Unnecessary Neuroimaging for Patients With Primary Headaches

Rationale for issuing neuroimaging requests for patients with primary headaches in China

OBJECTIVE

To investigate the prevalence of neuroimaging in patients with primary headaches and the clinician-based rationale for requesting neuroimaging in China.

DATA SOURCES AND STUDY SETTING

This study included patients with primary headaches admitted to hospitals and clinicians in China. We identified whether neuroimaging was requested and the types of neuroimaging conducted.

STUDY DESIGN

This was a cross-sectional study, and convenience sampling was used to recruit patients with primary headaches. Clinicians were interviewed using a combination of personal in-depth and topic-selection group interviews to explore why doctors requested neuroimaging.

DATA COLLECTION

We searched for the diagnosis of primary headache in the outpatient and inpatient systems according to the International Classification of Diseases-10 code of patients admitted to six hospitals in three provincial capitals by 2022.We selected three public and three private hospitals with neurology specialties that treated a corresponding number of patients.

PRINCIPLE FINDINGS

Among the 2263 patients recruited for this study, 1942 (89.75%) underwent neuroimaging. Of the patients, 1157 (51.13%) underwent magnetic resonance imaging (MRI), 246 (10.87%) underwent both head computed tomography (CT) and MRI, and 628 (27.75%) underwent CT. Fifteen of the 16 interviewed clinicians did not issue a neuroimaging request for patients with primary headaches. Furthermore, we found that doctors issued a neuroimaging request for patients with primary headaches mostly, to exclude the risk of misdiagnosis, reduce uncertainty, avoid medical disputes, meet patients' medical needs, and complete hospital assessment indicators.

CONCLUSIONS

For primary headaches, the probability of clinicians requesting neuroimaging was higher in China than in other countries. There is considerable room for improvement in determining appropriate strategies to reduce the use of low-value care for doctors and patients.

Utility of cranial MRI in non-traumatic headache patients with prior negative head CT within 1 month

AIM

To investigate the importance of additional cranial magnetic resonance imaging (cMRI) in non-traumatic headache patients with a prior negative head computed tomography (CT) examination within 1 month.

MATERIALS AND METHODS

This retrospective study analysed 162 adult patients with non-traumatic headache who underwent cMRI within 1 month of a negative initial head CT at the emergency department (ED). The diagnostic yield and false-referral rate were analysed according to the revisit duration (early [≤1 week] versus late [>1-4 weeks] revisits), patient care settings (ED versus outpatient clinics [OPC]), and clinical variables. Subsequent patient management change (PMC), such as admission and treatment (AT) or outpatient clinic treatment (OT), were also investigated.

RESULTS

The overall diagnostic yield of cMRI was 17.3% (28/162) and the false-referral rate was 1.2% (2/162). The diagnostic yield of cMRI was significantly different according to the patient care settings (ED, 24.7% [21/85] versus OPC, 9.1% [7/77]; p=0.02). The diagnostic yield was highest in the ED-early-revisit group (25.4% [18/71]), 45% (9/20) in those with systemic signs, and 46.7% (14/30) in those with symptom change. Among patients with positive cMRI findings, 90% (27/30) received AT and 3.3% (1/30) received OT. Among OPC-revisit-negative cMRI patients, PMC occurred in 0% (0/50).

CONCLUSION

The diagnostic yield of cMRI was relatively high for headache patients who revisited the ED earlier, especially in those with systemic signs or symptom change. Most positive cMRI cases experienced PMC. Negative cMRI in OPC-revisit patients might help clarify the benign nature of a condition.

Verification of a clinical decision support system for the diagnosis of headache disorders based on patient-computer interactions: a multi-center study

BACKGROUND

Although headache disorders are common, the current diagnostic approach is unsatisfactory. Previously, we designed a guideline-based clinical decision support system (CDSS 1.0) for diagnosing headache disorders. However, the system requires doctors to enter electronic information, which may limit widespread use.

METHODS

In this study, we developed the updated CDSS 2.0, which handles clinical information acquisition via human-computer conversations conducted on personal mobile devices in an outpatient setting. We tested CDSS 2.0 at headache clinics in 16 hospitals in 14 provinces of China.

