Diagnostic Checklist Research Articles

Initial development of a digitally based comprehensive child mental health questionnaire.

The present report describes the item development and initial validation of a comprehensive child mental health questionnaire through a series of four studies. To maximize clinical utility, the questionnaire was developed to directly reflect Diagnostic and Statistical Manual of Mental Disorders, fifth edition psychiatric criteria and diagnoses, cover all mental health conditions that present in youth, and capitalize on the benefits of digital administration, particularly tiered branching logic. Study 1 describes the item generation and development of a tiered item structure. Study 2 established internal consistency and discriminant validity in a representative community sample of 1,000 youth aged 7-17 and a parent. Study 3 examined the acceptability of the questionnaire's content and structure to families and made indicated text revisions. Finally, Study 4 cross validated the internal consistency and tiered structure of a revised version of the questionnaire in a second representative normative sample of 1,000 parent and child dyads. The four studies resulted in a questionnaire consisting of one general mental health question (parent-report only), 16 items (for both parent and child) on a diagnostic category checklist, and 40 scales with screener and follow-up items reflecting DSM-5 criteria for specific disorders (371 parent items and 326 child items). The data support the potential of the questionnaire to efficiently assess the breadth of youth psychiatric symptoms efficiently. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Measurement of Cardiothoracic Ratio on Chest X-rays Using Artificial Intelligence-A Systematic Review and Meta-Analysis.

Background: Chest X-rays (CXRs) are pivotal in clinical diagnostics, particularly in assessing cardiomegaly through the cardiothoracic ratio (CTR). This systematic review and meta-analysis evaluate the efficacy of artificial intelligence (AI) in automating CTR determination to enhance patient care and streamline diagnostic processes. They are concentrated on comparing the performance of AI models in determining the CTR against human assessments, identifying the most effective models for potential clinical implementation. This study was registered with PROSPERO (no. CRD42023437459). No funding was received. Methods: A comprehensive search of medical databases was conducted in June 2023. The search strategy adhered to the PICO framework. Inclusion criteria encompassed original articles from the last decade focusing on AI-assisted CTR assessment from standing-position CXRs. Exclusion criteria included systematic reviews, meta-analyses, conference abstracts, paediatric studies, non-original articles, and studies using imaging techniques other than X-rays. After initial screening, 117 articles were reviewed, with 14 studies meeting the final inclusion criteria. Data extraction was performed by three independent investigators, and quality assessment followed PRISMA 2020 guidelines, using tools such as the JBI Checklist, AMSTAR 2, and CASP Diagnostic Study Checklist. Risk of bias was assessed according to the Cochrane Handbook guidelines. Results: Fourteen studies, comprising a total of 70,472 CXR images, met the inclusion criteria. Various AI models were evaluated, with differences in dataset characteristics and AI technology used. Common preprocessing techniques included resizing and normalization. The pooled AUC for cardiomegaly detection was 0.959 (95% CI 0.944-0.975). The pooled standardized mean difference for CTR measurement was 0.0353 (95% CI 0.147-0.0760). Significant heterogeneity was found between studies (I2 89.97%, p < 0.0001), with no publication bias detected. Conclusions: Standardizing methodologies is crucial to avoid interpretational errors and advance AI in medical imaging diagnostics. Uniform reporting standards are essential for the further development of AI in CTR measurement and broader medical imaging applications.

Artificial intelligence/machine learning for neuroimaging to predict hemorrhagic transformation: Systematic review/meta-analysis.

