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Most cited protocols related to «Physician Assistant»

1
Polypharmacy in Elderly Patients: A Review
In the first phase of this study, a literature review was conducted within OVID for original articles published between January 1997 and May 2007, using the following search terms and phrases: ‘polypharmacy,’ ‘elderly,’ ‘geriatrics,’ ‘inappropriate medication,’ and ‘multiple medication use.’ English language articles available in local holding which described ‘polypharmacy’ or the issue of the simultaneous use of multiple medications in elderly patients were evaluated. Discrete definitions of polypharmacy were identified and recorded.
Throughout the literature, numerous articles used the term ‘polypharmacy’ and the phrase ‘inappropriate drug use’ interchangeably. The research reported that methods most often used for identifying inappropriate drug use involved the use of criteria, primarily the criteria developed, and more recently revised, by Beers and colleagues (Beers 1997 (link); Fick et al 2003 (link)). The investigators adapted a list of inappropriate drugs from two primary sources for use in this study (Fick et al 2003 (link); Bressler and Bahl 2003 (link)). The medications used in this research were based upon the Beers’ criteria but were limited to those identified as “high risk” (see Table 2). This list is labeled as ‘potentially inappropriate,’ because we recognize that use of one or more of these agents in an older adult could be justified by specific circumstances, for example, if safer alternatives had been exhausted.
Two different definitions of polypharmacy were applied to the database, which consisted of outpatient medical record data randomly collected by physician assistant students at the time of patient encounters during supervised clinical training from August 2006 to May 2007. Polypharmacy was defined as either “use of at least one potentially inappropriate drug” (see Table 2) or “the presence of six or more concurrent medications”. The database included patient demographics (ie, age, gender, ethnicity, educational level, and marital status), vital signs, diagnoses, prescription medications, health-related quality of life, and disease-specific markers when applicable (ie, blood pressure, urine microalbumin, hemoglobin A1c, creatinine clearance, liver transaminases, estimated left ventricular ejection fraction, and others). These outpatient data were collected from more than 500 outpatient clinical sites throughout the state of South Carolina representing the following disciplines: family medicine, general internal medicine, pediatrics, general surgery, gynecology and obstetrics, emergency medicine, and internal medicine subspecialties. At the time of analysis the database contained 10,455 discrete patient entries, and the 1270 entries involving patients 65-years or older were selected for investigation.
Bushardt R.L., Massey E.B., Simpson T.W., Ariail J.C, & Simpson K.N. (2008). Polypharmacy: Misleading, but manageable. Clinical Interventions in Aging, 3(2), 383-389.
Publication 2008
Aged Beer Blood Pressure Creatinine Diagnosis Ethnicity Gender Hemoglobin A, Glycosylated Liver Outpatients Patients Pharmaceutical Preparations Physician Assistant Polypharmacy Prescription Drugs Safety Signs, Vital Student Transaminases Urine Ventricular Ejection Fraction
2
MIHG GWAS Parkinson's Disease Protocol
Samples in the MIHG GWAS include individuals with PD collected by one of 13 ascertainment centers in the PD Genetics Collaboration (Scott et al. 2001 (link)) or by the Morris K. Udall Parkinson Disease Center of Excellence (J.M. Vance, PI) ascertainment core. These participants were recruited by participating movement disorder and neurology clinics, referrals, and advertisements. Unaffected spouse and friend controls were recruited when available and willing to participate. All participants provided written informed consent, in accord with protocols established by institutional review boards at each center.
All individuals with PD were examined by a board-certified neurologist. A neurological exam and standard clinical evaluation was performed on all participants with PD. Affected individuals exhibited at least two cardinal symptoms of PD, e.g. bradykinesia, resting tremor, and rigidity and no other causes of Parkinsonism or atypical clinical features. Unaffected individuals had no symptoms of PD upon physical examination and self-reported symptom questionnaire (Rocca et al. 1998 (link)). Individuals were excluded if there was a history of encephalitis, neuroleptic therapy within one year before diagnosis, evidence of normal pressure hydrocephalus, or a clinical course with unusual features suggesting atypical or secondary Parkinsonism. Additionally, a blood sample, family history, medical history, and standard cognitive test (Blessed Orientation Memory Concentration (BOMC) (Katzman et al. 1983 (link)) test or Modified Mini Mental Status exam (3MS) (Folstein et al. 1975 (link))) were obtained for each individual. To ensure diagnostic consistency across sites, clinical data for all participants were reviewed by a panel consisting of a board-certified neurologist with fellowship training in movement disorders, a board certified neurologist and medical geneticist, and a certified physician assistant.
