Perioperative Hidden Blood Loss in Lumbar Disk Herniation Patients With Percutaneous Endoscopic Transforaminal Discectomy and Influencing Factors

Hu, Man; Zhang, Yu; Zhao, Wen; Liu, Xin; Shi, Peng; Wang, Jun Wu; Cai, Tong; Zhang, Liang

doi:10.1097/bsd.0000000000001282

Cited by 10 publications

(10 citation statements)

References 27 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Hypertension( p = 0.002) and Diabetes( p < 0.001) were a positive influencing factor of hidden blood loss, which were contrary to the findings of Man Hu et al [ 18 ]. The author believes that this discrepancy may stem from the surgical approach (Percutaneous endoscopic transforaminal discectomy (PETD) for lumbar disc herniation no bone tissue damage and minimal soft tissue damage).…”

Section: Discussioncontrasting

confidence: 88%

Hidden blood loss of minimally invasive hybrid lumbar interbody fusion: an analysis of influencing factors

Dai

Feng

et al. 2022

BMC Musculoskelet Disord

View full text Add to dashboard Cite

Background Lumbar interbody fusion(LIF) is the leading way to treat Lumbar Degenerative Diseases(LDD). At present, there is a lack of research on the influencing factors of hidden blood loss in minimally invasive hybrid lumbar interbody fusion. This study comprehensively explores the definite factors affecting the hidden blood loss in minimally invasive hybrid lumbar interbody fusion. Materials and methods One hundred patients with Lumbar degenerative diseases who underwent minimally invasive hybrid lumbar interbody fusion in our center were included. Demographics, laboratory data, surgical data, and radiographic data were collected. The Gross equation and Sehat equation were used to calculate the estimated value of hidden blood loss. Multi-factor linear regression analysis was used to determine the influencing factors of hidden blood loss. Result We reviewed and collected 100 patients who underwent minimally invasive hybrid approach, mean age 65 ± 10 years, male: female 37:63; 17 patients of diabetes and 83 patients of non-diabetes; Total blood loss was 645.59 ± 376.37 ml, hidden blood loss was 421.39 ± 337.45 ml, the hidden blood loss percentage was 57 ± 26%. Results from the multi-factorial linear regression model: Diabetes (p < 0.05), hypertension (p < 0.05), psoas thickness (p < 0.05) and dorsal extensor group thickness (p < 0.05) were potential risk factors for postoperative hidden blood loss. Conclusion Although minimally invasive hybrid approach is minimally invasive surgery, there is still a significant amount of hidden blood loss. There is a greater risk of blood loss in diabetes, hypertension and preoperative MRI assessment of thickness of the psoas, thickness of the dorsal extensor group.

show abstract

Section: Discussioncontrasting

confidence: 88%

Hidden blood loss of minimally invasive hybrid lumbar interbody fusion: an analysis of influencing factors

Dai

Feng

et al. 2022

BMC Musculoskelet Disord

View full text Add to dashboard Cite

show abstract

“…To date, the most common complications occurring after arthroscopic surgery may be related to hidden blood loss, which is to rule out significant blood loss during surgery and postoperative drainage volume, as the part of the body’s hidden loss of blood volume. Hidden blood loss is generally associated with hematocele in the joint space, interstitial hematocele, hemolysis, and stress gastrointestinal bleeding leading to hemoglobin loss ( 9 ). However, there are few reports on the factors behind hidden blood loss after knee arthroscopic surgery.…”

Section: Discussionmentioning

confidence: 99%

The hidden blood loss and its factors in patients undergoing minimally invasive knee arthroscopy

Liang

2022

Front. Surg.

