RESUMEN
OBJECTIVE: Current guidelines do not specify timing for management of acute spinal cord injury (aSCI) due to lack of high-quality evidence supporting specific intervals for intervention. Randomized prospective trials may be unethical. Nonetheless, physicians have been sued for delays in diagnosis and intervention. METHODS: The authors reviewed both the medical literature supporting the guidelines and the legal cases reported in the Westlaw and Lexis Advance databases from 1972 to 2018 resulting in awards or settlements, to identify whether surgeons are vulnerable to litigation despite the existence of guidelines not mandating specific timing of care. RESULTS: Timing of intervention was related to claims in 59 (36%) of 163 cases involving SCI. All 22 trauma cases identified cited timing of intervention, sometimes related to delayed diagnosis, as a reason for the lawsuit. The mean award of 10 cases in which the plaintiffs' awards were disclosed was $4,294,384. In the majority of cases, award amounts were not disclosed. CONCLUSIONS: Because conduct of a prospective, randomized trial to investigate surgical timing of intervention for aSCI may not be achievable, evidence-based guidelines will be unlikely to mandate specific timing. Nonetheless, surgeons who unreasonably delay intervention for aSCI may be at risk for litigation due to treatment delay. This is increasingly likely in an environment where "complete" SCI is difficult to verify. SCI may at some point be recognized as a surgical emergency, as brain injury generally is, despite a lack of prospective randomized trials supporting this implementation, challenging the feasibility of the US trauma infrastructure to provide care for these patients.
Asunto(s)
Traumatismos de la Médula Espinal , Cirujanos , Adhesión a Directriz , Humanos , Estudios Prospectivos , Traumatismos de la Médula Espinal/cirugía , Columna VertebralRESUMEN
INTRODUCTION: Intra-detrusor botulinum toxin (Botox) injection is a minimally invasive alternative to augmentation cystoplasty in patients with refractory neurogenic bladder. Botox was first used for neurogenic bladder children two decades ago. However, there are no existing guidelines on indications or use among patients with spina bifida. Furthermore, there are little data regarding its use relative to bladder augmentation and patient volume on a national scale. OBJECTIVE: We sought to investigate the contemporary trends of intra-detrusor Botox injection and augment cystoplasty in free-standing children's hospitals. STUDY DESIGN: We queried the Pediatric Health Information System database to identify spina bifida patients from 2016 to 2019 who underwent intra-detrusor Botox injection and augment cystoplasty based on CPT and ICD-10 codes. Total spina bifida population under care in the free-standing children's hospitals was estimated by all inpatient and ambulatory surgery encounters as denominators to calculate frequency by time for both intra-detrusor Botox injections and augmentation cystoplasty. RESULTS: In total, we included 1924 intra-detrusor Botox injections and 842 augmentation cystoplasties. 1413 (51.1%) patients were female. Median age at surgery was 10.0 (interquartile range 6.98-13.5) years. There was a significant increase in intra-detrusor Botox injection frequency (p < 0.001). While there was an overall decreasing, but not significant, trend for augmentation cystoplasty, there was a significant increase in this procedure during the summer months compared to the rest of the year (p < 0.001, Figure 1). Sensitivity analysis using only first intra-detrusor Botox injection per patient demonstrated similarly significant increasing trend. DISCUSSION: Use of intra-detrusor Botox injection for the management of neurogenic bladder has significantly increased among patients with spina bifida while augmentation cystoplasty has slightly decreased, but not significantly. CONCLUSIONS: Over time, practice patterns for the treatments of neurogenic bladder among spina bifida children have favored minimally invasive Botox injections while augmentation cystoplasty use has not significantly changed.
