Effective prediction of postoperative complications for patients after open hepatectomy: a simplified scoring system based on perioperative parameters

The Effect of Preoperative Administration of Glucocorticoids on the Postoperative Complication Rate in Liver Surgery: A Systematic Review and Meta-Analysis of Randomized Controlled Trials

Background: Glucocorticoids may grant a protective effect against postoperative complications. The evidence on their efficacy, however, has been inconclusive thus far. We investigated the effects of preoperatively administered glucocorticoids on the overall postoperative complication rate, and on liver function recovery in patients undergoing major liver surgery. Methods: We performed a systematic literature search on PubMed, Embase, and CENTRAL in October 2021, and repeated the search in April 2023. Pre-study protocol was registered on PROSPERO (ID: CRD42021284559). Studies investigating patients undergoing liver resections or transplantation who were administered glucocorticoids preoperatively and reported postoperative complications were eligible. Meta-analyses were performed using META and DMETAR packages in R with a random effects model. Risk of bias was assessed using RoB2. Results: The selection yielded 11 eligible randomized controlled trials (RCTs) with 964 patients. Data from nine RCTs (n = 837) revealed a tendency toward a lower overall complication rate with glucocorticoid administration (odds ratio: 0.71; 95% confidence interval: 0.38-1.31, p = 0.23), but it was not statistically significant. Data pooled from seven RCTs showed a significant reduction in wound infections with glucocorticoid administration [odds ratio: 0.64; 95% confidence interval: 0.45-0.92 p = 0.02]. Due to limited data availability, meta-analysis of liver function recovery parameters was not possible. Conclusions: The preoperative administration of glucocorticoids did not significantly reduce the overall postoperative complication rate. Future clinical trials should investigate homogenous patient populations with a specific focus on postoperative liver recovery.

Association between white blood cell count to hemoglobin ratio and risk of in-hospital mortality in patients with lung cancer

BACKGROUND

The objective of this study was to investigate the association between white blood cell count to hemoglobin ratio (WHR) and risk of in-hospital mortality in patients with lung cancer.

METHODS

In this retrospective cohort study, the medical records of patients with lung cancer were retrieved from the electronic ICU (eICU) Collaborative Research Database between 2014 and 2015. The primary outcome was in-hospital mortality. The secondary outcome was the length of stay in intensive care unit (ICU). The cut-off value for the WHR was calculated by the X-tile software. The Cox model was applied to assess the association between WHR and in-hospital mortality among patients with lung cancer and the linear regression model was used to investigate the association between WHR and length of ICU stay. Subgroup analyses of age (< 65 years or >  = 65 years), Acute Physiology and Chronic Health Evaluation (APACHE) score (< 59 or >  = 59), gender, ventilation (yes or no), and vasopressor (yes or no) in patients with lung cancer were conducted.

RESULTS

Of the 768 included patients with lung cancer, 153 patients (19.92%) died in the hospital. The median total follow-up time was 6.88 (4.17, 11.23) days. The optimal cut-off value for WHR was 1.4. ICU lung cancer patients with WHR >  = 1.4 had a significantly higher risk of in-hospital mortality [Hazard ratio: (HR): 1.65, 95% confidence interval (CI): 1.15 to 2.38, P = 0.007) and length of stay in ICU (HR: 0.63, 0.01, 95% CI: 1.24 to 0.045, P = 0.045). According to the subgroup analysis, WHR was found to be associated with in-hospital mortality in patients with higher APACHE score (HR: 1.60, 95% CI: 1.06 to 2.41, P = 0.024), in male patients (HR: 1.87, 95% CI: 1.15 to 3.04, P = 0.012), and in patients with the treatment of ventilation (HR: 2.33, 95% CI: 1.49 to 3.64, P < 0.001).

CONCLUSION

This study suggests the association between WHR and risk of in-hospital mortality in patients with lung cancer and length of stay, which indicates the importance of attention to WHR for patients with lung cancer.

Real-time risk prediction of colorectal surgery-related post-surgical complications using GRU-D model

BACKGROUND

Post-surgical complications (PSCs) have been an increasing concern for hospitals in light of Medicare penalties for 30-day readmissions. PSCs have become a target for quality improvement and benchmark for the healthcare system. Over half (60 %) of the deep or organ space surgical site infections are discovered after discharge, leading to a readmission. There has thus been a push to develop risk prediction models for targeted preventive interventions for PSCs.

OBJECTIVE

We experiment several Gated Recurrent Unit with Decay (GRU-D) based deep learning architectures with various feature sampling schemes in predicting the risk of colorectal PSCs and compare with atemporal logistic regression models (logit).

