The prevalence and impact of potentially inappropriate prescribing among older persons in primary care settings: multilevel meta-analysis

2020 ◽  
Vol 49 (4) ◽  
pp. 570-579 ◽  
Author(s):  
Tau Ming Liew ◽  
Cia Sin Lee ◽  
Shawn Kuan Liang Goh ◽  
Zi Ying Chang
Keyword(s):  
Primary Care ◽  
Older Persons ◽  
Meta Analysis ◽  
Inappropriate Prescribing ◽  
Population Attributable Risk ◽  
Adverse Outcomes ◽  
Potentially Inappropriate Prescribing ◽  
Primary Care Settings ◽  
Prevalence Estimates ◽  
The Impact

Abstract Background Potentially inappropriate prescribing (PIP) may not have received as much attention in primary care settings (compared to tertiary hospital and nursing home settings), due to uncertainty about its prevalence in this healthcare setting. We conducted a systematic review with meta-analysis to summarise the prevalence of PIP specific to primary care settings and computed the population attributable risk (PAR) to estimate the impact of PIP in primary care. Method We searched PubMed, Embase, CINAHL, Web of Science, Scopus, PsycINFO and previous review articles for studies related to ‘older persons’, ‘primary care’ and ‘inappropriate prescribing’. Two reviewers selected eligible articles, extracted data and evaluated risk of bias. Multilevel meta-analysis was conducted to pool the prevalence estimates across the included studies, while meta-regression was conducted to investigate the sources of heterogeneity. Results Of the 4,259 articles identified, we included 67 articles with 111 prevalence estimates and a total of 5,054,975 participants. Overall, PIP had a pooled prevalence of 33.3% (95% CI 29.7–37.0%). Based on population attributable risks, PIP explained 7.7–17.3% of adverse outcomes related to older persons in primary care. If current PIP prevalence is halved, 37–79 cases of adverse outcomes may potentially be prevented (per 1,000 adverse outcomes). Conclusions The findings demonstrate the relevance and potential impact of PIP specific to primary care settings. Given the increasingly central role that primary care plays in coordinating healthcare, the findings highlight the need to prioritise PIP intervention in primary care as a key strategy to reduce iatrogenic medication-related harm among older persons in current healthcare system.

Primary care physician services and the frequency of comorbidities in patients with acute myocardial infarction

2021 ◽  
Vol 28 (Supplement_1) ◽  
Author(s):  
R King ◽  
D Giedrimiene
Keyword(s):  
Myocardial Infarction ◽  
Primary Care ◽  
Acute Myocardial Infarction ◽  
Primary Care Physician ◽  
Care Physician ◽  
Adverse Outcomes ◽  
Coronary Syndrome ◽  
Number Of Patients ◽  
Significant Difference ◽  
The Impact

Abstract Funding Acknowledgements Type of funding sources: None. Background The management of patients with multiple comorbidities represents a significant burden on healthcare each year. Despite requiring regular medical care to treat chronic conditions, a large number of these patients may not receive proper care. Significant disparities have been identified in patients with multiple comorbidities and those who experience acute coronary syndrome or acute myocardial infarction (AMI). Only limited data exists to identify the impact of comorbidities and utilization of primary care physician (PCP) services on the development of adverse outcomes, such as AMI. Purpose The primary objective was to analyze how PCP services utilization can be associated with comorbidities in patients who experienced an AMI. Methods This study was based on retrospective data analysis which included 250 patients admitted to the Hartford Hospital Emergency Department (ED) for an AMI. Out of these, 27 patients were excluded due to missing documentation. Collected data included age, gender, medications and recorded comorbidities, such as hypertension, hyperlipidemia, diabetes mellitus (DM), chronic kidney disease (CKD) and previous arrhythmia. Each patient was assessed regarding utilization of PCP services. Statistical analysis was performed in order to identify differences between patients with documented PCP services and those without by using the Chi-square test. Results The records allowed for identification of documented PCP services for 172 out of 223 (77.1%) patients. The most common comorbidities were hypertension and hyperlipidemia: in 165 (74.0%) and 157 (70.4%) cases respectively. The most frequent comorbidity was hypertension: 137 out of 172 (79.7%) in pts with PCP vs 28 out of 51 (54.9%) without PCP, and significantly more often in patients with PCP, p< 0.001. Hyperlipidemia was the second most frequent comorbidity: in 130 out of 172 (75.6%) vs 27 out of 51 (52.9%) accordingly, and also significantly more often (p< 0.002) in patients with PCP services. The number of comorbidities ranged from 0-5, including 32 (14.3%) patients without comorbidities: 16 (9.3%) with a PCP and 16 (31.4%) without PCP services. The majority of patients - 108 (48.5% of 223), had 2-3 documented comorbidities: 89 (51.8%) had two and 19 (34.6%) had three. The remaining 40 (17.9%) patients had 4-5 comorbidities: 37 (21.5%) of them with a PCP and 3 (10.3%) without, with a significant difference (p < 0.001) found for patients with a higher number of comorbidities who utilized PCP services. Conclusions Our study shows that the majority of patients who presented with an AMI had one or more comorbidities. Furthermore, patients who did not utilize PCP services had fewer identified comorbidities. This suggests that there may be a significant number of patients who experienced AMI with undiagnosed comorbidities due to not having access to PCP services.

