Prevalence of drug-drug interactions in pediatrics with cardiac disorders receiving off label drugs- a cross-sectional study

doi:10.21203/rs.3.rs-4919942/v1

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Prevalence of drug-drug interactions in pediatrics with cardiac disorders receiving off label drugs- a cross-sectional study

https://doi.org/10.21203/rs.3.rs-4919942/v1

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Background: Evidence based medical interventions have improved outcomes of cardiovascular diseases, however, pediatric therapy is still based on clinical experience and extrapolation of adult data. Lack of evidence-based therapy increases the exposure of children to off-label (OL) drugs and clinically significant drug-drug interactions (CSDDIs) ultimately leading to adverse drug reactions. This study evaluated the prevalence of CSDDIs, OL drug use and the associated predictors.

Methodology: A cross-sectional study was designed to assess prevalence of CSDDIs and OL prescriptions in 250 patients admitted to pediatric cardiology ward of Hayatabad Medical Complex, Pakistan. DDIs of major severity were categorized as CSDDI. Association of various predictors including OL drug use with CSDDIs was evaluated using logistic regression.

Result: Of the total 250 pediatric patients, 28.6% patients were exposed to at least one clinically significant DDI, while 228 (91.20%) patients received at least one OL prescription. Furosemide was the most frequently prescribed drug involved in CSDDIs, while it was also one of the highly prescribed OL drug. Multivariate analysis revealed that, adolescent age group (OR 12.795; CI 3.077-53.198) and patients prescribed > 5 drugs (OR 3.544; CI 1.906-6.589) were significantly 12.7 and 3.5 times more likely to experience CSDDIs in reference to their corresponding categories. Conclusion: A high prevalence of CSDDIs and OL prescriptions was observed. OL drug presence was also observed to be a significant predictor associated with an increased risk of CSDDIs. Thus, to improve pediatric pharmacotherapy suitable medical interventions are required to decrease OL drug use and CSDDIs.

Clinically significant Drug drug interactions

Off label drug use

Predictor

Cardiology ward

Pakistan

Improvements in the treatment outcomes of cardiovascular diseases can be ascribed mainly to the expanded use of evidence based medical interventions. However, the research leading to this approach misrepresented certain populations including women, elderly and children [1, 2]. Pediatric population commonly encounter acute diseases and a relatively smaller population have a chronic condition causing fewer patients to be enrolled in clinical trials to establish the safety and efficacy of drugs [3]. Other factors that hinder pharmaceutical companies to invest in pediatric trials are the high financial expenses and low returns form new pediatric drugs, strict guidelines and ethical concerns to include children in clinical trial [4]. Despite legislations being implemented by Food and drug administration modernization act (FDAMA) and European Union (EU), pediatric population is still being underrepresented in clinical trials [5].

Pediatric therapy is mostly based on clinical experience and extrapolation of adult data, rather than clinical trials. Thus majority of the drugs prescribed to pediatrics are not well studied and not labelled for use in children, [6] but this does not imply that a drug is contraindicated for use, rather means that inadequate data are available to give approved status to a drug and the risks or benefits of using a drug in a particular condition has not been determined yet [5]. In reference to all the factors, pediatricians face a tough choice to either prescribe a medication despite lack of evidence in pediatric population or deprive the child of a medication that can potentially be a better therapeutic option [6].

Pediatric population are exposed to a high number of CSDDIs [7]. These often lead to serious adverse outcomes like ketorolac when administered with ibuprofen causes gastrointestinal bleeding or perforation, metoclopramide with promethazine can cause extrapyramidal effects, fentanyl with morphine can cause additive respiratory depression and lidocaine with propofol can cause additive hypnotic effect of propofol [7]. Common predictors for CSDDIs are prescribed drugs and age groups [8, 9]. However, off label (OL) drug use has never been considered as a predictor for the occurrence of CSDDIs. The objectives of the study were to report the prevalence of CSDDIs and its predictors at a pediatric cardiology ward in a tertiary care hospital of Peshawar, Pakistan.

A prospective cross-sectional study was conducted at pediatric cardiology ward in Hayatabad Medical Complex (HMC), a government tertiary care setup in Peshawar, Pakistan. Pediatric patients from the rural, urban and suburban areas of northwestern region of Pakistan and Afghanistan visit HMC for treatment. A sample of 277 patients admitted to the pediatric cardiology ward between January 2023 and June 2023 was obtained from the Information Technology (IT) department of the hospital, as the hospital lacks an electronic health record (EHR) system.