Early and reliable prediction of hemorrhagic transformation (HT) in patients with acute ischemic stroke (AIS) is crucial for treatment decisions and early intervention. The purpose of this study was to conduct a systematic review and meta-analysis on the performance of artificial intelligence (AI) and machine learning (ML) models that utilize neuroimaging to predict HT. A systematic search of PubMed, EMBASE, and Web of Science was conducted until February 19, 2024. Inclusion criteria were as follows: patients with AIS who received reperfusion therapy; AI/ML algorithm using imaging to predict HT; or presence of sufficient data on the predictive performance. Exclusion criteria were as follows: articles with less than 20 patients; articles lacking algorithms that operate solely on images; or articles not detailing the algorithm used. The quality of eligible studies was assessed using the Quality Assessment of Diagnostic Accuracy Studies-2 and Checklist for Artificial Intelligence in Medical Imaging. Pooled sensitivity, specificity, and diagnostic odds ratio (DOR) were calculated using a random-effects model, and a summary receiver operating characteristic curve was constructed using the Reitsma method. We identified six eligible studies, which included 1640 patients. Aside from an unclear risk of bias regarding flow and timing identified in two of the studies, all studies showed low risk of bias and applicability concerns in all categories. Pooled sensitivity, specificity, and DOR were.849,.878, and 45.598, respectively. AI/ML models can reliably predict the occurrence of HT in AIS patients. More prospective studies are needed for subgroup analyses and higher clinical certainty and usefulness.

A Critical Examination of the Clinical Diagnosis of Functional Tic-like Behaviors.

Since the COVID-19 pandemic, movement disorder clinics have seen an increase in patients with an unusual type of tic-like symptoms: young adults with abrupt onset complex behaviors. It was quickly suspected that these patients suffered from functional neurological symptoms, later named Functional Tic-Like Behaviors (FTLB). Subsequent research on the differential diagnosis between FTLB and tics has been substantial and led to the development of diagnostic checklists. We conducted a theoretical reappraisal of the FTLB literature to clarify the validity of the concept and its diagnostic implications. This paper addresses several key aspects of the current FTLB literature: circular reasoning, the complications of the FTLB phenomenology and demographics, the impact of FTLB on tic literature at large, and issues with alignment of the FTLB concept with the diagnostic criteria for functional disorders. The clinical approach to FTLB might involve circular reasoning due to a lack of clinical benchmarks. The FTLB phenomenology and demographics may need more work to ensure a lack of bias and a proper description of this patient group including a clear distinction from tics. The impact of the FTLB discussion on the wider literature needs consideration. The validation of positive signs may help with both these endeavors and pave way to the inclusion of FTLB within psychiatric classification systems. Furthermore, the coexistence of FTLB and tics within the same patient needs to be addressed. More research may be needed to fully establish the diagnosis of FTLB and differentiate it from tics.

Design and validation of a diagnostic suspicion checklist to differentiate epileptic from psychogenic nonepileptic seizures (PNES-DSC)

ObjectivePsychogenic non-epileptic seizures (PNES) are complex clinical manifestations and misdiagnosis as status epilepticus remains high, entailing deleterious consequences for patients. Video-electroencephalography (vEEG) remains the gold-standard method for diagnosing PNES. However, time and economic constraints limit access to vEEG, and clinicians lack fast and reliable screening tools to assist in the differential diagnosis with epileptic seizures (ES). This study aimed to design and validate the PNES-DSC, a clinically based PNES diagnostic suspicion checklist with adequate sensitivity (Se) and specificity (Sp) to discriminate PNES from ES. MethodsA cross-sectional study with 125 patients (n = 104 drug-resistant epilepsy; n = 21 PNES) admitted for a vEEG protocolised study of seizures. A preliminary PNES-DSC (16-item) was designed and used by expert raters blinded to the definitive diagnosis to evaluate the seizure video recordings for each patient. Cohen's kappa coefficient, leave-one-out cross-validation (LOOCV) and balance accuracy (BAC) comprised the main validation analysis. ResultsThe final PNES-DSC is a 6-item checklist that requires only two to be present to confirm the suspicion of PNES. The LOOCV showed 71.4% BAC (Se = 45.2%; Sp = 97.6%) when the expert rater watched one seizure video recording and 83.4% BAC (Se = 69.6%; Sp = 97.2%) when the expert rater watched two seizure video recordings. ConclusionThe PNES-DSC is a straightforward checklist with adequate psychometric properties. With an integrative approach and appropriate patient history, the PNES-DSC can assist clinicians in expediting the final diagnosis of PNES when vEEG is limited. The PNES-DSC can also be used in the absence of patients, allowing clinicians to assess seizure recordings from smartphones.

