1
|
Nørgaard M, Nielsson MS, Heide-Jørgensen U. Birth and Neonatal Outcomes Following Opioid Use in Pregnancy: A Danish Population-Based Study. Subst Abuse 2015; 9:5-11. [PMID: 26512202 PMCID: PMC4599593 DOI: 10.4137/sart.s23547] [Citation(s) in RCA: 33] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 07/02/2015] [Revised: 09/03/2015] [Accepted: 09/07/2015] [Indexed: 01/10/2023]
Abstract
BACKGROUND Few population-based data exist on birth outcomes in women who received opioid maintenance treatment during pregnancy. We therefore examined adverse birth outcomes in women exposed to methadone or buprenorphine during pregnancy and the risk of neonatal abstinence syndrome (NAS) among neonates exposed to buprenorphine, methadone, and/or heroin in utero. PATIENTS AND METHODS This study included all female Danish residents with a live birth or a stillbirth from 1997 to 2011. We identified the study population, use of opioids and opioid substitution treatment, birth outcomes, and NAS through medical registers. Birth outcomes included preterm birth (born before 38th gestational week), low-birth weight (LBW) (<2,500 g, restricted to term births), small for gestational age (SGA) (weight <2 standard deviations from the sex- and gestational-week-specific mean), congenital malformations, and stillbirths. We used log-binomial regression to estimate the prevalence ratio (PR) for birth outcomes. RESULTS Among 950,172 pregnancies in a total of 571,823 women, we identified 557 pregnancies exposed to buprenorphine, methadone, and/or heroin (167 to buprenorphine, 197 to methadone, 28 to self-reported heroin, and 165 to combinations). Compared with nonexposed pregnancies, prenatal opioid use was associated with greater prevalence of preterm birth (PR of 2.8 (95% confidence interval (CI), 2.3–3.4)), LBW among infants born at term (PR of 4.3 (95% CI, 3.0–6.1)), and being SGA (PR of 2.7 (95% CI, 1.9–4.3)). Restricting the analyses to women who smoked slightly lowered these estimates. The prevalence of congenital malformations was 8.3% in opioid-exposed women compared with 4.2% in nonexposed women (PR of 2.0 (95% CI, 1.5–2.6)). The risk of NAS ranged from 7% in neonates exposed to buprenorphine only to 55% in neonates exposed to methadone only or to opioid combinations. CONCLUSION The maternal use of buprenorphine and methadone during pregnancy was associated with increased prevalence of adverse birth outcomes, and this increase could only be explained to a smaller extent by increased prevalence of smoking. The risk of NAS was eight-fold higher in methadone-exposed neonates than that in buprenorphine-exposed neonates, but this difference may at least partly be explained by differences in underlying indications (analgesic versus opioid maintenance treatment) between the two groups.
Collapse
Affiliation(s)
- Mette Nørgaard
- Department of Clinical Epidemiology, Institute of Clinical Medicine, Aarhus University Hospital, Aarhus, Denmark
| | - Malene Schou Nielsson
- Department of Clinical Epidemiology, Institute of Clinical Medicine, Aarhus University Hospital, Aarhus, Denmark
| | - Uffe Heide-Jørgensen
- Department of Clinical Epidemiology, Institute of Clinical Medicine, Aarhus University Hospital, Aarhus, Denmark
| |
Collapse
|
2
|
Valkhoff VE, Coloma PM, Masclee GMC, Gini R, Innocenti F, Lapi F, Molokhia M, Mosseveld M, Nielsson MS, Schuemie M, Thiessard F, van der Lei J, Sturkenboom MCJM, Trifirò G. Validation study in four health-care databases: upper gastrointestinal bleeding misclassification affects precision but not magnitude of drug-related upper gastrointestinal bleeding risk. J Clin Epidemiol 2014; 67:921-31. [PMID: 24794575 DOI: 10.1016/j.jclinepi.2014.02.020] [Citation(s) in RCA: 45] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2013] [Revised: 02/11/2014] [Accepted: 02/21/2014] [Indexed: 01/12/2023]
Abstract
