the reliability of LHL15 in the selection of hepatectomy candidates among the patient group with high ICG-R15.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCauses of PHLF\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eICG-R15\u0026thinsp;\u0026lt;\u0026thinsp;19\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eICG-R15 \u0026ge;19\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePHLF, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e33\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGrade A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10 (35.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6 (18.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGrade B\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18 (64.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25 (75.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGrade C\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (6.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMajor hepatectomy, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17 (60.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12 (36.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCause of PHLF, 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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIntraoperative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17 (60.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21 (63.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMorbidity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5 (17.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (3.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHepatic function\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6 (21.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11 (33.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003eICG-R15, indocyanine green retention rate at 15 minutes; PHLF, posthepatectomy liver failure.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003eThe extent of hepatectomy was classified according to the Japanese general rules for the clinical pathological study of primary liver cancer.\u003csup\u003e27\u003c/sup\u003e Hr1, 2, and 3 were classified as major hepatectomy. Cause of PHLF; Intraoperative factors mean PHLF caused by a prolonged operation time (\u0026ge;713 minutes) or intraoperative massive bleeding (\u0026ge;639 mL). Morbidity factors mean PHLF caused by postoperative complex. Hepatic functional factors mean PHLF caused by impaired hepatic function (PHLF except for intraoperative factors and morbidity factors).\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThere are several limitations to this study. First, this was a single-center, retrospective study, which might bias the demographics of the patients. Second, 99mTc-GSA scintigraphy is relatively widespread in Japan, but is not yet widely used in European countries; thus, it might be difficult to extrapolate this result to European countries. Third, this study included only patients who had received hepatectomy; patients who did not have received hepatectomy due to impaired hepatic function. As mentioned in previous reports,\u003csup\u003e40\u003c/sup\u003e this might imply that we excluded from this analysis patients with low LHL15 values for whom hepatectomy would not be safely performed due to impaired hepatic function.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eAlthough LHL15 and ICG-R15 correlated well overall, the correlation weakened as hepatic function worsened. In patients with good hepatic function, the contribution of LHL15 to the prediction of PHLF is small, but as ICG-R15 increased, the impact of LHL15 on PHLF became larger. In patients with low ICG-R15, assessing hepatic function by mALBI grade would be useful. In patients with high ICG-R15, evaluating hepatic function using LHL15 would be useful for predicting the risk of PHLF. For predicting PHLF, 99mTc-GSA scintigraphy and modified ALBI score can complement ICG.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eAUC: area under the curve\u003c/p\u003e\n\u003cp\u003eAUROC: area under the receiver-operating characteristic curve\u003c/p\u003e\n\u003cp\u003eISGLS: international study group of liver surgery\u003c/p\u003e\n\u003cp\u003eROC: receiver-operating characteristic\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments:\u0026nbsp;\u003c/strong\u003eThe authors would like to thank Maruzen-Yushodo Co., Ltd. (https://kw.maruzen.co.jp/kousei-honyaku/) for the English language editing.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and material:\u0026nbsp;\u003c/strong\u003eThe datasets used and/or analyses during the current study are available from the corresponding author upon reasonable request. Data is provided within supplementary information as supplementary files. The file name is \u0026quot;data file (supplementary material).csv\u0026quot;.