Identification of clinical and paraclinical findings predictive for headache occurrence during spontaneous subarachnoid hemorrhage

Ljubisavljević, Srdjan; Milošević, Vuk; Stojanov, Aleksandar; Ljubisavljevic, Marina; Dunjić, Olivera; Živković, Mladen

doi:10.1016/j.clineuro.2017.04.017

Cited by 4 publications

(1 citation statement)

References 19 publications

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“…In support of this, the loss of consciousness could be recognized as a negative predictor for headache occurrence. The presence of neurological symptoms and loss of consciousness are identified as a negative predictor for headache occurrence in SAH patients [ 19 ]. The neurological findings and loss of consciousness are GCS items that change even in the first hours after ICH onset; they are identified as independent prognostic tools for the prediction of ICH clinical evolution [ 11 , 20 ].…”

Section: Discussionmentioning

confidence: 99%

Headache secondary to nontraumatic brain hemorrhage: a single-center, retrospective clinical study

2019

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Introduction: The predictive accuracy of clinical and paraclinical findings for headache occurrence in patients having nontraumatic intracerebral hemorrhage (ICH) was tested. Material and methods: The medical records of 341 consecutive nontraumatic ICH patients (106 females and 235 males), average age 56.2 ±7.7 years, presenting with headache (25.5%) and without a headache (74.5%), over a period of 5 years, were retrospectively analyzed. Results: The presence of focal neurological symptoms (OR = 0.129, 95% CI: 0.044-0.372, p = 0.000), loss of consciousness (OR = 0.174, 95% CI: 0.060-0.504, p = 0.001), body temperature (OR = 0.586, 95% CI: 0.389-0.882, p = 0.010), and the values of C-reactive protein (OR = 0.989, 95% CI: 0.978-0.999, p = 0.048) at admission, as well as the presence of hematoma in the basal ganglia (OR = 0.308, 95% CI: 0.159-0.596, p = 0.000) and the presence of arterial hypertension in the medical history (OR = 0.478, 95% CI: 0.230-0.991, p = 0.047), are recognized as negative predictors for headache occurrence in ICH. The regular use of antihypertensive therapy is a prominent positive predictor for headache occurrence in ICH (OR = 1.906, 95% CI: 1.075-3.381, p = 0.027). Patients presenting with headache had a favorable clinical outcome compared to those without headache in ICH presentation (p < 0.001). Conclusions: The present results might be clinically useful for considering further diagnostic and therapeutic procedures as early as possible in patients with symptoms clinically suggestive of ICH, with and without headache in ICH clinical presentation. These data require confirmation in a prospective large-scale study.

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Section: Discussionmentioning

confidence: 99%

Headache secondary to nontraumatic brain hemorrhage: a single-center, retrospective clinical study

2019

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Electronic Medical Record–Based Case Phenotyping for the Charlson Conditions: Scoping Review

Lee¹,

Doktorchik²,

Martin³

et al. 2021

JMIR Med Inform

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Background Electronic medical records (EMRs) contain large amounts of rich clinical information. Developing EMR-based case definitions, also known as EMR phenotyping, is an active area of research that has implications for epidemiology, clinical care, and health services research. Objective This review aims to describe and assess the present landscape of EMR-based case phenotyping for the Charlson conditions. Methods A scoping review of EMR-based algorithms for defining the Charlson comorbidity index conditions was completed. This study covered articles published between January 2000 and April 2020, both inclusive. Embase (Excerpta Medica database) and MEDLINE (Medical Literature Analysis and Retrieval System Online) were searched using keywords developed in the following 3 domains: terms related to EMR, terms related to case finding, and disease-specific terms. The manuscript follows the Preferred Reporting Items for Systematic reviews and Meta-analyses extension for Scoping Reviews (PRISMA) guidelines. Results A total of 274 articles representing 299 algorithms were assessed and summarized. Most studies were undertaken in the United States (181/299, 60.5%), followed by the United Kingdom (42/299, 14.0%) and Canada (15/299, 5.0%). These algorithms were mostly developed either in primary care (103/299, 34.4%) or inpatient (168/299, 56.2%) settings. Diabetes, congestive heart failure, myocardial infarction, and rheumatology had the highest number of developed algorithms. Data-driven and clinical rule–based approaches have been identified. EMR-based phenotype and algorithm development reflect the data access allowed by respective health systems, and algorithms vary in their performance. Conclusions Recognizing similarities and differences in health systems, data collection strategies, extraction, data release protocols, and existing clinical pathways is critical to algorithm development strategies. Several strategies to assist with phenotype-based case definitions have been proposed.

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Electronic Medical Record–Based Case Phenotyping for the Charlson Conditions: Scoping Review (Preprint)

Lee¹,

Doktorchik²,

Martin³

et al. 2020

Preprint

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BACKGROUND Electronic medical records (EMRs) contain large amounts of rich clinical information. Developing EMR-based case definitions, also known as EMR phenotyping, is an active area of research that has implications for epidemiology, clinical care, and health services research. OBJECTIVE This review aims to describe and assess the present landscape of EMR-based case phenotyping for the Charlson conditions. METHODS A scoping review of EMR-based algorithms for defining the Charlson comorbidity index conditions was completed. This study covered articles published between January 2000 and April 2020, both inclusive. Embase (Excerpta Medica database) and MEDLINE (Medical Literature Analysis and Retrieval System Online) were searched using keywords developed in the following 3 domains: terms related to EMR, terms related to case finding, and disease-specific terms. The manuscript follows the Preferred Reporting Items for Systematic reviews and Meta-analyses extension for Scoping Reviews (PRISMA) guidelines. RESULTS A total of 274 articles representing 299 algorithms were assessed and summarized. Most studies were undertaken in the United States (181/299, 60.5%), followed by the United Kingdom (42/299, 14.0%) and Canada (15/299, 5.0%). These algorithms were mostly developed either in primary care (103/299, 34.4%) or inpatient (168/299, 56.2%) settings. Diabetes, congestive heart failure, myocardial infarction, and rheumatology had the highest number of developed algorithms. Data-driven and clinical rule–based approaches have been identified. EMR-based phenotype and algorithm development reflect the data access allowed by respective health systems, and algorithms vary in their performance. CONCLUSIONS Recognizing similarities and differences in health systems, data collection strategies, extraction, data release protocols, and existing clinical pathways is critical to algorithm development strategies. Several strategies to assist with phenotype-based case definitions have been proposed. CLINICALTRIAL

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Identification of clinical and paraclinical findings predictive for headache occurrence during spontaneous subarachnoid hemorrhage

Cited by 4 publications

References 19 publications

Headache secondary to nontraumatic brain hemorrhage: a single-center, retrospective clinical study

Headache secondary to nontraumatic brain hemorrhage: a single-center, retrospective clinical study

Electronic Medical Record–Based Case Phenotyping for the Charlson Conditions: Scoping Review

Electronic Medical Record–Based Case Phenotyping for the Charlson Conditions: Scoping Review (Preprint)

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