Delivery of Cervical and Colorectal Cancer Screenings During the Pandemic in Community Health Centers: Practice Changes and Recovery Strategies.

BACKGROUND: The coronavirus disease 2019 pandemic led to clinical practice changes, which affected cancer preventive care delivery. OBJECTIVES: To investigate the impact of the coronavirus disease 2019 pandemic on the delivery of colorectal cancer (CRC) and cervical cancer (CVC) screenings. RESEARCH DESIGN: Parallel mixed methods design using electronic health record data (extracted between January 2019 and July 2021). Study results focused on 3 pandemic-related periods: March-May 2020, June-October 2020, and November 2020-September 2021. SUBJECTS: Two hundred seventeen community health centers located in 13 states and 29 semistructured interviews from 13 community health centers. MEASURES: Monthly up-to-date CRC and CVC screening rates and monthly rates of completed colonoscopies, fecal immunochemical test (FIT)/fecal occult blood test (FOBT) procedures, Papanicolaou tests among age and sex-eligible patients. Analysis used generalized estimating equations Poisson modeling. Qualitative analysts developed case summaries and created a cross-case data display for comparison. RESULTS: The results showed a reduction of 75% for colonoscopy [rate ratio (RR) = 0.250, 95% CI: 0.224-0.279], 78% for FIT/FOBT (RR = 0.218, 95% CI: 0.208-0.230), and 87% for Papanicolaou (RR = 0.130, 95% CI: 0.125-0.136) rates after the start of the pandemic. During this early pandemic period, CRC screening was impacted by hospitals halting services. Clinic staff moved toward FIT/FOBT screenings. CVC screening was impacted by guidelines encouraging pausing CVC screening, patient reluctance, and concerns about exposure. During the recovery period, leadership-driven preventive care prioritization and quality improvement capacity influenced CRC and CVC screening maintenance and recovery. CONCLUSIONS: Efforts supporting quality improvement capacity could be key actionable elements for these health centers to endure major disruptions to their care delivery system and to drive rapid recovery.

How Does Prior Experience Pay Off in Large-Scale Quality Improvement Initiatives?

INTRODUCTION: To examine the association of prior investment on the effectiveness of organizations delivering large-scale external support to improve primary care. METHODS: Mixed-methods study of 7 EvidenceNOW grantees (henceforth, Cooperatives) and their recruited practices (n = 1720). Independent Variable: Cooperatives's experience level prior to EvidenceNOW, defined as a sustained track record in delivering large-scale quality improvement (QI) to primary care practices (high, medium, or low). Dependent Variables: Implementation of external support, measured as facilitation dose; effectiveness at improving (1) clinical quality, measured as practices' performance on Aspirin, Blood Pressure, Cholesterol, and Smoking (ABCS); and (2) practice capacity, measured using the Adaptive Reserve (AR) score and Change Process Capacity Questionnaire (CPCQ). Data were analyzed using multivariable linear regressions and a qualitative inductive approach. RESULTS: Cooperatives with High (vs low) levels of prior experience with and investment in large-scale QI before EvidenceNOW recruited more geographically dispersed and diverse practices, with lower baseline ABCS performance (differences ranging from 2.8% for blood pressure to 41.5% for smoking), delivered more facilitation (mean=+20.3 hours, P = .04), and made greater improvements in practices' QI capacity (CPCQ: +2.04, P < .001) and smoking performance (+6.43%, P = .003). These Cooperatives had established networks of facilitators at the start of EvidenceNOW and leadership experienced in supporting this workforce, which explained their better recruitment, delivery of facilitation, and improvement in outcomes. DISCUSSION: Long-term investment that establishes regionwide organizations with infrastructure and experience to support primary care practices in QI is associated with more consistent delivery of facilitation support, and greater improvement in practice capacity and some clinical outcomes.

Effective Facilitator Strategies for Supporting Primary Care Practice Change: A Mixed Methods Study.