Edwards T.L., Scott W.K., Almonte C., Burt A., Powell E.H., Beecham G.W., Wang L., Züchner S., Konidari I., Wang G., Singer C., Nahab F., Scott B., Stajich J.M., Pericak-Vance M., Haines J., Vance J.M, & Martin E.R. (2010). Genome-wide association study confirms SNPs in SNCA and the MAPT region as common risk factors for Parkinson disease. Annals of human genetics, 74(2), 97-109.
Publication 2010
Antipsychotic Agents BLOOD Bradykinesia Cognitive Testing Diagnosis Encephalitis Ethics Committees, Research Fellowships Friend Genome-Wide Association Study Hydrocephalus, Normal Pressure Memory Mini Mental State Examination Movement Disorders Muscle Rigidity Neurologists Parkinson Disease Parkinsonian Disorders Physical Examination Physician Assistant Resting Tremor Secondary Parkinson Disease Spouse Therapeutics
3
Nursing Home Residents with Advanced Dementia: Longitudinal Study
Data on nursing home residents were collected from chart reviews, interviews with nurses, and brief physical examinations at baseline and once per quarter for up to 18 months; for residents who died during the study period, data were also collected within 14 days after the death. These data included sociodemographic characteristics, health status, clinical complications, distressing symptoms, burdensome interventions (hospitalization, emergency room visit, parenteral therapy, or tube feeding), and use of hospice care.
The sociodemographic data (from the baseline chart review) included information on age, sex, length of nursing home stay, race or ethnic group, marital status, and whether the resident lived in a special care unit for dementia. Data on health status included the underlying cause of dementia documented in the chart (Alzheimer’s disease, vascular dementia, or another cause), functional and cognitive status, and coexisting conditions. Functional status was quantified by nurses with the use of the Bedford Alzheimer’s Nursing Severity Subscale (on which scores range from 7 to 28, with higher scores indicating greater functional disability).16 (link) A brief cognitive examination included the Test for Severe Impairment (on which scores range from 0 to 24, with lower scores indicating greater impairment).17 (link)
All clinical complications occurring between assessments were determined from a chart review, including suspected pneumonia, febrile episodes, eating problems, and other sentinel events. If pneumonia was suspected, documentation by a physician, nurse practitioner, or physician assistant was required. Febrile episodes (exclusive of suspected pneumonia episodes) were defined according to temperature (oral, ≥37.8°C [100°F]; rectal, ≥38.3°C [101°F]; or axillary, ≥37.2°C [99°F]) and timing (at least once within a 7-day period, with more than one occurrence of fever recorded within 7 days considered to be a single episode). Eating problems included documentation of weight loss, swallowing or chewing problems, refusal to eat or drink, suspected dehydration, and persistently reduced oral intake. Other sentinel events were defined as acute medical conditions that had the potential to lead to a clinically significant change in health status (e.g., hip fracture).
Signs of pain and dyspnea as observed and documented by the residents’ care providers were quantified as follows: “none,” “rarely” (<5 days per month), “sometimes” (5 to 10 days per month), “often” (11 to 20 days per month), and “almost daily” (more than 20 days per month). These variables were dichotomized as none or rarely versus sometimes, often, or almost daily. Aspiration, agitated behavior, and pressure ulcers were documented on the basis of interviews with nurses. (For pressure ulcers, the number and stage — I through IV — were recorded18 and categorized as “any pressure ulcer stage II or greater” or “none or stage I only.”)
The exact dates on which residents underwent the following interventions were ascertained from charts: parenteral therapy (defined as intravenous or subcutaneous hydration or administration of intravenous or intramuscular antimicrobial agents), hospitalizations, emergency room visits, and tube feeding. Referral to hospice care was also determined as recorded on patient charts.
