Predictive value of diaphragmatic thickness fraction and integrated pulmonary index on extubation outcome in patients with severe acute pancreatitis

Abstract

Objective

This study was performed to explore the predictive value of the diaphragmatic thickness fraction (DTF) combined with the integrated pulmonary index (IPI) for the extubation outcome in patients with severe acute pancreatitis (SAP).

Methods

This prospective study involved 93 patients diagnosed with SAP and treated with mechanical ventilation in our hospital from October 2020 to September 2023. The patients were divided into a successful extubation group (61 patients) and an extubation failure group (32 patients) based on the extubation outcomes. The predictive value of the DTF, IPI, and their combination for extubation failure was analyzed.

Results

The DTF and IPI were independent risk factors for extubation failure in patients with SAP undergoing mechanical ventilation. In addition, the combination of the DTF and IPI showed predictive value for extubation failure in these patients.

Conclusion

The DTF and IPI hold predictive value for extubation failure in patients with SAP undergoing mechanical ventilation, and their combined use may improve the predictive efficiency.

Keywords

Severe acute pancreatitis diaphragmatic thickness fraction integrated pulmonary index extubation outcome predictive value mechanical ventilation

Introduction

Severe acute pancreatitis (SAP) is a grave condition typically characterized by inflammation and damage to the pancreatic tissue.¹ Clinically, it manifests as severe abdominal pain, nausea, vomiting, fever, and abdominal distension, potentially leading to severe complications such as pancreatic necrosis, infection, bleeding, and multiple organ dysfunction syndrome.² Mechanical ventilation is a crucial symptomatic treatment measure for patients with SAP and is capable of effectively improving respiratory function. However, patients with SAP are prone to developing complications such as abdominal compartment syndrome or intra-abdominal hypertension, which may lead to reduced lung compliance and increased circulatory resistance, consequently prolonging the duration of mechanical ventilation.³ Prolonged use of ventilators can lead to complications such as ventilator-associated pneumonia and diaphragmatic dysfunction, adversely affecting patients’ pulmonary prognosis.⁴ Therefore, identifying efficient and accurate indicators to predict extubation outcomes is of significant clinical importance for increasing the success rate of extubation.

Methods used to determine the timing of extubation in the clinical setting include diaphragmatic ultrasound and the rapid shallow breathing index. The diaphragmatic thickness fraction (DTF) can be accurately assessed by bedside ultrasound to evaluate diaphragmatic function, and it has demonstrated good results in predicting extubation outcomes in mechanically ventilated patients.⁵ However, practical clinical experience indicates that factors affecting extubation are comprehensive and multifaceted, and the use of single indicators for extubation timing often results in insufficient efficacy.⁶

The integrated pulmonary index (IPI) was developed in 2017 by Israeli and American scholars based on fuzzy logic and mathematical models to predict extubation outcomes, and it has shown good application value in predicting extubation failure and managing postoperative anesthesia care.⁷ However, there is a paucity of research on the combined application of the DTF and IPI in predicting extubation outcomes. The present study was performed to analyze the predictive value of the DTF combined with the IPI on extubation outcomes in patients with SAP in terms of identifying early changes in patients’ conditions, intervening in a timely manner, and thereby improving extubation outcomes.

Patients and methods

Patients

This prospective study involved 93 patients who were diagnosed with SAP and underwent mechanical ventilation at Chongqing General Hospital from October 2020 to September 2023. The failed extubation group comprised 32 patients, and the successful extubation group comprised 61 patients.

Inclusion criteria

The inclusion criteria for the study were as follows.

Diagnosis of SAP according to the presence of at least two of the following three criteria: (i) abdominal pain consistent with the disease, (ii) biochemical evidence of pancreatitis (serum amylase and/or lipase concentration greater than three times the upper limit of normal), and (iii) characteristic findings on abdominal imaging⁸

Age of >18 years

Undergoing mechanical ventilation for the first time with a continuous duration of >24 hours

Meeting the spontaneous breathing trial (SBT) criteria and entering the first extubation process

Availability of complete clinical data

Exclusion criteria

The exclusion criteria were as follows.