CONTENT EVALUATION OF DIAGNOSTIC AND TREATMENT INFORMATION QUALITIES OF YOUTUBE VIDEOS ON CARPAL TUNNEL SYNDROME

Introduction: One of the leading video sharing platforms is YouTube (YT). Due to their increased use, these can possibly create misconceptions about the condition, especially the associated treatment and signs and symptoms of carpal tunnel syndrome. Thus, this evaluates the information quality of YT videos about carpal tunnel syndrome (CTS). Methods: This is a descriptive-evaluated study focused on assessing the information qualities of CTS videos on YT. Using Macleod et al. information quality index (2015), modified Diagnostic Information Quality Assessment Checklist (DIQAC) and Treatment Information Quality Assessment Checklist (TIQAC) were utilized. DIQAC measures the elements explanation, history, physical examination and ancillary procedures; while TIQAC, presurgical, surgical procedure, rehabilitation and complication elements. YT videos from 2020 onwards were searched using keywords "carpal tunnel syndrome", "diagnosis" and "treatment", and screened for duplicates, non-related to topic and without audio. Out of 31 videos retrieved, 11 YT videos on CTS were evaluated by physical therapists to determine the reliability of YT videos on CTS. Results: Results showed that YT-CTS videos are highly reliable in the elements explanation (45%) and history (36.36%), moderate to reliable in ancillary procedure (54.54%) and moderately reliable in physical examination (36%), in terms of DIQAC scoring. Whereas in TIQAC scoring, YT-CTS videos obtained a highly reliable presurgical scoring (45.45%). Surprisingly, it is poorly reliable in complication scoring (45.45%), very poorly to poor reliable in rehabilitation scoring (72.72%), and very poorly reliable in surgical scoring (45.45%). Overall, diagnosis information quality is high (65%), but low treatment information quality (32%). Discussion: This demonstrates that YT videos are technological tool that a physical therapist or a clinicians can utilize to educate and diagnose. Treatment information can hardly be explained in videos, which can vary form case to case, and is best explained through medical advice of a doctor to his patient with CTS.

Head-to-head comparison of cone-beam breast computed tomography and mammography in the diagnosis of primary breast cancer: A systematic review and meta-analysis

IntroductionTo compare the diagnostic performance of cone-beam breast computed tomography (CBBCT) and mammography (MG) in primary breast cancer. MethodsPubMed, Embase, Web of Science, China National Knowledge Infrastructure, WanFang DATA, and China Science and Technology Journal databases were searched comprehensively from inception to March 2023. Sensitivity and specificity were calculated using bivariate random-effects models, and a summary receiver operating characteristic (SROC) curve was constructed. Bivariate I2 statistics and meta-regression analyses were also performed. The differences in diagnostic performance between CBBCT and MG were analysed using Z-test statistics. Clinical utility was explored using Fagan’s nomogram, and quality assessment was conducted utilising the Quality Assessment of Diagnostic Accuracy Studies-2 checklist. ResultsThe summary sensitivity and specificity for CBBCT in diagnosing primary breast cancer were 0.92 (95 % CI: 0.87–0.94) and 0.79 (95 % CI: 0.71–0.85), respectively, and the area under the curve (AUC) of the SROC was 0.93 (95 % CI: 0.90–0.95). For MG, the summary sensitivity and specificity were 0.77 (95 % CI: 0.69–0.83) and 0.75 (95 % CI: 0.66–0.82), respectively, with an AUC of 0.83 (95 % CI: 0.80–0.86). The Z-test revealed that the summary sensitivity of CBBCT was significantly higher than that of MG (P < 0.001). Additionally, the summary AUC of CBBCT was significantly higher than that of MG (P < 0.001). ConclusionThe diagnostic performance of CBBCT for primary breast cancer was better than that of MG. However, the results of both the CBBCT and MG are based on studies with small sample sizes. Further studies with larger sample sizes and more comprehensive designs are required to address this issue.