METHOD

We used electronic health record (EHR) data of 3,535 colorectal surgical patients involved in the national surgical quality improvement program (NSQIP) between 2006 and 2018. Single layer, stacked layer, and multimodal GRU-D models with sigmoid activation were used to develop risk prediction models. Area Under the Receiver Operating Characteristic curve (AUROC) was calculated by comparing predicted probability of developing complications versus truly observed PSCs (NSQIP adjudicated) within 30 days after surgery. We set up cross-validation and an independent held-out dataset for testing model performance consistency.

RESULTS AND CONCLUSION

The primary contribution of our study is the formulation of a novel real-time PSC risk prediction task using GRU-D with demonstrated clinical utility. GRU-D outperforms the logit model in predicting wound and organ space infection and shows improved performance as additional data points become available. Logit model outperforms GRU-D before surgery for superficial infection and bleeding. For the same sampling scheme, there is no obvious advantage of complex architectures (stacked, multimodal) over single layer GRU-D. Obtaining more data points closer to the occurrence of PSCs is more important than using a more frequent sampling scheme in training GRU-D models. The fourth predicted risk quartile by single layer GRU-D contains 63 %, 59 %, and 66 % organ space infection cases, at 4 h before, 72 h after, and 168 h after surgery, respectively, suggesting its potential application as a bedside risk assessment tool.

Individualized risk estimation for postoperative pulmonary complications after hepatectomy based on perioperative variables

BACKGROUND

At present, there is no perfect system to evaluate pulmonary complications of liver surgery using perioperative variables.

AIM

To design and verify a risk assessment system for predicting postoperative pulmonary complications (PPCs) after hepatectomy based on perioperative variables.

METHODS

A retrospective analysis was performed on 1633 patients who underwent liver surgery. The variables were screened using univariate and multivariate analyses, and graded scores were assigned to the selected variables. Logistic regression was used to develop the liver operation pulmonary complication scoring system (LOPCSS) for the prediction of PPCs. The LOPCSS was verified using the receiver operating characteristic curve.

RESULTS

According to the multivariate correlation analysis, the independent factors which influenced PPCs of liver surgery were age [≥ 65 years old/< 65 years old, odds ratio (OR) = 1.926, P = 0.011], medical diseases requiring drug treatment (yes/no, OR = 3.523, P < 0.001), number of liver segments to be removed (≥ 3/≤ 2, OR = 1.683, P = 0.002), operation duration (≥ 180 min/< 180 min, OR = 1.896, P = 0.004), and blood transfusion (yes/no, OR = 1.836, P = 0.003). The area under the curve (AUC) of the LOPCSS was 0.742. The cut-off value of the expected score for complications was 5. The incidence of complications in the group with ≤ 4 points was significantly lower than that in the group with ≥ 6 points (2.95% vs 33.40%, P < 0.001). Furthermore, in the validation dataset, the corresponding AUC of LOPCSS was 0.767.

CONCLUSION

As a novel and simplified assessment system, the LOPCSS can effectively predict PPCs of liver surgery through perioperative variables.

Application value of mixed reality in hepatectomy for hepatocellular carcinoma

BACKGROUND

As a new digital holographic imaging technology, mixed reality (MR) technology has unique advantages in determining the liver anatomy and location of tumor lesions. With the popularization of 5G communication technology, MR shows great potential in preoperative planning and intraoperative navigation, making hepatectomy more accurate and safer.

AIM

To evaluate the application value of MR technology in hepatectomy for hepatocellular carcinoma (HCC).

METHODS

The clinical data of 95 patients who underwent open hepatectomy surgery for HCC between June 2018 and October 2020 at our hospital were analyzed retrospectively. We selected 95 patients with HCC according to the inclusion criteria and exclusion criteria. In 38 patients, hepatectomy was assisted by MR (Group A), and an additional 57 patients underwent traditional hepatectomy without MR (Group B). The perioperative outcomes of the two groups were collected and compared to evaluate the application value of MR in hepatectomy for patients with HCC.

RESULTS

We summarized the technical process of MR-assisted hepatectomy in the treatment of HCC. Compared to traditional hepatectomy in Group B, MR-assisted hepatectomy in Group A yielded a shorter operation time (202.86 ± 46.02 min vs 229.52 ± 57.13 min, P = 0.003), less volume of bleeding (329.29 ± 97.31 mL vs 398.23 ± 159.61 mL, P = 0.028), and shorter obstructive time of the portal vein (17.71 ± 4.16 min vs 21.58 ± 5.24 min, P = 0.019). Group A had lower alanine aminotransferas and higher albumin values on the third day after the operation (119.74 ± 29.08 U/L vs 135.53 ± 36.68 U/L, P = 0.029 and 33.60 ± 3.21 g/L vs 31.80 ± 3.51 g/L, P = 0.014, respectively). The total postoperative complications and hospitalization days in Group A were significantly less than those in Group B [14 (37.84%) vs 35 (60.34%), P = 0.032 and 12.05 ± 4.04 d vs 13.78 ± 4.13 d, P = 0.049, respectively].

