The Need to Rethink Harm Reduction for People Using Drugs Alone to Reduce Overdose Fatalities.

Background: During the ongoing opioid epidemic, Cuyahoga County (second largest in Ohio) reported overdose mortality rates (54/per 100,000) higher than the national average. Prior research demonstrates that people who use drugs often use alone but there is minimal research on people who died of overdose while using alone. The objective of this study is to examine sociodemographic, toxicologic, and injury characteristics, and emergency medical response to overdose decedents who died using drugs alone. Method: Data from the Cuyahoga County Medical Examiner's Office (2016-2020, N = 2944) on unintentional overdose deaths in adults was tabulated including socio-demographic, toxicologic, and injury-related information. Decedents using drugs alone were identified and compared to those not using alone via Chi-square and Fisher's exact tests. We further fit a multivariate logistic regression model to evaluate socio-demographic, toxicologic, and injury-related factors associated with increased odds of using alone. All results are reported with 95% confidence intervals. Result: Among decedents, 75% (n = 2205) were using drugs alone. Decedents using alone were more likely to be using drugs at home (p = 0.001) or be found dead at the scene (p < 0.001) and less likely to receive naloxone (p < 0.001) have other person/bystander, not using, present (p = 0.002). Using drugs at home (aOR = 1.61[1.19-2.20]) was associated with higher odds of using alone; and being married (aOR = 0.57[0.38-0.86]), having history of illicit drug use (aOR = 0.25[0.08-0.81]) and other person present, who was not using (aOR = 0.58[0.42-0.79]) were associated with lower odds of using alone. Conclusion: New harm reduction approaches targeting people using drugs alone are needed to reduce overdose deaths.

Trends in Cardiovascular Disease Mortality by County-Level Social Vulnerability Index in the United States.

Background Although cardiovascular mortality (CVM) rates in the United States have been declining overall, our study evaluated whether this holds true for areas with increased social deprivation. Methods and Results We used county-level cross-sectional age-adjusted CVM rates (aa-CVM) (2000-2019) linked to the Centers for Disease Control and Prevention Social Vulnerability Index (SVI-2010). We grouped counties as per SVI (Groups I 0-0.2, II 0.21-0.4, III 0.41-0.6, IV 0.61-0.8, and V 0.81-1) and calculated the relative change in the aa-CVM between 2000 to 2003 and 2016 to 2019. We used adjusted linear regression analyses to explore the association between a higher SVI and temporal aa-CVM improvement; we studied this temporal change in aa-CVM across subgroups of race, sex, and location. The median aa-CVM rate (per 100 000) was 272.6 (interquartile range [IQR]: 237.5-311.7). The aa-CVM was higher in men (315.6 [IQR: 273.4-363.9]) than women (221.3 [IQR: 189.6-256.7]), and in Black residents (347.2 [IQR: 301.1-391.1]; P<0.001) than White residents (258.9 [IQR: 226-299.1]; P<0.001). The aa-CVM for SVI I (233.6 [IQR: 214.8-257.0]) was significantly lower than that of group V (323.6 [IQR: 277.2-359.2]; P<0.001). The relative reduction in CVM was significantly higher for SVI group I (32.2% [IQR: 24.2-38.4]) than group V (27.2% [IQR: 19-34.1]) counties. After multivariable adjustment, a higher SVI index was associated with lower relative improvement in the age-adjusted CVM (model coefficient -3.11 [95% CI, -5.66 to -1.22]; P<0.001). Conclusions Socially deprived counties in the United States had higher aa-CVM rates, and the improvement in aa-CVM over the past 20 years was lower in these counties.

A case study for local data surveillance in opioid overdose fatalities in Cuyahoga County, OH 2016-2020.