Data on health care proxies were collected at baseline and included information on age, sex, relationship to the resident, whether the proxy understood the type of clinical complications expected in advanced dementia, and whether a nursing home physician had informed the proxy of the prognosis or the clinical complications expected in advanced dementia. At each quarterly assessment, the health care proxy was asked whether he or she thought the resident had less than 6 months to live. Health care proxies were also asked to estimate the number of years since the diagnosis of dementia had been made.
Mitchell S.L., Teno J.M., Kiely D.K., Shaffer M.L., Jones R.N., Prigerson H.G., Volicer L., Givens J.L, & Hamel M.B. (2009). The Clinical Course of Advanced Dementia. The New England journal of medicine, 361(16), 1529-1538.
Publication 2009
Acute Disease Axilla Cognition Dehydration Dementia, Vascular Diagnosis Disabled Persons Dyspnea Ethnicity Fever Hip Fractures Hospice Care Hospitalization Hypodermoclysis Intravenous Infusion Microbicides Nurses Pain Parenteral Nutrition Physical Examination Physician Assistant Physicians Pneumonia Practitioner, Nurse Presenile Dementia Pressure Ulcer Prognosis Rectum Therapeutics
4
Field Survey of Diabetes Patients
This study was part of a larger project, the Vermont Diabetes Information System (VDIS), a cluster-randomized trial of a laboratory-based diabetes decision support system in a region-wide sample of 8808 adults with diabetes from 73 Primary Care practices in Vermont and nearby parts of the United States [7 (link)]. Primary care in these predominantly rural practices is provided by General Internists, Family Physicians, Physician Assistants, and Nurse Practitioners who provide the bulk of long-term care for these and other patients. There are few diabetes specialists in the region and most diabetes care is provided in the practices. All 119 eligible primary care practices near the thirteen participating hospitals were invited to participate [7 (link)]. The participating practices range in size from one provider (in 41 practices) to two practices with six providers each.
A field survey targeted at a sub-sample of subjects was designed to provide a better understanding of the non-laboratory features of the patients before intervention. Field survey subjects were selected at random from the patients participating in the VDIS and invited by telephone to participate in an in-home interview. Patient names were randomly sorted and patients contacted until a sample of approximately 15% of the patients from each practice agreed to an interview. We attempted to contact 4,209 patients and reached 1,576 (37%). Of these, 1,006 (64%) agreed to be interviewed.
Subjects who agreed were mailed a questionnaire and were scheduled for an interview by a trained field interviewer. During the visit, the interviewer reviewed any missing or ambiguous questionnaire items. If necessary, the interviewer read the questions aloud for subjects and recorded their responses for them. Then the interviewer measured the subject as described below and administered a few more instruments that were not included in the questionnaire. The interviews took place during the baseline phase of the study before any interventions were in place. All subjects provided written informed consent. The protocol was approved by the institutional review board of the University of Vermont.
Littenberg B, & MacLean C.D. (2006). Intra-cluster correlation coefficients in adults with diabetes in primary care practices: the Vermont Diabetes Information System field survey. BMC Medical Research Methodology, 6, 20.
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Publication 2006
Adult Diabetes Mellitus Dietary Fiber Ethics Committees, Research Interviewers Long-Term Care Patients Physician Assistant Physicians, Family Practitioner, Nurse Primary Health Care Specialists
5
Evaluating Discrepancies in ASA-PS Classification Across Clinics
After obtaining IRB approval, this single-center study was completed. Surgical scheduling software was queried for all patients >/= 65 years of age undergoing elective total hip or total knee replacements with surgical dates between 01 Jan 2015 and 31 Dec 2016 at a contemporary military treatment facility (MTF). A total of 303 patients were screened in the specified time period. These records were reviewed to eliminate emergent cases as well as to ensure that the patients had visited both the internal medicine preoperative clinic and the preoperative anesthetic unit (PAU). The resulting 177 records were reviewed of which 101 records were assigned an ASA-PS classification by both the medicine preoperative clinic and the PAU clinic (Table 2). These were included in the data analysis (Fig. 1).