CONCLUSION

MR has some application value in three-dimensional visualization of the liver, surgical planning, and intraoperative navigation during hepatectomy, and it significantly improves the perioperative outcomes of hepatectomy for HCC.

Association of Diabetes Mellitus With Postoperative Complications and Mortality After Non-Cardiac Surgery: A Meta-Analysis and Systematic Review

BACKGROUND

Although a variety of data showing that diabetes mellitus (DM) (Type 1 or Type 2) is associated with postoperative complication, there is still a lack of detailed studies that go through the specific diabetic subgroups. The goal of this meta-analysis is to assess the relationship between DM and various complications after non-cardiac surgery.

METHODS

We searched articles published in three mainstream electronic databases (PubMed, EMBASE, Web of science) before November, 2020. A random effects model was conducted since heterogeneity always exist when comparing results between different types of surgery.

RESULTS

This paper included 125 studies with a total sample size of 3,208,776 participants. DM was a risk factor for any postoperative complication (Odds ratio (OR)=1.653 [1.487, 1.839]). The risk of insulin-dependent DM (OR=1.895 [1.331, 2.698]) was higher than that of non-insulin-dependent DM (OR=1.554 [1.061, 2.277]) for any postoperative complication. DM had a higher risk of infections (OR=1.537 [1.322, 1.787]), wound healing disorders (OR=2.010 [1.326, 3.046]), hematoma (OR=1.369 [1.120, 1.673]), renal insufficiency (OR=1.987 [1.311, 3.013]), myocardial infarction (OR=1.372 [0.574, 3.278]). Meanwhile, DM was a risk factor for postoperative reoperation (OR=1.568 [1.124, 2.188]), readmission (OR=1.404 [1.274, 1.548]) and death (OR=1.606 [1.178, 2.191]).

CONCLUSIONS

DM is a risk factor for any postoperative complications, hospitalization and death after non-cardiac surgery. These findings underscore the importance of preoperative risk factor assessment of DM for the safe outcome of surgical patients.

Combining ALT/AST Values with Surgical APGAR Score Improves Prediction of Major Complications after Hepatectomy

Hepatectomy is a complex procedure with high morbidity and mortality. Early prediction/prevention of major complications is highly valuable for patient care. Surgical APGAR score (SAS) has been validated to predict post-surgical complications (PCs). We aimed to define a simple complications classification following hepatectomy based on a therapy-oriented severity Clavien-Dindo classification (CDC). 119 patients undergoing liver resection were included. PCs were determined at follow-up based on CDC. Clinicopathological factors were used to calculate SAS. A receiver-operator characteristic (ROC) curve analysis estimated the predictive value of SAS for PCs. Circulating markers levels of liver injury were analyzed as critical elements on PCs. SAS (P=0.008), estimated blood-loss (P=0.018) and operation time (P=0.0008) were associated with PCs. SAS was reduced in patients with (+) compared to those without (-) complications (6.64±1.84 vs 5.70±1.79, P=0.0079). The area-under-the-curve was 0.646 by ROC, indicating an acceptable discrimination with 65% possibility to distinguish (-) and (+) groups (P=0.004). Best cutoff value for SAS was ≤6/≥7, at which sensitivity and specificity were maximal. ALT/ASL levels were significantly different within the group with 9-10 SAS points (P=0.01 and 0.02). In conclusion, SAS provides accurate risk stratification for major PCs after hepatectomy, and might help improving the overall patient outcome.

Predicting Intraoperative Difficulty of Open Liver Resections: The DIFF-scOR Study, An Analysis of 1393 Consecutive Hepatectomies From a French Multicenter Cohort

OBJECTIVE

The aim of this study was to build a predictive model of operative difficulty in open liver resections (LRs).

SUMMARY BACKGROUND DATA

Recent attempts at classifying open-LR have been focused on postoperative outcomes and were based on predefined anatomical schemes without taking into account other anatomical/technical factors.