RESULTS

Of the 653 patients recruited, 18.68% (122/652) were suspected by specialists to have secondary headaches. According to "red-flag" responses, all these participants were warned of potential secondary risks by CDSS 2.0. For the remaining 531 patients, we compared the diagnostic accuracy of assessments made using only electronic data firstly. In Comparison A, the system correctly recognized 115/129 (89.15%) cases of migraine without aura (MO), 32/32 (100%) cases of migraine with aura (MA), 10/10 (100%) cases of chronic migraine (CM), 77/95 (81.05%) cases of probable migraine (PM), 11/11 (100%) cases of infrequent episodic tension-type headache (iETTH), 36/45 (80.00%) cases of frequent episodic tension-type headache (fETTH), 23/25 (92.00%) cases of chronic tension-type headache (CTTH), 53/60 (88.33%) cases of probable tension-type headache (PTTH), 8/9 (88.89%) cases of cluster headache (CH), 5/5 (100%) cases of new daily persistent headache (NDPH), and 28/29 (96.55%) cases of medication overuse headache (MOH). In Comparison B, after combining outpatient medical records, the correct recognition rates of MO (76.03%), MA (96.15%), CM (90%), PM (75.29%), iETTH (88.89%), fETTH (72.73%), CTTH (95.65%), PTTH (79.66%), CH (77.78%), NDPH (80%), and MOH (84.85%) were still satisfactory. A patient satisfaction survey indicated that the conversational questionnaire was very well accepted, with high levels of satisfaction reported by 852 patients.

CONCLUSIONS

The CDSS 2.0 achieved high diagnostic accuracy for most primary and some secondary headaches. Human-computer conversation data were well integrated into the diagnostic process, and the system was well accepted by patients. The follow-up process and doctor-client interactions will be future areas of research for the development of CDSS for headaches.

ACR Appropriateness Criteria® Headache: 2022 Update

Headache is an ancient problem plaguing a large proportion of the population. At present, headache disorders rank third among the global causes of disability, accounting for over $78 billion per year in direct and indirect costs in the United States. Given the prevalence of headache and the wide range of possible etiologies, the goal of this document is to help clarify the most appropriate initial imaging guidelines for headache for eight clinical scenarios/variants, which range from acute onset, life-threatening etiologies to chronic benign scenarios. The American College of Radiology Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed annually by a multidisciplinary expert panel. The guideline development and revision process support the systematic analysis of the medical literature from peer reviewed journals. Established methodology principles such as Grading of Recommendations Assessment, Development, and Evaluation or GRADE are adapted to evaluate the evidence. The RAND/UCLA Appropriateness Method User Manual provides the methodology to determine the appropriateness of imaging and treatment procedures for specific clinical scenarios. In those instances where peer reviewed literature is lacking or equivocal, experts may be the primary evidentiary source available to formulate a recommendation.

Pediatric Migraines: A Comprehensive Review and Perspectives on Diagnosis and Treatment

Pediatric migraine (PM) is one of the most prevalent neurological disorders in children. It has numerous variants and the sufferers often present to emergency departments with a wide variety of signs and symptoms that make diagnosis difficult. The trend in diagnosing and managing PM cases remain suboptimal despite the comprehensive diagnostic criteria and various therapeutic options. In this review, we discuss PM, provide an approach to the diagnosis, and describe the various available management options. However, the diagnosis of migraine is based on history and physical examination; no specific diagnostic test is available. The main management aspects are acute pain relief, prevention, and identifying triggering factors.

Primary Headache Approach in the Emergency Departments: A Systematic Scoping Review of Prospective Studies

This systematic scoping review aims to answer questions related to the main characteristics of primary headache, the need for neuroimaging, and the presence of red flags in these patients. A review of prospective studies including the MEDLINE/PubMed, Scopus, LILACS, and SCIELO databases, as well as the grey literature, was conducted. The methodological quality of the selected investigations was also assessed. Six investigations met the selection criteria. The mean age of people with primary headache was less than 43 years, with ages ranging from 39 to 46 years. Most of the studies reported the presence of nausea/vomiting, between 12% and 60% of the patients studied. To a lesser extent, there was also the presence of intense and moderate pain, loss of consciousness, stiff neck, presence of aura, and photophobia. The most frequent diagnoses were unspecified headache, migraine, and tension headache. The studies did not recommend neuroimaging and no red flags were reported. Primary headache occurred more frequently in women, in those under 46 years of age with a history of migraine and similar episodes. Moreover, the presence of red flags and the need for neuroimaging in patients with primary headaches were not evidenced.