Asunto(s)
Toxinas Botulínicas Tipo A , Hospitales Pediátricos , Disrafia Espinal , Vejiga Urinaria Neurogénica , Humanos , Toxinas Botulínicas Tipo A/administración & dosificación , Femenino , Masculino , Vejiga Urinaria Neurogénica/cirugía , Vejiga Urinaria Neurogénica/tratamiento farmacológico , Niño , Estados Unidos , Adolescente , Estudios Retrospectivos , Inyecciones Intramusculares , Preescolar , Procedimientos Quirúrgicos Urológicos/métodos , Fármacos Neuromusculares/administración & dosificaciónRESUMEN
BACKGROUND: Retained surgical items (RSI) are preventable events that pose a significant risk to patient safety. Current strategies for preventing RSIs rely heavily on manual instrument counting methods, which are prone to human error. This study evaluates the feasibility and performance of a deep learning-based computer vision model for automated surgical tool detection and counting. METHODS: A novel dataset of 1,004 images containing 13,213 surgical tools across 11 categories was developed. The dataset was split into training, validation, and test sets at a 60:20:20 ratio. An artificial intelligence (AI) model was trained on the dataset, and the model's performance was evaluated using standard object detection metrics, including precision and recall. To simulate a real-world surgical setting, model performance was also evaluated in a dynamic surgical video of instruments being moved in real-time. RESULTS: The model demonstrated high precision (98.5%) and recall (99.9%) in distinguishing surgical tools from the background. It also exhibited excellent performance in differentiating between various surgical tools, with precision ranging from 94.0 to 100% and recall ranging from 97.1 to 100% across 11 tool categories. The model maintained strong performance on a subset of test images containing overlapping tools (precision range: 89.6-100%, and recall range 97.2-98.2%). In a real-time surgical video analysis, the model maintained a correct surgical tool count in all non-transition frames, with a median inference speed of 40.4 frames per second (interquartile range: 4.9). CONCLUSION: This study demonstrates that using a deep learning-based computer vision model for automated surgical tool detection and counting is feasible. The model's high precision and real-time inference capabilities highlight its potential to serve as an AI safeguard to potentially improve patient safety and reduce manual burden on surgical staff. Further validation in clinical settings is warranted.
RESUMEN
Perforated appendicitis is a rare but serious clinical scenario typically requiring urgent surgical intervention. Herein, we discuss the case of a 62-year-old woman with COVID-19 and ruptured retrocecal appendicitis presenting as a right lower extremity soft tissue infection that was successfully managed using non-operative measures. This unique case illustrates the feasibility of conservative care - rather than urgent surgical intervention - in the treatment of an atypical presentation of complicated appendicitis in a high-risk patient.
RESUMEN
OBJECTIVE: Hearing loss (HL) is highly prevalent, yet underrecognized and underdiagnosed. Lack of standardized screening, awareness, cost, and access to hearing testing present barriers to HL identification. To facilitate prescreening and selection of patients who warrant audiometric evaluation, we developed a machine learning (ML) model to predict speech-frequency pure-tone average (PTA). STUDY DESIGN: Cross-sectional study. SETTING: National Health and Nutrition Examination Survey (NHANES). METHODS: The cohort included 8918 adults (≥20 years) who completed audiometric testing with NHANES (2012-2018). The primary outcome measure was the prediction of better hearing ear speech-frequency PTA. Relevant predictors included demographics, medical conditions, and subjective assessment of hearing. Supervised ML with a tree-based architecture was used. Regression performance was determined by the mean absolute error (MAE) with binary classification assessed with area under the receiver operating characteristic curve (AUC). RESULTS: Using the full set of predictors, the test set MAE between the ML-predicted and actual PTA was 5.29 dB HL (95% confidence interval [CI]: 4.97-5.61). The 5 most influential predictors of higher PTA were increased age, worse subjective hearing, male gender, increased body mass index, and history of smoking. The 5-factor abbreviated model performed comparably to the extended feature set with MAE 5.36 (95% CI: 5.03-5.69) and AUC for PTA > 25 dB HL of 0.92 (95% CI: 0.90-0.94). CONCLUSION: The ML model was able to predict PTA with patient demographics, clinical factors, and subjective hearing status. ML-based prediction may be used to identify individuals who could benefit most from audiometric evaluation.