Previous diaphragmatic dysfunction or mechanical trauma

Severe intra-abdominal hypertension

Acute pulmonary embolism

Body mass index (BMI) of >40 kg/m²

Sepsis

Shock complicated with heart failure or pulmonary heart disease

Other diseases that may affect the nutritional status

Ethics statement

This study complied with the Declaration of Helsinki, and all patients provided written informed consent for participation in the research. The study was approved by the Medical Ethics Committee of Chongqing General Hospital (No. KY S2023-054-01). All patient details have been de-identified. The reporting of this study conforms to the STROBE guidelines.⁹

Research methods

Extubation methods and definition of extubation failure

After achieving control of the patients’ primary disease, the indications for extubation were assessed every 6 hours. The SBT was implemented using the pressure support ventilation mode, and the level of pressure support was gradually reduced. When the pressure had decreased to 5 cm H₂O, the positive end-expiratory pressure was 5 cm H₂O, and the fraction of inspired oxygen (FiO₂) was ≤0.40, the patient was subjected to an extubation trial. Patients who met any of the following criteria were considered to have extubation failure¹⁰: failure to pass the SBT; inability to maintain spontaneous breathing within 48 hours of extubation, necessitating reintubation or tracheotomy; the need for noninvasive ventilation or high-flow nasal cannula oxygen therapy after extubation; or death within 48 hours after extubation.

Data collection

The following clinical data were collected from all patients before the SBT: age, sex, BMI, oxygenation index (PaO₂/FiO₂), Sequential Organ Failure Assessment (SOFA) score, Acute Physiology and Chronic Health Evaluation II (APACHE II) score, serum albumin concentration, heart rate, mean arterial pressure, and tidal volume.

DTF monitoring

Two professionally trained physicians performed a right diaphragmatic ultrasound assessment using an ultrasound machine. The measurement technique was performed as previously described.¹¹ The patient was placed in the 30° lateral decubitus position, and a 3.5-MHz ultrasound probe was placed between the midaxillary line and the posterior axillary line at the patient’s right costal margin, with the liver as the detection window. This position was considered optimal for monitoring diaphragm activity. Changes in diaphragm thickness at the end of inhalation (DTei) and at the end of exhalation (DTee) were measured by M-mode ultrasound, and the DTF was calculated as (DTei − DTee)/DTee × 100%. These indicators were measured three times consecutively, and the average value was used for further analysis.

IPI monitoring

The IPI was calculated for all patients within 1 hour after extubation. First, the end-tidal carbon dioxide pressure (PetCO₂), respiratory rate (RR), oxygen saturation (SpO₂), and pulse rate (PR) were recorded. Based on the fuzzy logic algorithm, PetCO₂ and RR were categorized into five levels: very high, high, normal, low, and very low. SpO₂ and PR were categorized into three levels: high, normal, and low. The patients’ results from these four indicators were used for matrix conversion. The IPI was calculated according to the method described in a previous report,¹² and all assessors underwent training before evaluation. The final converted IPI score ranged from 1 to 10, with a lower score indicating a greater need for additional intervention.

Statistical methods

Data analysis was performed using SPSS 23.0 statistical software (IBM Corp., Armonk, NY, USA). Quantitative data conforming to a normal distribution are presented as mean ± standard deviation, and comparisons between groups were performed using the independent-samples t-test. Categorical data are expressed as n (%), and comparisons between groups were conducted using the chi-square test. Multivariate logistic regression analysis was used to explore the factors influencing weaning failure in patients with SAP undergoing mechanical ventilation. A receiver operating characteristic (ROC) curve was drawn using GraphPad 8.0 software (GraphPad Software, La Jolla, CA, USA) to evaluate the predictive value of the DTF, IPI, and their combination for weaning failure in patients with SAP undergoing mechanical ventilation. A P-value of <0.05 was considered statistically significant.

Results

Comparison of clinical data between successful and failed extubation groups

In total, 93 patients with SAP were included in this study (61 in the successful extubation group and 32 in the failed extubation group). There were no statistically significant differences in age, sex, oxygenation index, SOFA score, APACHE II score, heart rate, or mean arterial pressure between the successful and failed extubation groups. However, the tidal volume, DTF, IPI, and albumin concentration were significantly lower and the BMI was significantly higher in the failed extubation group than in the successful extubation group (P < 0.05). Further details are shown in Table 1.