ASA-PS classification distribution by clinic

MedicineAnesthesia PAUAnesthesia DOS
1001
2665149
3324950
4311

Consort diagram

At our institution, surgeons and anesthesia providers can make referrals to the internal medicine preoperative clinic based on clinical judgment. There is no algorithm that establishes which patients would benefit from additional resources in the form of an internal medicine preoperative visit. There is a stratification process in which the surgeons can determine who completes a PAU clinic visit versus who can bypass the PAU. Bypass is reserved for ASA-PS 1 and 2 patients. These patients are contacted telephonically by the PAU to determine if there are any outstanding issues that may need to be addressed by a PAU visit. The surgeons can refer ASA-PS 1 and ASA-PS 2 to the PAU based on their preference or if the surgeon believes they would benefit from seeing an anesthesia provider prior to the day of surgery. The order in which these visits occur is variable as the appointments are booked by the patient. The ASA-PS classification used in this study was the ASA-PS classification assigned following the initial encounter by both the PAU and the internal medicine clinic (Table 3).

ASA-PS class by PAU provider

ProviderNumberPercent
NP2727
PA2323
SRNA44
Staff CRNA3939
Anes resident55
Staff physician22
For these records, the ASA classification from each visit as well as the day of surgery (DOS) ASA-PS class recorded by the anesthesia provider completing the case were collected. Supplemental data including age, BMI, gender, tobacco use, alcohol use, drug use, cardiac risk score, exercise tolerance (measured in metabolic equivalents), identified medical comorbidities, current medications, preoperative EKGs, additional preoperative cardiac study results, and preoperative pulmonary function test results were also collected (Table 4).

ASA-PS class by DOS provider

ProviderNumberPercent
SRNA1111.1
Staff CRNA2626.3
Anes resident4040.4
Staff physician2222.2
The outcome measures noted were the ASA-PS classification assigned by the internal medicine clinic provider, the ASA-PS classification assigned by the PAU clinic provider, and the ASA-PS classification assigned on the DOS by the anesthesia provider. There is no formal training in assigning an ASA-PS classification in our internal medicine department. Training is provided to PAU providers that are not anesthesia trained, specifically the Nurse Practioners and the Physician Assistants that see patients in the clinic.
Data analysis software was used to perform the following analyses [SPSS v22.0 (IBM Corp. Released 2013. IBM SPSS Statistics for Windows, Version 22.0. Armonk, NY: IBM Corp)]. To assess the overall disagreement between the data sets, a McNemar test was completed with the following pairings: medicine and PAU, medicine and DOS, and PAU and DOS. To assess the overall agreement between the data sets, kappa statistics along with 95% confidence intervals were calculated for the aforementioned pairings (Table 5).

McNemar and Kappa statistic

Medicine versus PAUMedicine versus DOSDOS versus PAU
Kappa CI: (LB, UB)0.170 (− 0.001, 0.340)p = 0.0570.156 (− 0.015, 0.327)p = 0.0790.863 (0.696, 1.030)p = 0.000
McNemar6.769 (p = 0.034)7.400 (p = 0.025)0.143 (p = 0.705)
Knuf K.M., Maani C.V, & Cummings A.K. (2018). Clinical agreement in the American Society of Anesthesiologists physical status classification. Perioperative Medicine, 7, 14.
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Publication 2018
4-azidosalicylic acid-phosphatidylserine Anesthesia Anesthetics Clinical Reasoning Clinic Visits Electrocardiogram Exercise Tolerance Gender Heart Knee Replacement Arthroplasty Metabolic Equivalent Military Personnel Nurses Operative Surgical Procedures Patients Pharmaceutical Preparations Physician Assistant Surgeons Surgery, Day Tests, Pulmonary Function

Most recents protocols related to «Physician Assistant»

