Decreased skeletal muscle density is an independent predictor of mortality in necrotizing pancreatitis- A single tertiary center experience in 507 patients

Beyond body mass index: exploring the role of visceral adipose tissue in intensive care unit outcomes

Obesity is a worldwide health crisis and poses significant challenges in critical care. Many studies suggest an 'obesity paradox', in which obesity, defined by body mass index (BMI), is associated with better outcomes. However, the inability of BMI to discriminate between fat and muscle or between visceral adipose tissue and subcutaneous adipose tissue, limits its prediction of metabolic ill health. We suggest that the 'obesity paradox' may be more reflective of the limitations of BMI than the protective effect of obesity. We explore the biological processes leading to visceral fat accumulation, and the evidence linking it to outcomes in critical illness. In the 'spillover' hypothesis of adipose tissue expansion, caloric excess and impaired expansion of storage capacity in the subcutaneous adipose tissue lead to accumulation of visceral adipose tissue. This is associated with a chronic inflammatory state, which is integral to the link between visceral adiposity, type 2 diabetes mellitus, and ischaemic heart disease. We review the current evidence on visceral adiposity and critical illness outcomes. In COVID-19, increased visceral adipose tissue, irrespective of BMI, is associated with more severe disease. This is mirrored in acute pancreatitis, suggesting visceral adiposity is linked to poorer outcomes in some hyperinflammatory conditions. We suggest that visceral adiposity's chronic inflammatory state may potentiate acute inflammation in conditions such as COVID-19 and acute pancreatitis. Further work is required to investigate other critical illnesses, especially sepsis and acute respiratory distress syndrome, in which current evidence is scarce. This may give further insights into pathophysiology and inform tailored treatment and nutrition strategies based on body fat distribution.

Measurement of adipose body composition using an artificial intelligence-based CT Protocol and its association with severe acute pancreatitis in hospitalized patients

BACKGROUND/OBJECTIVES

The clinical utility of body composition in predicting the severity of acute pancreatitis (AP) remains unclear. We aimed to measure body composition using artificial intelligence (AI) to predict severe AP in hospitalized patients.

METHODS

We performed a retrospective study of patients hospitalized with AP at three tertiary care centers in 2018. Patients with computer tomography (CT) imaging of the abdomen at admission were included. A fully automated and validated abdominal segmentation algorithm was used for body composition analysis. The primary outcome was severe AP, defined as having persistent single- or multi-organ failure as per the revised Atlanta classification.

RESULTS

352 patients were included. Severe AP occurred in 35 patients (9.9%). In multivariable analysis, adjusting for male sex and first episode of AP, intermuscular adipose tissue (IMAT) was associated with severe AP, OR = 1.06 per 5 cm2, p = 0.0207. Subcutaneous adipose tissue (SAT) area approached significance, OR = 1.05, p = 0.17. Neither visceral adipose tissue (VAT) nor skeletal muscle (SM) was associated with severe AP. In obese patients, a higher SM was associated with severe AP in unadjusted analysis (86.7 vs 75.1 and 70.3 cm2 in moderate and mild, respectively p = 0.009).

CONCLUSION

In this multi-site retrospective study using AI to measure body composition, we found elevated IMAT to be associated with severe AP. Although SAT was non-significant for severe AP, it approached statistical significance. Neither VAT nor SM were significant. Further research in larger prospective studies may be beneficial.

Impact of Hepatic Steatosis, Psoas Muscle Mass, and Density on Outcomes in Patients with Moderately Severe and Severe Acute Pancreatitis: A Serial Computed Tomography-Based Retrospective Study

Background and Objective There is limited literature on the association of fatty liver and muscle mass with outcomes of acute pancreatitis (AP) in Indian patients. We aim to investigate the impact of these parameters on clinical outcomes in AP patients based on serial computed tomography (CT) scans.

Materials and Methods Consecutive patients of AP who had a baseline CT scan within 2 weeks of pain onset and a follow-up CT scan within 2 months of initial CT scan were included. Fatty liver, spleen to liver attenuation difference (AD), psoas muscle area (PMA), and psoas muscle attenuation (PMAt) were assessed on baseline and follow-up portal venous CT scans. Their association with the length of hospitalization, intensive care unit (ICU) admission, length of ICU stay, surgery, and mortality were assessed using univariate and multivariate analysis.

