A Novel Method to Predict Mortality and Length of Stay after Transfemoral Transcatheter Aortic Valve Implantation

Zisiopoulou, Maria; Berkowitsch, Alexander; Seppelt, Philipp; Zeiher, Andreas M.; Vasa‐Nicotera, Mariuca

doi:10.3390/medicina57121332

Cited by 6 publications

(5 citation statements)

References 33 publications

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“…The most common reason is a change in the concentration of the agent causing the problem or a change in the way the host and parasite interact. [32][33][34][35][36][37][38][39][40][41] Regarding EFT, it can indicate the initiation or occurrence of a particular immune response to the pathogens responsible for the condition. Three patients experienced complete resolution of EFT following a double-blind trial of oral flucloxacillin.…”

Section: Discussionmentioning

confidence: 99%

Serial neutrophils count as a stratifying tool for early follicular tonsilitis remission

Hayfa Suleiman Mefleh Obeidat,

Wajdi Nidal Jeries Smirat,

Mousa Mohammad Ali Almashagbah

et al. 2024

World J. Bio. Pharm. Health Sci.

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Background/Aim: This study examines the correlation between sequential serum neutrophil levels and the overall improvement status or reduction rate of intravenous antibiotic administration. This study seeks to identify a cost-effective and easily accessible biomarker that can accurately predict the need for hospitalisation in patients with acute tonsillitis who are receiving intravenous broad-spectrum antibiotics. The goal is to determine the patients' suitability for early discontinuation of intravenous antibiotics and discharge. Methods: This study was conducted at the King Hussein Medical Centre in Jordan, focusing on patients with severe acute tonsillitis who did not respond to oral antibiotics. Data was collected from the electronic medical record system (Hakeem) from January 2018 to May 2021. The study classified serial serum neutrophil measurements during the first week of hospital admission into four categories. The levels were compared between the non-penicillin Cohort (Group I) and penicillin Cohort (Group II) using an Independent-T Test. The outcomes of interest included a drop in neutrophil counts exceeding 50%, a decrease in the use of intravenous antibiotics in favor of oral antibiotics, and early eligibility for discharge. The study also examined serial neutrophil counts over the tested days and compared to the outcomes of positive and negative states using receiver operating curve analyses. The optimal cutoff operating point for each ROC curve was determined by selecting the highest Youden's index of each prognosticator day level. The analysis of all results was conducted using SPSS version 20 with a significance level set at p-value <0.05. Results: This study analyzed 1638 adult and elderly patients admitted to KHMC, RMS, Amman, Jordan between January 2018 and May 2021. The average age was 51.88±16.22 years, with patients dependent on intravenous penicillin being slightly older. The distribution of males and females was significant, with males making up 2.55 times the number of females. The odds ratio for positive outcomes was 4.12, with a high rate of poor outcomes in 1318 out of all eligible patients. A total of 994 (60.7%) medical patients were treated with intravenous administration, while 644 (39.3%) surgical patients were scheduled for a tonsillectomy procedure. The risk estimate for patients admitted from medical wards compared to surgical wards was an odds ratio of 0.562. The study also provided sensitivity analysis for the four tested serial neutrophil prognosticators at different day levels. Conclusion: The study supports the use of Somatic Nucleated Cell (SNC) as a reliable measure for evaluating EFR in cases of catarrhal acute tonsillitis. The maximum SNC count in Group one was 11,269 cells per cubic millimeter. Acute streptococcal infection often exhibits an ESR higher than 40, but this may be concealed by other complications. The SNC test has advantages like simplicity, quickness, and cost-effectiveness, but lacks specificity. Monitoring SNC and EFR fluctuations can initiate treatment cessation, preventing relapse and severe complications during recovery.

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Section: Discussionmentioning

confidence: 99%

Serial neutrophils count as a stratifying tool for early follicular tonsilitis remission

Hayfa Suleiman Mefleh Obeidat,

Wajdi Nidal Jeries Smirat,

Mousa Mohammad Ali Almashagbah

et al. 2024

World J. Bio. Pharm. Health Sci.

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“…25 The combination of KCCQ and estimated glomerular filtration rate (eGFR) can better predict midterm mortality than ESII alone. 6 Additionally, the combination of eGFR, N-terminal pro brain natriuretic peptide (NTproBNP) and EQ5D5L can reliably predict LoS after TAVI.…”

Section: Discussionmentioning

confidence: 99%

“…There are few prospective studies using PROM data for the prediction of key clinical endpoints, such as mortality, length of stay (LoS) and hospitalisation costs. 6 Among PROMs, the Kansas City Cardiomyopathy Questionnaire (KCCQ), although originally developed to monitor heart failure outcomes, has been shown to provide valid information regarding TAVI outcomes. [6][7][8][9][10] Additionally, prospectively acquired data from TAVI patients using the patient-reported EuroQol-5 Dimension-5 Levels (EQ5D5L) questionnaire values have shown great potential to be a reliable predictor of TAVI outcomes.…”