Table 1.

Comparison of clinical data between successful and failed extubation groups.

Item	Failed extubation group (n = 32)	Successful extubation group (n = 61)	χ²/t	P
Age, years	60.53 ± 2.66	61.30 ± 3.68	1.048	0.298
Sex
Male	18 (56.25)	34 (55.74)	0.002	0.962
Female	14 (43.75)	27 (44.26)
BMI, kg/m²	23.72 ± 1.77	21.92 ± 1.80	4.607	<0.001
PaO₂/FiO₂, mmHg	238.81 ± 17.65	234.77 ± 18.05	1.033	0.304
SOFA score	10.19 ± 1.45	9.95 ± 1.06	0.911	0.365
APACHE II score	21.63 ± 2.57	24.02 ± 3.16	2.265	0.064
Albumin, g/L	32.52 ± 4.33	34.41 ± 3.84	2.157	0.034
Heart rate, beats/min	80.19 ± 4.42	79.64 ± 3.10	0.693	0.490
MAP, mmHg	75.57 ± 2.47	74.95 ± 1.92	1.338	0.184
Tidal volume, mL	391.98 ± 64.43	403.88 ± 38.89	3.384	0.011
DTF, %	29.20 ± 1.46	31.70 ± 0.77	10.837	<0.001
IPI score	3.28 ± 1.37	4.80 ± 0.95	6.268	<0.001

Data are presented as mean ± standard deviation or n (%).

BMI: body mass index; PaO₂/FiO₂: oxygenation index; SOFA: Sequential Organ Failure Assessment; APACHE II: Acute Physiology and Chronic Health Evaluation II; MAP: mean arterial pressure; DTF: diaphragmatic thickness fraction; IPI: integrated pulmonary index.

Multivariate logistic regression analysis to identify factors influencing extubation failure in patients with SAP undergoing mechanical ventilation

Indicators with statistically significant differences in the univariate analysis were used as independent variables, and weaning failure of patients with SAP undergoing mechanical ventilation was used as the dependent variable. Multivariate logistic regression analysis was then performed. The results showed that the DTF and IPI were independent risk factors for weaning failure in patients with SAP undergoing mechanical ventilation (P < 0.001), as shown in Table 2.

Table 2.

Multivariate logistic regression analysis of factors influencing extubation failure in patients with severe acute pancreatitis undergoing mechanical ventilation.

Factor	β	SE	Ward χ²	P	OR	95% CI
BMI	0.279	0.168	2.761	0.061	1.322	0.951–1.838
Albumin	−0.015	0.289	0.003	0.784	0.985	0.559–1.736
Tidal volume	−0.068	0.108	0.400	0.122	0.934	0.756–1.154
DTF	−0.270	0.149	3.296	<0.001	0.763	0.570–1.022
IPI	−0.126	0.034	13.639	<0.001	0.882	0.825–0.943

SE: standard error; OR: odds ratio; CI: confidence interval; BMI: body mass index; DTF: diaphragmatic thickness fraction; IPI: integrated pulmonary index.

ROC curve analysis of DTF, IPI, and their combined prediction of extubation failure in patients with SAP undergoing mechanical ventilation

The results of the ROC curve analysis showed that the area under the curve (AUC) for predicting extubation failure in patients with SAP undergoing mechanical ventilation was 0.778 (95% confidence interval (CI): 0.686–0.869) for the DTF and 0.844 (95% CI: 0.771–0.917) for the IPI. The optimal cutoff values were 30 and 4, respectively, with sensitivities of 72.34% and 57.45% and specificities of 84.31% and 60.78%, respectively. The AUC for prediction using the combination of the DTF and IPI was 0.931 (95% CI: 0.866–0.996), as shown in Table 3 and Figure 1.

Table 3.

Receiver operating characteristic curve analysis of DTF, IPI, and their combined prediction of extubation failure in patients with severe acute pancreatitis undergoing mechanical ventilation.

Index	AUC	Optimal cutoff value	Sensitivity	Specificity	95% CI	P
DTF	0.778	30 points	72.34	57.45	0.686–0.869	<0.001
IPI	0.844	4 points	84.31	60.78	0.771–0.917	<0.001
Combined	0.931		93.62	65.96	0.866–0.996	<0.001

AUC: area under the curve; CI: confidence interval; DTF: diaphragmatic thickness fraction; IPI: integrated pulmonary index.