OBJECTIVE To evaluate the accuracy of disease codes and free text in identifying upper gastrointestinal bleeding (UGIB) from electronic health-care records (EHRs). STUDY DESIGN AND SETTING We conducted a validation study in four European electronic health-care record (EHR) databases such as Integrated Primary Care Information (IPCI), Health Search/CSD Patient Database (HSD), ARS, and Aarhus, in which we identified UGIB cases using free text or disease codes: (1) International Classification of Disease (ICD)-9 (HSD, ARS); (2) ICD-10 (Aarhus); and (3) International Classification of Primary Care (ICPC) (IPCI). From each database, we randomly selected and manually reviewed 200 cases to calculate positive predictive values (PPVs). We employed different case definitions to assess the effect of outcome misclassification on estimation of risk of drug-related UGIB. RESULTS PPV was 22% [95% confidence interval (CI): 16, 28] and 21% (95% CI: 16, 28) in IPCI for free text and ICPC codes, respectively. PPV was 91% (95% CI: 86, 95) for ICD-9 codes and 47% (95% CI: 35, 59) for free text in HSD. PPV for ICD-9 codes in ARS was 72% (95% CI: 65, 78) and 77% (95% CI: 69, 83) for ICD-10 codes (Aarhus). More specific definitions did not have significant impact on risk estimation of drug-related UGIB, except for wider CIs. CONCLUSIONS ICD-9-CM and ICD-10 disease codes have good PPV in identifying UGIB from EHR; less granular terminology (ICPC) may require additional strategies. Use of more specific UGIB definitions affects precision, but not magnitude, of risk estimates.
Collapse
Affiliation(s)
- Vera E Valkhoff
- Department of Medical Informatics, Erasmus University Medical Center, Wytemaweg 80, 3015 CN, Rotterdam, The Netherlands; Department of Gastroenterology and Hepatology, Erasmus University Medical Center, Wytemaweg 80, 3015 CN, Rotterdam The Netherlands
| | - Preciosa M Coloma
- Department of Medical Informatics, Erasmus University Medical Center, Wytemaweg 80, 3015 CN, Rotterdam, The Netherlands
| | - Gwen M C Masclee
- Department of Medical Informatics, Erasmus University Medical Center, Wytemaweg 80, 3015 CN, Rotterdam, The Netherlands; Department of Gastroenterology and Hepatology, Erasmus University Medical Center, Wytemaweg 80, 3015 CN, Rotterdam The Netherlands
| | - Rosa Gini
- Agenzi Regionali di Sanità della Toscana, Via Pietro Dazzi 1 - 50141, Firenze, Italy
| | - Francesco Innocenti
- Health Search, Italian College of General Practitioners, Via del Pignoncino, 9-11,50142, Florence, Italy
| | - Francesco Lapi
- Centre for Clinical Epidemiology, Jewish General Hospital, 3755 Côte-Sainte-Catherine Road, Montréal, QC H3T 1E2, Canada; Department of Preclinical and Clinical Pharmacology, University of Florence, Piazza di San Marco, 4, 50121 Firenze, Italy
| | - Mariam Molokhia
- Department of Primary Care and Public Health Sciences, Kings College London, Division of Health and Social Care Research, 7th Floor, Capital House, 42 Weston Street, London SE1 3QD, United Kingdom
| | - Mees Mosseveld
- Department of Medical Informatics, Erasmus University Medical Center, Wytemaweg 80, 3015 CN, Rotterdam, The Netherlands
| | - Malene Schou Nielsson
- Department of Clinical Epidemiology, Aarhus University Hospital, Olof Palmes Allé 43-45 DK-8200 Aarhus N, Denmark
| | - Martijn Schuemie
- Department of Medical Informatics, Erasmus University Medical Center, Wytemaweg 80, 3015 CN, Rotterdam, The Netherlands
| | - Frantz Thiessard
- LESIM, ISPED, Universite Bordeaux 2', 146 Rue Léo Saignat, 33076 Bordeaux, France
| | - Johan van der Lei
- Department of Medical Informatics, Erasmus University Medical Center, Wytemaweg 80, 3015 CN, Rotterdam, The Netherlands
| | - Miriam C J M Sturkenboom
- Department of Medical Informatics, Erasmus University Medical Center, Wytemaweg 80, 3015 CN, Rotterdam, The Netherlands; Department of Epidemiology, Erasmus University Medical Center, Wytemaweg 80, 3015 CN, Rotterdam, The Netherlands
| | - Gianluca Trifirò
- Department of Medical Informatics, Erasmus University Medical Center, Wytemaweg 80, 3015 CN, Rotterdam, The Netherlands; Department of Clinical and Experimental Medicine and Pharmacology, Via Consolare Pompea, 1, Messina, University of Messina, Italy.
