Sex, race, and socioeconomic distinctions in incisional hernia management.

BACKGROUND: We sought to explore the impact of sex, race, and insurance status on operative management of incisional hernias. METHODS: A retrospective cohort study was conducted to explore adult patients diagnosed with an incisional hernia. Adjusted odds for non-operative versus operative management and time to repair were queried. RESULTS: Of the 29,475 patients with an incisional hernia, 20,767 (70.5%) underwent non-operative management. In relation to private insurance, Medicaid (aOR 1.40, 95% CI 1.27-1.54), Medicare (aOR 1.53, 95% CI 1.42-1.65), and uninsured status (aOR 1.99, 95% CI 1.71-2.36) were independently associated with non-operative management. African American race (aOR 1.30, 95% CI 1.17-1.47) was associated with non-operative management while female sex (aOR 0.81, 95% CI 0.77-0.86) was predictive of elective repair. For patients who underwent elective repair, both Medicare (aOR 1.40, 95% CI 1.18-1.66) and Medicaid (aOR 1.49, 95% CI 1.29-1.71) insurance, but not race, were predictive of delayed repair (>90 days after diagnosis). CONCLUSIONS: Sex, race, and insurance status influence incisional hernia management. Development of evidence-based management guidelines may help to ensure equitable care.

The Risk of Incarceration During Nonoperative Management of Incisional Hernias: A Population-based Analysis of 30,998 Patients.

OBJECTIVE: The aim of the study was to quantify the risk of incarceration of incisional hernias. BACKGROUND: Operative repair is the definitive treatment for incisional ventral hernias but is often deferred if the perceived risk of elective operation is elevated secondary to comorbid conditions. The risk of incarceration during nonoperative management (NOM) factors into shared decision making by patient and surgeon; however, the incidence of acute incarceration remains largely unknown. METHODS: A retrospective analysis of adult patients with an International Classification of Diseases, Ninth Revision or Tenth Revision diagnosis of incisional hernia was conducted from 2010 to 2017 in 15 hospitals of a single healthcare system. The primary outcome was incarceration necessitating emergent operation. The secondary outcome was 30-, 90-, and 365-day mortality. Univariate and multivariate analyses were used to determine independent predictors of incarceration. RESULTS: Among 30,998 patients with an incisional hernia (mean age 58.1 ±â€Š15.9 years; 52.7% female), 23,022 (78.1%) underwent NOM of whom 540 (2.3%) experienced incarceration, yielding a 1- and 5-year cumulative incidence of 1.24% and 2.59%, respectively. Independent variables associated with incarceration included: age older than 40 years, female sex, current smoker, body mass index 30 or greater, and a hernia-related inpatient admission. All-cause mortality rates at 30, 90, and 365 days were significantly higher in the incarceration group at 7.2%, 10%, and 14% versus 1.1%, 2.3%, and 5.3% in patients undergoing successful NOM, respectively. CONCLUSIONS: Incarceration is an uncommon complication of NOM but is associated with a significant risk of death. Tailored decision making for elective repair and considering the aforementioned risk factors for incarceration provides an initial step toward mitigating the excess morbidity and mortality of an incarceration event.

Development and validation of a five-factor score for prediction of pathologic pneumatosis.

BACKGROUND: The significance of pneumatosis intestinalis (PI) remains challenging. While certain clinical scenarios are predictive of transmural ischemia, risk models to assess the presence of pathologic PI are needed. The aim of this study was to determine what patient factors at the time of radiographic diagnosis of PI predict the risk for pathologic PI. METHODS: We conducted a retrospective cohort study examining patients with PI from 2010 to 2016 at a multicenter hospital network. Multivariate logistic regression was used to develop a predictive model for pathologic PI in a derivation cohort. Using regression-coefficient-based methods, the final multivariate model was converted into a five-factor-based score. Calibration and discrimination of the score were then assessed in a validation cohort. RESULTS: Of 305 patients analyzed, 102 (33.4%) had pathologic PI. We identified five factors associated with pathologic PI at the time of radiographic diagnosis: small bowel PI, age 70 years or older, heart rate 110 bpm or greater, lactate of 2 mmol/L or greater, and neutrophil-lymphocyte ratio 10 or greater. Using this model, patients in the validation cohort were assigned risk scores ranging from 0 to 11. Low-risk patients were categorized when scores are 0 to 4; intermediate, score of 5 to 6; high, score of 7 to 8; and very high risk, 9+. In the validation cohort, very high-risk patients (n = 17; 18.1%) had predicted rates of pathologic pneumatosis of 88.9% and an observed rate of 82.4%. In contrast, patients labeled as low risk (n = 37; 39.4%) had expected rates of pathologic pneumatosis of 1.3% and an observed rate of 0%. The model showed excellent discrimination (area under the curve, 0.90) and good calibration (Hosmer-Lemeshow goodness-of-fit, p = 0.37). CONCLUSION: Our score accurately stratifies patient risk of pathologic pneumatosis. This score has the potential to target high-risk individuals for expedient operation and spare low-risk individuals invasive interventions. LEVEL OF EVIDENCE: Prognostic Study, Level III.