Results One hundred and ninety-eight patients (143 [72.2%] males, mean age 37.9 [ ± 12.4] years) were included. The mean interval between the two CT scans was 30 days (± 13.5 days). Twenty-four (12.1%) patients had fatty liver at baseline CT and 58 (29.3%) patients had fatty liver on follow-up CT (p < 0.001). The mean AD at the baseline scan was –10.2 (± 12.3) Hounsfield units (HU) and on follow up was –18.8 (± 21.7) HU (p < 0.001). PMA in baseline CT was 13.9 (± 5.5) mm2 and on follow-up was 11.2 (± 4.6) mm2 (p < 0.001). PMAt on baseline CT was 49.2 (± 8.2) HU and on follow-up was 47.1 (± 12.1) HU (p < 0.001). In multivariate analysis, the PMA and PMAt were significantly associated with the clinical outcomes. There was no association of fatty liver with clinical outcomes. The parameter with the highest area under the curve for predicting clinical outcomes was PMAt at follow-up CT.

Conclusion Psoas muscle-based assessment is associated with clinical outcomes in patients with AP.

Psoas Muscle Index and Density as Prognostic Predictors in Patients Hospitalized with Acute Pancreatitis

Background: Early prognostication of acute pancreatitis (AP) patients for those at high risk of complications during hospitalization can facilitate clinical decision-making. Sarcopenia has been proven to be a risk factor for poor prognosis in patients with AP. We aimed to evaluate the association between the muscle parameters measured in computed tomography (CT) and the clinical outcomes of hospitalized patients with AP. Methods: A total of 132 consecutive patients hospitalized between 1 January 2015 and 31 December 2021 for AP with a valid CT scan were analyzed. The first CT conducted during hospitalization was analyzed for psoas muscle area (PMA), index (PMI), and density (PMD) at the L3 vertebral level. The main adverse outcomes indicating a worse prognosis were the development of extrapancreatic complications, infections, ICU transfer, in-hospital mortality, and hospitalization length. Results: The lowest tertile of PMI, as a surrogate for sarcopenia, was significantly correlated with increased rates of extrapancreatic complications, infections, and longer hospitalizations. It was additionally correlated with a worse CT severity index. The results for PMA and PMD also showed worse outcomes, largely mirroring the results for PMI. Although in-hospital mortality was relatively low, none of the patients died in the highest tertile of PMI. A clear cutoff with sufficient predictive capability could not be found. Conclusions: A low psoas muscle index can serve as an additional potential predictive marker for more severe disease and worse outcomes in hospitalized acute pancreatitis patients. More studies are needed to determine its combination with existing prediction tools.

Low skeletal muscle quality extracted from CT is associated with poor outcomes in severe acute pancreatitis patients

PURPOSE

To evaluate the association between body composition parameters derived from computed tomography (CT) scans and clinical outcomes in patients with severe acute pancreatitis (AP).

METHODS

Patients who have been diagnosed AP with a CT scan at ICU admission were included. Body composition parameters were measured on a single slice at L2-3 of the unenhanced CT scans. The intermuscular adipose tissue (IMAT), visceral adipose tissue (VAT), skeletal muscle area (SMA) and skeletal muscle density (SMD) were assessed using HUs by image analysis software. Univariable and multivariable analyses were performed to analyze the association between body composition parameters and clinical outcomes including all-cause mortality or prolonged ICU stay. The area under the curve (AUC) of a receiver operating characteristic curve was used to explore the predictive value of the body composition on treatment clinical outcomes.

