All Public Health is Local: Lessons From Eagle County During the First 2 Years of the Coronavirus Disease-2019 Pandemic.

BACKGROUND: During the coronavirus disease-2019 (COVID-19) pandemic cumulative United States COVID-19 deaths per capita were higher than all other large, high-income nations, but with substantial variation across the country. OBJECTIVE: The aim was to detail the public health response during the pandemic in Eagle County, Colorado. RESEARCH DESIGN AND MEASURES: Observational study using pre-COVID-19 county public health metrics. Pandemic actions were recorded from a narrative summary of daily phone consultations by a county-wide taskforce and interviews. Outcomes obtained from local, state, and nationally reported databases. METHODS: Eagle County began with a life expectancy of 85.9, low all-cause age-adjusted death rates equal for both White and Latinx populations, a high household median income, and other prepandemic advantages. It also launched an innovative, independent county-wide taskforce lead by experienced mid-level managers. The taskforce implemented rapid communication of decision consequences, made immediate course corrections without traditional organizational approvals or contradictory political pressures. RESULTS: Eagle County was first in Colorado to obtain Personal Protective Equipment and to establish a drive-through testing facility. The COVID-19 case fatality rate was 0.34%. The sole intensive care unit never reached maximum capacity. By March 2022, Eagle County had administered at least 1 vaccine dose to 100% of the population and 83% were fully vaccinated. CONCLUSIONS: It is not possible to directly attribute superior outcomes to either the baseline characteristics of Eagle County or its innovative taskforce design and deployment. Rather this report highlights the potential impact that improving the baseline health status of US citizens and permitting novel problem-solving approaches by local public health officials might have for the next pandemic.

Initial Misidentification of Thumb Poroma by Shave Biopsy.

Poromas are benign adnexal neoplasms originating from the intraepidermal portion of sweat gland ducts. With the possibility of malignant transformation, accurate clinical diagnosis and treatment are crucial. Numerous reports of hand poroma lesions have been reported. We present an unusual case of a distal thumb poroma originally identified as a squamous cell lesion in a shave biopsy and eventually accurately identified after excisional biopsy. This report highlights the limitations of shave biopsy associated with soft tissue hand lesions and the need to consider poroma when evaluating a soft tissue lesion of the hand.

Oncologic reconstruction of the hand and upper extremity: Maximizing functional outcomes.

Upper extremity malignancies have the potential to create significant functional impairment, and as such represent an opportunity for collaborative reconstruction to minimize potential morbidity. Given the increased complexity and array of potential reconstruction solutions, functional limb preservation is overwhelmingly and increasingly successful in appropriately selected patients. The purpose of this review is to familiarize the reader with the general functional considerations of the upper extremity, review major reconstructive options, and present a general algorithm for reconstruction and maintenance of function. J. Surg. Oncol. 2016;113:946-954. © 2016 Wiley Periodicals, Inc.

Characterizing genetic variants for clinical action.

Genome-wide association studies, DNA sequencing studies, and other genomic studies are finding an increasing number of genetic variants associated with clinical phenotypes that may be useful in developing diagnostic, preventive, and treatment strategies for individual patients. However, few variants have been integrated into routine clinical practice. The reasons for this are several, but two of the most significant are limited evidence about the clinical implications of the variants and a lack of a comprehensive knowledge base that captures genetic variants, their phenotypic associations, and other pertinent phenotypic information that is openly accessible to clinical groups attempting to interpret sequencing data. As the field of medicine begins to incorporate genome-scale analysis into clinical care, approaches need to be developed for collecting and characterizing data on the clinical implications of variants, developing consensus on their actionability, and making this information available for clinical use. The National Human Genome Research Institute (NHGRI) and the Wellcome Trust thus convened a workshop to consider the processes and resources needed to: (1) identify clinically valid genetic variants; (2) decide whether they are actionable and what the action should be; and (3) provide this information for clinical use. This commentary outlines the key discussion points and recommendations from the workshop.

Changes in hospital mortality for United States intensive care unit admissions from 1988 to 2012.