Figure 1.

Receiver operating characteristic curve for prediction of extubation failure in patients with SAP undergoing mechanical ventilation by DTF, IPI, and their combination. SAP, severe acute pancreatitis; DTF, diaphragmatic thickness fraction; IPI, integrated pulmonary index.

Discussion

SAP poses a significant threat to patients’ health, often leading to systemic inflammatory response syndrome and multiple organ dysfunction syndrome. Among its complications, acute lung injury is of particular concern. However, the precise pathogenesis of SAP-associated acute lung injury remains elusive. It is thought to involve an intricate interplay of factors such as pancreatic necrosis, bacteremia, intestinal barrier dysfunction, inflammatory cascades, and diffuse alveolar damage.¹³ As the condition progresses, patients become prone to developing acute respiratory distress syndrome, often accompanied by persistent hypoxemia. For various reasons, patients with SAP may develop pancreatic duct obstruction, acidification, and the release of bile acids through the ducts, directly leading to an “inflammatory storm.”¹⁴ This results in an increase in pancreatic duct pressure, necrosis of the pancreatic parenchyma and peripancreatic tissues, and a resultant increase in intra-abdominal pressure.³ If abdominal compartment syndrome occurs concurrently and the diaphragm is displaced upward, diaphragmatic dysfunction is highly likely to occur, potentially increasing the mortality rate to 49%.¹⁴ This substantially increases the difficulty of weaning from mechanical ventilation.

Although invasive mechanical ventilation is used worldwide for respiratory support in critically ill patients, it cannot improve or cure the cause of respiratory failure. Instead, it provides critical time to treat the primary disease. The goal is not only to improve the primary disease but also to permanently wean the patient off the ventilator. Therefore, determining the optimal timing for ventilator discontinuation has always been a major challenge for clinicians.¹⁵ Premature discontinuation of ventilation can place the respiratory and cardiovascular systems under severe stress, hindering the patient’s recovery. However, prolonged use of ventilation can lead to a series of complications such as disuse atrophy of the diaphragm and ventilator-associated pneumonia,^16,17 while also prolonging the patient’s hospital stay and increasing the economic burden on the family. Therefore, identifying indicators that can efficiently and accurately predict the outcome of weaning is of great clinical significance to improving the success rate of weaning.

This study ultimately included 93 patients with SAP who required mechanical ventilation, with 61 patients successfully weaned and 32 patients failing to be weaned; thus, the weaning failure rate was 34.41%. This rate is higher than the 3% to 30% failure rates reported in the literature.¹⁸ One possible explanation for this discrepancy is that the patients selected for this study had SAP, and such patients are likely to develop conditions such as diaphragmatic dysfunction. This can lead to local changes in the thoracic wall pressure, decreasing the chest–abdominal pressure gradient to some extent and causing excessive loss of the lung ventilation area, which can lead to weaning failure. To further clarify the factors affecting weaning failure in patients with SAP, we performed a univariate analysis and multivariate logistic regression analysis. The results indicated that the DTF is an independent risk factor for weaning failure in patients with SAP undergoing mechanical ventilation (P < 0.001). The DTF is calculated based on the changes in diaphragmatic thickness at the end of expiration and inspiration and is considered a good indicator of diaphragmatic inspiratory effort. A decrease in its value is associated with a longer stay in the intensive care unit and a higher mortality rate.¹⁹ One meta-analysis revealed that the DTF had the highest predictive ability for weaning failure, with a pooled sensitivity of 0.76 (95% CI: 0.67–0.83) and specificity of 0.86.¹⁹ A possible reason for its impact on weaning failure may be that DTF is closely related to lung capacity. In patients with SAP, diaphragmatic weakness secondary to atelectasis can lead to increased pulmonary resistance and a decrease in diaphragmatic strength, resulting in an imbalance between respiratory capacity and load. Respiratory muscle weakness is also considered an important factor affecting ventilatory loss during the SBT. Thus, the DTF can play an effective role in predicting the outcome of weaning.