| | | |
Collapse
|
3
|
Coloma PM, Valkhoff VE, Mazzaglia G, Nielsson MS, Pedersen L, Molokhia M, Mosseveld M, Morabito P, Schuemie MJ, van der Lei J, Sturkenboom M, Trifirò G. Identification of acute myocardial infarction from electronic healthcare records using different disease coding systems: a validation study in three European countries. BMJ Open 2013; 3:bmjopen-2013-002862. [PMID: 23794587 PMCID: PMC3686251 DOI: 10.1136/bmjopen-2013-002862] [Citation(s) in RCA: 92] [Impact Index Per Article: 8.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/04/2022] Open
Abstract
OBJECTIVE To evaluate positive predictive value (PPV) of different disease codes and free text in identifying acute myocardial infarction (AMI) from electronic healthcare records (EHRs). DESIGN Validation study of cases of AMI identified from general practitioner records and hospital discharge diagnoses using free text and codes from the International Classification of Primary Care (ICPC), International Classification of Diseases 9th revision-clinical modification (ICD9-CM) and ICD-10th revision (ICD-10). SETTING Population-based databases comprising routinely collected data from primary care in Italy and the Netherlands and from secondary care in Denmark from 1996 to 2009. PARTICIPANTS A total of 4 034 232 individuals with 22 428 883 person-years of follow-up contributed to the data, from which 42 774 potential AMI cases were identified. A random sample of 800 cases was subsequently obtained for validation. MAIN OUTCOME MEASURES PPVs were calculated overall and for each code/free text. 'Best-case scenario' and 'worst-case scenario' PPVs were calculated, the latter taking into account non-retrievable/non-assessable cases. We further assessed the effects of AMI misclassification on estimates of risk during drug exposure. RESULTS Records of 748 cases (93.5% of sample) were retrieved. ICD-10 codes had a 'best-case scenario' PPV of 100% while ICD9-CM codes had a PPV of 96.6% (95% CI 93.2% to 99.9%). ICPC codes had a 'best-case scenario' PPV of 75% (95% CI 67.4% to 82.6%) and free text had PPV ranging from 20% to 60%. Corresponding PPVs in the 'worst-case scenario' all decreased. Use of codes with lower PPV generally resulted in small changes in AMI risk during drug exposure, but codes with higher PPV resulted in attenuation of risk for positive associations. CONCLUSIONS ICD9-CM and ICD-10 codes have good PPV in identifying AMI from EHRs; strategies are necessary to further optimise utility of ICPC codes and free-text search. Use of specific AMI disease codes in estimation of risk during drug exposure may lead to small but significant changes and at the expense of decreased precision.