INTRODUCTION: A decrease in disease-specific mortality over the last twenty years has been reported for patients admitted to United States (US) hospitals, but data for intensive care patients are lacking. The aim of this study was to describe changes in hospital mortality and case-mix using clinical data for patients admitted to multiple US ICUs over the last 24 years. METHODS: We carried out a retrospective time series analysis of hospital mortality using clinical data collected from 1988 to 2012. We also examined the impact of ICU admission diagnosis and other clinical characteristics on mortality over time. The potential impact of hospital discharge destination on mortality was also assessed using data from 2001 to 2012. RESULTS: For 482,601 ICU admissions there was a 35% relative decrease in mortality from 1988 to 2012 despite an increase in age and severity of illness. This decrease varied greatly by diagnosis. Mortality fell by >60% for patients with chronic obstructive pulmonary disease, seizures and surgery for aortic dissection and subarachnoid hemorrhage. Mortality fell by 51% to 59% for six diagnoses, 41% to 50% for seven diagnoses, and 10% to 40% for seven diagnoses. The decrease in mortality from 2001 to 2012 was accompanied by an increase in discharge to post-acute care facilities and a decrease in discharge to home. CONCLUSIONS: Hospital mortality for patients admitted to US ICUs has decreased significantly over the past two decades despite an increase in the severity of illness. Decreases in mortality were diagnosis specific and appear attributable to improvements in the quality of care, but changes in discharge destination and other confounders may also be responsible.

Building the evidence base for decision making in cancer genomic medicine using comparative effectiveness research.

The clinical utility is uncertain for many cancer genomic applications. Comparative effectiveness research (CER) can provide evidence to clarify this uncertainty. The aim of this study was to identify approaches to help stakeholders make evidence-based decisions and to describe potential challenges and opportunities in using CER to produce evidence-based guidance. We identified general CER approaches for genomic applications through literature review, the authors' experiences, and lessons learned from a recent, seven-site CER initiative in cancer genomic medicine. Case studies illustrate the use of CER approaches. Evidence generation and synthesis approaches used in CER include comparative observational and randomized trials, patient-reported outcomes, decision modeling, and economic analysis. Significant challenges to conducting CER in cancer genomics include the rapid pace of innovation, lack of regulation, and variable definitions and evidence thresholds for clinical and personal utility. Opportunities to capitalize on CER methods in cancer genomics include improvements in the conduct of evidence synthesis, stakeholder engagement, increasing the number of comparative studies, and developing approaches to inform clinical guidelines and research prioritization. CER offers a variety of methodological approaches that can address stakeholders' needs and help ensure an effective translation of genomic discoveries.

Teleconferencing for Virtual Visiting Professors and Virtual Grand Rounds.

SUMMARY: The 2020 global pandemic related to the coronavirus has led to unprecedented interruptions in typical patient care and resident education. Teleconferencing software was deployed by many institutions to comply with quarantine and social-distancing regulations. To supplement the loss of clinical experience for trainees, the authors implemented a novel virtual-educational programming using virtual visiting professors and virtual grand rounds. The authors describe the two different formats and advantages such as access to multiple speakers on diverse, innovative topics and decreased financial burdens to the host program. However, the authors do acknowledge some disadvantages from lack of face-to-face social interaction/networking and the need to consider time-zone differences. Both new programs were embraced by trainees at the authors' own institution and residents/medical students across the United States and Canada and around the world. The authors believe teleconferencing should be permanently incorporated into future educational opportunities for plastic surgeons, as it provides easy access to high-quality information.

Carpometacarpal 4/5 Fracture Dislocations: Fracture Morphology and Surgical Treatment.

We conducted a retrospective review of six patients with carpometacarpal (CMC) ⅘ fracture-dislocations managed with ORIF by a single surgeon between October 2006 and August 2017. An open, dorsal approach to the hamate was used with a combination of interfragmentary screw fixation and Kirschner wire reduction in the CMC joints. At a mean of 96 days follow-up (range: 31-265), all patients had recovered wrist motion, excellent grip strength, and complete resolution of pain. There were no complications or reoperations during the postoperative period. Radiographic review showed restoration of anatomy and well-maintained congruity of the CMC joints. Our study has shown favorable outcomes after open reduction and internal fixation of the hamate body fracture with interfragmentary screws, when combined with stabilization of the CMC dislocation with percutaneous Kirschner wires. Fracture morphology does not appear to guide choice for specific hardware (size screw, headed/headless) or use of a washer. This is a level IV, therapeutic study.