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u0026nbsp;\u003c/strong\u003eThis work was not supported by any grants or funding.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003cstrong\u003e:\u0026nbsp;\u003c/strong\u003eMii Satoshi, Takeshi Takahara, Susumu Shibasaki, Yutaro Kato, and Koichi Suda have no commercial association or financial involvement that might be construed as a conflict of interest in connection with the submitted article. Koichi Suda was funded by Medicaroid, Inc., in relation to the Collaborative Laboratory for Research and Development in Advanced Surgical Intelligence, Fujita Health University, and has also received advisory fees from Medicaroid, Inc., outside the submitted work.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical approval and consent to participate statement:\u0026nbsp;\u003c/strong\u003eThis study was approved by the institutional review board of Fujita Health University (HM19-064) and other participating hospitals. This study was also performed in accordance with the ethical standards laid down in the 1964 Declaration of Helsinki and its later amendments. Informed consent for this study was obtained through an opt-out method.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions:\u0026nbsp;\u003c/strong\u003eAll authors have fully satisfied the ICMJE authorship criteria as follows: study design: Satoshi Mii, Takeshi Takahara, Susumu Shibasaki, and Koichi Suda; data collection: Satoshi Mii and Yutaro Kato; statistical analysis and interpretation of results: Satoshi Mii, Takuma Ishihara, Takeshi Takahara, Susumu Shibasaki, and Koichi Suda; drafting of the manuscript: Satoshi Mii, Takuma Ishihara, Takeshi Takahara, Susumu Shibasaki, and Koichi Suda; and critical revision of the manuscript for important intellectual content: Takeshi Takahara, Susumu Shibasaki, Yutaro Kato, and Koichi Suda. All authors have read and approved the final manuscript and are accountable for all aspects of the work, particularly in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eZhong JH, Ke Y, Gong WF, Xiang BD, Ma L, Ye XP, et al. Hepatic resection associated with good survival for selected patients with intermediate and advanced-stage hepatocellular carcinoma. Ann Surg. 2014;260:329-40.\u003c/li\u003e\n\u003cli\u003ePinna AD, Yang T, Mazzaferro V, De Carlis L, Zhou J, Roayaie S, et al. Liver transplantation and hepatic resection can achieve cure for hepatocellular carcinoma. Ann Surg. 2018;268:868-75.\u003c/li\u003e\n\u003cli\u003eMargonis GA, Buettner S, Andreatos N, Sasaki K, Ijzermans JNM, van Vugt JLA, et al. Anatomical resections improve disease-free survival in patients with KRAS-mutated colorectal liver metastases. 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Surgery. 2015;157:20-6.\u003c/li\u003e\n\u003cli\u003eHiraoka A, Michitaka K, Kumada T, Izumi N, Kadoya M, Kokudo N, et al. Validation and potential of albumin-bilirubin grade and prognostication in a nationwide survey of 46,681 hepatocellular carcinoma patients in Japan: the need for a more detailed evaluation of hepatic function. Liver Cancer. 2017;6:325-36.\u003c/li\u003e\n\u003cli\u003eAida T, Haruki K, Akaoka M, Furukawa K, Onda S, Shirai Y, et al. A novel combined C-reactive protein‐albumin ratio and modified albumin‐bilirubin score can predict long‐term outcomes in patients with hepatocellular carcinoma after hepatic resection. Anna Gastroenterol Surg. 2023.\u003c/li\u003e\n\u003cli\u003eTomimaru Y, Eguchi H, Gotoh K, Kawamoto K, Wada H, Asaoka T, et al. Platelet count is more useful for predicting posthepatectomy liver failure at surgery for hepatocellular carcinoma than indocyanine green clearance test. J Surg Oncol. 2016;113:565-9.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-surgery","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bsur","sideBox":"Learn more about [BMC Surgery](http://bmcsurg.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bsur/default.aspx","title":"BMC Surgery","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"99mTc-GSA scintigraphy, LHL15, modified ALBI grade, hepatic functional reserve","lastPublishedDoi":"10.21203/rs.3.rs-3997930/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3997930/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cem\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e\u003c/em\u003e Posthepatectomy liver failure (PHLF) remains a severe complication after liver resection. This retrospective study investigated the correlation of three hepatic functional tests and whether 99mTc-galactosyl human serum albumin (99mTc-GSA) scintigraphy and modified albumin–bilirubin (ALBI) score are useful for predicting PHLF.