PURPOSE: Practice facilitation is an evidence-informed implementation strategy to support quality improvement (QI) and aid practices in aligning with best evidence. Few studies, particularly of this size and scope, identify strategies that contribute to facilitator effectiveness. METHODS: We conducted a sequential mixed methods study, analyzing data from EvidenceNOW, a large-scale QI initiative. Seven regional cooperatives employed 162 facilitators to work with 1,630 small or medium-sized primary care practices. Main analyses were based on facilitators who worked with at least 4 practices. Facilitators were defined as more effective if at least 75% of their practices improved on at least 1 outcome measure-aspirin use, blood pressure control, smoking cessation counseling (ABS), or practice change capacity, measured using Change Process Capability Questionnaire-from baseline to follow-up. Facilitators were defined as less effective if less than 50% of their practices improved on these outcomes. Using an immersion crystallization and comparative approach, we analyzed observational and interview data to identify strategies associated with more effective facilitators. RESULTS: Practices working with more effective facilitators had a 3.6% greater change in the mean percentage of patients meeting the composite ABS measure compared with practices working with less effective facilitators (P <.001). More effective facilitators cultivated motivation by tailoring QI work and addressing resistance, guided practices to think critically, and provided accountability to support change, using these strategies in combination. They were able to describe their work in detail. In contrast, less effective facilitators seldom used these strategies and described their work in general terms. Facilitator background, experience, and work on documentation did not differentiate between more and less effective facilitators. CONCLUSIONS: Facilitation strategies that differentiate more and less effective facilitators have implications for enhancing facilitator development and training, and can assist all facilitators to more effectively support practice changes.

How Does Prior Experience Pay Off in Large-Scale Quality Improvement Initiatives?

INTRODUCTION: To examine the association of prior investment on the effectiveness of organizations delivering large-scale external support to improve primary care. METHODS: Mixed-methods study of 7 EvidenceNOW grantees (henceforth, Cooperatives) and their recruited practices (n = 1720). Independent Variable: Cooperatives's experience level prior to EvidenceNOW, defined as a sustained track record in delivering large-scale quality improvement (QI) to primary care practices (high, medium, or low). Dependent Variables: Implementation of external support, measured as facilitation dose; effectiveness at improving (1) clinical quality, measured as practices' performance on Aspirin, Blood Pressure, Cholesterol, and Smoking (ABCS); and (2) practice capacity, measured using the Adaptive Reserve (AR) score and Change Process Capacity Questionnaire (CPCQ). Data were analyzed using multivariable linear regressions and a qualitative inductive approach. RESULTS: Cooperatives with High (vs low) levels of prior experience with and investment in large-scale QI before EvidenceNOW recruited more geographically dispersed and diverse practices, with lower baseline ABCS performance (differences ranging from 2.8% for blood pressure to 41.5% for smoking), delivered more facilitation (mean=+20.3 hours, P = .04), and made greater improvements in practices' QI capacity (CPCQ: +2.04, P < .001) and smoking performance (+6.43%, P = .003). These Cooperatives had established networks of facilitators at the start of EvidenceNOW and leadership experienced in supporting this workforce, which explained their better recruitment, delivery of facilitation, and improvement in outcomes. DISCUSSION: Long-term investment that establishes regionwide organizations with infrastructure and experience to support primary care practices in QI is associated with more consistent delivery of facilitation support, and greater improvement in practice capacity and some clinical outcomes.

The Effects of Major Disruptions on Practice Participation in Facilitation During a Primary Care Quality Improvement Initiative.

BACKGROUND: Disruptions in primary care practices, like ownership change, clinician turnover, and electronic health record system implementation, can stall quality improvement (QI) efforts. However, little is known about the relationship between these disruptions and practice participation in facilitated QI. METHODS: We explore this relationship using data collected from EvidenceNOW in a mixed-methods convergent design. EvidenceNOW was a large-scale facilitation-based QI initiative in small and medium primary care practices. Data included practice surveys, facilitator time logs, site visit field notes, and interviews with facilitators and practices. Using multivariate regression, we examined associations between disruptions during interventions and practice participation in facilitation, measured by in-person facilitator hours in 987 practices. We analyzed qualitative data on 40 practices that described disruptions. Qualitative and quantitative teams iterated analyses based on each other's emergent findings. RESULTS: Many practices (51%) reported experiencing 1 or more disruptions during the 3- to 15-month interventions. Loss of clinicians (31.6%) was most prevalent. In adjusted analyses, disruptions were not significantly associated with participation in facilitation. Qualitative data revealed that practices that continued active participation were motivated, had some QI infrastructure, and found value in working with their facilitators. Facilitators enabled practice participation by doing EHR-related work for practices, adapting work for available staff, and helping address needs beyond the explicit aims of EvidenceNOW. CONCLUSIONS: Disruptions are prevalent in primary care, but practices can continue participating in QI interventions, particularly when supported by a facilitator. Facilitators may benefit from additional training in approaches for helping practices attenuate the effects of disruptions and adapting strategies to help interventions work to continue building QI capacity.