A mixed Rasch model analysis of multiple profiles in L2 writing

The present study used the Mixed Rasch Model (MRM) to identify multiple profiles in L2 students’ writing with regard to several linguistic features, including content, organization, grammar, vocabulary, and mechanics. To this end, a pool of 500 essays written by English as a foreign language (EFL) students were rated by four experienced EFL teachers using the Empirically-derived Descriptor-based Diagnostic (EDD) checklist. The ratings were subjected to MRM analysis. Two distinct profiles of L2 writers emerged from the sample analyzed including: (a) Sentence-Oriented and (b) Paragraph-Oriented L2 Writers. Sentence-Oriented L2 Writers tend to focus more on linguistic features, such as grammar, vocabulary, and mechanics, at the sentence level and try to utilize these subskills to generate a written text. However, Paragraph-Oriented Writers are inclined to move beyond the boundaries of a sentence and attend to the structure of a whole paragraph using higher-order features such as content and organization subskills. The two profiles were further examined to capture their unique features. Finally, the theoretical and pedagogical implications of the identification of L2 writing profiles and suggestions for further research are discussed.

Comparing mental health semi-structured diagnostic interviews and symptom checklists to predict poor life outcomes: an 8-year cohort study from childhood to young adulthood in Brazil

Semi-structured diagnostic interviews and symptom checklists present similar internal reliability. We aim to investigate whether they differ in predicting poor life outcomes in the transition from childhood to young adulthood. For this longitudinal study, we used data from the Brazilian High Risk Cohort Study for Childhood Mental Health Conditions. Eligible participants were aged 6-14 years on the day of study enrolment (January to February, 2010) and were enrolled in public schools by a biological parent in Porto Alegre and São Paulo, Brazil. 2511 young people and their caregivers were assessed at baseline in 2010-11, and 1917 were assessed 8 years later (2018-19; 76·3% retention). Clinical thresholds were derived using semi-structured parent-report interview based on the Diagnostic and Statistical Manual of Mental Disorders, according to the Developmental and Well-being Assessment (DAWBA), and clinical scores as defined by the Child Behavior Checklist (CBCL; T-score ≥70 considered positive caseness). At 8 years, participants were assessed for a composite life-threatening outcome (a composite of death, suicide attempts, severe self-harm, psychiatric inpatient admission, or emergency department visits) and a composite poor life chances outcome (a composite of any criminal conviction, substance misuse, or school dropout). We evaluated the accuracy of DAWBA and CBCL to predict these outcomes. Logistic regression models were adjusted for age, sex, race or ethnicity, study site, and socioeconomic class. DAWBA and CBCL had similar sensitivity, specificity, predictive values, and test accuracy for both composite outcomes and their components. Any mental health problem, as classified by DAWBA and CBCL, was independently associated with the composite life-threatening outcome (DAWBA adjusted odds ratio 1·62, 95% CI 1·20-2·18; CBCL 1·66, 1·19-2·30), but only CBCL independently predicted poor life chances (1·56, 1·19-2·04). Participants classified by both approaches did not have higher odds of the life-threatening outcome when compared with participants classified by DAWBA or CBCL alone, nor for the poor life chances outcome when compared with those classified by CBCL alone. Classifying children and adolescents based on a semi-structured diagnostic interview was not statistically different to symptom checklist in terms of test accuracy and predictive validity for relevant life outcomes. Classification based on symptom checklist might be a valid alternative to costly and time-consuming methods to identify young people at risk for poor life outcomes. Conselho Nacional de Desenvolvimento Científico e Tecnológico; Fundação de Amparo à Pesquisa do Estado de São Paulo; and Medical Research Council, European Research Council. For the Portuguese translation of the abstract see Supplementary Materials section.