Introduction: Fentanyl and fentanyl analogs have increased the overdose mortality rates in the United States, significantly impacting states like Ohio. We examined carfentanil overdose deaths, other contributing Cause of Death (COD) drugs, and drug seizure trends from 2016 to 2020 in Northeast Ohio. Materials and methods: We studied death investigation data from the Cuyahoga County, Ohio Medical Examiner's Office (CCMEO) of all fatal accidental opioid overdoses as well as drug seizure data from Cuyahoga County Regional Forensic Science Laboratory (CCRFSL). We also compared decedents' race, gender, age, residential locality, drugs contributing to the COD in opioid cases, and for carfentanil, fentanyl, and cocaine seizures in Cuyahoga County from 2016 to 2020 (N = 2948). Results: Decedents' had an average of three different drugs contributing to their COD. A bimodal carfentanil spike was observed in fatal accidental overdoses in Cuyahoga County for the years 2017 and 2019. Decedents in urban residency, who were Non-Hispanic, White and younger, significantly predicted the presence of carfentanil contributing to the COD. In 2020, decedents who were Black and older were significantly associated with cocaine contributing to the COD. Carfentanil and carfentanil-related overdoses were significantly correlated. Discussion: The pervasiveness of illicitly manufactured fentanyl and fentanyl analog (e.g., carfentanil) mixtures with other drugs are changing the demographics of persons who fatally overdose in Cuyahoga County, OH. Significant trending shifts can also be observed for the presence of carfentanil in decedent and seizure county data. Conclusions: Local data of drug-related overdose deaths and drug seizures from a medical examiner's office and affiliated forensic laboratory lab can be used for timely public health surveillance, and informing prevention, and intervention at the county level.

Systematic review and meta-analysis: a brief introduction.

LEARNING OBJECTIVES: 1. Understand the basic structure and parts of a systematic review 2. Be able to read and critically appraise a published systematic review.

Model-free estimates that complement information obtained from the hazard ratio.

Understand the limitations of the modeling of survival data, especially as pertains to the Cox proportional hazards model.An introduction to model-free estimates of survival, namely, the restricted mean survival time/restricted mean lost time.Use R (The R Foundation for Statistical Computing, Austria) or STATA® (The STATACorp, College Station, TX, USA) to perform analyses and obtain these parameters from a dataset. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s12055-021-01167-4.

Survival analysis-part 3: intermediate events and the importance of competing risks.

LEARNING OBJECTIVES: Understand what events can be labelled as intermediate events in survival analysis.Understand why the Kaplan and Meier method cannot be used in the presence of competing events.Regression analysis in the presence of competing events.

Survival analysis-part 2: Cox proportional hazards model.

Learning objectives: 1. To understand the log-rank test and limitations of the log-rank test in comparing survival between groups. 2. To understand the fundamental concepts of the proportional hazards assumption. 3. To understand basic steps in the development of the Cox proportional hazards model and reported hazard ratios. 4. To understand how results of a Cox model run using STATA© (a commonly used proprietary statistical software) can be understood and interpreted. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s12055-020-01108-7.

The fentanyl phase of the opioid epidemic in Cuyahoga County, Ohio, United States.

Since late 2014, fentanyl has become the major driver of opioid mortality in the United States. However, a descriptive analysis of fentanyl victims is limited. We studied the 2016 fentanyl and heroin overdose deaths and compared them to previously studied heroin-associated fatalities from 2012 over a wide range of demographic and investigative variables, including overdose scene findings, toxicology results, and prescription drug history. We observed a significant increase in fentanyl-related deaths (n = 421, 2016) versus heroin deaths (n = 160, 2012) but the baseline demographics between both cohorts remained similar. Victims were predominantly of ages 35-64 years (60%-64%), White (83%-85%), and male (73%-76%). 2016 fentanyl decedents were more likely to have naloxone administered upon overdose, and the majority still had a positive prescription history for a controlled substance. Toxicology data showed a decrease in mean morphine and 6-monoacetylmorphine concentrations when cointoxication with fentanyl occurred. Our study emphasizes the medical examiner's role as a public health data source and bridge between different stakeholders combating the opioid epidemic.

