Multiple postoperative complications: Making sense of the trajectories

Development and validation of an interpretable Markov-embedded multilabel model for predicting risks of multiple postoperative complications among surgical inpatients: a multicenter prospective cohort study

BACKGROUND

When they encounter various highly related postoperative complications, existing risk evaluation tools that focus on single or any complications are inadequate in clinical practice. This seriously hinders complication management because of the lack of a quantitative basis. An interpretable multilabel model framework that predicts multiple complications simultaneously is urgently needed.

MATERIALS AND METHODS

The authors included 50 325 inpatients from a large multicenter cohort (2014-2017). The authors separated patients from one hospital for external validation and randomly split the remaining patients into training and internal validation sets. A MARKov-EmbeDded (MARKED) multilabel model was proposed, and three models were trained for comparison: binary relevance, a fully connected network (FULLNET), and a deep neural network. Performance was mainly evaluated using the area under the receiver operating characteristic curve (AUC). The authors interpreted the model using Shapley Additive Explanations. Complication-specific risk and risk source inference were provided at the individual level.

RESULTS

There were 26 292, 6574, and 17 459 inpatients in the training, internal validation, and external validation sets, respectively. For the external validation set, MARKED achieved the highest average AUC (0.818, 95% CI: 0.771-0.864) across eight outcomes [compared with binary relevance, 0.799 (0.748-0.849), FULLNET, 0.806 (0.756-0.856), and deep neural network, 0.815 (0.765-0.866)]. Specifically, the AUCs of MARKED were above 0.9 for cardiac complications [0.927 (0.894-0.960)], neurological complications [0.905 (0.870-0.941)], and mortality [0.902 (0.867-0.937)]. Serum albumin, surgical specialties, emergency case, American Society of Anesthesiologists score, age, and sex were the six most important preoperative variables. The interaction between complications contributed more than the preoperative variables, and formed a hierarchical chain of risk factors, mild complications, and severe complications.

CONCLUSION

The authors demonstrated the advantage of MARKED in terms of performance and interpretability. The authors expect that the identification of high-risk patients and the inference of the risk source for specific complications will be valuable for clinical decision-making.

Construction and evaluation of networks among multiple postoperative complications

BACKGROUND AND OBJECTIVE

Postoperative complications confer an increased risk of reoperation, prolonged length of hospital stay, and increased mortality. Many studies have attempted to identify the complex associations among complications to preemptively interrupt their progression, but few studies have looked at complications as a whole to reveal and quantify their possible trajectories of progression. The main objective of this study was to construct and quantify the association network among multiple postoperative complications from a comprehensive perspective to elucidate the possible evolution trajectories.

METHODS

In this study, a Bayesian network model was proposed to analyze the associations among 15 complications. Prior evidence and score-based hill-climbing algorithms were used to build the structure. The severity of complications was graded according to their connection to death, with the association between them quantified using conditional probabilities. The data of surgical inpatients used in this study were collected from four regionally representative academic/teaching hospitals in a prospective cohort study in China.

RESULTS

In the network obtained, 15 nodes represented complications or death, and 35 arcs with arrows represented the directly dependent relationship between them. With three grades classified on that basis, the correlation coefficients of complications within grades increased with increased grade, ranging from -0.11 to -0.06, 0.16, and 0.21 to 0.4 in grade 1 to grade 3, respectively. Moreover, the probability of each complication in the network increased with the occurrence of any other complication, even mild complications. Most seriously, once cardiac arrest requiring cardiopulmonary resuscitation occurs, the probability of death will be up to 88.1%.

CONCLUSIONS

The present evolving network can facilitate the identification of strong associations among specific complications and provides a basis for the development of targeted measures to prevent further deterioration in high-risk patients.

Network prediction of surgical complication clusters: a prospective multicenter cohort study

Complicated relationships exist in both occurrence and progression of surgical complications, which are difficult to account for using a separate quantitative method such as prediction or grading. Data of 51,030 surgical inpatients were collected from four academic/teaching hospitals in a prospective cohort study in China. The relationship between preoperative factors, 22 common complications, and death was analyzed. With input from 54 senior clinicians and following a Bayesian network approach, a complication grading, cluster-visualization, and prediction (GCP) system was designed to model pathways between grades of complication and preoperative risk factor clusters. In the GCP system, there were 11 nodes representing six grades of complication and five preoperative risk factor clusters, and 32 arcs representing a direct association. Several critical targets were pinpointed on the pathway. Malnourished status was a fundamental cause widely associated (7/32 arcs) with other risk factor clusters and complications. American Society of Anesthesiologists (ASA) score ⩾3 was directly dependent on all other risk factor clusters and influenced all severe complications. Grade III complications (mainly pneumonia) were directly dependent on 4/5 risk factor clusters and affected all other grades of complication. Irrespective of grade, complication occurrence was more likely to increase the risk of other grades of complication than risk factor clusters.