Nerve Diameter in the Hand: A Cadaveric Study.

BACKGROUND: Nerve injuries in the hand are common and often pose a challenge for the upper extremity surgeon. A range of reconstructive options exist for nerve repair, but proper matching of nerve diameter is important for many of these techniques. The purposes of this study were to (1) describe the nerve diameters of the hand and their relative differences and (2) investigate whether there is a relationship between nerve diameter and external hand dimensions or body mass index. METHODS: We utilized 18 freshly frozen cadaveric hands from adult donors aged 20-86 of both sexes for this study. Two independent observers measured each nerve diameter to the nearest 0.1 mm using a digital caliper. RESULTS: Using the flexor zones as boundaries, a total of 33 nerve measurements were performed for each cadaveric hand. Nerve diameter increased from the distal to the proximal flexor zones. The internal common digital nerves in flexor zone 3 were larger than the external digital nerves. The median nerve was found to be nearly 2 times larger than the ulnar nerve at 2 locations within the wrist. There was a positive correlation between body mass index, hand span, hand width, and nerve diameter at several measured locations. CONCLUSIONS: This study provides reference values for nerve diameters of the hand and wrist and describes their relative differences. It is important for surgeons to be aware of these differences and to consider this information as we advance our efforts to reconstruct the hand and develop technologies for nerve repair.

A Case-Control Study to Add Volumetric or Clinical Mammographic Density into the Tyrer-Cuzick Breast Cancer Risk Model.

BACKGROUND: Accurate breast cancer risk assessment for women attending routine screening is needed to guide screening and preventive interventions. We evaluated the accuracy of risk predictions from both visual and volumetric mammographic density combined with the Tyrer-Cuzick breast cancer risk model. METHODS: A case-control study (474 patient participants and 2243 healthy control participants) of women aged 40-79 years was performed using self-reported classical risk factors. Breast density was measured by using automated volumetric software and Breast Imaging and Reporting Data System (BI-RADS) density categories. Odds ratios (95% CI) were estimated by using logistic regression, adjusted for age, demographic factors, and 10-year risk from the Tyrer-Cuzick model, for a change from the 25th to 75th percentile of the adjusted percent density distribution in control participants (IQ-OR). RESULTS: After adjustment for classical risk factors in the Tyrer-Cuzick model, age, and body mass index (BMI), BI-RADS density had an IQ-OR of 1.55 (95% CI = 1.33 to 1.80) compared with 1.40 (95% CI = 1.21 to 1.60) for volumetric percent density. Fibroglandular volume (IQ-OR = 1.28, 95% CI = 1.12 to 1.47) was a weaker predictor than was BI-RADS density (Pdiff = 0.014) or volumetric percent density (Pdiff = 0.065). In this setting, 4.8% of women were at high risk (8% + 10-year risk), using the Tyrer-Cuzick model without density, and 7.1% (BI-RADS) compared with 6.8% (volumetric) when combined with density. CONCLUSION: The addition of volumetric and visual mammographic density measures to classical risk factors improves risk stratification. A combined risk could be used to guide precision medicine, through risk-adapted screening and prevention strategies.

Relemed: sentence-level search engine with relevance score for the MEDLINE database of biomedical articles.