Asunto(s)
Sordera , Pérdida Auditiva , Masculino , Adulto , Humanos , Encuestas Nutricionales , Estudios Transversales , Pérdida Auditiva/diagnóstico , Pérdida Auditiva/epidemiología , Audición , Aprendizaje Automático , Demografía , Audiometría de Tonos PurosRESUMEN
OBJECTIVE: To develop scalable objective methods for differentiating patients with and without detrusor overactivity (DO) using quantitative Fast Fourier Transform (FFT)-based measures and routinely captured cystometry data. METHODS: Retrospective cystometry data were collected as prevoid vesical and abdominal pressure signals from 18 DO and 10 SUI (non-DO) cystometry recordings. Data were filtered and divided into two equal-duration segments, Early and Late Fill, representing the first and second halves of filling. FFT was applied, followed by subtraction of abdominal spectra from vesical spectra. Spectral Power (SP) and Weighted Average Frequency (WAF) measures were calculated for each segment spectra within 1-6 cycles min-1. RESULTS: Compared to non-DO, the mean SP was significantly higher in DO patients for both Early and Late Fill segments. WAF was significantly lower in DO patients for both segments. Changes in spectral pressures appeared to be linked to the presence of detrusor contractions (DCs) and were especially visible when DCs were present in the Early Fill segments of cystometry. CONCLUSION: FFT-based spectral measures derived from routinely captured cystometry data are significantly different between DO and non-DO patients. This preliminary method is clinically scalable and can be further developed to facilitate the detection of DO, classify disease phenotype, and capture therapeutic efficacy.
Asunto(s)
Vejiga Urinaria Neurogénica , Vejiga Urinaria Hiperactiva , Humanos , Estudios Retrospectivos , Urodinámica , Vejiga Urinaria , Vejiga Urinaria Hiperactiva/diagnósticoRESUMEN
Background and Aims: Modern health care faces a plethora of challenges including the delivery of quality and cost-efficient care. Physicians are first-hand observers of clinical problems but may lack the requisite training and education to develop innovations that improve patient care. Few medical education programs address innovation, leadership, and transdisciplinary collaboration despite being highlighted by national medical and education organizations including the American Medical Association. The University of Minnesota has implemented the Augustine program over the last 10-years to produce physicians that are leaders in medical innovation. Methods: As a novel joint engineering-medical school curriculum to educate medical students, residents, and fellows, the Augustine program incorporates engineering coursework, biomedical research, and a multidisciplinary design and business development experience to produce physicians capable of designing and marketing "disruptive technologies." The Augustine program takes 1-year to complete in addition to the 4-year medical education and provides a Master of Biomedical Engineering upon completion. Results: Augustine program graduates (n = 6) have reported significant contributions related to the joint engineering-medical education including peer-reviewed publications (Median: 13), deployable assets (Median: 2), and intellectual property (Median: 1). Most surveyed graduates (n = 5, 83%) continue to be active contributors to medical innovation and all (n = 6, 100%) utilize their transdisciplinary education to improve patient care. Conclusion: Augustine program graduates impact the entire spectrum of innovation and continue to improve patient care. The program will seek to emphasize the inclusion of physician residents and fellows with position expansion. The addition of a multi-week medical innovation clerkship will provide a more focused experience for students unable to dedicate an entire year to a transdisciplinary experience.
RESUMEN
OBJECTIVE: To document the incidence, risk factors, and prevalence of sacral insufficiency fractures (SIF) among patients who have undergone total pubectomy for osteomyelitis. METHODS: A retrospective chart review was performed of patients undergoing total pubectomy for osteomyelitis at a single institution from 2016 to 2021. Descriptive statistics and univariate analysis were performed using the Wilcoxon rank-sum test and Fisher exact test as appropriate. RESULTS: Sixteen patients underwent total pubectomy for osteomyelitis. The median age was 68 years. 12 of 16 (75%) had previously received pelvic radiotherapy. The median BMI was 27.8 kg/m2. Eleven (68.75%) had postoperative pelvic imaging, of which 3 (27.3%) had a new SIF. One other patient had a SIF 3 days before pubectomy. Three SIFs were detected via MRI and 1 by CT scan. The median BMI of patients with SIF was significantly lower than those without SIF (22.4 vs 30.5, Pâ¯=â¯.004). All patients with SIF presented with new pelvic or perineal pain without radiculopathy. Symptoms resolved for three patients with non-opioid analgesics, physical therapy, and/or a brief trial of opioids. CONCLUSION: Sacral insufficiency fracture is a rare sequela of total pubectomy for osteomyelitis. Lower BMI is significantly associated with SIF perhaps due to reduced muscle mass or poor bone condition and, as a result, baseline pelvic instability. Medical management should be first-line therapy.
