Use of a predictive equation for diagnosis of acute gangrenous cholecystitis

Abstract Background Standardized uptake value (SUV) normalized by lean body mass ([LBM] SUL) is recommended as metric by PERCIST 1.0. The James predictive equation (PE) is a frequently used formula for LBM estimation, but may cause substantial error for an individual. The purpose of this study was to introduce a novel and reliable method for estimating LBM by limited-coverage (LC) CT images from PET/CT examinations and test its validity, then to analyse whether SUV normalised by LC-based LBM could change the PERCIST 1.0 response classifications, based on LBM estimated by the James PE. Methods First, 199 patients who received whole-body PET/CT examinations were retrospectively retrieved. A patient-specific LBM equation was developed based on the relationship between LC fat volumes (FVLC) and whole-body fat mass (FMWB). This equation was cross-validated with an independent sample of 97 patients who also received whole-body PET/CT examinations. Its results were compared with the measurement of LBM from whole-body CT (reference standard) and the results of the James PE. Then, 241 patients with solid tumours who underwent PET/CT examinations before and after treatment were retrospectively retrieved. The treatment responses were evaluated according to the PE-based and LC-based PERCIST 1.0. Concordance between them was assessed using Cohen’s κ coefficient and Wilcoxon’s signed-ranks test. The impact of differing LBM algorithms on PERCIST 1.0 classification was evaluated. Results The FVLC were significantly correlated with the FMWB (r=0.977). Furthermore, the results of LBM measurement evaluated with LC images were much closer to the reference standard than those obtained by the James PE. The PE-based and LC-based PERCIST 1.0 classifications were discordant in 27 patients (11.2%; κ = 0.823, P=0.837). These discordant patients’ percentage changes of peak SUL (SULpeak) were all in the interval above or below 10% from the threshold (±30%), accounting for 43.5% (27/62) of total patients in this region. The degree of variability is related to changes in LBM before and after treatment. Conclusions LBM algorithm-dependent variability in PERCIST 1.0 classification is a notable issue. SUV normalised by LC-based LBM could change PERCIST 1.0 response classifications based on LBM estimated by the James PE, especially for patients with a percentage variation of SULpeak close to the threshold.

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Prediction of optimal continuous positive airway pressure in Thai patients with obstructive sleep apnea

Scientific Reports ◽

10.1038/s41598-021-93554-5 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Narongkorn Saiphoklang ◽

Kanyada Leelasittikul ◽

Apiwat Pugongchai

Keyword(s):

Obstructive Sleep Apnea ◽

Sleep Apnea ◽

Continuous Positive Airway Pressure ◽

Airway Pressure ◽

Positive Airway Pressure ◽

Linear Regression Analysis ◽

Prediction Equation ◽

Apnea Hypopnea Index ◽

Predictive Equation ◽

Obstructive Sleep

AbstractContinuous positive airway pressure (CPAP) is simple and effective treatment for obstructive sleep apnea (OSA) patients. However, the CPAP prediction equation in each country is different. This study aimed to predict CPAP in Thai patients with OSA. A retrospective study was conducted in Thai patients, who OSA was confirmed by polysomnography and CPAP titration from January 2015 to December 2018. Demographics, body mass index (BMI), neck circumference (NC), Epworth sleepiness scale, apnea–hypopnea index (AHI), respiratory disturbance index (RDI), mean and lowest pulse oxygen saturation (SpO2), and optimal pressure were recorded. A total of 180 subjects were included: 72.8% men, age 48.7 ± 12.7 years, BMI 31.0 ± 6.3 kg/m2, NC 40.7 ± 4.1 cm, AHI 42.5 ± 33.0 per hour, RDI 47.1 ± 32.8 per hour, and lowest SpO2 77.1 ± 11.0%. Multiple linear regression analysis identified NC, BMI, RDI, and lowest SpO2. A final CPAP predictive equation was: optimal CPAP (cmH2O) = 4.614 + (0.173 × NC) + (0.067 × BMI) + (0.030 × RDI) − (0.076 × lowest SpO2). This model accounted for 50.0% of the variance in the optimal pressure (R2 = 0.50). In conclusion, a CPAP prediction equation can be used to explain a moderate proportion of the titrated CPAP in Thai patients with OSA. However, the CPAP predictive equation in each country may be different due to differences of ethnicity and physiology.Trial registration: TCTR20200108003.

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Hepatobiliary and Pancreatic: Plate-like atelectasis mimics pneumoperitoneum in patient with acute gangrenous cholecystitis

Journal of Gastroenterology and Hepatology ◽

10.1111/jgh.13274 ◽

2016 ◽

Vol 31 (5) ◽

pp. 911-911

Author(s):

N Lakananurak

Keyword(s):

Gangrenous Cholecystitis

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Statistical Simulation of Boxing Day Tsunami of The Indian Ocean and a Predictive Equation for Beach Run up Heights Based on Work-Energy Theorem

Marine Geodesy ◽

10.1080/01490410600939215 ◽

2006 ◽

Vol 29 (3) ◽

pp. 223-231 ◽

Cited By ~ 2

Author(s):

G. Muraleedharan ◽

Mourani Sinha ◽

A. D. Rao ◽

T. S. Murty

Keyword(s):

Indian Ocean ◽

Statistical Simulation ◽

Predictive Equation ◽

The Indian Ocean ◽

Run Up

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Prediction of Patients with Acute Cholecystitis Requiring Emergent Cholecystectomy: A Simple Score

Gastroenterology Research and Practice ◽

10.1155/2010/901739 ◽

2010 ◽

Vol 2010 ◽

pp. 1-5 ◽

Cited By ~ 33

Author(s):

Wael N. Yacoub ◽

Mikael Petrosyan ◽

Indu Sehgal ◽

Yanling Ma ◽

Parakrama Chandrasoma ◽

...

Keyword(s):

Heart Rate ◽

Logistic Regression ◽

Acute Cholecystitis ◽

High Probability ◽

Acute Inflammation ◽

Gallbladder Wall ◽

Cutoff Score ◽

Gangrenous Cholecystitis ◽

Pathological Review ◽

Low Probability

The objective was to develop a score, to stratify patients with acute cholecystitis into high, intermediate, or low probability of gangrenous cholecystitis. The probability of gangrenous cholecystitis (score) was derived from a logistic regression of a clinical and pathological review of 245 patients undergoing urgent cholecystectomy. Sixty-eight patients had gangrenous inflammation, 132 acute, and 45 no inflammation. The score comprised of: age > 45 years (1 point), heart rate > 90 beats/min (1 point), male (2 points), Leucocytosis > 13,000/mm3(1.5 points), and ultrasound gallbladder wall thickness>4.5 mm (1 point). The prevalence of gangrenous cholecystitis was 13% in the low-probability (0–2 points), 33% in the intermediate-probability (2–4.5 points), and 87% in the high probability category (>4.5 points). A cutoff score of 2 identified 31 (69%) patients with no acute inflammation (PPV 90%). This scoring system can prioritize patients for emergent cholecystectomy based on their expected pathology.

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