Stability After Initial Decline in Coronary Revascularization Rates in the United States.

BACKGROUND: It remains uncertain how advances in revascularization techniques, availability of new evidence, and updated guidelines have influenced the annual rates of coronary revascularization in the United States. METHODS: We used the Nationwide Inpatient Sample data from 2005 to 2014 with appropriate weighting to determine national procedural volumes. To present accurately overall percutaneous coronary intervention (PCI) rates, PCI with same-day discharge numbers per year were estimated from the available literature and added to annual PCI procedures performed. RESULTS: Annual PCI rate declined from 353 per 100,000 adults in 2005 to 277 per 100,000 adults in 2009 (P < .001) but remained stable thereafter (P = .50). Annual coronary artery bypass grafting (CABG) rate declined steadily, at a shallower slope than PCI, from 120 per 100,000 in 2005 to 93 per 100,000 in 2009 (P = .02) but remained stable thereafter (P = .60). Similar trends were seen in men and women. Both PCI and CABG rates were lower in women than men over the study period (PCI, 482 to 324/100,000 in men vs 232 to 153/100,000 in women; CABG, 172 to 118/100,000 in men vs 64 to 38/100,000 in women). Annual PCI rates were higher than CABG rates in patients of all age groups including in younger patients (age < 50) and octogenarians. The proportion of coronary revascularization procedures performed per insurance type remained relatively similar across the study period. CONCLUSIONS: Annual rates of coronary revascularization have changed significantly over time, potentially because of advances in revascularization techniques, availability of new evidence, and updated guidelines. Rates of PCI declined more steeply than CABG before plateauing but remained higher than rates of CABG across the study period.

Risk Calculator to Predict 30-Day Readmission After Coronary Artery Bypass: A Strategic Decision Support Tool.

BACKGROUND: Re-admission is an important source of patient dissatisfaction and increased hospital costs. A simple calculator to determine the probability of re-admission may help guide patient dismissal planning. METHODS: Using the national readmissions database (NRD), we identified admissions for isolated primary coronary artery bypass (CABG) and stratified them according to 30-day readmission. Including pre, intra and postoperative variables, we prepared a logistic regression model to determine the probability for re-admission. The model was tested for reliability with boot-strapping and 10-fold cross-validation. RESULTS: From 135,699 procedures, 19,355 were readmitted at least once within 30days of dismissal. Patients who were readmitted were older (67±10 vs 65 ± 10 years, p<0.01), females (32% vs 24%; p<0.01) and had a higher Elixhauser comorbidity score (1.5±1.4 vs 1.1±1.2; p<0.01). Our final model (c- statistic=0.65) consisted of 16 pre and three postoperative factors. End-stage renal disease (OR 1.79 [1.57-2.04]) and length of stay>9days (OR 1.60 [1.52-1.68]) were most prominent indicators for readmission. Compared to Medicaid beneficiaries, those with private insurance (OR 0.62 [0.57-0.68]) and Medicare (OR 0.85 [0.79-0.92]) coverage were less likely to be readmitted. CONCLUSIONS: Our simple 30-days CABG readmission calculator can be used as a strategic tool to help reduce readmissions after coronary artery bypass surgery.

Clinical, endoscopic, and histological differentiations between Crohn's disease and intestinal tuberculosis.