Collapse
Affiliation(s)
- Preciosa M Coloma
- Department of Medical Informatics, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - Vera E Valkhoff
- Department of Medical Informatics, Erasmus MC University Medical Center, Rotterdam, The Netherlands
- Department of Gastroenterology and Hepatology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - Giampiero Mazzaglia
- Department of Research, Health Search, Italian College of General Practitioners, Florence, Italy
| | | | - Lars Pedersen
- Department of Clinical Epidemiology, Aarhus University Hospital, Aarhus, Denmark
| | - Mariam Molokhia
- Primary Care and Population Sciences, Kings College, London, UK
| | - Mees Mosseveld
- Department of Medical Informatics, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - Paolo Morabito
- Department of Clinical and Experimental Medicine and Pharmacology, University of Messina, Messina, Italy
| | - Martijn J Schuemie
- Department of Medical Informatics, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - Johan van der Lei
- Department of Medical Informatics, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - Miriam Sturkenboom
- Department of Medical Informatics, Erasmus MC University Medical Center, Rotterdam, The Netherlands
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - Gianluca Trifirò
- Department of Medical Informatics, Erasmus MC University Medical Center, Rotterdam, The Netherlands
- Department of Clinical and Experimental Medicine and Pharmacology, University of Messina, Messina, Italy
| | | |
Collapse
|
4
|
Nielsson MS, Erichsen R, Frøslev T, Taylor A, Acquavella J, Ehrenstein V. Positive predictive values of the coding for bisphosphonate therapy among cancer patients in the Danish National Patient Registry. Clin Epidemiol 2012; 4:233-6. [PMID: 22977313 PMCID: PMC3437793 DOI: 10.2147/clep.s32868] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022] Open
Abstract
BACKGROUND The purpose of this study was to estimate the positive predictive value (PPV) of the coding for bisphosphonate treatment in selected cancer patients from the Danish National Patient Registry (DNPR). METHODS Through the DNPR, we identified all patients with recorded cancer of the breast, prostate, lung, kidney, and with multiple myeloma. We restricted the study sample to patients with bisphosphonate treatment recorded during an admission to Aalborg Hospital, Denmark, from 2005 through 2009. We retrieved and reviewed medical records of these patients from the initial cancer diagnosis onwards to confirm or rule out bisphosphonate therapy. We calculated the PPV of the treatment coding as the proportion of patients with confirmed bisphosphonate treatment. RESULTS We retrieved and reviewed the medical records of 60 cancer patients with treatment codes corresponding to bisphosphonate therapy. Recorded code corresponded to treatment administered intravenously for 59 of 60 patients, corresponding to a PPV of 98.3% (95% confidence interval 92.5-99.8). In the remaining patient, bisphosphonate treatment was also confirmed but was an orally administered bisphosphonate; thus, the treatment for any bisphosphonate regardless of administration was confirmed for all 60 patients (PPV of 100%, 95% confidence interval 95.9-100.0). CONCLUSION The PPV of bisphosphonate treatment coding among cancer patients in the DNPR is very high and the recorded treatment nearly always corresponds to intravenous administration.
Collapse
|
5
|
Ording AG, Nielsson MS, Frøslev T, Friis S, Garne JP, Søgaard M. Completeness of breast cancer staging in the Danish Cancer Registry, 2004-2009. Clin Epidemiol 2012; 4 Suppl 2:11-6. [PMID: 22936852 PMCID: PMC3429150 DOI: 10.2147/clep.s31574] [Citation(s) in RCA: 21] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022] Open
Abstract
Background The purpose of this study was to investigate the completeness of TNM (Tumor, Node, Metastasis) staging for breast cancer in the Danish Cancer Registry. Methods We identified 26,488 patients with a first diagnosis of breast cancer between 2004 and 2009 from the Danish Cancer Registry. We obtained information on comorbidity through the Danish National Patient Registry. We estimated the completeness of TNM registration in the Danish Cancer Registry and stratified the analysis by gender, age, year of cancer diagnosis, and comorbidity. We designed an algorithm categorizing breast cancer into localized, regional, distant, or unknown stage based on TNM codes. Results The overall completeness of TNM registration was 85.4%. The completeness varied little by gender and study year, but decreased from 91.3% in patients aged 0–39 years to 57.0% in patients aged 80 years or more, and from 87.9% among patients with a low level of comorbidity to 69.7% among patients with a high level of comorbidity. Conclusion The completeness of the TNM registration varied substantially by age and level of comorbidity. Thus, depending on the outcome under study, stage-specific analyses may yield biased results. The completeness of TNM should be considered in study designs using TNM information.
Collapse
|