Characterizing and quantifying low-value diagnostic imaging internationally: a scoping review

BACKGROUND

Inappropriate and wasteful use of health care resources is a common problem, constituting 10-34% of health services spending in the western world. Even though diagnostic imaging is vital for identifying correct diagnoses and administrating the right treatment, low-value imaging-in which the diagnostic test confers little to no clinical benefit-is common and contributes to inappropriate and wasteful use of health care resources. There is a lack of knowledge on the types and extent of low-value imaging. Accordingly, the objective of this study was to identify, characterize, and quantify the extent of low-value diagnostic imaging examinations for adults and children.

METHODS

A scoping review of the published literature was performed. Medline-Ovid, Embase-Ovid, Scopus, and Cochrane Library were searched for studies published from 2010 to September 2020. The search strategy was built from medical subject headings (Mesh) for Diagnostic imaging/Radiology OR Health service misuse/Medical overuse OR Procedures and Techniques Utilization/Facilities and Services Utilization. Articles in English, German, Dutch, Swedish, Danish, or Norwegian were included.

RESULTS

A total of 39,986 records were identified and, of these, 370 studies were included in the final synthesis. Eighty-four low-value imaging examinations were identified. Imaging of atraumatic pain, routine imaging in minor head injury, trauma, thrombosis, urolithiasis, after thoracic interventions, fracture follow-up and cancer staging/follow-up were the most frequently identified low-value imaging examinations. The proportion of low-value imaging varied between 2 and 100% inappropriate or unnecessary examinations.

CONCLUSIONS

A comprehensive list of identified low-value radiological examinations for both adults and children are presented. Future research should focus on reasons for low-value imaging utilization and interventions to reduce the use of low-value imaging internationally.

SYSTEMATIC REVIEW REGISTRATION

PROSPERO: CRD42020208072.

Genetics, pathophysiology, diagnosis, treatment, management, and prevention of migraine

Migraine is a neurological ailment that is characterized by severe throbbing unilateral headache and associated with nausea, photophobia, phonophobia and vomiting. A full and clear mechanism of the pathogenesis of migraine, though studied extensively, has not been established yet. The current available information indicates an intracranial network activation that culminates in the sensitization of the trigemino-vascular system, release of inflammatory markers, and initiation of meningeal-like inflammatory reaction that is sensed as headache. Genetic factors might play a significant role in deciding an individual's susceptibility to migraine. Twin studies have revealed that a single gene polymorphism can lead to migraine in individuals with a monogenic migraine disorder. In this review, we describe recent advancements in the genetics, pathophysiology, diagnosis, treatment, management, and prevention of migraine. We also discuss the potential roles of genetic and abnormal factors, including some of the metabolic triggering factors that result in migraine attacks. This review will help to accumulate current knowledge about migraine and understanding of its pathophysiology, and provides up-to-date prevention strategies.

Headache in the neurology clinic: a 2-year audit

BACKGROUND

Headache is the most common reason for referral to neurology outpatient clinics in Ireland and represents approximately 30% of all new appointments.

AIM

To evaluate diagnoses and outcomes of all patients newly referred with headache to a consultant neurologist at an Irish university teaching hospital over a 2-year period.

DESIGN

A retrospective analysis and audit.

METHODS

Data including patient demographics, red flags, investigations, diagnosis, and outcome were collected on consecutive patients newly referred with headache to a consultant neurologist's outpatient clinic over a 2-year period.

RESULTS

Two hundred and seventy patients with headache were seen; 75% were women with mean age of 39 years. 89.26% (241/270) were diagnosed with a primary headache disorder alone; 4.44% (12/270) with a secondary headache disorder alone; 3.33% (9/270) with both a primary and secondary headache disorders; and 2.96% (8/270) with a painful cranial neuropathy. Migraine was the most common diagnosis, frequently associated with medication overuse. Non-attendance rates were high. Although imaging abnormalities were frequently found, on no occasion was it thought to be the cause of the headache.

CONCLUSIONS

Most patients referred to a neurology outpatient clinic with headache have a primary headache disorder. Alternate pathways should be considered to reduce the burden on Ireland's limited neurology resources without compromising patient safety.