How Type of Practice Ownership Affects Participation with Quality Improvement External Facilitation: Findings from EvidenceNOW.

BACKGROUND: Facilitation is an implementation strategy that can help primary care practices improve healthcare quality and build quality improvement (QI) capacity when delivered in a flexible manner by trained professionals. Practice ownership is associated with use of QI. However, little is known about how practices of different ownership participate in external facilitation, and this could inform future initiatives. OBJECTIVE: Using data from EvidenceNOW, we examined how practice ownership influences participation in external facilitation. STUDY DESIGN: We used an iterative mixed-methods design. PARTICIPANTS, APPROACH, AND MEASURES: We collected data from practices on practice characteristics (e.g., location, size, payer mix) and ownership type via surveys and from facilitators on the number of hours, encounters, and months each practice had with a facilitator via facilitation logs. Using multivariable linear regression, we examined the association between facilitation and ownership (n = 1117 practices). We conducted semi-structured interviews with EvidenceNOW leadership (n = 12) and facilitators (n = 51) and observed facilitators in a subset of practices (n = 64); we analyzed this qualitative data for patterns of facilitation. KEY RESULTS: In the fully adjusted model, differences by ownership were non-significant; FQHCs, however, had significantly less participation in facilitation than clinician-owned practices across two measures (unadjusted difference: - 2.83, p < 0.01 for number of encounters, and - 2.04, p < 0.01 for number of months with encounters). Qualitative data showed that Health System and FQHC ownership influenced types of practices enrolled in EvidenceNOW, and suggested that in these practices lower autonomy and greater complexity compared to clinician-owned ownership influenced facilitation participation patterns. CONCLUSIONS: Practice ownership shaped how but not how much practices participated in external facilitation. This finding highlights the importance of tailoring facilitation approaches based on ownership-related characteristics in future QI initiatives.

Effectiveness of an insurance enrollment support tool on insurance rates and cancer prevention in community health centers: a quasi-experimental study.

BACKGROUND: Following the ACA, millions of people gained Medicaid insurance. Most electronic health record (EHR) tools to date provide clinical-decision support and tracking of clinical biomarkers, we developed an EHR tool to support community health center (CHC) staff in assisting patients with health insurance enrollment documents and tracking insurance application steps. The objective of this study was to test the effectiveness of the health insurance support tool in (1) assisting uninsured patients gaining insurance coverage, (2) ensuring insurance continuity for patients with Medicaid insurance (preventing coverage gaps between visits); and (3) improving receipt of cancer preventive care. METHODS: In this quasi-experimental study, twenty-three clinics received the intervention (EHR-based insurance support tool) and were matched to 23 comparison clinics. CHCs were recruited from the OCHIN network. EHR data were linked to Medicaid enrollment data. The primary outcomes were rates of uninsured and Medicaid visits. The secondary outcomes were receipt of recommended breast, cervical, and colorectal cancer screenings. A comparative interrupted time-series using Poisson generalized estimated equation (GEE) modeling was performed to evaluate the effectiveness of the EHR-based tool on the primary and secondary outcomes. RESULTS: Immediately following implementation of the enrollment tool, the uninsured visit rate decreased by 21.0% (Adjusted Rate Ratio [RR] = 0.790, 95% CI = 0.621-1.005, p = .055) while Medicaid-insured visits increased by 4.5% (ARR = 1.045, 95% CI = 1.013-1.079) in the intervention group relative to comparison group. Cervical cancer preventive ratio increased 5.0% (ARR = 1.050, 95% CI = 1.009-1.093) immediately following implementation of the enrollment tool in the intervention group relative to comparison group. Among patients with a tool use, 81% were enrolled in Medicaid 12 months after tool use. For the 19% who were never enrolled in Medicaid following tool use, most were uninsured (44%) at the time of tool use. CONCLUSIONS: A health insurance support tool embedded within the EHR can effectively support clinic staff in assisting patients in maintaining their Medicaid coverage. Such tools may also have an indirect impact on evidence-based practice interventions, such as cancer screening. TRIAL REGISTRATION: This study was retrospectively registered on February 4th, 2015 with Clinicaltrials.gov (#NCT02355262). The registry record can be found at https://www.clinicaltrials.gov/ct2/show/NCT02355262 .