A prospective study evaluating the effect of a ‘Diagnostic Stewardship Care-Bundle’ for automated blood culture diagnostics

We prospectively implemented a diagnostic stewardship care-bundle checklist, 'Sepsis-48 DSB', with the aim of reducing intervening duration of key steps of automated blood culture diagnostics (aBCD). Sepsis-48 DSB was implemented for automated blood culture bottles (BCBs) received from adult intensive care units (AICUs) during the intervention period (P2; July 2020-June 2021) and intervening durations were compared with those during the retrospective, pre-intervention period (P1; March-June 2020). During both periods, provisional blood culture reports (pBCR) were issued wherein direct microbial identification (dID) was performed in BCBs with Gram-negatives by directly inoculating conventional biochemical tests and direct antimicrobial susceptibility testing (dAST) using EUCAST RAST method. The results were compared with the standard of care (SoC) method (i.e. full incubation followed by identification and AST by VITEKⓇ-2 Compact). During P2, significant reductions in loading time (LT) [median: 63.5 vs. 32 minutes, P < 0.001], time to dID+dAST performance (TTD) [186 vs. 115 minutes, P=0.0018] and an increase in compliance to bundle targets [LT ≤45: 44% vs. 66%, P=0.006 and TTD ≤120: 34% vs. 51.7%, P=0.03] were observed. Using dID+dAST method, results were read 694 minutes earlier than SoC method. Of 176 pBCR, 165 (94%) were concordant with SoC in microbial identification of species. Categorical agreement for any drug-bug combination was 92.7% (1079/1164) and corresponding major, very major, and minor error rates were 8.8% (19/216), 4.9% (45/921), and 1.8% (21/1164), respectively. The 'diagnostic stewardship care-bundle' strategy was successfully implemented with considerable diagnostic accuracy leading to significant reductions in duration of targeted steps of aBCD.

Implementing diagnostic stewardship to improve diagnosis of urinary tract infections across three medical centers: A qualitative assessment.

Urine-culture diagnostic stewardship aims to decrease misdiagnosis of urinary tract infections (UTIs); however, these interventions are not widely adopted. We examined UTI diagnosis and management practices to identify barriers to and facilitators of diagnostic stewardship implementation. Using a qualitative descriptive design, we conducted semistructured interviews at 3 Veterans' Affairs medical centers. Interviews were conducted between November 2021 and May 2022 via Zoom videoconferencing using an interview guide and visual prototypes of proposed interventions. Interviewees were asked about current practices and thoughts on proposed interventions for urine-culture ordering, processing, and reporting. We used a rapid analysis matrix approach to summarize key interview findings and compare practices and perceptions across sites. We interviewed 31 stakeholders and end users. All sites had an antimicrobial stewardship program but limited initiatives targeting appropriate diagnosis and management of UTIs. The majority of those interviewed identified the importance of diagnostic stewardship. Perceptions of specific interventions ranged widely by site. For urine-culture ordering, all 3 sites agreed that documentation of symptomology would improve culturing practices but did not want it to interrupt workflow. Representatives at 2 sites expressed interest in conditional urine-culture processing and 1 was opposed. All sites had similar mechanisms to report culture results but varied in perceptions of the proposed interventions. Feedback from end users was used to develop a general diagnostic stewardship implementation checklist. Interviewees thought diagnostic stewardship was important. Qualitative assessment involving key stakeholders in the UTI diagnostic process improved understanding of site-specific beliefs and practices to better implement interventions for urine-culture ordering, processing, and reporting.

The Performance Diagnostic Checklist and Its Variants: A Systematic Review

ABSTRACT The Performance Diagnostic Checklist (PDC) is an indirect assessment tool used to identify the variables supporting problematic employee performance. The tool includes four domains; based on PDC results, an assessment-based intervention targeting one or more of these domains is evaluated. In recent years, PDC variants such as the PDC-Human Services (PDC-HS), the PDC-Safety, and the PDC-Parent have been developed. The purpose of this study is to review the research that has employed the PDC and its variants. We found twenty-eight published studies which have used the PDC or one of its variants. The PDC-HS has been most commonly used, followed by the PDC, the PDC-Safety, and PDC-Parent. The PDC and its variants have most often been completed with supervisors of employees exhibiting performance concerns. Many studies have identified multiple PDC domains as problematic, although domains representing antecedents and consequences are most commonly indicated. Interventions have typically been developed based on the highest scoring domain. Few studies have collected data on social validity or maintenance of intervention effects. Overall, results support the utility of the PDC and its variants, but also highlight PDC-related topics in need of additional research