Asunto(s)
Fracturas por Estrés , Osteomielitis , Fracturas de la Columna Vertebral , Humanos , Anciano , Fracturas por Estrés/etiología , Fracturas por Estrés/cirugía , Estudios Retrospectivos , Sacro , Fracturas de la Columna Vertebral/complicaciones , Fracturas de la Columna Vertebral/cirugía , Osteomielitis/cirugía , Osteomielitis/complicacionesRESUMEN
PURPOSE: We quantified patient record documentation of sacral neuromodulation (SNM) threshold testing and programming parameters at our institution to identify opportunities to improve therapy outcomes and future SNM technologies. METHODS: A retrospective review was conducted using 127 records from 40 SNM patients. Records were screened for SNM documentation including qualitative and quantitative data. The qualitative covered indirect references to threshold testing and the quantitative included efficacy descriptions and device programming used by the patient. Findings were categorized by visit type: percutaneous nerve evaluation (PNE), stage 1 (S1), permanent lead implantation, stage 2 (S2) permanent impulse generator implantation, device-related follow-up, or surgical removal. RESULTS: Documentation of threshold testing was more complete during initial implant visits (PNE and S1), less complete for S2 visits, and infrequent for follow-up clinical visits. Surgical motor thresholds were most often referred to using only qualitative comments such as "good response" (88%, 100% for PNE, S1) and less commonly included quantitative values (68%, 84%), locations of response (84%, 83%) or specific contacts used for testing (0%). S2 motor thresholds were less well documented with qualitative, quantitative, and anatomical location outcomes at 70%, 48%, and 36% respectively. Surgical notes did not include specific stimulation parameters or contacts used for tests. Postoperative sensory tests were often only qualitative (80%, 67% for PNE, S1) with quantitative values documented much less frequently (39%, 9%) and typically lacked sensory locations or electrode-specific results. For follow-up visits, <10% included quantitative sensory test outcomes. Few records (<7%) included device program settings recommended for therapy delivery and none included therapy-use logs. CONCLUSION: While evidence suggests contact and parameter-specific programming can improve SNM therapy outcomes, there is a major gap in the documentation of this data. More detailed testing and documentation could improve therapeutic options for parameter titration and provide design inputs for future technologies.
RESUMEN
The presentation of incontinence in a patient with complex neurological disorders can vary substantially and depend on the location and nature of neurological injuries. In this case report, a 53-year-old female with cerebral palsy presents with recurrent episodes of catheter discharge and incontinence due to presumed bladder spasms. However, urodynamics (UDS) study reveals the spasms to be abdominal in origin. This unique case illustrates the diagnostic utility of UDS and important considerations when evaluating patients with complex medical and neurological disorders.