Section: What This Study Addsmentioning

confidence: 99%

“…6 Among PROMs, the Kansas City Cardiomyopathy Questionnaire (KCCQ), although originally developed to monitor heart failure outcomes, has been shown to provide valid information regarding TAVI outcomes. [6][7][8][9][10] Additionally, prospectively acquired data from TAVI patients using the patient-reported EuroQol-5 Dimension-5 Levels (EQ5D5L) questionnaire values have shown great potential to be a reliable predictor of TAVI outcomes. 6 Also, the easy-to-use Clinical Frailty Scale (CFS) scores have been used in various acute conditions, 11 including TAVI procedures, 10 12 as strong predictors of patient outcomes.…”

Section: What This Study Addsmentioning

confidence: 99%

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Personalised preinterventional risk stratification of mortality, length of stay and hospitalisation costs in transcatheter aortic valve implantation using a machine learning algorithm: a pilot trial

Zisiopoulou,

Berkowitsch,

Redlich

et al. 2024

Open Heart

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IntroductionRisk stratification based on Euroscore II (ESII) is used in some centres to assist decisions to perform transcatheter aortic valve implant (TAVI) procedures. ESII is a generic, non-TAVI-specific metric, and its performance fades for mortality at follow-up longer than 30 days. We investigated if a TAVI-specific predictive model could achieve improved predictive preinterventional accuracy of 1-year mortality compared with ESII.Patients and methodsIn this prospective pilot study, 284 participants with severe symptomatic aortic valve stenosis who underwent TAVI were enrolled. Standard clinical metrics (American Society of Anesthesiology (ASA), New York Heart Association and ESII) and patient-reported outcome measures (EuroQol-5 Dimension-Visual Analogue Scale, Kansas City Cardiomyopathy Questionnaire and Clinical Frailty Scale (CFS)) were assessed 1 day before TAVI. Using these data, we tested predictive models (logistic regression and decision tree algorithm (DTA)) with 1-year mortality as the dependent variable.ResultsLogistic regression yielded the best prediction, with ASA and CFS as the strongest predictors of 1-year mortality. Our logistic regression model score showed significantly better prediction accuracy than ESII (area under the curve=0.659 vs 0.800; p=0.002). By translating our results to a DTA, cut-off score values regarding 1-year mortality risk emerged for low, intermediate and high risk. Treatment costs and length of stay (LoS) significantly increased in high-risk patients.Conclusions and significanceA novel TAVI-specific model predicts 1-year mortality, LoS and costs after TAVI using simple, established, transparent and inexpensive metrics before implantation. Based on this preliminary evidence, TAVI team members and patients can make informed decisions based on a few key metrics. Validation of this score in larger patient cohorts is needed.

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“…The same group of clinicians/interventional cardiologists, with prior extensive experience, performed all transfemoral TAVI interventions. In addition, this is one of the few studies [ 16 ] with a prospective design to specifically assess the usefulness of preoperative PROMs in the calculation of LoS after TAVI.…”

Section: Discussionmentioning

confidence: 99%

Personalized Preoperative Prediction of the Length of Hospital Stay after TAVI Using a Dedicated Decision Tree Algorithm

Zisiopoulou

Berkowitsch

Neuber

et al. 2022

JPM

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Background: The aim of this study was to identify pre-operative parameters able to predict length of stay (LoS) based on clinical data and patient-reported outcome measures (PROMs) from a scorecard database in patients with significant aortic stenosis who underwent TAVI (transfemoral aortic valve implantation). Methods: 302 participants (51.7% males, age range 78.2–84.2 years.) were prospectively recruited. After computing the median LoS value (=6 days, range = 5–8 days), we implemented a decision tree algorithm by setting dichotomized values at median LoS as the dependent variable and assessed baseline clinical variables and PROMs (Clinical Frailty Scale (CFS), EuroQol-5 Dimension-5 Levels (EQ-5D) and Kansas City Cardiomyopathy Questionnaire (KCCQ)) as potential predictors. Results: Among clinical parameters, only peripheral arterial disease (p = 0.029, HR = 1.826) and glomerular filtration rate (GFR, cut-off < 33 mL/min/1.73 m2, p = 0.003, HR = 2.252) were predictive of LoS. Additionally, two PROMs (CFS; cut-off = 3, p < 0.001, HR = 1.324 and KCCQ; cut-off = 30, p = 0.003, HR = 2.274) were strong predictors. Further, a risk score for LoS (RS_LoS) was calculated based on these predictors. Patients with RS_LoS = 0 had a median LoS of 5 days; patients RS_LoS ≥ 3 had a median LoS of 8 days. Conclusions: based on the pre-operative values of the above four predictors, a personalized prediction of LoS after TAVI can be achieved.

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A Novel Method to Predict Mortality and Length of Stay after Transfemoral Transcatheter Aortic Valve Implantation

Cited by 6 publications

References 33 publications

Serial neutrophils count as a stratifying tool for early follicular tonsilitis remission

Serial neutrophils count as a stratifying tool for early follicular tonsilitis remission

Personalised preinterventional risk stratification of mortality, length of stay and hospitalisation costs in transcatheter aortic valve implantation using a machine learning algorithm: a pilot trial

Personalized Preoperative Prediction of the Length of Hospital Stay after TAVI Using a Dedicated Decision Tree Algorithm

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