Implementation and adoption of a health insurance support tool in the electronic health record: a mixed methods analysis within a randomized trial.

BACKGROUND: In addition to delivering vital health care to millions of patients in the United States, community health centers (CHCs) provide needed health insurance outreach and enrollment support to their communities. We developed a health insurance enrollment tracking tool integrated within the electronic health record (EHR) and conducted a hybrid implementation-effectiveness trial in a CHC-based research network to assess tool adoption using two implementation strategies. METHODS: CHCs were recruited from the OCHIN practice-based research network. Seven health center systems (23 CHC clinic sites) were recruited and randomized to receive basic educational materials alone (Arm 1), or these materials plus facilitation (Arm 2) during the 18-month study period, September 2016-April 2018. Facilitation consisted of monthly contacts with clinic staff and utilized audit and feedback and guided improvement cycles. We measured total and monthly tool utilization from the EHR. We conducted structured interviews of CHC staff to assess factors associated with tool utilization. Qualitative data were analyzed using an immersion-crystallization approach with barriers and facilitators identified using the Consolidated Framework for Implementation Research. RESULTS: The majority of CHCs in both study arms adopted the enrollment tool. The rate of tool utilization was, on average, higher in Arm 2 compared to Arm 1 (20.0% versus 4.7%, p < 0.01). However, by the end of the study period, the rate of tool utilization was similar in both arms; and observed between-arm differences in tool utilization were largely driven by a single, large health center in Arm 2. Perceived relative advantage of the tool was the key factor identified by clinic staff as driving tool utilization. Implementation climate and leadership engagement were also associated with tool utilization. CONCLUSIONS: Using basic education materials and low-intensity facilitation, CHCs quickly adopted an EHR-based tool to support critical outreach and enrollment activities aimed at improving access to health insurance in their communities. Though facilitation carried some benefit, a CHC's perceived relative advantage of the tool was the primary driver of decisions to implement the tool. TRIAL REGISTRATION: ClinicalTrials.gov: NCT02355262, Posted February 4, 2015.

Dedicated Workforce Required to Support Large-Scale Practice Improvement.

BACKGROUND: Facilitation is an effective approach for helping practices implement sustainable evidence-based practice improvements. Few studies examine the facilitation infrastructure and support needed for large-scale dissemination and implementation initiatives. METHODS: The Agency for Health care Research and Quality funded 7 Cooperatives, each of which worked with over 200 primary care practices to rapidly disseminate and implement improvements in cardiovascular preventive care. The intervention target was to improve primary care practice capacity for quality initiative and the ABCS of cardiovascular disease prevention: aspirin in high-risk individuals, blood pressure control, cholesterol management, and smoking cessation. We identified the organizational elements and infrastructures Cooperatives used to support facilitators by reviewing facilitator logs, online diary data, semistructured interviews with facilitators, and fieldnotes from facilitator observations. We analyzed these data using a coding and sorting process. RESULTS: Each Cooperative partnered with 2 to 16 organizations, piecing together 16 to 35 facilitators, often from other quality improvement projects. Quality assurance strategies included establishing initial and ongoing training, processes to support facilitators, and monitoring to assure consistency and quality. Cooperatives developed facilitator toolkits, implemented initiative-specific training, and developed processes for peer-to-peer learning and support. CONCLUSIONS: Supporting a large-scale facilitation workforce requires creating an infrastructure, including initial training, and ongoing support and monitoring, often borrowing from other ongoing initiatives. Facilitation that recognizes the need to support the vital integrating functions of primary care might be more efficient and effective than this fragmented approach to quality improvement.

Effects of Practice Turnover on Primary Care Quality Improvement Implementation.

Primary care practices often engage in quality improvement (QI) in order to stay current and meet quality benchmarks, but the extent to which turnover affects practices' QI ability is not well described. The authors examined qualitative data from practice staff and external facilitators participating in a large-scale QI initiative to understand the relationship between turnover and QI efforts. The examination found turnover can limit practices' ability to engage in QI activities in various ways. When a staff member leaves, remaining staff often absorb additional responsibilities, and QI momentum slows as new staff are trained or existing staff are reengaged. Turnover alters staff dynamics and can create barriers to constructive working relationships and team building. When key practice members leave, they can take with them institutional memory about QI purpose, processes, and long-term vision. Understanding how turnover affects QI may help practices, and those helping them with QI, manage the disruptive effects of turnover.