Developing and evaluating an empirically-based diagnostic checklist for assessing second language integrated writing

Writing in academic contexts typically includes integrated or source-based writing tasks. Given the significance of identifying students’ strengths and weaknesses and providing them with fine-grained feedback, this study aimed at developing and validating an empirically-based, binary-choice diagnostic checklist for L2 reading-listening-writing (RLW) integrated tasks. First, with reference to L2 students’ verbalizations of their challenges in integrated writing tasks, a diagnostic checklist was developed and then examined and revised by two ESL writing experts, resulting in the construction of a checklist comprising 30 items. Each item was a one-sentence descriptor that addressed a specific aspect of an integrated essay. The study evaluated the checklist’s function in providing reliable and effective diagnostic information by examining score consistency across raters on different essay prompts, raters’ confidence in rating, relationship between the checklist scores and scores awarded using TOEFL’s rating scale, and students’ perception of the feedback provided through the checklist. The results supported the benefits of using a descriptor-based checklist for assessing students’ performance in integrated writing and providing fine-grained diagnostic feedback. Implications of the use of the checklist to provide diagnostic feedback to students and to apply cognitive diagnostic models to writing data are also discussed.

Career Development and Psychopathological Symptoms on Female Workers

Women workers face a variety of challenges in the world of work. In addition to facing dual role conflicts for married female workers, they also face various stressors at their jobs. This will leave women vulnerable and have an impact on workers' emotional well-being. This study sought to ascertain the connection between female workers' propensity for psychopathological symptoms and occupational stressors. One hundred and thirty-four female office workers were recruited for this cross-sectional study. Subjects were questioned about age, education, marital status, and years of work for describing respondents’ characteristics. The diagnostic stress survey and symptom checklist 90 were used for measuring work stressors and determining the tendency of psychopathological symptoms, respectively. Data were statistically analyzed using the chi-square test, the Fisher exact test, and logistic regression, where appropriate, with a meaningfulness level of p &lt; 0,05. Results show that quantitative workload stressors, qualitative workloads, and career development are associated with psychopathological symptoms, but after continuing with The Logistic regression test found that career development stressors were mainly associated with the appearance of psychopathological symptoms ( p= 0.003; OR= 10,069.95 % CI 2,238 – 45,296). Female workers who experience barriers to career development have a 10-fold risk for the occurrence of psychopathological symptoms.&#x0D; Keywords: Female Worker, work stressor, a psychopathological tendency

3D multimodal image fusion based on MRI in the preoperative evaluation of microvascular decompression: A meta‑analysis.