BACKGROUND: Receiving extraneous articles in response to a query submitted to MEDLINE/PubMed is common. When submitting a multi-word query (which is the majority of queries submitted), the presence of all query words within each article may be a necessary condition for retrieving relevant articles, but not sufficient. Ideally a relationship between the query words in the article is also required. We propose that if two words occur within an article, the probability that a relation between them is explained is higher when the words occur within adjacent sentences versus remote sentences. Therefore, sentence-level concurrence can be used as a surrogate for existence of the relationship between the words. In order to avoid the irrelevant articles, one solution would be to increase the search specificity. Another solution is to estimate a relevance score to sort the retrieved articles. However among the >30 retrieval services available for MEDLINE, only a few estimate a relevance score, and none detects and incorporates the relation between the query words as part of the relevance score. RESULTS: We have developed "Relemed", a search engine for MEDLINE. Relemed increases specificity and precision of retrieval by searching for query words within sentences rather than the whole article. It uses sentence-level concurrence as a statistical surrogate for the existence of relationship between the words. It also estimates a relevance score and sorts the results on this basis, thus shifting irrelevant articles lower down the list. In two case studies, we demonstrate that the most relevant articles appear at the top of the Relemed results, while this is not necessarily the case with a PubMed search. We have also shown that a Relemed search includes not only all the articles retrieved by PubMed, but potentially additional relevant articles, due to the extended 'automatic term mapping' and text-word searching features implemented in Relemed. CONCLUSION: By using sentence-level matching, Relemed can deliver higher specificity, thus eliminating more false-positive articles. By introducing an appropriate relevance metric, the most relevant articles on which the user wishes to focus are listed first. Relemed also shrinks the displayed text, and hence the time spent scanning the articles.

Colo-colonic anastomosis in a continuous-flow left ventricular assist device patient.

Noncardiac operations are being increasingly performed on patients with left ventricular assist devices (LVADs). However, little is known on the impact of continuous-flow LVADs on the vascular supply of the colon for anastomoses. In this case, a 67-year-old male supported on an LVAD underwent four successful noncardiac operations including two intestinal anastomoses; left colon and small bowel anastomosis. To the best of our knowledge, no existing literature has reported successful colonic anastomosis on a continuous-flow LVAD. This case illustrates the plausibility of performing colonic anastomoses with appropriately selected patients supported on an LVAD. A 67-year-old male with congestive heart failure underwent LVAD placement for decompensated heart failure while awaiting orthotopic transplantation. During his recovery, he developed a stage IV sacral decubitus ulcer which required a sigmoid loop colostomy placement and a rotational flap. Subsequent stoma closure with partial sigmoid colectomy and stapled anastomosis was performed, and healed without evidence of anastomotic leak. This case illustrates the potential for colonic anastomoses for patients on continuous-flow LVAD support. Although oxygenation is known to be an important aspect of healing, this patient's outcome suggests that intestinal anastomoses can be performed on the induced pulseless environment of an LVAD. Further studies will be needed to further elucidate the success of longer segment resections and appropriate surgical candidates.

What Do Women Know About Breast Density? Results From a Population Survey of Virginia Women.

PURPOSE: Breast density reduces the sensitivity of mammography and is a moderate independent risk factor for breast cancer. Virginia is one of 24 states that currently require notification of patients when they have dense breasts. However, little is known about what women in the general population know about breast density. This survey study assessed knowledge about breast density and about its impact on mammography and breast cancer risk. METHODS: A random sample of 1024 Virginia women between ages 35 and 70 years without breast cancer, reached by landline and cell phone, who completed a 24-minute interview. Bivariate and multivariate analysis was performed. RESULTS: Thirty-six percent of respondents had been informed about their breast density. These women were more likely to be familiar with the term "breast density." Seventy-five percent of respondents reported being either somewhat or very familiar with risk factors for breast cancer, but <1% spontaneously listed breast density as a risk factor. About half of women who had a mammogram in the last year were aware of their breast density. Overall, only one in five women were aware that density reduces the sensitivity of mammography and only one in eight were aware that density increases breast cancer risk. Very few respondents (5.3%) were able to correctly answer three density knowledge questions. Lower-education, African-American, and Jewish women were less knowledgeable about breast density. CONCLUSIONS: Although women are becoming aware of the term "breast density," they may not understand its relationship to cancer detection on mammography and, especially, its relationship to breast cancer risk.

Impact of patient distance to radiation therapy on mastectomy use in early-stage breast cancer patients.