1
Cross-sectional Survey of German Physician Assistants
This study was a cross-sectional survey study conducted from May to July 2020 using the online survey tool SoSci Survey (43 ). The link to the survey was distributed to PAs working in Germany through the snowball system and by the German University Association for Physician Assistants (DHPA, Deutscher Hochschulverband Physician Assistant e.V.). For snowball sampling, the link to the survey was sent to the working email address of the PA network of the authors and DHPA. In addition, participating PAs were asked to further distribute the link within their network of colleagues.
Participation in the survey was voluntary, and the study participants could have ended the survey at any time and did not belong to a vulnerable group. The data were handled in accordance with the local data protection regulations and were not shared with a third party. Study participants did not receive any compensation for their participation in the survey study. The study was approved by the ethics committee of the HSD University of Applied Sciences, Germany (BEth_54_222). Study participants had no time limit to answer the questionnaire and the time for answering the questionnaire varied between 5 and 8 min.
Treusch Y., Möckel L, & Kohlstedt K. (2023). Working conditions, authorizations, mental health, and job satisfaction of physician assistants in Germany. Frontiers in Public Health, 11, 1082463.
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Publication 2023
9-(2,3-dihydroxypropyl)adenine Ethics Committees Physician Assistant
2
Rheumatology Healthcare Provider Guidelines
These consensus-based and evidence-based points to consider were developed for individual rheumatologists or groups of rheumatologists (eg, in a hospital). They were designed to be applicable across different healthcare systems. For the development of the points to consider, we used the EULAR standardised operating procedure for recommendations10 (link) and the additional EULAR guidance on methodology.11 Of note, where the word ‘rheumatologist’ is used, the task force means any rheumatology healthcare provider prescribing b/tsDMARDs, including among others rheumatology trainees, and in some countries also nurse specialists and physician assistants. For the definition of cost-effectiveness, we used an adapted version of the NICE definition: ‘Guideline recommendations should be based on the estimated costs of the interventions or services in relation to their expected health benefits (that is, their “cost-effectiveness”), rather than on the total cost or resource impact of implementing them’.7
van der Togt C.J., Van den Bemt B., Aletaha D., Alten R., Chatzidionysiou K., Galloway J., Isaac J., Mulleman D., Verschueren P., Vulto A.G., Welsing P.M., Verhoef L, & den Broeder A.A. (2023). Points to consider for cost-effective use of biological and targeted synthetic DMARDs in inflammatory rheumatic diseases: results from an umbrella review and international Delphi study. RMD Open, 9(1), e002898.
Publication 2023
Health Personnel Nurse Specialists Physician Assistant Rheumatologist
3
Assessing Physicians' Knowledge and Attitudes on Aortic Emergencies in China
Using the survey tool “So Jump” [20 ], three authors (X.L, Z.D, and Z.H) drafted a questionnaire (see eAppendix in the Supplement) based on their own extensive experience treating AE and researching the disease within numerous published projects [5 (link)–7 (link), 21 –23 ]. They aligned the questionnaire content to the Chinese Expert Consensus on AE Management [2 ]. The content validity and test-retest reliability of the knowledge section of this questionnaire were assessed (see eTable1 and eMethods in the Supplement) [24 (link)]. The correlation coefficients were 1.0 for content validity and 0.9 for test-retest reliability. The questionnaire contained three parts (Part A, Part B and Part C). More detailed description of the questionnaire can be seen in the eMethods in the supplement. Additional description of terms and definitions used on the survey are explained as follow [25 ]:
House physician: primary title, practice under the guidance and supervision of the attending physician or above.
Attending physician: middle job title, higher than the house physician, lower than the assistant director physician.
Assistant director physician: vice-senior title, equivalent to associate professor, higher than the attending physician, lower than the director physician.
Director physician: senior title, equivalent to professor.
In China, all hospitals are classified into 3 levels: primary, secondary, and tertiary [26 ]. Primary hospitals (primary level, < 100 beds normally) aim to provide basic public health services and consulting for their residents. Secondary (moderate level, 101–500 beds normally) and tertiary (high level, ≥ 500 beds normally) hospitals provide specialized care. In addition, the tertiary hospitals could be divided to academic tertiary hospitals and non-academic tertiary hospitals. Clinicians working in academic tertiary hospitals have duty of conducting clinical/basic research, teaching and tutoring in addition to daily clinical work.
Li A., Guo K., Liu X., Gong X., Li X., Zhou D, & Hong Z. (2023). Limitations on knowledge of autoimmune encephalitis and barriers to its treatment among neurologists: a survey from western China. BMC Neurology, 23, 99.
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Publication 2023
Chinese Dietary Supplements Physician Assistant Physicians Supervision Vision
4
Evaluating U-Sleep on Sleep Staging
In all our experiments we evaluate U-Sleep as stated in11 . The model scores the full PSG, without considering the predicted class on a segment with a label different from the five sleep stages (e.g., segment labeled as ’UNKNOWN’ or as ’MOVEMENT’). The final prediction is the results of all the possible combinations of the available EEG and EOG channels for each PSG. Hence, we use the majority vote, i.e., the ensemble of predictions given by the multiple combination of channels in input.