METHODS

Four intraoperative variables were perceived by the authors as to reflect operative difficulty: operation and transection times, blood loss, and number of Pringle maneuvers. A hierarchical ascendant classification (HAC) was used to identify homogeneous groups of operative difficulty, based on these variables. Predefined technical/anatomical factors were then selected to build a multivariable logistic regression model (DIFF-scOR), to predict the probability of pertaining to the highest difficulty group. Its discrimination/calibration was assessed. Missing data were handled using multiple imputation.

RESULTS

HAC identified 2 clusters of operative difficulty. In the "Difficult LR" group (20.8% of the procedures), operation time (401 min vs 243 min), transection time (150 vs.63 minute), blood loss (900 vs 400 mL), and number of Pringle maneuvers (3 vs 1) were higher than in the "Standard LR" group. Determinants of operative difficulty were body weight, number and size of nodules, biliary drainage, anatomical or combined LR, transection planes between segments 2 and 4, 4, and 8 or 7 and 8, nonanatomical resections in segments 2, 7, or 8, caval resection, bilioentric anastomosis and number of specimens. The c-statistic of the DIFF-scOR was 0.822. By contrast, the discrimination of the DIFF-scOR to predict 90-day mortality and severe morbidity was poor (c-statistic: 0.616 and 0.634, respectively).

CONCLUSION

The DIFF-scOR accurately predicts open-LR difficulty and may be used for various purposes in clinical practice and research.

Preoperative Fasting Abbreviation With Whey Protein Reduces the Occurrence of Postoperative Complications in Patients With Head and Neck Cancer: A Randomized Clinical Trial

BACKGROUND

Surgery has become the treatment of choice for head and neck cancer (HNC) in most cases. Preoperative fasting abbreviation and nutrition screening have been suggested to reduce the occurrence of postoperative complications. This study aimed to evaluate the addition of whey protein in the preoperative fasting abbreviation and to analyze the association of nutrition status on postoperative complications in patients with HNC.

METHODS

A randomized, single-blind clinical trial was performed. Patients recruited from March to November 2018 at a national cancer reference center in Brazil were divided into 2 groups: intervention group (clear fluids with carbohydrate plus whey protein [CHO-P]) and control group (clear fluids with carbohydrate only [CHO]). All patients were evaluated by the Patient-Generated Subjective Global Assessment (PG-SGA) and body mass index. Logistic regression analyses were performed to assess associations between the studied variables, generating odds ratios (ORs) and 95% confidence intervals (CIs).

RESULTS

A total of 49 patients met the eligibility criteria and enrolled in the study. A PG-SGA score of 4-8, indicating moderate malnutrition (OR, 10.91; 95% CI, 1.05-112.91), was an independent factor that increased the risk of postoperative complication, whereas the CHO-P group (OR, 0.04; 95% CI, 0.01-0.26) was found to be an independent factor in reducing such risk.

CONCLUSION

The addition of whey protein to clear fluids (CHO-P group) was associated with a reduced risk of postoperative complications compared with the CHO group. Furthermore, moderate malnourishment was associated with an increased risk of postoperative complications for patients with HNC.

Obesity is an Independent Risk Factor for Mortality in Otherwise Healthy Patients After Hepatectomy

BACKGROUND

Obesity is often associated with comorbidities that limit remnant liver recovery after hepatectomy. The extent to which obesity, in the absence of comorbidities, impacts surgical risk after hepatectomy is unknown. We hypothesized that an obese population without major comorbidities would not be at increased risk of adverse outcomes after hepatectomies.

METHODS

We performed a retrospective analysis identifying patients who underwent hepatectomies from the American College of Surgeons National Surgical Quality Improvement Program data set 2005-2017. Outcomes of interest included the following: mortality, any morbidity, critical care complications, and failure to discharge home. Body mass index (BMI) was the primary variable of interest, grouped as ≥35 and <35 based on bivariate tests of associations with candidate cut-off points. In attempt to isolate the effect of obesity on outcomes among patients "without major comorbidities" (WOC), we included patients without diabetes, chronic obstructive pulmonary disease, renal insufficiency, and nonsmokers; remaining patients were grouped as "with major comorbidities" (WC). Multivariable logistic regression was used to test whether obesity is independently associated with the outcomes of interest after adjustment for other covariates.

RESULTS

A total of 36,396 patients were included. There were 13,754 patients in the WOC group and 22,642 in the WC group. Among patients in the WOC group, the adjusted odds of mortality were 2.2 times higher for patients with a BMI ≥35 versus a BMI <35. Among the patients in the WC group, a BMI ≥35 was not a statistically significant predictor of mortality after adjustment for other covariates. Obese patients had increased odds of each outcome among the WOC group.

CONCLUSIONS

Our hypothesis was refuted by these data. In fact, the adverse effect of obesity was more evident among healthy patients.