View full text Add to dashboard Cite

BackgroundWith respect to knee arthroscopy, assessing the amount of hidden blood loss is of great importance to avoid potential complications such as fever, anemia, difficulty in wound healing and wound infection. The current study aims to investigate the hidden blood loss and its factors in patients who underwent minimally invasive knee arthroscopy.MethodsConsecutive patients with knee joint injury, who underwent arthroscopic minimally invasive treatment, were enrolled from January 2019 to November 2020 and were retrospectively studied. Demographic information on these patients, such as medical history and biochemical parameters, was collected. The hidden blood loss was calculated. Multivariate linear regression analysis was used to confirm independent factors associated with hidden blood loss.ResultsFinally, a total of 100 patients aged 44.78 ± 13.67 (range 17–66) years were reviewed, and it was found that a substantial amount of [387.02 ± 252.56 (range 18.89–1130.06) ml] hidden blood loss occurred after minimally invasive knee arthroscopy. Univariate analysis showed that this hidden blood loss was negatively correlated with age, gender, postoperative hemoglobin, and postoperative hematocrit (all P < 0.05), while it was positively correlated with body mass index (BMI), length of hospital stay, preoperative red blood cells, preoperative hemoglobin, preoperative hematocrit, blood volume, and the presence of medical conditions (all P < 0.05). Further multivariate linear regression indicated that preoperative hematocrit, blood volume, and postoperative hematocrit were independent factors associated with actual blood loss, and preoperative hematocrit, blood volume, postoperative hematocrit, and gender were independent factors associated with hidden blood loss, respectively (all P < 0.05).ConclusionPreoperative hematocrit, preoperative blood volume, postoperative hematocrit, and gender are the influencing factors of hidden blood loss in patients undergoing minimally invasive treatment under knee arthroscopy. More attention should be paid to hidden blood loss and its factors during the perioperative period.

show abstract

“…At present, there are several reports on the relationship between total operational time and perioperative HBL. A retrospective study reported that patients' HBL increased in direct proportion to the length of the surgery ( 26 ). Another retrospective cohort analysis discovered a significant correlation between the quantity of HBL and the overall operating time ( 27 ).…”

Section: Discussionmentioning

confidence: 99%

“…Furthermore, APTT is another coagulation activity indicator, and its reduction is regarded as activation of the endogenous coagulation pathway. Most of the literature reported that pre-operative APTT was not correlated to patients' HBL during the perioperative period ( 8 , 26 ). In contrast, some clinical research has identified APTT as a positive risk factor for HBL in TBF patients, and increased APTT can promote an increase in HBL, which could be explained by hemolysis ( 6 ).…”

Section: Discussionmentioning

confidence: 99%

Application of supervised machine learning algorithms to predict the risk of hidden blood loss during the perioperative period in thoracolumbar burst fracture patients complicated with neurological compromise

Yang

Gao

Wang

et al. 2022

Front. Public Health

View full text Add to dashboard Cite

BackgroundMachine learning (ML) is a type of artificial intelligence (AI) and has been utilized in clinical research and practice to construct high-performing prediction models. Hidden blood loss (HBL) is prevalent during the perioperative period of spinal treatment and might result in a poor prognosis. The aim of this study was to develop a ML-based model for identifying perioperative HBL-related risk factors in patients with thoracolumbar burst fracture (TBF).MethodsIn this study, single-central TBF patients were chosen. The medical information on patients, including clinical characteristics, laboratory indicators, and surgery-related parameters, was extracted. After comparing various ML model algorithms, we selected the best model with high performance. The model was validated using the internal validation set before performing recursive feature elimination (RFE) to determine the importance of HBL-related risk factors. The area under the receiver operating characteristic (AUC) curve, accuracy (ACC), sensitivity, and specificity were reported as critical model measures for evaluating predictive performance.ResultsIn this study, 62 (38.5%) of the 161 TBF patients were positive for HBL. There was a significant statistical difference in age, body mass index (BMI), diabetes, hypertension, Beta (percentage of vertebral restoration), duration of operation, and other pre-operative laboratory indicators between the HBL-positive and HBL-negative groups. Nine ML-based models were built and validated, with the Random Forest model having the greatest AUC in both the training set (0.905) and internal validation set (0.864). Furthermore, following RFE, age, duration of operation, Beta, pre-operative fibrinogen (Fib), and activated partial thromboplastin time (APTT) were identified as the five main important risk factors in patients with TBF during the perioperative period.ConclusionIn this study, we built and validated ML algorithms for an individualized prediction of HBL-related risk factors in the perioperative period of TBF. The importance of HBL-related risk factors could be determined, which contributes to clinicians' decision-making and improves perioperative management.

show abstract

Perioperative Hidden Blood Loss in Lumbar Disk Herniation Patients With Percutaneous Endoscopic Transforaminal Discectomy and Influencing Factors

Cited by 10 publications

References 27 publications

Hidden blood loss of minimally invasive hybrid lumbar interbody fusion: an analysis of influencing factors

Hidden blood loss of minimally invasive hybrid lumbar interbody fusion: an analysis of influencing factors

The hidden blood loss and its factors in patients undergoing minimally invasive knee arthroscopy

Application of supervised machine learning algorithms to predict the risk of hidden blood loss during the perioperative period in thoracolumbar burst fracture patients complicated with neurological compromise

Contact Info

Product

Resources

About