Spontaneous spondylodiscitis and endocarditis: interdisciplinary experience from a tertiary institutional case series and proposal of a treatment algorithm.
Lennart ViezensMarc DreimannAndré StrahlAnnika HeuerLeon-Gordian KoepkeBenjamin BayChristoph WaldeyerMartin StangenbergPublished in: Neurosurgical review (2021)
Previously, the simultaneous presence of endocarditis (IE) has been reported in 3-30% of spondylodiscitis cases. The specific implications on therapy and outcome of a simultaneous presence of both diseases are not yet fully evaluated. Therefore, the aim of this study was to investigate the influence of a simultaneously present endocarditis on the course of therapy and outcome of spondylodiscitis. A prospective database analysis of 328 patients diagnosed with spontaneous spondylodiscitis (S) using statistical analysis with propensity score matching was conducted. Thirty-six patients (11.0%) were diagnosed with concurrent endocarditis (SIE) by means of transoesophageal echocardiography. In our cohort, the average age was 65.82 ± 4.12 years and 64.9% of patients were male. The incidence of prior cardiac or renal disease was significantly higher in the SIE group (coronary heart disease SIE n = 13/36 vs. S n = 57/292, p < 0.05 and chronic heart failure n = 11/36 vs. S n = 41/292, p < 0.05, chronic renal failure SIE n = 14/36 vs. S n = 55/292, p < 0.05). Complex interdisciplinary coordination and diagnostics lead to a significant delay in surgical intervention (S = 4.5 ± 4.5 days vs. SIE = 8.9 ± 9.5 days, p < 0.05). Mortality did not show statistically significant differences: S (13.4%) and SIE (19.1%). Time to diagnosis and treatment is a key to efficient treatment and patient safety. In order to counteract delayed therapy, we developed a novel therapy algorithm based on the analysis of treatment processes of the SIE group. We propose a clear therapy pathway to avoid frequently observed pitfalls and delays in diagnosis to improve patient care and outcome.
Keyphrases
- patient safety
- ejection fraction
- end stage renal disease
- newly diagnosed
- machine learning
- randomized controlled trial
- chronic kidney disease
- prognostic factors
- pulmonary hypertension
- deep learning
- computed tomography
- risk factors
- cardiovascular disease
- squamous cell carcinoma
- cardiovascular events
- radiation therapy
- combination therapy
- quality improvement
- atrial fibrillation
- neural network
- adverse drug
- patient reported
- electronic health record
- left atrial appendage