OBJECTIVES: The clinical, endoscopic, and histological features of Crohn's disease (CD) and intestinal tuberculosis mimic each other so much that it becomes difficult to differentiate between them. The aim was to find out clinical, endoscopic, and histological predictor features for differentiation between CD and intestinal tuberculosis. METHODS: We recruited 106 patients, 53 each with CD and intestinal tuberculosis, in this study. The clinical, histological, and endoscopic features were subjected to univariate, bivariate, and multivariate analyses. On the basis of regression coefficients of the final multivariate logistic model, a score to discriminate between CD and intestinal tuberculosis was devised. For the validation of the score, the same model was tested on 20 new patients, each with CD and intestinal tuberculosis. RESULTS: On univariate analysis, although longer duration of disease, chronic diarrhea, blood in stool, perianal disease, extra-intestinal manifestations, involvement of left colon, skip lesions, aphthous ulcers, cobblestoning, longitudinal ulcers, focally enhanced colitis, and microgranulomas were significantly more common in CD, partial intestinal obstruction, constipation, presence of nodular lesions, higher number, and larger granulomas were significantly more common in intestinal tuberculosis. On multivariate analysis, blood in stool (odds ratio (OR) 0.1 (confidence interval (CI) 0.04-0.5)), weight loss (OR 9.8 (CI 2.2-43.9)), histologically focally enhanced colitis (OR 0.1 (CI 0.03-0.5)), and involvement of sigmoid colon (OR 0.07(0.01-0.3)) were independent predictors of intestinal tuberculosis. On the basis of regression coefficients of the final multivariate logistic model, a score that varied from 0.3 to 9.3 was devised. Higher score predicted more likelihood of intestinal tuberculosis. Once the cutoff was set at 5.1, then the sensitivity, specificity, and ability to correctly classify the two diseases were 83.0, 79.2, and 81.1%, respectively. Area under the curve for receiver-operating characteristic (ROC) to assess the ability of these features to discriminate between CD and intestinal tuberculosis was 0.9089. The area under ROC in the validation data set was 89.2% (95% CI 0.79-0.99). With a similar cutoff score of 5.1, sensitivity and specificity in the validation model were 90% (95% CI 66.9-98.2) and 60% (95% CI 36.4-80.0), respectively. CONCLUSIONS: Blood in stool, weight loss, focally enhanced colitis, and involvement of the sigmoid colon were the most important features in differentiating CD from intestinal tuberculosis.

Spectrum of microscopic colitis in a tertiary care centre in India.

INTRODUCTION: The incidence of microscopic colitis has recently increased. Although collagenous colitis and lymphocytic colitis are the two main subtypes of microscopic colitis, many patients may not fit into either category and are thus included under the header nonspecific colitis. Of late, the spectrum of microscopic colitis has widened to include minimal change colitis, microscopic colitis not otherwise specified and microscopic colitis with giant cells. There is a lack of information concerning the spectrum of microscopic colitis in Asia. METHOD: In a retrospective analysis, case records of 29 patients diagnosed with microscopic colitis between 1999-2005 were analysed. Drug use parasitic infection and common bacterial infections were excluded. Colonoscopic/ sigmoidoscopic examination was done and multiple colonic mucosal biopsies were stained serially with haematoxylin and eosin for detailed histological examination and Masson trichrome for sub-epithelial collagen band. Based on histological criteria, patients were categorised into five subtypes: collagenous colitis (presence of collagenous thickening of surface epithelium basement membrane > 10 microm), lymphocytic colitis (intra-epithelial lymphocytes more than 20 per 100 colonocytes), minimal change colitis (crypt architectural abnormality in the form of cryptitis and crypt dilatation in the absence of increase in intraepithelial lymphocytes and subepithelial collagenous band), microscopic colitis not otherwise specified (increased inflammatory cell infiltrates in the lamina propria in the absence of other abnormalities) and microscopic colitis with giant cells. RESULTS: Mean age of patients was 38.59 years (range 12-62). Of 29 patients with microscopic colitis, 7 (24.1%), 4 (13.8%), 7 (24.1%) and 11 (37.9%) were classified as collagenous colitis, lymphocytic colitis, minimal change colitis and microscopic colitis not otherwise specified, respectively. None of these patients had giant cells. There was no significant correlation between disease type and clinical manifestations. CONCLUSION: Microscopic colitis has a wide histological spectrum. Cases reported as non-specific colitis, may be categorised into definite subtypes of microscopic colitis.