HIGH RISK PREGNANCY DETECTION USING TELEHEALTH-BASED SCREENING

High-risk pregnancy is a pregnancy that is likely to cause harm or complications to the mother and fetus. Given the high rate of disease transmission, the use of telehealth technology can be an effective and efficient way to deal with the spread of the virus. Telehealth is one solution to overcome the problem of access to health, with telehealth it can perform screening to detect high-risk pregnancies early, so that pregnant women can get continuous monitoring. Telehealth can operate as a filter that is able to expand and facilitate access to services, especially in the examination and screening of risks in pregnancy and can apply high risk detection instruments in pregnancy in applications, so as to facilitate decision making. Telehealth can detect high-risk pregnancies early, so that pregnant women can get continuous monitoring. The purpose of this activity is to conduct and determine the effectiveness of telehealth-based high-risk detection in pregnant women. The method of activity is in the form of community service through webinars and screenings which are carried out within 6 months online. The result of the activity is an increase in the knowledge of webinar respondents with an average pre-test value of 120 and post-test 157 out of a total of 200. Based on the results of screening using the SIBIDAN application, from 25 pregnant women in trimesters 1,2, and 3 who became respondents, the results were 52%, low risk group, 32% high risk group, and 16% very high-risk group. Therefore, further assistance, monitoring, and referral are needed to minimize pregnancy complications.

Home Healthcare Clinicians’ Perspectives on Electronic Health Records: A Qualitative Study

Clinicians’ perspectives on the electronic health records (EHR) in home healthcare (HHC) are understudied. To explore this topic, qualitative interviews were conducted with 15 HHC clinicians in the Northeastern USA. Thematic analysis was conducted to identify key themes emerging from the interviews. While some EHR benefits were recognized, overall satisfaction with the EHR was low. The results suggest EHR limitations are tied to poor usability, restrictions, and redundancy in documentation leading to increased documentation workload. Clinicians have recommendations to mitigate these limitations via additional EHR functions and better patient risk detection. Future stakeholders should consider the results of this study when developing and updating the EHR in HHC.

“Hard to Say, Hard to Understand, Hard to Live”: Possible Associations between Neurologic Language Impairments and Suicide Risk

In clinical practice, patients with language impairments often exhibit suicidal ideation (SI) and suicidal behavior (SB, covering the entire range from suicide attempts, SA, to completed suicides). However, only few studies exist regarding this subject. We conducted a mini-review on the possible associations between neurologic language impairment (on the motor, comprehension, and semantic sides) and SI/SB. Based on the literature review, we hypothesized that language impairments exacerbate psychiatric comorbidities, which, in turn, aggravate language impairments. Patients trapped in this vicious cycle can develop SI/SB. The so-called “affective prosody” provides some relevant insights concerning the interaction between the different language levels and the world of emotions. This hypothesis is illustrated in a clinical case that we reported, consisting of the case of a 74-year old woman who was admitted to a psychiatric emergency department (ED) after a failed SA. Having suffered an ischemic stroke two years earlier, she suffered from incomplete Broca’s aphasia and dysprosody. She also presented with generalized anxiety and depressive symptoms. We observed that her language impairments were both aggravated by the exacerbations of her anxiety and depressive symptoms. In this patient, who had deficits on the motor side, these exacerbations were triggered by her inability to express herself, her emotional status, and suffering. SI was fluctuant, and—one year after the SA—she completed suicide. Further studies are needed to ascertain possible reciprocal and interacting associations between language impairments, psychiatric comorbidities, and SI/SB. They could enable clinicians to better understand their patient’s specific suffering, as brought on by language impairment, and contribute to the refining of suicide risk detection in this sub-group of affected patients.

Affect Dynamic Signatures of Psychosis Risk Across Multiple Timescales and Contexts

There is a critical need for identifying time-sensitive and cost-effective markers of psychosis riskearly in the illness course. One solution may lie in affect dynamics, or the fluctuations of affect across time, which have been demonstrated to predict transitions in psychopathology. Across three studies, the current research is the first to comprehensively investigate affect dynamics in relation to subthreshold positive symptoms (perceptual aberration and magical ideation) and negative symptoms (social anhedonia) of the psychosis spectrum. Across multiple timescales and contexts, affect dynamics were modeled from inexpensive laboratory paradigms and social media text. Findings provided strong evidence for positive symptoms linked to heightened magnitude and frequency of affective fluctuations in response to emotional materials. Alternatively, negative symptoms showed modest association with heightened persistence of baseline states. These affect dynamic signatures of psychosis risk provide insight on the distinct developmental pathways to psychosis and could facilitate current risk detection approaches.

Financial Early Warning System Model Combining Hybrid Semantic Hierarchy with Group Method of Data Handling Neural Network for Detection of Banks’ Risks

Banks, financial, and credit institutions encountering the weakening financial system and increased risk factors cause high inflation and great losses for an economy. Detecting financial risks in advance could help financial institutions avoid losses, and the financial system could be eventually affected less. Early warning systems for banks could be helpful to identify financial risks and take measures to deal with hazardous situations. Various approaches have already been put forward. However, inaccuracy issues in risk detection are one of the main issues. Combining semantic hierarchy with the GMDH neural network to predict financial risks is proposed. A semantic hierarchy approach based on converting risk-related values and picking influential variables could be practical in risk detection. Besides, the GMDH algorithm utilizing neural networks based on available data has the capability of predicting possible risks that could occur in the future. The outcomes of the proposed method when compared to non-data mining methods suggest that it improves accuracy by almost 20%.

Hypertension in Women: Should There be a Sex-specific Threshold?

Conventionally, hypertension is defined by the same blood pressure (BP) threshold (systolic BP ≥140 and/or diastolic BP ≥90 mmHg) in both women and men. Several studies have documented that women with hypertension are more prone to develop BP-associated organ damage and that high BP is a stronger risk factor for cardiovascular disease (CVD) in women than men. While healthy young women have lower BP than men, a steeper increase in BP is found in women from the third decade of life. Studies have documented that the BP-attributable risk for acute coronary syndromes (ACS), heart failure and AF increases at a lower level of BP in women than in men. Even high normal BP (130–139/80–89 mmHg) is associated with an up to twofold higher risk of ACS during midlife in women, but not in men. Whether sex-specific thresholds for definition of hypertension would improve CVD risk detection should be considered in future guidelines for hypertension management and CVD prevention.