Characterization of essential oil distribution in the root cross-section of Valeriana officinalis L. s.l. by using histological imaging techniques.

BACKGROUND: The essential oil is an important compound of the root and rhizome of medicinally used valerian (Valeriana officinalis L. s.l.), with a stated minimum content in the European pharmacopoeia. The essential oil is located in droplets, of which the position and distribution in the total root cross-section of different valerian varieties, root thicknesses and root horizons are determined in this study using an adapted fluorescence-microscopy and automatic imaging analysis method. The study was initiated by the following facts:A probable negative correlation between essential oil content and root thickness in selected single plants (elites), observed during the breeding of coarsely rooted valerian with high oil content.Higher essential oil content after careful hand-harvest and processing of the roots. RESULTS: In preliminary tests, the existence of oil containing droplets in the outer and inner regions of the valerian roots was confirmed by histological techniques and light-microscopy, as well as Fourier-transform infrared spectroscopy. Based on this, fluorescence-microscopy followed by image analysis of entire root cross-sections, showed that a large number of oil droplets (on average 43% of total oil droplets) are located close to the root surface. The remaining oil droplets are located in the inner regions (parenchyma) and showed varying density gradients from the inner to the outer regions depending on genotype, root thickness and harvesting depth. CONCLUSIONS: Fluorescence-microscopy is suitable to evaluate prevalence and distribution of essential oil droplets of valerian in entire root cross-sections. The oil droplet density gradient varies among genotypes. Genotypes with a linear rather than an exponential increase of oil droplet density from the inner to the outer parenchyma can be chosen for better stability during post-harvest processing. The negative correlation of essential oil content and root thickness as observed in our breeding material can be counteracted through a selection towards generally high oil droplet density levels, and large oil droplet sizes independent of root thickness.

Feasibility of Using a Community-Supported Agriculture Program to Increase Access to and Intake of Vegetables among Federally Qualified Health Center Patients.

OBJECTIVE: This study explored the feasibility of using a 23-week subsidized community-supported agriculture program to increase access to and intake of vegetables among Federally Qualified Health Center patients. METHODS: Outcomes were measured using pre-post intervention surveys (n = 9). Process data were collected in post-intervention surveys and focus groups (n = 15). RESULTS: Most participants (77%) indicated that the program improved their health and all (100%) reported that they were eating a greater variety of vegetables because of their participation in the program. Three themes emerged from the focus groups: increased access to fresh and/or organic vegetables, improved diet quality, and the importance of social support during the program. CONCLUSIONS AND IMPLICATIONS: Linking subsided community-supported agriculture programs with Federally Qualified Health Centers has the potential to increase access to and intake of vegetables among low-income patients. However, further research is needed with a larger sample size and a more robust study design.

Evolution of POMC: origin, phylogeny, posttranslational processing, and the melanocortins.

The proopiomelanocortin (POMC) gene was most likely derived from an ancestral opioid-coding gene following the 1R chordate genome duplication event. During the radiation of the jawless fish, the POMC organization plan emerged multiple melanocortin sequences (α-MSH/ACTH and ß-MSH) and a C-terminally extended opioid sequence (ß-endorphin). Following the 2R genome duplication event, the γ-MSH sequence was gained. Among the jawed vertebrates, three distinct trends in the evolution of the POMC gene are apparent: the gain of the δ-MSH sequence (cartilaginous fish), the loss of the γ-MSH sequence (ray-finned fish), and the retention of the post 2R POMC organization plan (lobe-finned fish/tetrapods). POMC is synthesized in the pituitary gland and in neurons of the hypothalamus, where an array of posttranslational processing mechanisms, such as endoproteolytic cleavage and N-acetylation, generate distinct sets of end-products in these tissues. A striking feature of the melanocortin end-products is the rigorous conservation of the primary sequence of α-MSH and the first 25 amino acids of ACTH.

Technical problems and complications in the removal of the less invasive stabilization system.