Early Prediction of a Serious Postoperative Course in Perihilar Cholangiocarcinoma: Trajectory Analysis of the Comprehensive Complication Index

OBJECTIVE

The aim of this study was to visualize the postoperative clinical course using the comprehensive complication index (CCI) and to propose an early alarming sign for subsequent serious outcomes in perihilar cholangiocarcinoma.

BACKGROUND

Surgery for this disease carries a high risk of morbidity and mortality. The developmental course of the overall morbidity burden and its clinical utility are unknown.

METHODS

Patients who underwent major hepatectomy for perihilar cholan-giocarcinoma between 2010 and 2019 were reviewed retrospectively. All postoperative complications were evaluated according to the Clavien-Dindo classification (CDC), and the CCI was calculated on a daily basis until postoperative day 14 to construct an accumulating graph as a trajectory. Group-based trajectory modeling was conducted to categorize the trajectory into clinically distinct patterns and the predictive power of early CCI for a subsequent serious course was assessed.

RESULTS

A total of 4230 complications occurred in the 484 study patients (CDC grade I, n = 27; II, n = 132; IlIa, n = 290; IIIb, n = 4; IVa, n = 21; IVb, n = 1; and V, n = 9). The trajectory was categorized into 3 patterns: mild (n = 209), moderate (n = 235), and severe (n = 40) morbidity courses. The 90-day mortality rate significantly differed among the courses: 0%, 0.9%, and 17.5%, respectively (P<0.001). The cutoff values of the CCI on postoperative days 1, 4, and 7 for predicting a severe morbidity course were 15.0, 28.5, and 40.6 with areas under the curves of 0.780, 0.924, and 0.984, respectively.

CONCLUSIONS

The CCI could depict the chronological increase in the overall morbidity burden, categorized into 3 patterns. Early CCI potentially predicted sequential progression to serious outcomes.

Timing and Severity of Postoperative Complications and Associated 30-Day Mortality Following Hepatic Resection: a National Surgical Quality Improvement Project Study

BACKGROUND

The effect of varying severity and timing of complications after hepatic resection on 30-day mortality has not been thoroughly examined.

METHODS

National Surgical Quality Improvement Program Patient User Files (NSQIP-PUF) were used to identify patients who underwent elective hepatic resection between 2014 and 2019. The impact of number, timing, and severity of complications on 30-day mortality was examined.

RESULTS

Among 25,084 patients who underwent hepatic resection, 7436 (29.9%) patients developed at least one NSQIP complication, while 2688 (10.7%) had multiple (≥2) complications. Overall, 30-day mortality was 1.7% (n=424), among whom 81.4% (n=345) patients had ≥2 complications. The 30-day mortality was highest among patients with three consecutive severe complications (47.8%), as well as patients with one non-severe and two subsequent severe complications (47.6%). The adjusted probability of 30-day mortality was 35.5% (95%CI: 29.5-41.4%) when multiple severe complications occurred within the first postoperative week and 16.2% (95%CI: 7.2-25.1%) when the second severe complication occurred at least one week apart. The adjusted risk of 30-day mortality after even two non-severe complications was as high as 5.3% (95%CI: 3.7-6.9%) when the second complication occurred within a week postoperatively.

CONCLUSION

Approximately 1 in 10 patients developed multiple complications following hepatectomy. Timing and severity of complications were independently associated with 30-day mortality.

Morbidity and mortality analysis in general surgery operations. Is there any room for improvement?

BACKGROUND

The aim of this work is to examine the performance of surgeries, by evaluating the results. The evaluation of the results, with particular attention to complications, is the corner stone to identify the causes leading to correction of any predisposing factors and reducing risks, to improve quality of care.

METHODS

We performed a retrospective analysis of 952 consecutive patients who had elective or emergency surgery from November 1, 2018 to October 31, 2019. We classified surgical intervention according to their complexity. The Clavien Dindo classification was used to categorize the complications. We performed a stepwise multivariate logistic-regression analysis, with the presence of post-operative complications as dependent variable and age, gender, BMI, ASA, type of surgery procedures, complexity of surgery, operative time as covariates.

RESULTS

A total of 952 surgical procedures were included in this study. Abdominal procedures were the most frequent type of surgery performed (52.1%). Post-operative complications occurred in 120 surgical procedures (12.6%), these are related to the increase of the ASA score and the longer average operative time, with an increase of developing complication of 5% for each additional 10 minutes of surgery.