The IPI is a heuristic algorithm that integrates four respiratory function monitoring indicators: the SpO₂, PetCO₂, RR, and PR. This algorithm simplifies the IPI by assigning values from 1 to 10 that represent different respiratory states of patients, with 1 indicating severe respiratory insufficiency and 10 indicating the optimal respiratory state. The algorithm is based on a fuzzy logic reasoning model that compares expert interpretations of actual clinical situations with IPI monitoring values and adjusts the algorithm accordingly.²⁰ In a prospective observational trial of 62 patients who underwent tracheal intubation and mechanical ventilation, 48 patients were successfully extubated and 14 patients failed to be extubated.²¹ There was no significant difference in the IPI between the two groups of patients either before extubation or 5 minutes after extubation. However, at 1 hour after extubation, the IPI was lower in the extubation failure than success group.²¹ A downward trend of the IPI after extubation indicates that patients may have respiratory insufficiency. Therefore, a decrease of the IPI in patients with tracheal intubation and mechanical ventilation over time is helpful for early identification of patients with extubation failure. In the present study, the IPI was also an independent risk factor for failure of weaning from mechanical ventilation in patients with SAP. This may have occurred because as the patient transitions to spontaneous breathing during weaning, the respiratory load increases significantly, and the intrathoracic pressure becomes negative. If the diaphragm is decompensated, contractility can readily decrease, leading to alveolar collapse and resulting in an imbalance between respiratory load and respiratory muscle work ability. Decreased alveolar ventilation function and lung compliance are important causes of weaning failure. The PetCO₂, RR, SpO₂, and PR, as components of the IPI, can comprehensively reflect the patient’s pulmonary ventilation function and pulmonary blood flow. Therefore, the IPI can be used to predict the success of weaning.

Sole application of multivariate logistic regression analysis fails to quantify the risk of weaning failure in mechanically ventilated patients, and it cannot determine the optimal threshold for the IPI in predicting weaning failure. The results of the ROC curve analysis showed that the AUC for predicting extubation failure in patients with SAP undergoing mechanical ventilation was 0.778 (95% CI: 0.686–0.869) for the DTF and 0.844 (95% CI: 0.771–0.917) for the IPI, suggesting that both the DTF and IPI have potential in predicting the weaning outcomes in patients with SAP. Additionally, the combined use of the DTF and IPI in this study yielded an AUC of 0.931 (95% CI: 0.866–0.996) for predicting weaning failure, indicating that the combined application of the DTF and IPI can further enhance the predictive power for weaning outcomes in patients with SAP.

In summary, the DTF and IPI have certain predictive value for failure of weaning in patients with SAP undergoing mechanical ventilation, and their combined use may improve the predictive efficiency. Notably, this study was limited in that the dynamic changes in the DTF and IPI were not evaluated longitudinally. Another limitation is the single-center prospective design with inclusion of few observation indicators. Multicenter studies are needed to further verify the conclusions of this study.

Conclusion

The DTF and IPI significantly decreased in patients with extubation failure, showing the predictive value for the failure of weaning in patients with SAP undergoing mechanical ventilation. The combination of the DTF and IPI may improve the predictive efficiency and facilitate determination of the severity of SAP in the early stage of weaning. This will provide a standardized basis to further guide the practice of SAP weaning.

Footnotes

Authors’ contributions

Donglin Fu, Huan Luo, Qiuhong Zhang, Liang Chen, and Honghao Guo collected, analyzed, and interpreted the patient data. Donglin Fu was a major contributor to the writing of the manuscript. Meng Zhang was responsible for the design, supervision, and manuscript revision. All authors read and approved the final manuscript.

Availability of data and materials

The datasets used and analyzed during the current study are available from the corresponding author on reasonable request.

Consent for publication

Written informed consent for publication was obtained from all participants.

Declaration of competing interests

The authors declare that there are no conflict of interests.

Ethics approval and consent to participate

The present study was approved by the Medical Ethics Committee of Chongqing General Hospital (No. KY S2023-054-01). All patients provided written informed consent for participation in the research.

Funding

The present study was supported by the Chongqing Science and Health Joint Medical Scientific Research Surface Project (No. 2024MSXM091) to Meng Zhang.

ORCID iD

Meng Zhang

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