OBJECTIVES: This study was designed to evaluate the frequency of intraoperative problems and complications involved with Less Invasive Stabilization System (LISS) plate removal. DESIGN: Retrospective study. SETTING: Single academic level I trauma center. METHODS: Medical records were reviewed for demographics, surgical technique, plate length, number and position of screws, time from internal fixation to plate removal, reason for removal, operating time for removal, and perioperative complications. Pre- and post-op radiographs were also reviewed to confirm plate and screw positions. The independent factors including age, sex, plate site, plate screws placed/available holes, union status, and time from internal fixation to removal were compared between patients in whom screw removal was complicated to those in whom screw removal proceeded without difficulty. Mann-Whitney and Fisher Exact tests were calculated with the level of significance at P < 0.05. RESULTS: There were 33 patients (24 men and 9 women) that underwent LISS plate removal from 36 extremities (15 tibias and 21 femurs). The average time from internal fixation to removal was 13.2 months. The plates removed were 13-hole plates (16 cases), 9-hole plates (18 cases), and 5-hole plates (2 cases), which included a total of 349 screws. The specific reasons for plate removal were symptomatic implants after bone union (21 cases), nonunion requiring additional fixation (12 cases), early loss of fixation (2 cases), and a peri-implant fracture after bone union (1 case). The average operating time for plate removal was 71.3 minutes (range, 28-180 minutes). Five cases required more than 120 minutes. Difficulty with screw removal was encountered in 37 screws (10.6%) from 14 cases (38.9%). Two plates and 11 screw heads required cutting using a carbide or diamond tipped burr. Six cases required tearing the plate off bone by levering with a total of 10 screws still attached. Five screws were cut using a large bolt cutter. The other screws were stripped and removed with a stripped screw removal tap. Two patients developed a postoperative superficial wound infection that required treatment with oral antibiotics. One patient had a postoperative peroneal nerve palsy that recovered spontaneously. There were no statistical differences in predictors for patients with screw removal difficulty. CONCLUSIONS: Difficulty with removal due to cold welding or screw head stripping is common in locking LISS plate screws. LISS plate removal can often require prolonged operating time and the use of specialized removal tools. Surgeons should anticipate the possibility of difficulties when removing these implants and be appropriately prepared.

Combined injuries of the pelvis and acetabulum: nature of a devastating dyad.

OBJECTIVES: To describe the clinical characteristics of combined injuries of the pelvis and acetabulum, which have not been previously described. We hypothesize that this combination of injuries affects not only the postinjury hemodynamics of the patient, but the outcome of subsequent acetabular fracture treatment. DESIGN: Retrospective study. SETTING: Level I trauma center. METHODS: The data collected included patient demographics, fracture classification, Injury Severity Score, systolic blood pressure on arrival, amount of packed red blood cells transfused, time to operation, perioperative complications, and radiographic outcomes. Age- and sex-matched control groups of patients with pure pelvic fractures and pure acetabular fractures were compared with the combined injury group to assess injury severity characteristics. To determine the independent factors influencing the postoperative residual displacement of the acetabulum, multiple linear regression analysis was used. RESULTS: Between January 1, 1998, and December 31, 2007, there were 1612 patients with either pelvic or acetabular fractures requiring admission to our institution, of which 82 (5.1%) had the combination of an unstable pelvic injury (Orthopaedic Trauma Association [OTA] 61 Types B/C) and a displaced acetabular fracture (OTA 62). Eighty-two patients with an isolated unstable pelvic injury and 82 patients with an isolated displaced acetabular fracture were chosen from the same study period to act as control groups. Patients in the combined group were significantly more injured as compared with the displaced acetabular fracture control group with regard to Injury Severity Score (P < 0.001), systolic blood pressure (P < 0.001), and packed red blood cells (P < 0.001). In the combined group, the most common pelvic fracture patterns were OTA 61.B1 and B2. Transverse-type acetabular fractures patterns (OTA 62.B1 and B2) accounted for 61.2% of all acetabular fractures in the combined group. The most frequent injury combination was a transverse-type acetabular fracture with an associated ipsilateral anterior disruption of the sacroiliac joint. Sixty-eight patients underwent surgical intervention at a mean time of 5.7 days. The mean postoperative displacement of acetabular fracture reduction was 2.2 mm as evaluated by radiographs. Multiple regression analysis revealed that the amount of postoperative posterior pelvic displacement, Type B2 acetabular fractures, and patient age were significant predictors of the amount of residual acetabular displacement found postoperatively. CONCLUSION: Patients with combined pelvic and acetabular fractures represent a serious injury that includes the resuscitative challenges of pelvic injuries coupled with the difficulties of precise reduction of acetabular fractures. To obtain optimal reduction of the acetabulum, initial accurate reduction of the posterior pelvic lesion appears to be necessary.

