The discrepancy between admission and discharge diagnoses: Underlying factors and potential clinical outcomes in a low socioeconomic country

Objective: The discrepancy between admission and discharge diagnosis can lead to possible adverse patient outcomes. There are gaps in integrated studies, and less is understood about its characteristics and effects. Therefore, this study was conducted to determine the frequency, characteristics, and outcomes of diagnostic discrepancies at admission and discharge.Design and data sources: This retrospective study reviewed the admitting and discharge diagnoses of adult patients admitted at Aga Khan University Hospital (AKUH), Internal Medicine Department between October 2018 and February 2019. The frequency and outcomes of discrepancies in patient diagnoses were noted among Emergency Department (ED) physician versus admitting physician, admitting physician versus discharge physician, and ED physician versus discharge physician for the full match, partial match, and mismatch diagnoses. The studied outcomes included interdepartmental transfer, Intensive Care Unit (ICU) transfer, in-hospital mortality, readmission within 30 days, and the length of stay. For simplicity, we only analyzed the factors for the discrepancy among ED physicians and discharge physicians.Results: Out of 537 admissions, there were 25.3-27.2% admissions with full match diagnoses while 18.6-19.4% and 45.3-47.9% had mismatch and partial match diagnoses respectively. The discrepancy resulted in an increased number of interdepartmental transfers (5-5.8%), ICU transfers (5.6-8.7%), in-hospital mortality (8-11%), and readmissions within 30 days in ED (14.4%-16.7%). A statistically significant difference was observed for the ward\u27s length of stay with the most prolonged stay in partially matched diagnoses (6.3 ± 5.4 days). Among all the factors that were evaluated for the diagnostic discrepancy, older age, multi-morbidities, level of trainee clerking the patient, review by ED faculty, incomplete history, and delay in investigations at ED were associated with significant discrepant diagnoses.Conclusions: Diagnostic discrepancies are a relevant and significant healthcare problem. Fixed patient or physician characteristics do not readily predict diagnostic discrepancies. To reduce the diagnostic discrepancy, emphasis should be given to good history taking and thorough physical examination. Patients with older age and multi-morbidity should receive significant consideration

Association of ABO blood group with delayed cerebral ischemia and clinical outcomes following aneurysmal subarachnoid hemorrhage in Pakistan

Background: The ABO blood type, due to its various hemostaseologic properties, has been associated with several vascular diseases, including aneurysmal subarachnoid hemorrhage (aSAH). However, the role of ABO blood type in delayed cerebral ischemia (DCI) onset and other clinical outcomes after aSAH is largely unexplored. This study aimed to investigate the association between ABO blood type and outcomes after aSAH, primarily DCI. Methods: A retrospective analysis was made on the data collected from 175 aSAH patients at a tertiary supraregional neurosurgery department over 5 years. Socio-demographic factors, clinical variables (DCI, mFG, WFNS grade, and Glasgow Outcome Scale at discharge), EVD placement, and aneurysm size were analyzed for their association with ABO blood type. Results: DCI was reported in 25% of patients with ‘O’ blood type and 9.6% with ‘non-O’ blood type. A stepwise logistic regression model showed that after adjusting for BMI, mFG, WFNS grade, and EVD placement, ‘O’ type blood group was an independent risk factor for DCI, greatly increasing the risk of DCI as compared to ‘non-O’ type groups (OR = 3.27, 95% CI: 1.21–8.82). Conclusion: This study provides evidence that individuals with ‘O’ blood type may have a higher risk of DCI onset after aSAH. However, further studies are essential to address the limitations of our work and confirm our findings

Reporting and interpretation of subgroup analyses in heart failure randomized controlled trials.

AimsThis study aimed to investigate the reporting of subgroup analyses in heart failure (HF) randomized controlled trials (RCTs) and to determine the strength and credibility of subgroup claims.Methods and resultsAll primary HF RCTs published in nine high-impact journals from 1 January 2008 to 31 December 2017 were included. Multivariable regression analysis was used to identify factors that may favour the reporting of results in specific subgroups. Strength of the subgroup effect claimed was classified into (i) strong, (ii) likely, or (iii) suggestive. Credibility of subgroup claim was scored using a pre-specified 10 pointer criteria. Of the 261 HF RCTs studied, 107 (41%) reported subgroup analyses. Twenty-five (23%) RCTs claimed a subgroup effect for the primary outcome of which six (24%) made a strong claim, eight (32%) claimed a likely effect, and 11 (44%) suggested a possible subgroup effect. Seven of the 25 RCTs did not employ interaction testing for subgroup claims of the primary outcome. Three out of 10 pre-specified credibility criteria were satisfied by half of the trials. Fourteen trials justified the choice of subgroups, and 10 explicitly stated they were underpowered to detect differences within subgroups. Source of funding did not influence the frequency of reporting subgroup analyses (OR 0.53, 95% CI 0.78-3.62, P = 0.52).ConclusionsAppropriate credibility criteria were rarely met even by HF RCTs that held strong subgroup claims. Subgroup analyses should be pre-specified, be adequately powered, present interaction terms, and be replicated in independent data before being integrated into clinical decision making

Reporting and interpretation of subgroup analyses in heart failure randomized controlled trials.

AimsThis study aimed to investigate the reporting of subgroup analyses in heart failure (HF) randomized controlled trials (RCTs) and to determine the strength and credibility of subgroup claims.Methods and resultsAll primary HF RCTs published in nine high-impact journals from 1 January 2008 to 31 December 2017 were included. Multivariable regression analysis was used to identify factors that may favour the reporting of results in specific subgroups. Strength of the subgroup effect claimed was classified into (i) strong, (ii) likely, or (iii) suggestive. Credibility of subgroup claim was scored using a pre-specified 10 pointer criteria. Of the 261 HF RCTs studied, 107 (41%) reported subgroup analyses. Twenty-five (23%) RCTs claimed a subgroup effect for the primary outcome of which six (24%) made a strong claim, eight (32%) claimed a likely effect, and 11 (44%) suggested a possible subgroup effect. Seven of the 25 RCTs did not employ interaction testing for subgroup claims of the primary outcome. Three out of 10 pre-specified credibility criteria were satisfied by half of the trials. Fourteen trials justified the choice of subgroups, and 10 explicitly stated they were underpowered to detect differences within subgroups. Source of funding did not influence the frequency of reporting subgroup analyses (OR 0.53, 95% CI 0.78-3.62, P = 0.52).ConclusionsAppropriate credibility criteria were rarely met even by HF RCTs that held strong subgroup claims. Subgroup analyses should be pre-specified, be adequately powered, present interaction terms, and be replicated in independent data before being integrated into clinical decision making