RESULTS

A total of 158 patients were included. The IMAT (8.3 cm2 vs 6.0 cm2, P = 0.001) and VAT (190.3 cm2 vs 143.7 cm2, P < 0.001) were significantly higher in the severe AP group than in the moderately severe group, but were notassociatedwithoutcomes. For 1 HU of SMD increased, the risk of poor clinical outcomes decresed 11 % (adjusted OR 0.892, 95 %CI 0.806-0.987, P = 0.026), while an SMD below the median value (32.1 HU for males and 28.5 HU for females) was independently associated with worse outcomes in the multivariable analysis (adjusted OR 8.868, 95 % CI 2.146-36.650, P = 0.003). The SMD had a good predictive ability for clinical outcomes, AUC was 0.824 (95 % CI, 0.715-0.933) for males and 0.803 (95 % CI, 0.639-0.967) for females.

CONCLUSION

Low SMD was associated with poor outcomes in patients with severe and moderately severe AP and might be used as a novel marker to predict outcomes in patients suffering from severe and moderately severe AP.

Sarcopenia and Sarcopenic Obesity on Body Composition Analysis is a Significant Predictor of Mortality in Severe Acute Pancreatitis: A Longitudinal Observational Study

BACKGROUND

The prevalence and impact of sarcopenia and sarcopenic obesity noted on body composition analysis in severe acute pancreatitis (SAP) is unknown. This study investigates the prevalence of sarcopenia at different timepoints and its effect on post-pancreatitis complications and mortality.

METHODS

A prospective database of SAP admissions with organ failure at a single institution from 2015 to 2019 were analysed. Sarcopenia was determined by IMAGE J software on CT. Database was further queried for post-pancreatitis complications and mortality.

RESULTS

141 patients with a median age of 59 (range 18-88) and M:F ratio 1.52:1 of were analysed. Sarcopenia was present in 111/141 (79%) patients at admission, 78/79 (99%) at 3 months and 26/36 (72%) at 12 months. 67/111 patients with sarcopenia on admission had sarcopenic obesity. The mortality at 30 days, 3 months and 12 months was 16/141 (11%), 30/141 (21%) and 42/141 (30%) respectively. Mortality was significantly higher in sarcopenic patients at admission (35.14%) compared to the non-sarcopenic group (10%), P = 0.008). Mortality in the sarcopenic obesity group was significantly higher (45%) compared to the sarcopenic non-obese group (20%), P = 0.009) at admission. Multivariate logistic regression identified sarcopenic obesity (OR: 2.880), age (OR: 1.048) and number of organ failures (OR: 3.225) as significant predictors of mortality.

CONCLUSIONS

Sarcopenia and Sarcopenic obesity are highly prevalent in SAP patients on admission and during follow up. Furthermore, sarcopenic obesity was shown to be a significant predictor of mortality at admission, suggesting that body composition analysis could be a potential predictive marker of mortality in SAP patients.

Role of Machine Learning-Based CT Body Composition in Risk Prediction and Prognostication: Current State and Future Directions

CT body composition analysis has been shown to play an important role in predicting health and has the potential to improve patient outcomes if implemented clinically. Recent advances in artificial intelligence and machine learning have led to high speed and accuracy for extracting body composition metrics from CT scans. These may inform preoperative interventions and guide treatment planning. This review aims to discuss the clinical applications of CT body composition in clinical practice, as it moves towards widespread clinical implementation.

Clinical characteristics and risk factors of organ failure and death in necrotizing pancreatitis

BACKGROUND

Organ failure (OF) and death are considered the most significant adverse outcomes in necrotizing pancreatitis (NP). However, there are few NP-related studies describing the clinical traits of OF and aggravated outcomes.

PURPOSE

An improved insight into the details of OF and death will be helpful to the management of NP. Thus, in our research, we addressed the risk factors of OF and death in NP patients.

METHODS

We performed a study of 432 NP patients from May 2017 to December 2021. All patients with NP were followed up for 36 months. The primary end-points were risk factors of OF and death in NP patients. The risk factors were evaluated by logistic regression analysis.

RESULTS

NP patients with OF or death patients were generally older, had a higher APACHE II score, longer hospital stay, longer ICU stay, as well as a higher incidence of severe acute pancreatitis (SAP), shock and pancreatic necrosis. Independent risk factors related to OF included BMI, APACHE II score and SAP (P < 0.05). Age, shock and APACHE II score (P < 0.05) were the most significant factors correlated with the risk of death in NP patients. Notably, increased mortality was linked to the number of failed organs.