Modeling the evolution of the MC2R and MC5R genes: studies on the cartilaginous fish, Heterondotus francisci.

Comparative studies support the hypothesis that the proliferation of melanocortin receptor genes (MCRs) in gnathostomes corresponds to the 2R hypothesis for the radiation of gene families in Phylum Chordata. This mini-review will initially focus on the distribution of MCRs in cartilaginous fish and the relationship between the shark MC5R gene and the proposed ancestral MC5R/2R gene. This section will be followed by the results of recent studies on the features of the ligand binding site common to all melanocortin receptors. These data will provide the background for a set of hypotheses to explain the unique ligand selectivity of the MC2 receptor in teleosts and tetrapods.

Tracking the evolution of the proenkephalin gene in tetrapods.

In gnathostomes there is remarkable consistency in the organization of the proenkephalin gene. This opioid precursor encodes seven opioid (YGGF) sequences: five pentapeptide sequences, a met-enkephalin-7 sequence and a met-enkephalin-8 sequence. Yet, within vertebrate lineages there can be distinct sets of pentapeptide opioids (YGGFM or YGGFL). In the Sarcopterygii, the sixth opioid position in lungfishes and anuran amphibian proenkephalin genes encodes a met-enkephalin (YGGFM) sequence. However, in mammalian proenkephalin there is a leu-enkephalin (YGGFL) sequence at this position. This study was done to test the hypothesis that the presence of the leu-enkephalin sequence in mammals is a feature common to amniote vertebrates, but not present in anamniote vertebrates. To resolve this issue, proenkephalin cDNAs were cloned from the urodele amphibians, Amphiuma means and Necturus maculosus, and two amniote vertebrates, the turtle, Chrysemys scripta, and the brown snake, Storeria dekayi. As predicted, a met-enkephalin sequence is present at the sixth opioid position in urodele amphibians; whereas, a leu-enkephalin sequence is present at this opioid site in the reptile proenkephalin sequences. These data are consistent with the conclusion that the transition from a met-enkephalin sequence to a leu-enkephalin sequence at the sixth opioid position in tetrapod proenkephalins occurred in the ancestral proto-reptiles. Phylogenetic analyses, using the Maximum Parsimony and Neighbor-Joining algorithms, of the amphibian proenkephalin sequences supported the position that anuran and urodele amphibians are a monophyletic assemblage. The same analysis of reptile-related proenkephalin sequences, including the deduced amino acid sequence of a partially characterized alligator proenkephalin cDNA, could not conclusively resolve the phylogeny of the major reptilian orders.

Analyzing the evolution of beta-endorphin post-translational processing events: studies on reptiles.

In many cartilaginous fishes, most ray-finned fishes, lungfishes, and amphibians, the post-translational processing of POMC includes the monobasic cleavage of beta-endorphin to yield an opioid that is eight to ten amino acids in length. The amino acid motif within the beta-endorphin sequence required for a monobasic cleavage event is -E-R-(S/G)-Q-. Mammals and birds lack this motif and as a result beta-endorphin(1-8) is a not an end-product in either group. Since both mammals and birds were derived from ancestors with reptilian origins, an analysis of beta-endorphin sequences from extant groups of reptiles should provide insights into the manner in which beta-endorphin post-translational processing mechanisms have evolved in amniotes. To this end a POMC cDNA was cloned from the pituitary of the turtle, Chrysemys scripta. The beta-endorphin sequence in this species was compared to other reptile beta-endorphin sequences (i.e., Chinese soft shell turtle and gecko) and to known bird and mammal sequences. This analysis indicated that either the loss of the arginine residue at the cleavage site (the two turtle species, chick, and human) or a substitution at the glutamine position in the consensus sequence (gecko and ostrich) would account for the loss of the monobasic cleavage reaction in that species. Since amphibians are capable of performing the beta-endorphin monobasic reaction, it would appear that the amino acid substitutions that eliminated this post-translational process event in reptilian-related tetrapods must have occurred in the ancestral amniotes.