Interactive NLP in Clinical Care: Identifying Incidental Findings in Radiology Reports.

BACKGROUND: Despite advances in natural language processing (NLP), extracting information from clinical text is expensive. Interactive tools that are capable of easing the construction, review, and revision of NLP models can reduce this cost and improve the utility of clinical reports for clinical and secondary use. OBJECTIVES: We present the design and implementation of an interactive NLP tool for identifying incidental findings in radiology reports, along with a user study evaluating the performance and usability of the tool. METHODS: Expert reviewers provided gold standard annotations for 130 patient encounters (694 reports) at sentence, section, and report levels. We performed a user study with 15 physicians to evaluate the accuracy and usability of our tool. Participants reviewed encounters split into intervention (with predictions) and control conditions (no predictions). We measured changes in model performance, the time spent, and the number of user actions needed. The System Usability Scale (SUS) and an open-ended questionnaire were used to assess usability. RESULTS: Starting from bootstrapped models trained on 6 patient encounters, we observed an average increase in F1 score from 0.31 to 0.75 for reports, from 0.32 to 0.68 for sections, and from 0.22 to 0.60 for sentences on a held-out test data set, over an hour-long study session. We found that tool helped significantly reduce the time spent in reviewing encounters (134.30 vs. 148.44 seconds in intervention and control, respectively), while maintaining overall quality of labels as measured against the gold standard. The tool was well received by the study participants with a very good overall SUS score of 78.67. CONCLUSION: The user study demonstrated successful use of the tool by physicians for identifying incidental findings. These results support the viability of adopting interactive NLP tools in clinical care settings for a wider range of clinical applications.

Identifying incidental findings from radiology reports of trauma patients: An evaluation of automated feature representation methods.

BACKGROUND: Radiologic imaging of trauma patients often uncovers findings that are unrelated to the trauma. These are termed as incidental findings and identifying them in radiology examination reports is necessary for appropriate follow-up. We developed and evaluated an automated pipeline to identify incidental findings at sentence and section levels in radiology reports of trauma patients. METHODS: We created an annotated dataset of 4,181 reports and investigated automated feature representations including traditional word and clinical concept (such as SNOMED CT) representations, as well as word and concept embeddings. We evaluated these representations by using them with traditional classifiers such as logistic regression and with deep learning methods such as convolutional neural networks (CNNs). RESULTS: The best performance was observed using word embeddings with CNNs with F1 scores of 0.66 and 0.52 at section and sentence levels respectively. The F1 score was statistically significantly higher for sections compared to sentences (Wilcoxon; Z < 0.001, p < 0.05). Compared to using words alone, the addition of SNOMED CT concepts did not improve performance. At the sentence level, the F1 score improved significantly from 0.46 to 0.52 when using pre-trained embeddings (Wilcoxon; Z < 0.001, p < 0.05). CONCLUSION: The results show that the best performance was achieved by using embeddings with CNNs at both sentence and section levels. This provides evidence that such a pipeline is capable of accurately identifying incidental findings in radiology reports in an automated manner.

Preoperative risk analysis index for frailty predicts short-term outcomes after hepatopancreatobiliary surgery.

BACKGROUND: The Risk Analysis Index (RAI) for frailty is a rapid survey for comorbidities and performance status, which predicts mortality after general surgery. We aimed to validate the RAI in predicting outcomes after hepatopancreatobiliary surgery. METHODS: Associations of RAI, determined in 162 patients prior to undergoing hepatopancreatobiliary surgery, with prospectively collected 30-day post-operative outcomes were analyzed with multivariate logistic and linear regression. RESULTS: Patients (age 62 ± 14, 51% female) had a median RAI of 7, range 0-25. With every unit increase in RAI, length of stay increased by 5% (95% CI: 2-7%), odds of ICU admission increased by 10% (0-20%), ICU length of stay increased by 21% (9-34%), and odds of discharge to a nursing facility increased by 8% (0-17%) (all P < 0.05). Particularly in patients who suffered a first post-operative complication, RAI was associated with additional complications (1.6 unit increase in Comprehensive Complication Index per unit increase in RAI, P = 0.002). In a direct comparison in a subset of 74 patients, RAI and the ACS-NSQIP Risk Calculator performed comparably in predicting outcomes. CONCLUSION: While RAI and ACS-NSQIP Risk Calculator comparatively predicted short-term outcomes after HPB surgery, RAI has been specifically designed to identify frail patients who can potentially benefit from preoperative prehabilitation interventions.