PURPOSE: Treatment access underlies quality cancer care. We hypothesize that mastectomy rates in a rural state are independently influenced by distance to radiation therapy (XRT) and by changing XRT access through opening new facilities. PATIENTS AND METHODS: Early-stage breast cancer patients diagnosed from 1996 to 2000 were identified in the Virginia state registry. Distance from patient zip code to nearest XRT facility was calculated with geographical software. Distance to XRT facility (< or = 10, > 10 to 25, > 25 to 50, and > 50 miles), American Joint Committee on Cancer tumor stage, age, race, and diagnosis year were evaluated for influencing mastectomy rate. Mastectomy use within 15 miles of five new facilities was assessed before and after opening. RESULTS: Among 20,094 patients, 43% underwent mastectomy, 53% underwent lumpectomy, and therapy of 4% of patients is unknown. Twenty-nine percent of patients lived more than 10 miles from XRT facility. Mastectomy increased with distance to XRT facility (43% at < or = 10 miles, 47% at > 10 to 25 miles, 53% at > 25 to 50 miles, and 58% at > 50 miles; P < .001). Among 11,597 patients with T1 (< 2 cm) tumors, mastectomy also varied by distance (31% at < or = 10 miles, 36% at > 10 to 25 miles, 41% at > 25 to 50 miles, and 49% at > 50 miles; P < .001). In multivariate analysis, mastectomy use was independently influenced by XRT distance after adjusting for age, race, T stage, and diagnosis year. Over the study period, mastectomy rates declined from 48% to 43% across Virginia, and there were similar declines in a 15-mile area around four new radiation facilities in urban settings. However, mastectomies decreased from 61% to 45% around a new XRT facility in a rural setting. CONCLUSION: Distance to XRT facility significantly impacts mastectomy use. Opportunities for increasing breast-conservation rates through improved XRT access exist.

Locating previously unknown patterns in data-mining results: a dual data- and knowledge-mining method.

BACKGROUND: Data mining can be utilized to automate analysis of substantial amounts of data produced in many organizations. However, data mining produces large numbers of rules and patterns, many of which are not useful. Existing methods for pruning uninteresting patterns have only begun to automate the knowledge acquisition step (which is required for subjective measures of interestingness), hence leaving a serious bottleneck. In this paper we propose a method for automatically acquiring knowledge to shorten the pattern list by locating the novel and interesting ones. METHODS: The dual-mining method is based on automatically comparing the strength of patterns mined from a database with the strength of equivalent patterns mined from a relevant knowledgebase. When these two estimates of pattern strength do not match, a high "surprise score" is assigned to the pattern, identifying the pattern as potentially interesting. The surprise score captures the degree of novelty or interestingness of the mined pattern. In addition, we show how to compute p values for each surprise score, thus filtering out noise and attaching statistical significance. RESULTS: We have implemented the dual-mining method using scripts written in Perl and R. We applied the method to a large patient database and a biomedical literature citation knowledgebase. The system estimated association scores for 50,000 patterns, composed of disease entities and lab results, by querying the database and the knowledgebase. It then computed the surprise scores by comparing the pairs of association scores. Finally, the system estimated statistical significance of the scores. CONCLUSION: The dual-mining method eliminates more than 90% of patterns with strong associations, thus identifying them as uninteresting. We found that the pruning of patterns using the surprise score matched the biomedical evidence in the 100 cases that were examined by hand. The method automates the acquisition of knowledge, thus reducing dependence on the knowledge elicited from human expert, which is usually a rate-limiting step.

Data mining and clinical data repositories: Insights from a 667,000 patient data set.

Clinical repositories containing large amounts of biological, clinical, and administrative data are increasingly becoming available as health care systems integrate patient information for research and utilization objectives. To investigate the potential value of searching these databases for novel insights, we applied a new data mining approach, HealthMiner, to a large cohort of 667,000 inpatient and outpatient digital records from an academic medical system. HealthMiner approaches knowledge discovery using three unsupervised methods: CliniMiner, Predictive Analysis, and Pattern Discovery. The initial results from this study suggest that these approaches have the potential to expand research capabilities through identification of potentially novel clinical disease associations.