RESUMEN
Cystometry is a standard procedure for the clinical evaluation of lower urinary tract disorders such as detrusor overactivity (DO). The utility of this procedure for DO diagnosis, however, is limited by the use of physician observations of bladder contractions and patient reported filling sensations. Although a number of preclinical and clinical studies have observed and developed methods to characterize bladder pressure dynamics, these techniques have not been scaled for routine clinical application. The goal of this study was to evaluate the feasibility of using an awake large animal model to characterize bladder pressure signals from cystometry as bladder pressure spectra and quantify changes in spectra during bladder filling. Two adult female sheep were trained for quiet catheterization in a minimally supportive sling and underwent multiple awake and limited anesthetized cystometry tests. In each test, bladder pressure was measured during continuous filling or with filling that included periods of no filling (constant volume). A Fast-Fourier Transform (FFT)-based algorithm was then used to quantify changes in pre-voiding bladder pressure spectra. Changes in Spectral Power (SP) and Weighted Average Frequency (WAF) were calculated during filling. To visualize temporal changes in bladder pressure frequencies during filling, Continuous Wavelet Transform (CWT) was also applied to cystometry data. Results showed that a significant increase in SP and decrease in WAF were both associated with bladder filling. However, during awake constant volume tests, SP significantly increased while changes in WAF were nonsignificant. Anesthetized tests demonstrated comparable values to awake tests for WAF while SP was considerably reduced. CWT facilitated visualization of spectral changes associated with SP and WAF as well as apparent non-voiding contractions during awake and anesthetized volume tests.Clinical Relevance-Bladder pressure spectra during cystometry are detectable in sheep and the changes during filling are similar to those observed in human retrospective clinical data. Sheep cystometry may be a valuable testbed for establishing and testing quantitative pressure spectra for use as a clinical diagnostic tool.
Asunto(s)
Vejiga Urinaria , Urodinámica , Animales , Estudios de Factibilidad , Femenino , Humanos , Estudios Retrospectivos , Ovinos , MicciónRESUMEN
Neuroplasticity is a fundamental property of the respiratory control system, enabling critical adaptations in breathing to meet the challenges, but little is known whether neonates express neuroplasticity similar to adults. We tested the hypothesis that, similar to adults, tyrosine receptor kinase B (TrkB) or adenosine A2a receptor activation in neonates are independently sufficient to elicit respiratory motor facilitation, and that co-induction of TrkB and A2a receptor-dependent plasticity undermines respiratory motor facilitation. TrkB receptor activation with 7,8-dihydroxyflavone (DHF) in neonatal brainstem-spinal cord preparations induced a long-lasting increase in respiratory motor output in 55 % of preparations, whereas adenosine A2a receptor activation with CGS21680 only sporadically induced respiratory motor plasticity. CGS21680 and DHF co-application prevented DHF-dependent respiratory motor facilitation, whereas co-application of MSX-3 (adenosine A2a receptor antagonist) and DHF more rapidly induced respiratory motor plasticity. Collectively, these data suggest that mechanisms underlying respiratory neuroplasticity may be only partially operational in early neonatal life, and that adenosine A2a receptor activation undermines TrkB-induced respiratory plasticity.
Asunto(s)
Agonistas del Receptor de Adenosina A2/farmacología , Antagonistas del Receptor de Adenosina A2/farmacología , Flavonas/farmacología , Plasticidad Neuronal/fisiología , Receptor de Adenosina A2A/metabolismo , Receptor trkB/agonistas , Receptor trkB/metabolismo , Fenómenos Fisiológicos Respiratorios , Adenosina/análogos & derivados , Adenosina/farmacología , Animales , Animales Recién Nacidos , Tronco Encefálico/efectos de los fármacos , Modelos Animales de Enfermedad , Plasticidad Neuronal/efectos de los fármacos , Fenetilaminas/farmacología , Ratas , Fenómenos Fisiológicos Respiratorios/efectos de los fármacos , Médula Espinal/efectos de los fármacosRESUMEN
Purpose: Clinicians rely on imaging features to calculate complexity of renal masses based on validated scoring systems. These scoring methods are labor-intensive and are subjected to interobserver variability. Artificial intelligence has been increasingly utilized by the medical community to solve such issues. However, developing reliable algorithms is usually time-consuming and costly. We created an international community-driven competition (KiTS19) to develop and identify the best system for automatic segmentation of kidneys and kidney tumors in contrast CT and report the results. Methods: A training and test set of CT scans that was manually annotated by trained individuals were generated from consecutive patients undergoing renal surgery for whom demographic, clinical and outcome data were available. The KiTS19 Challenge was a machine learning competition hosted on grand-challenge.org in conjunction with an international conference. Teams were given 3 months to develop their algorithm using a full-annotated training set of images and an unannotated test set was released for 2 weeks from which average Sørensen-Dice coefficient between kidney and tumor regions were calculated across all 90 test cases. Results: There were 100 valid submissions that were based on deep neural networks but there were differences in pre-processing strategies, architectural details, and training procedures. The winning team scored a 0.974 kidney Dice and a 0.851 tumor Dice resulting in 0.912 composite score. Automatic segmentation of the kidney by the participating teams performed comparably to expert manual segmentation but was less reliable when segmenting the tumor. Conclusion: Rapid advancement in automated semantic segmentation of kidney lesions is possible with relatively high accuracy when the data is released publicly, and participation is incentivized. We hope that our findings will encourage further research that would enable the potential of adopting AI into the medical field.