The unweighted F1-score metric59 (link) is computed on all the testing sets to evaluate the performance of the model on all the experiments. We compute the F1-score for all the five classes, we then combine them by calculating the unweighted mean. Note that the unweighted F1-scores reduce the absolute scores due to lower performance on less abundant classes such as sleep stage N1. For this reason, we also report in Supplementary Table 10, Supplementary Table 11, and Supplementary Table 12 the results achieved in terms of weighted F1-score - i.e., the metric is weighted by the number of true instances for each label, so as to consider the high imbalance between the sleep stages. In that case, the absolute scores significantly increases on all the experiments. In Supplementary Table 10, Supplementary Table 11, and Supplementary Table 12 we also report the Cohen’s kappa metric, given its valuable property of correcting the chance of agreement between the automatic sleep scoring algorithm, i.e., overall predicted sleep stages, and the ground truth, i.e., the sleep labels given by the physicians.
* The Bern Sleep Data Base BSDB registry usage was ethically approved in the framework of the E12034 - SPAS (Sleep Physician Assistant System) Eurostar-Horizon 2020 program (Kantonale Ethikkommission Bern, 2020-01094).
Fiorillo L., Monachino G., van der Meer J., Pesce M., Warncke J.D., Schmidt M.H., Bassetti C.L., Tzovara A., Favaro P, & Faraci F.D. (2023). U-Sleep’s resilience to AASM guidelines. NPJ Digital Medicine, 6, 33.
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Publication 2023
Movement Physician Assistant Physicians Sleep Sleep Stages
5
Integrated Care Program for Knee Arthroplasty Patients
The development of the care program under study involved various steps, including a systematic review with meta-analysis [14 (link)], focus groups with total knee arthroplasty patients [26 ], and a Delphi study with orthopaedic surgeons, physiotherapists, occupational physicians and a physician assistant [27 (link)] to develop the algorithms for the ikHerstel app.
Our systematic review showed that integrated care programs consisting of one or a combination of: an active referral to a case-manager, a patient tailored rehabilitation program using goal setting and/or eHealth, showed small effects on work- and/or sports participation post-surgery [14 (link)]. Moreover, previous studies by our research group showed positive effects on societal participation of integrated care programs with similar intervention elements among other patient populations, such as low back pain patients [28 (link), 29 (link)] and gynaecological or abdominal surgery patients [30 (link)–32 (link)]. For the gynaecological and abdominal surgery patients, an eHealth intervention using the ikHerstel app was developed to support and advise them during their post-operative course. This app was previously found to be effective for returning to daily life activities, where patients in the intervention group returned to daily (work) activities 5–13 days earlier than those in the usual care group [30 (link)–32 (link)]. Because of the promising effectiveness results of the ikHerstel app, we have further developed this care program according to the wishes and preferences of knee arthroplasty patients with focus groups and an algorithm that was developed in a Delphi study [26 , 27 (link)]. In the latter study, with an expert panel including orthopaedic surgeons, physiotherapists, occupational physicians and an orthopaedic physician assistant, we have developed uniform and multidisciplinary recommendations for the resumption of daily life activities after knee arthroplasty [27 (link)]. The recommendations were implemented in our smartphone ikHerstel app. Moreover, an activity tracker was linked to the ikHerstel app to enhance resumption of physical activity [33 (link)–35 (link)]. Goal attainment scaling was added to the intervention, given the promising results on satisfaction with occupational and leisure time physical activities among younger knee arthroplasty patients [36 (link), 37 (link)].
Based on the above, in the ACTIVE trial, patients will receive an intervention consisting of three components: 1) a personalized eHealth intervention (the ikHerstel app) including an activity tracker, consisting of a mobile phone app available for Android and Apple devices, 2) goal setting using goal attainment scaling to improve rehabilitation and 3) a referral to a case-manager to secure and oversee an adequate start of the pre- and postoperative care. As our target population is patients of relatively young (< 67 years) age, we expect that an app will make our intervention more approachable for them. The protocol timeline for the enrolment and intervention components is outlined in Table 1.

Protocol timeline

Straat A.C., Maarleveld J.M., Smit D.J., Visch L., Hulsegge G., Huirne J.A., van Dongen J.M., van Geenen R.C., Kerkhoffs G.M., Anema J.R., Coenen P, & Kuijer P.P. (2023). (Cost-)effectiveness of a personalized multidisciplinary eHealth intervention for knee arthroplasty patients to enhance return to activities of daily life, work and sports – rationale and protocol of the multicentre ACTIVE randomized controlled trial. BMC Musculoskeletal Disorders, 24, 162.
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Publication 2023
Abdomen Case Manager Knee Replacement Arthroplasty Low Back Pain Medical Devices Operative Surgical Procedures Orthopedic Surgeons Patients Physical Examination Physical Therapist Physician Assistant Physicians Postoperative Care Program Development Rehabilitation Satisfaction Target Population Telehealth TimeLine Youth

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More about "Physician Assistant"

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