Automatic migraine classification using artificial neural networks

Background: Previous studies of migraine classification have focused on the analysis of brain waves, leading to the development of complex tests that are not accessible to the majority of the population. In the early stages of this pathology, patients tend to go to the emergency services or outpatient department, where timely identification largely depends on the expertise of the physician and continuous monitoring of the patient. However, owing to the lack of time to make a proper diagnosis or the inexperience of the physician, migraines are often misdiagnosed either because they are wrongly classified or because the disease severity is underestimated or disparaged. Both cases can lead to inappropriate, unnecessary, or imprecise therapies, which can result in damage to patients' health. Methods: This study focuses on designing and testing an early classification system capable of distinguishing between seven types of migraines based on the patient's symptoms. The methodology proposed comprises four steps: data collection based on symptoms and diagnosis by the treating physician, selection of the most relevant variables, use of artificial neural network models for automatic classification, and selection of the best model based on the accuracy and precision of the diagnosis. Results: The artificial neural network models used provide an excellent classification performance, with accuracy and precision levels >97% and which exceed the classifications made using other model, such as logistic regression, support vector machines, nearest neighbor, and decision trees. Conclusions: The implementation of migraine classification through artificial neural networks is a powerful tool that reduces the time to obtain accurate, reliable, and timely clinical diagnoses.

Automatic migraine classification using artificial neural networks

Background: Previous studies of migraine classification have focused on the analysis of brain waves, leading to the development of complex tests that are not accessible to the majority of the population. In the early stages of this pathology, patients tend to go to the emergency services or outpatient department, where timely identification largely depends on the expertise of the physician and continuous monitoring of the patient. However, owing to the lack of time to make a proper diagnosis or the inexperience of the physician, migraines are often misdiagnosed either because they are wrongly classified or because the disease severity is underestimated or disparaged. Both cases can lead to inappropriate, unnecessary, or imprecise therapies, which can result in damage to patients' health. Methods: This study focuses on designing and testing an early classification system capable of distinguishing between seven types of migraines based on the patient's symptoms. The methodology proposed comprises four steps: data collection based on symptoms and diagnosis by the treating physician, selection of the most relevant variables, use of artificial neural network models for automatic classification, and selection of the best model based on the accuracy and precision of the diagnosis. Results: The neural network models used provide an excellent classification performance, with accuracy and precision levels >97% and which exceed the classifications made using other model, such as logistic regression, support vector machines, nearest neighbor, and decision trees. Conclusions: The implementation of migraine classification through neural networks is a powerful tool that reduces the time to obtain accurate, reliable, and timely clinical diagnoses.

Neuroimaging for Migraine: The American Headache Society Systematic Review and Evidence-Based Guideline

OBJECTIVE

To provide updated evidence-based recommendations about when to obtain neuroimaging in patients with migraine.

METHODS

Articles were included in the systematic review if they studied adults 18 and over who were seeking outpatient treatment for any type of migraine and who underwent neuroimaging (MRI or CT). Medline, Web of Science, and Cochrane Clinical Trials were searched from 1973 to August 31, 2018. Reviewers identified studies, extracted data, and assessed the quality of the evidence in duplicate. We assessed study quality using the Newcastle-Ottawa Scale.

RESULTS

The initial search yielded 2269 publications. Twenty three articles met inclusion criteria and were included in the final review. The majority of studies were retrospective cohort or cross-sectional studies. There were 4 prospective observational studies. Ten studies evaluated the utility of CT only, 9 MRI only, and 4 evaluated both. Common abnormalities included chronic ischemia or atrophy with CT and MRI scanning, and non-specific white matter lesions with MRI. Clinically meaningful abnormalities requiring intervention were relatively rare. Clinically significant neuroimaging abnormalities in patients with headaches consistent with migraine without atypical features or red flags appeared no more common than in the general population.

RECOMMENDATIONS

There is no necessity to do neuroimaging in patients with headaches consistent with migraine who have a normal neurologic examination, and there are no atypical features or red flags present. Grade A Neuroimaging may be considered for presumed migraine for the following reasons: unusual, prolonged, or persistent aura; increasing frequency, severity, or change in clinical features, first or worst migraine, migraine with brainstem aura, migraine with confusion, migraine with motor manifestations (hemiplegic migraine), late-life migraine accompaniments, aura without headache, side-locked headache, and posttraumatic headache. Most of these are consensus based with little or no literature support. Grade C.