Neurovascular compression (NVC) is the main cause of hemifacial spasm (HFS) or trigeminal neuralgia (TN), and frequently occurs at the root entry zone of cranial nerves. Microvascular decompression (MVD) is an effective surgical treatment for TN and HFS caused by NVC. The accurate preoperative diagnosis of NVC is crucial to the evaluation of MVD as an appropriate treatment for TN and HFS. Three-dimensional (3D) time-of-flight magnetic resonance angiography (3D TOF MRA) and high resolution T2-weighted imaging (HR T2WI) are used to detect NVC prior to MVD; however, this combination alone has certain disadvantages. Multimodal image fusion (MIF) may combine two or more images from the same or different modalities, allowing neurosurgeons to use the reconstructed 3D model to observe anatomical details more clearly from different perspectives. The aim of the present meta-analysis was to evaluate the effect of 3D MIF based on 3D TOF MRA combined with HR T2WI in the preoperative diagnosis of NVC, and thus to evaluate its clinical application value in the preoperative evaluation of MVD. Relevant studies available on PubMed, Embase, Web of Science, Scopus, China National Knowledge Infrastructure and the Cochrane Library, and published from the inception of each database to September 2022, were retrieved. Studies using 3D MIF based on 3D TOF MRA combined with HR T2WI to diagnose NVC in patients with TN or HFS were included. The Quality Assessment of Diagnostic Accuracy Studies checklist was used to evaluate the quality of the included studies. The statistical software Stata 16.0 was used to perform the meta-analysis. Data extraction was performed by two independent investigators and discrepancies were resolved by discussion. Pooled sensitivities, specificities, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR) and the area under the receiver operating characteristic curve (AUROC) were calculated as the main summary effect size. The I² and Q-test were used to assess heterogeneity. The present search identified 702 articles, of which 7 (comprising 390 patients) fulfilled the inclusion criteria. Bivariate analysis indicated that the pooled sensitivity and specificity of 3D MIF based on 3D TOF MRA combined with HR T2WI for detecting NVC were 0.97 (95% CI, 0.95-0.99) and 0.89 (95% CI, 0.77-0.95), respectively. The pooled PLR was 8.8 (95% CI, 4.1-18.6), the pooled NLR was 0.03 (95% CI, 0.02-0.06) and the pooled DOR was 291 (95% CI, 99-853). The AUROC was 0.98 (95% CI, 0.97-0.99). The studies had no substantial heterogeneity (I2=0; Q=0.000; P=0.50). The present results suggested that 3D MIF based on 3D TOF MRA combined with HR T2WI had excellent sensitivity and specificity for diagnosing NVC in patients with TN or HFS. Therefore, this method should serve a key role in MVD preoperative evaluation.

Acquisitions of divested business units: A typology and strategies for success

Acquisitions are notoriously difficult to execute successfully. Poor implementation of the postacquisition integration process is a major source of acquisition value destruction. To find new solutions for this vexing problem, we leverage the emerging, triadic view of mergers and acquisitions (M&A) activities, which emphasizes the interconnectedness between sellers, acquirers, and the units that are transferred between them. We apply the triadic lens to acquisitions of divested business units, and we find that a unit’s experiences with its seller before and during divestiture can profoundly shape the unit’s needs and expectations, which, in turn, must be addressed by the acquirer in the integration process. We identify four key mechanisms—status, resource accessibility, trust, and self-sufficiency—that underpin the seller’s impact on the divested unit, and we develop a typology—comprising favored, neglected, shocked, and independent units—that animates the ramifications of the seller’s actions. Then, for each type, we discern strategies for its postacquisition integration execution that are tailored to its distinctive needs, which originate from its experiences with the seller. To make these insights practical and readily implementable, we provide a diagnostic checklist for identifying the four types of divested units and offer an action plan of type-specific strategies for successfully managing them in the postacquisition integration process.

Fibroblast Activation Protein Inhibitor (FAPI)-Based Theranostics—Where We Are at and Where We Are Heading: A Systematic Review

Cancer is the leading cause of death around the globe, followed by heart disease and stroke, with the highest mortality to this day. We have reached great levels of understanding of how these various types of cancer operate at a cellular level and this has brought us to what we call "precision medicine" where every diagnostic examination and the therapeutic procedure is tailored to the patient. FAPI is among the new tracers that can be used to assess and treat many types of cancer. The aim of this review was to gather all the known literature on FAPI theranostics. A MEDLINE search was conducted on four web libraries, PUBMED, Cochrane, Scopus, and Web of Sciences. All of the available articles that included both diagnoses and therapy with FAPI tracers were collected and put through the CASP (Critical Appraisal Skills Programme) questionnaire for systematic reviewing. A total of 8 records were deemed suitable for CASP review, ranging from 2018 to November 2022. These studies were put through the CASP diagnostic checklist, in order to assess the goal of the study, diagnostic and reference tests, results, descriptions of the patient sample, and future applications. Sample sizes were heterogeneous, both for size as well as for tumor type. Only one author studied a single type of cancer with FAPI tracers. Progression of disease was the most common outcome, and no relevant collateral effects were noted. Although FAPI theranostics is still in its infancy and lacks solid grounds to be brought into clinical practice, it does not show any collateral effects that prohibit administration to patients, thus far, and has good tolerability profiles.