Attenuation of maternal weight gain impacts infant birthweight: systematic review and meta-analysis

2018 ◽  
Vol 10 (4) ◽  
pp. 387-405 ◽  
Author(s):  
C. J. Bennett ◽  
R. E. Walker ◽  
M. L. Blumfield ◽  
J. Ma ◽  
F. Wang ◽  
...  
Keyword(s):  
Weight Gain ◽  
Gestational Age ◽  
Weighted Mean Difference ◽  
Meta Analysis ◽  
Adverse Outcomes ◽  
Large For Gestational Age ◽  
Maternal Weight ◽  
Clinical Trial Registry ◽  
Meta Analyses ◽  
The Impact

AbstractDespite many interventions aiming to reduce excessive gestational weight gain (GWG), it is currently unclear the impact on infant anthropometric outcomes. The aim of this review was to evaluate offspring anthropometric outcomes in studies designed to reduce GWG. A systematic search of seven international databases, one clinical trial registry and three Chinese databases was conducted without date limits. Studies were categorised by intervention type: diet, physical activity (PA), lifestyle (diet + PA), other, gestational diabetes mellitus (GDM) (diet, PA, lifestyle, metformin and other). Meta-analyses were reported as weighted mean difference (WMD) for birthweight and birth length, and risk ratio (RR) for small for gestational age (SGA), large for gestational age (LGA), macrosomia and low birth weight (LBW). Collectively, interventions reduced birthweight, risk of macrosomia and LGA by 71 g (WMD: −70.67, 95% CI −101.90 to −39.43,P<0.001), 16% (RR: 0.84, 95% CI 0.73–0.98,P=0.026) and 19% (RR: 0.81, 95% CI 0.69–0.96,P=0.015), respectively. Diet interventions decreased birthweight and LGA by 99 g (WMD −98.80, 95% CI −178.85 to −18.76,P=0.016) and 65% (RR: 0.35, 95% CI 0.17–0.72,P=0.004). PA interventions reduced the risk of macrosomia by 51% (RR: 0.49, 95% CI 0.26–0.92,P=0.036). In women with GDM, diet and lifestyle interventions reduced birthweight by 211 and 296 g, respectively (WMD: −210.93, 95% CI −374.77 to −46.71,P=0.012 and WMD:−295.93, 95% CI −501.76 to −90.10,P=0.005, respectively). Interventions designed to reduce excessive GWG lead to a small reduction in infant birthweight and risk of macrosomia and LGA, without influencing the risk of adverse outcomes including LBW and SGA.

scholarly journals The Effects of Heatwaves on Human Morbidity in Primary Care Settings: A Case-Crossover Study

2022 ◽  
Vol 19 (2) ◽  
pp. 832
Author(s):  
Mahmoud Alsaiqali ◽  
Katrien De Troeyer ◽  
Lidia Casas ◽  
Rafiq Hamdi ◽  
Christel Faes ◽  
...  
Keyword(s):  
Primary Care ◽  
Crossover Study ◽  
Respiratory Infection ◽  
Respiratory Infections ◽  
Infection Risk ◽  
Incidence Density ◽  
Acute Effects ◽  
Primary Care Settings ◽  
Case Crossover ◽  
The Impact

Purpose: This study assesses the potential acute effects of heatwaves on human morbidities in primary care settings. Methods: We performed a time-stratified case-crossover study to assess the acute effects of heatwaves on selected morbidities in primary care settings in Flanders, Belgium, between 2000 and 2015. We used conditional logistic regression models. We assessed the effect of heatwaves on the day of the event (lag 0) and X days earlier (lags 1 to X). The associations are presented as Incidence Density Ratios (IDR). Results: We included 22,344 events. Heatwaves are associated with increased heat-related morbidities such as heat stroke IDR 3.93 [2.94–5.26] at lag 0, dehydration IDR 3.93 [2.94–5.26] at lag 1, and orthostatic hypotension IDR 2.06 [1.37–3.10] at lag 1. For cardiovascular morbidities studied, there was only an increased risk of stroke at lag 3 IDR 1.45 [1.04–2.03]. There is no significant association with myocardial ischemia/infarction or arrhythmia. Heatwaves are associated with decreased respiratory infection risk. The IDR for upper respiratory infections is 0.82 [0.78–0.87] lag 1 and lower respiratory infections (LRI) is 0.82 [0.74–0.91] at lag 1. There was no significant effect modification by age or premorbid chronic disease (diabetes, hypertesnsion). Conclusion: Heatwaves are associated with increased heat-related morbidities and decreased respiratory infection risk. The study of heatwaves’ effects in primary care settings helps evaluate the impact of heatwaves on the general population. Primary care settings might be not suitable to study acute life-threatening morbidities.

Risk factors for potentially inappropriate prescribing to older patients in primary care

2015 ◽  
Vol 72 (1) ◽  
pp. 93-107 ◽  
Author(s):  
Ivana Projovic ◽  
Dubravka Vukadinovic ◽  
Olivera Milovanovic ◽  
Milena Jurisevic ◽  
Radisa Pavlovic ◽  
...  
Keyword(s):  
Risk Factors ◽  
Primary Care ◽  
Older Patients ◽  
Inappropriate Prescribing ◽  
Potentially Inappropriate Prescribing
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