RESUMEN
There is a large body of literature linking anatomic and geometric characteristics of kidney tumors to perioperative and oncologic outcomes. Semantic segmentation of these tumors and their host kidneys is a promising tool for quantitatively characterizing these lesions, but its adoption is limited due to the manual effort required to produce high-quality 3D segmentations of these structures. Recently, methods based on deep learning have shown excellent results in automatic 3D segmentation, but they require large datasets for training, and there remains little consensus on which methods perform best. The 2019 Kidney and Kidney Tumor Segmentation challenge (KiTS19) was a competition held in conjunction with the 2019 International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI) which sought to address these issues and stimulate progress on this automatic segmentation problem. A training set of 210 cross sectional CT images with kidney tumors was publicly released with corresponding semantic segmentation masks. 106 teams from five continents used this data to develop automated systems to predict the true segmentation masks on a test set of 90 CT images for which the corresponding ground truth segmentations were kept private. These predictions were scored and ranked according to their average Sørensen-Dice coefficient between the kidney and tumor across all 90 cases. The winning team achieved a Dice of 0.974 for kidney and 0.851 for tumor, approaching the inter-annotator performance on kidney (0.983) but falling short on tumor (0.923). This challenge has now entered an "open leaderboard" phase where it serves as a challenging benchmark in 3D semantic segmentation.
Asunto(s)
Neoplasias Renales , Tomografía Computarizada por Rayos X , Estudios Transversales , Humanos , Procesamiento de Imagen Asistido por Computador , Riñón/diagnóstico por imagen , Neoplasias Renales/diagnóstico por imagenRESUMEN
Objective: To understand better the public perception and comprehension of medical technology such as artificial intelligence (AI) and robotic surgery. In addition to this, to identify sensitivity to their use to ensure acceptability and quality of counseling. Subjects and Methods: A survey was conducted on a convenience sample of visitors to the MN Minnesota State Fair (n = 264). Participants were randomized to receive one of two similar surveys. In the first, a diagnosis was made by a physician and in the second by an AI application to compare confidence in human and computer-based diagnosis. Results: The median age of participants was 45 (interquartile range 28-59), 58% were female (n = 154) vs 42% male (n = 110), 69% had completed at least a bachelor's degree, 88% were Caucasian (n = 233) vs 12% ethnic minorities (n = 31) and were from 12 states, mostly from the Upper Midwest. Participants had nearly equal trust in AI vs physician diagnoses. However, they were significantly more likely to trust an AI diagnosis of cancer over a doctor's diagnosis when responding to the version of the survey that suggested that an AI could make medical diagnoses (p = 9.32e-06). Though 55% of respondents (n = 145) reported that they were uncomfortable with automated robotic surgery, the majority of the individuals surveyed (88%) mistakenly believed that partially autonomous surgery was already happening. Almost all (94%, n = 249) stated that they would be willing to pay for a review of medical imaging by an AI if available. Conclusion: Most participants express confidence in AI providing medical diagnoses, sometimes even over human physicians. Participants generally express concern with surgical AI, but they mistakenly believe that it is already being performed. As AI applications increase in medical practice, health care providers should be cognizant of the potential amount of misinformation and sensitivity that patients have to how such technology is represented.