Background Context
Long-term follow-up of patient-reported outcome measures (PROM) is essential in both modern spinal care and research. Lack of time and staff are commonly reported barriers to implementing long-term follow-up of PROM. Automated and digital follow-up systems for PROM collection are seeing widespread use, yet their validity and comparative effectiveness have never been evaluated.Purpose
The present study aimed to assess the validity of digital follow-up systems in comparison with the conventional paper-based follow-up (PB-FU).Study Design
This is a retrospective analysis of prospectively collected double follow-up data.Patient Sample
Patients who underwent lumbar spinal fusion for spondylolisthesis or degenerative disc disease between 2013 and 2016 were included in the study.Outcome Measures
The study determined the Oswestry Disability Index (ODI) and Numeric Rating Scale (NRS) for back and leg pain severity at baseline, 6 weeks, 12 months, and 24 months.Materials and Methods
After lumbar spinal fusion surgery, a double follow-up of PROM was carried out by conventional PB-FU during clinical visits, while simultaneously completing an automatically dispatched digital follow-up questionnaire. As the primary end point, we assessed the intraindividual discrepancy in PROM between PB-FU and automated digital follow-up (AD-FU).Results
Forty patients completed all parts of the dual follow-up trajectory and were analyzed. We detected no discrepancy in ODI or NRS for back and leg pain severity at any of the baseline, 6-week, 12-month, or 24 month follow-ups (all p>.05). This was confirmed in a sensitivity analysis.Conclusions
In an analysis of dual paper-based and digital follow-up after lumbar fusion surgery, patients report highly similar values using either method of follow-up. It appears that AD-FU without incentives produces lower response rates. To reassess the validity of these systems for data collection in spinal patient care, a prospective validation with higher statistical power is warranted. 相似文献Purpose
Injuries to the internal carotid artery (ICA) are potentially lethal complications in transsphenoidal surgery (TSS) for pituitary lesions. The intercarotid distance (ICD) is thus a major parameter, determining the width of the surgical corridor in TSS. The purpose of the study is to investigate changes in ICD at different levels of the ICA during and after TSS using high definition intraoperative MRI (3T-iMRI).Methods
Pre-, intra- and 3 months postoperative MRI images of 85 TSS patients were reviewed. ICD was measured at the horizontal (ICDC4h) and vertical (ICDC4v) intracavernous C4 segment as well as at the C6 segment (ICDC6). Association between ICD change at different levels and time points were compared and potential factors predicting ICD reduction were analyzed.Results
ICD decreased intraoperatively at all three segments of ICA by ?3% (median decreases: ICDC4h: ?0.5 mm, ICDC4v: ?0.7 mm ICDC6: ?0.4 mm). At 3 months postoperative MRI, ICD reduced by a further ?4%, ?2% and ?4% respectively (median decreases ICDC4h: ?0.7, ICDC4v: ?0.4 mm, ICDC6: ?0.5 mm). Postoperative narrowing in ICD occurred independent of further resection after 3T-iMRI. ICD change correlated between different levels of the ICA indicating a uniform shift perioperatively. Preoperative ICD was significantly associated with the intraoperative reduction in ICDC4v and ICDC6.Conclusions
We have demonstrated a uniform narrowing in ICD at different levels of the ICA during and after TSS adenoma resection. Surgeons should be aware of this change since it determines the width of the surgical corridor and can thus influence the ease of surgery.Hyponatremia after pituitary surgery is a frequent finding with potential severe complications and the most common cause for readmission. Several studies have found parameters associated with postoperative hyponatremia, but no reliable specific predictor was described yet. This pilot study evaluates the feasibility of machine learning (ML) algorithms to predict postoperative hyponatremia after resection of pituitary lesions.
MethodsRetrospective screening of a prospective registry of patients who underwent transsphenoidal surgery for pituitary lesions. Hyponatremia within 30 days after surgery was the primary outcome. Several pre- and intraoperative clinical, procedural and laboratory features were selected to train different ML algorithms. Trained models were compared using common performance metrics. Final model was internally validated on the testing dataset.
ResultsFrom 207 patients included in the study, 44 (22%) showed a hyponatremia within 30 days postoperatively. Hyponatremic measurements peaked directly postoperatively (day 0–1) and around day 7. Bootstrapped performance metrics of different trained ML-models showed largest area under the receiver operating characteristic curve (AUROC) for the boosted generalized linear model (67.1%), followed by the Naïve Bayes classifier (64.6%). The discriminative capability of the final model was assessed by predicting on unseen dataset. Large AUROC (84.3%; 67.0–96.4), sensitivity (81.8%) and specificity (77.5%) with an overall accuracy of 78.4% (66.7–88.2) was reached.
ConclusionOur trained ML-model was able to learn the complex risk factor interactions and showed a high discriminative capability on unseen patient data. In conclusion, ML-methods can predict postoperative hyponatremia and thus potentially reduce morbidity and improve patient safety.
相似文献Electrolyte disorders are relatively frequent and potentially serious complications after pituitary surgery. Both DI (diabetes insipidus) and SIADH (syndrome of inappropriate antidiuresis) can complicate and prolong hospital and intensive care unit stay, and the latter may even be preventable. We aim to assess the incidence of both electrolyte disorders and their risk factors. From a prospective registry of patients who underwent endoscopic transnasal transsphenoidal surgery (TSS) for pituitary adenoma, patients with postoperative DI and SIADH were identified. Univariable and multivariable statistics were carried out to identify factors independently associated with the occurrence of either DI or SIADH. A total of 174 patients were included, of which 73 (42%) were female. Mean age was 54 years (range 20–88). During postoperative hospital stay, 13 (7.5%) patients presenting with DI and 11 (6.3%) with SIADH were identified. Patients who developed DI after surgery had significantly longer hospital stays (p?=?0.022), as did those who developed SIADH (p?=?0.002). Four (2.3%) patients were discharged with a diagnosis of persistent DI, and 2 (1.1%) with the diagnosis of SIADH. At the last follow-up, 5 (2.9%) patients presented with persistent DI, while none of the patients suffered from SIADH. Younger age (odds ratio (OR) 0.97, 95% confidence interval (CI) 0.94–1.01, p?=?0.166) and pituitary apoplexy (OR 2.69, 95% CI 0.53–10.65, p?=?0.184) were weakly associated with the occurrence of DI. We identified younger age (OR 0.96, 95% CI 0.92–0.99, p?=?0.045) and lower preoperative serum sodium (OR 0.83, 95% CI 0.71–0.95, p?=?0.008) as independent risk factors for SIADH. Although we found a weak association among age, pituitary apoplexy, and the occurrence of DI, no independent predictor was identified for DI. For postoperative SIADH however, lower age and preoperative serum sodium were identified as significant predictors. None of these findings were sufficiently supported by preexisting literature. Both electrolyte disorders are exquisitely hard to predict preoperatively, and further research into their early detection and prevention is warranted.
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