CONCLUSIONS

NP is a potentially fatal disease with a long hospital or ICU stay. Our study indicated that the incidence of OF and death in NP patients was 69.9% and 10.2%, respectively. BMI, SAP, APACHE II score, age and shock are potential risk factors of OF and death in NP patients. Clinicians should focus on these factors for early diagnosis and appropriate therapy.

Association Between the Growth Hormone/Insulin-Like Growth Factor-1 Axis and Muscle Density in Children and Adolescents of Short Stature

OBJECTIVE

To evaluate the association between the growth hormone (GH)/insulin-like growth factor-1 (IGF-1) axis and muscle density in children and adolescents of short stature.

METHODS

Participants were children and adolescents of short stature hospitalized in the Affiliated Hospital of Jining Medical University between January 2020 and June 2021. All participants had CT scan images available. We performed an analysis of the images to calculate the muscle density or skeletal muscle attenuation (SMA), skeletal muscle index (SMI), and fat mass index (FMI). Bioelectrical impedance analysis (BIA) was used to ensure that chest CT is a credible way of evaluating body composition.

RESULTS

A total of 297 subjects were included with the mean age of 10.00 ± 3.42 years, mean height standard deviation score (SDS) of -2.51 ± 0.53, and mean IGF-1 SDS of -0.60 ± 1.07. The areas of muscle and fat tissues at the fourth thoracic vertebra level in the CT images showed strong correlation with the total weights of the participants (R²  = 0.884 and 0.897, respectively). The peak of GH was negatively associated with FMI (r = - 0.323, P <.01) and IGF-1 SDS was positively associated with SMI (r = 0.303, P <.01). Both the peak GH and IGF-1 SDS were positively associated with SMA (r = 0.244, P <.01 and r = 0.165, P <.05, respectively). Multiple stepwise linear regression analysis demonstrated that the GH peak was the predictor of FMI (β = - 0.210, P < .01), the IGF-1 SDS was the predictor of SMI (β = 0.224, P < .01), and both the peak GH and IGF-1 SDS were predictors of SMA (β = 0.180, P < .01 and β = 0.222, P < .01).

CONCLUSIONS

A chest CT scan is a credible method of evaluating body composition in children and adolescents of short stature. In these patients, peak GH and IGF-1 SDS are independent predictors of muscle density and the GF/IGF-1 axis may regulate body composition through complex mechanisms.

Impacts of body composition parameters and liver cirrhosis on the severity of alcoholic acute pancreatitis

AIM

Liver cirrhosis and features of muscle or adipose tissues may affect the severity of acute pancreatitis (AP). We aimed to evaluate the impact of body composition parameters and liver cirrhosis on the severity of AP in patients with alcohol-induced AP (AAP).

METHODS

Patients with presumed AAP who underwent CT within one week after admission were retrospectively enrolled. L3 sectional areas of abdominal fat and muscle, and mean muscle attenuations (MMAs) were quantified. The presence of liver cirrhosis was determined using clinical and CT findings. Factors potentially associated with moderately severe or severe AP were included in the multivariable logistic regression analysis.

RESULTS

A total of 242 patients (47.0 ± 12.6 years, 215 males) with presumed AAP were included. The mild and moderately severe/severe (MSS) groups included 137 (56.6%) and 105 patients (43.4%), respectively. Patients in the MSS group had higher rates of liver cirrhosis, organ failure, and local complications. Among body composition parameters, mean MMA (33.4 vs 36.8 HU, P<0.0001) and abdominal muscle mass (126.5 vs 135.1 cm2, P = 0.029) were significantly lower in the MSS group. The presence of liver cirrhosis (OR, 4.192; 95% CI, 1.620-10.848) was found to be a significant risk factor for moderately severe or severe AP by multivariable analysis.

CONCLUSION

The results of this study suggest that liver cirrhosis has a significant impact on the severity of AAP. Of the body composition parameters examined, MMA and abdominal muscle mass showed potential as promising predictors.