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eMethods: \u003c/strong\u003e\u003c/em\u003eA total of 413 consecutivepatients undergoing hepatectomies between January 2017 and December 2020 at our institution were enrolled in this retrospective cohort study. To evaluate preoperative hepatic functional reserve, modified ALBI grade, indocyanine green clearance (ICG-R15), and 99mTc-GSA scintigraphy (LHL15) were routinely examined before the scheduled hepatectomy. Based on the retrospective chart review, multivariate logistic regression analysis adjusted for confounding factors was performed to confirm that ALBI, ICG-R15, and LHL15 are independent risk factors for PHLF.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eResults: \u003c/strong\u003e\u003c/em\u003eICG-R15 and LHL15 were moderately correlated (\u003cem\u003er\u003c/em\u003e = −0.61). However, the correlation with LHL15 weakened when ICG-R15 was about ³20. Weak correlations were observed between LHL15 and ALBI score (\u003cem\u003er\u003c/em\u003e = −0.269) and ALBI score and ICG-R15 (\u003cem\u003er\u003c/em\u003e = 0.339). Of 413 patients, 66 (19%) developed PHLF (grade A: n = 20, grade B: n = 44, grade C: n = 2). Multivariable logistic regression analyses, mALBI grade (\u003cem\u003eP\u003c/em\u003e= .014) and ICG-R15 (\u003cem\u003eP\u003c/em\u003e \u0026lt; .001) were significant independent risk factors for PHLF. Subgroup analysis showed that ICG-R15 \u0026lt;19, major hepatectomy, and mALBI grade and ICG-R15 ³19, major hepatectomy, and LHL15 were significant independent risk factors for PHLF (\u003cem\u003eP\u003c/em\u003e =.036,.020,.043, and.013, respectively).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eConclusion:\u003c/strong\u003e\u003c/em\u003e LHL15 and mALBI grade would be complementary to ICG-R15 for predicting PHLF risk.\u003c/p\u003e","manuscriptTitle":"99mTc-GSA scintigraphy and modified albumin–bilirubin score can be complementary to ICG for predicting posthepatectomy liver failure","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-03-21 15:33:55","doi":"10.21203/rs.3.rs-3997930/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-09-02T07:39:43+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-08-28T10:27:41+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-08-20T09:28:04+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-08-19T13:48:18+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-08-16T02:06:06+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-08-15T11:21:08+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"531509511050460200447805192831822665","date":"2024-08-15T05:39:12+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"73292185793883359553438995869399749146","date":"2024-08-15T05:27:21+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"8020332241056933640804189931999050482","date":"2024-08-14T22:54:15+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"256683105715918100681625721423629611117","date":"2024-08-14T14:00:03+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"18802407895165158085897971243414249476","date":"2024-08-14T10:02:47+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"280493134298235278610051755702423627645","date":"2024-08-13T23:56:35+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-06-24T07:47:48+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-06-19T11:09:12+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2024-03-19T10:52:40+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-03-19T10:50:15+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Surgery","date":"2024-02-28T22:34:17+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-surgery","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bsur","sideBox":"Learn more about [BMC Surgery](http://bmcsurg.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bsur/default.aspx","title":"BMC Surgery","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"df3dbb52-2e35-4786-97ec-cda045a8698f","owner":[],"postedDate":"March 21st, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-11-04T16:22:06+00:00","versionOfRecord":{"articleIdentity":"rs-3997930","link":"https://doi.org/10.1186/s12893-024-02624-8","journal":{"identity":"bmc-surgery","isVorOnly":false,"title":"BMC Surgery"},"publishedOn":"2024-11-01 16:04:57","publishedOnDateReadable":"November 1st, 2024"},"versionCreatedAt":"2024-03-21 15:33:55","video":"","vorDoi":"10.1186/s12893-024-02624-8","vorDoiUrl":"https://doi.org/10.1186/s12893-024-02624-8","workflowStages":[]},"version":"v1","identity":"rs-3997930","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3997930","identity":"rs-3997930","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}