Compulsive Gambling in the Stock Market: Evidence from an Emerging Market

During the COVID-19 pandemic, many new individual investors globally entered the stock markets, often pursuing speculative investment strategies that resemble gambling. A concern is that trading as a form of gambling can become addictive for some people, as documented by several recent studies in developed markets. We contribute to this literature by adding new evidence from a large emerging market, Thailand, where most forms of traditional gambling are illegal. We field a diagnostic checklist from the American Psychiatric Association for compulsive gambling, changing the content of each item to refer to stock market trading instead of gambling. In a survey of 285 Thai investors, we document that 9.5% are potential problem gamblers, while 4.9% meet the stricter criteria for addiction. The trading addiction score explains speculative trading behavior such as frequent trading, day trading and buying high-risk “lottery” stocks, beyond common factors such as overconfidence and high risk-tolerance. Further, the trading addiction score is positively related to high levels of stress and alcohol use, problems often associated with gambling disorders. Our results raise awareness about investors whose objectives are more related to gambling than long-term investment, and the associated problems when such behavior becomes compulsive.

Deep Learning for Detecting Brain Metastases on MRI: A Systematic Review and Meta-Analysis.

Since manual detection of brain metastases (BMs) is time consuming, studies have been conducted to automate this process using deep learning. The purpose of this study was to conduct a systematic review and meta-analysis of the performance of deep learning models that use magnetic resonance imaging (MRI) to detect BMs in cancer patients. A systematic search of MEDLINE, EMBASE, and Web of Science was conducted until 30 September 2022. Inclusion criteria were: patients with BMs; deep learning using MRI images was applied to detect the BMs; sufficient data were present in terms of detective performance; original research articles. Exclusion criteria were: reviews, letters, guidelines, editorials, or errata; case reports or series with less than 20 patients; studies with overlapping cohorts; insufficient data in terms of detective performance; machine learning was used to detect BMs; articles not written in English. Quality Assessment of Diagnostic Accuracy Studies-2 and Checklist for Artificial Intelligence in Medical Imaging was used to assess the quality. Finally, 24 eligible studies were identified for the quantitative analysis. The pooled proportion of patient-wise and lesion-wise detectability was 89%. Articles should adhere to the checklists more strictly. Deep learning algorithms effectively detect BMs. Pooled analysis of false positive rates could not be estimated due to reporting differences.

Efficiency and accuracy of artificial intelligence in the radiographic detection of periodontal bone loss: A systematic review.

Artificial intelligence (AI) is poised to play a major role in medical diagnostics. Periodontal disease is one of the most common oral diseases. The early diagnosis of periodontal disease is essential for effective treatment and a favorable prognosis. This study aimed to assess the effectiveness of AI in diagnosing periodontal bone loss through radiographic analysis. A literature search involving 5 databases (PubMed, ScienceDirect, Scopus, Health and Medical Collection, Dentistry and Oral Sciences) was carried out. A specific combination of keywords was used to obtain the articles. The PRISMA guidelines were used to filter eligible articles. The study design, sample size, type of AI software, and the results of each eligible study were analyzed. The CASP diagnostic study checklist was used to evaluate the evidence strength score. Seven articles were eligible for review according to the PRISMA guidelines. Out of the 7 eligible studies, 4 had strong CASP evidence strength scores (7-8/9). The remaining studies had intermediate CASP evidence strength scores (3.5-6.5/9). The highest area under the curve among the reported studies was 94%, the highest F1 score was 91%, and the highest specificity and sensitivity were 98.1% and 94%, respectively. AI-based detection of periodontal bone loss using radiographs is an efficient method. However, more clinical studies need to be conducted before this method is introduced into routine dental practice.