CONCLUSIONS

many factors influence postoperative morbidity and mortality. Particular attention was due to complication's evaluation, about all in abdominal surgery and high complexity procedures. We argue that key factors which influence the favourable surgical outcome are: compliance with standardized safety procedures, volume of activity of the structure, presence of interdisciplinary care groups, and ability of health professionals in recognizing and promptly treating complications.

Network Analysis of Postoperative Surgical Complications in a Cohort of Children Reported to the National Surgical Quality Improvement Program: Pediatric

OBJECTIVE

To understand the temporal relationships of postoperative complications in children and determine if they are related to each other in a predictable manner.

SUMMARY OF BACKGROUND DATA

Children with multiple postoperative complications have increased suffering and higher risk for mortality. Rigorous analysis of the temporal relations between complications, how complications might cluster, and the implications of such clusters for children have not been published. Herein, we analyze the relationships between postoperative complications in children.

METHODS

Data source: Surgical operations included in the National Surgical Quality Improvement Program Pediatric Participant Use Data File from 2013 to 2017. The main outcomes measure was presence of 1 or more postoperative complications within 30 days of surgery. Operations followed by multiple complications were analyzed using network analysis to study prevalence, timing, and co-occurrences of clusters of complications.

RESULTS

This study cohort consisted of 432,090 operations; 388,738 (89.97%) had no postoperative complications identified, 36,105 (8.35%) operations resulted in 1 postoperative complication and 7247 (1.68%) operations resulted in 2 or more complications. Patients with multiple complications were more likely to be younger, male, African American, with a higher American Society of Anesthesiologists score, and to undergo nonelective operations (P < 0.001). More patients died with 2 complication versus 1 complication vs no complication (5.3% vs 1.5% vs 0.14%, P < 0.001). Network analysis identified 4 Louvain clusters of complications with dense intracluster relationships.

CONCLUSIONS

Children with multiple postoperative complications are at higher risk of death, than patients with no complication, or a single complication. Multiple complications are grouped into defined clusters and are not independent.

Can Early Postoperative Complications Predict High Morbidity and Decrease Failure to Rescue Following Major Abdominal Surgery?

OBJECTIVE

To assess whether specific patterns of early postoperative complications may predict overall severe morbidity after major surgery, warranting early escalation of care and prevention of failure to rescue.

SUMMARY OF BACKGROUND DATA

It is unclear whether early postoperative complications predict a poor outcome. Detailed knowledge of the chronology and type of early complications after major surgery may alert clinicians when to expect higher risk for subsequent major negative events.

METHODS

All 90-day postoperative events following complex pancreas, liver, and rectal surgeries, and liver transplantation were analyzed over a 3-year period in a single tertiary center. Each complication was recorded regarding severity, type (cardiac, infectious, etc), etiology (surgical/medical), and timing of occurrence. The Comprehensive Complication Index (CCI), covering the first 7 postoperative days, was calculated as a measure for early cumulative postoperative morbidity. The statistical analysis (descriptive, sequence pattern analyses, and logistic regression analyses) aimed to detect any combinations of events predicting poor outcome as defined by a cumulative CCI ≥37.1 at 90-days.

RESULTS

The occurrence of ≥2 complications, irrespective of severity, type or etiology, was strongly associated with a severe postoperative course (P < 0.001). Even 2 mild complications (≤ grade II) greatly increased the chance for high morbidity compared to patients with 0 or 1 complication within the first postoperative week (odds ratio 10.2, 95% confidence interval 5.82-17.98). The CCI at postoperative day 7 strongly predicted high 90-day morbidity (odds ratio 3.96 per 10 CCI points, P < 0.001).

CONCLUSION

Multiple complications of any cause or severity within the first postoperative days represents a "warning-signal" for overall high morbidity by 90 days, which should be used to trigger an escalation of care to prevent failure to rescue and eventually poor outcome.

Severity of Postoperative Complications From the Perspective of the Patient

Background:

Although provider-derived surgical complication severity grading systems exist, little is known about the patient perspective.

Objective:

To assess patient-rated complication severity and determine concordance with existing grading systems.

Methods:

A survey asked general surgery patients to rate the severity of 21 hypothetical postoperative events representing grades 1 to 5 complications from the Accordion Severity Grading System. Concordance with the Accordion scale was examined. Separately, descriptive ratings of 18 brief postoperative events were ranked.

Results:

One hundred sixty-eight patients returned a mailed survey following their discharge from a general surgery service. Patients rated grade 4 complications highest. Grade 1 complications were rated similarly to grade 5 and higher than grades 2 and 3 (P ≤ .01). Patients rated one event not considered an Accordion scale complication higher than all but grade 4 complications (P < .001). The brief events also did not follow the Accordion scale, other than the grade 6 complication ranking highest.

Conclusion:

Patient-rated complication severity is discordant with provider-derived grading systems, suggesting the need to explore important differences between patient and provider perspectives.