Management of anticoagulation with rivaroxaban in trauma and acute care surgery: Complications and reversal strategies as compared to warfarin therapy.

BACKGROUND: Rivaroxaban has gained popularity as an anticoagulant (AC) for stroke prevention in nonvalvular atrial fibrillation (afib) and venous thromboembolism (VTE). Although adverse bleeding events are associated with all AC, lack of point-of-care testing to measure the effect of rivaroxaban in emergent situations has contributed to perceived increased risk among physicians. METHODS: This study aims to describe a single-center experience with trauma and emergency general surgery (EGS) patients taking rivaroxaban and evaluate outcomes compared with patients taking warfarin using a propensity score analysis. Trauma and EGS patients taking rivaroxaban or warfarin for afib/VTE over a 2-year period were eligible for inclusion and matched for injury/illness severity in a 1:2 ratio using propensity score matching. In a single quaternary referral center, 192 warfarin patients were matched to 96 rivaroxaban patients. Groups were well matched with no significant difference in age/sex, admission systolic blood pressure/heart rate, admission hemoglobin, injury severity score (trauma patients), or need for ICU admission. Conditional logistic regression determined association of AC type with bleeding complications, adjusting for age/sex, AC indication, coagulation laboratory values, antiplatelet medications or other AC, comorbidities, renal impairment, and operative intervention. Primary outcome was bleeding complications, defined as hemorrhage during admission or as a presenting problem. Secondary outcomes included invasive interventions, AC reversal, VTE complications, and mortality. RESULTS: There was no difference between rivaroxaban and warfarin for bleeding complications (37% vs. 39%, p = 0.49), VTE complications (4.2% vs. 5.7%, p = 0.44), or mortality (4.2% vs. 5.8%, p = 0.63). Fewer rivaroxaban patients underwent surgical or interventional radiology procedures during admission (32% vs. 43%, p = 0.01), but there was no difference in procedures specifically for bleeding (10% vs. 12% p = 0.68). Rivaroxaban patients less frequently underwent AC reversal (34% vs. 46%, p = 0.01) or received multiple reversal agents (20% vs. 29%, p = 0.02). Regression analysis confirmed AC type was not associated with bleeding complications (rivaroxaban vs. warfarin relative risk 1.02; 95% CI 0.85-1.22, p = 0.85). CONCLUSION: Reversal of rivaroxaban was less common and required fewer agents, whereas bleeding complications and hemostatic interventions do not seem to be different between these AC types. LEVEL OF EVIDENCE: Therapeutic study, level II.

Rapid spectrophotometric technique for quantifying iron in cells labeled with superparamagnetic iron oxide nanoparticles: potential translation to the clinic.

Labeling cells with superparamagnetic iron oxide (SPIO) nanoparticles provides the ability to track cells by magnetic resonance imaging. Quantifying intracellular iron concentration in SPIO labeled cells would allow for the comparison of agents and techniques used to magnetically label cells. Here we describe a rapid spectrophotometric technique (ST) to quantify iron content of SPIO-labeled cells, circumventing the previous requirement of an overnight acid digestion. Following lysis with 10% sodium dodecyl sulfate (SDS) of magnetically labeled cells, quantification of SPIO doped or labeled cells was performed using commonly available spectrophotometric instrument(s) by comparing absorptions at 370 and 750 nm with correction for turbidity of cellular products to determine the iron content of each sample. Standard curves demonstrated high linear correlation (R(2) = 0.998) between absorbance spectra of iron oxide nanoparticles and concentration in known SPIO-doped cells. Comparisons of the ST with inductively coupled plasma-mass spectroscopy (ICP-MS) or nuclear magnetic resonance relaxometric (R(2)) determinations of intracellular iron contents in SPIO containing samples resulted in significant linear correlation between the techniques (R(2) vs ST, R(2) > 0.992, p < 0.0001; ST vs ICP-MS, R(2) > 0.995, p < 0.0001) with the limit of detection of ST for iron = 0.66 µg ml(-1) for 10(6) cells ml(-1). We have developed a rapid straightforward protocol that does not require overnight acid digestion for quantifying iron oxide content in magnetically labeled cells using readily available analytic instrumentation that should greatly expedite advances in comparing SPIO agents and protocols for labeling cells.