2.1 Ethical Consent

The study was approved by the ethical committees of the hospital through letter number 8075-79/HMC. Ethical principles under the declaration of Helsinki were followed [10]. Protected Health Information (PHI) of patients were coded and stored in a secured location.

2.2 Patient selection

Sample size was calculated using the formula for known populations,[11] which resulted in sample of 250 patients. Patients with a stay of 24 hours in pediatric cardiology ward were included in the study. Patients’ drug profiles lacking relevant information required for the study were excluded. IV stock’s solutions, oxygen therapy and topical medicines were also excluded. Simple random sampling was employed to collect patient data from the cohort. A predesigned proforma was used to collect patient demographics and clinical profiles which included details about diagnosis, stay, prescribed drugs, dose, frequency and duration of regimen. All the data was collected manually from clinical drug profiles of patients. Patient data was evaluated using Thomson healthcare Micromedex® DrugDex and DrugReax (Watson health, IBM Corporation).

2.3 Definition of variables

Pediatrics age was categorized according to WHO classification as infants (age 0–2 years), children (2–12 years) and adolescent (12 to 18 years) [12]. Off label drug use was defined as the use of drug outside information labelled on the product license. Categories for off label drug use were (1) the drug not approved for specific age of pediatric (2) use of a drug for a specific indication not approved (3) dose administered not mentioned in labelled information (4) dosage form used other than approved ones [13]. DDIs were screened using Micromedex® Drug Reax which classifies DDIs based on severity, documentation and onset DDIs with a major severity were considered to be CSDDIs and included in the regression analyses [14].

2.4 Statistical analysis

Statistical analysis was performed using IBM SPSS Statistics for Windows, version 20. (Armonk, NY: IBM Corp.). Descriptive analysis of patient characteristics and clinical outcomes were performed. Univariate binary logistic regression was employed to calculate odds ratio with 95% confidence interval for predictors of CSDDIs, including age, number of prescribed drugs, hospital stay and off label drugs. Predictors with a significant association were further included in a multivariate binary logistic regression model. Medians were used to group the predictors (number of prescribed drugs, hospital stay) for regression analysis.

3.1 Patient demographics

The profiles of 250 patients were screened, of which male patients (55.60%) and infant age group (57.60%) were prevalent. Median number of prescribed drugs and hospital stay was 5, while 61.5% patients were prescribed ≥ 5 drugs and 51.6% had a hospital stay of ≥ 5 days. Out of total 228 patients who receiving at least one-off label drug, 82 (38.5%) patients were exposed to CSDDIs as shown in Table 1. Adolescent age group (P < 0.000), prescribed drugs ≥ 5 (P < 0.000) and off label drug use (P < 0.035) were significantly associated with the occurrence of clinically significant DDI.

Table 1

General characteristics of patients in pediatric cardiology ward
Variables		Clinically Significance		Total	P value
Variables		Clinically significant	Clinically insignificant	Total	P value
Gender	Male	96	43	139	0.252
	Female	69	42	111
	Total	165	85	250
Age groups	Infants	106	38	144	0.000***
	Children	55	33	88
	Adolescent	4	14	18
	Total	165	85	250
Prescribed drugs	≤ 5 drugs	120	33	153	0.000***
	< 5 drugs	45	52	97
	Total	165	85	250
Hospital stays	≤ 5 days	90	39	129	0.194*
	< 5 days	75	46	121
	Total	165	85	250
Patients receiving at least one Off label drug	Yes	146	82	228	0.035**
	No	19	3	22
	Total	165	85	250
* All categories’ values were calculated for 250 patients
Significant at p < 0.1 significant at p < 0.05 *significant at p < 0.01*

International statistical classification of disease and related health problems (ICD 10) system was used to categorize diagnosis. Cardiomyopathy (15.60%) was the most frequent diagnosis followed by ventricular septal defect (14.00%), tetralogy of fallot (8.00%), patent ductus arteriosus (6.00%), secundum atrial septal defect (4.80%), dilated dysfunction left ventricle (3.60%), pulmonary hypertension of newborn (3.60%), pulmonary valve stenosis (3.20%), atrioventricular septal defect (2.80%) and rheumatic heart disease (2.80%). Other diagnoses included pneumonia (9.20%) and lower respiratory tract infections (2.8%).

3.2 Prescribed drugs and dosing

Drugs were categorized according to Anatomical Therapeutic Chemical (ATC) Classification system. Anti-bacterials (27.21%), diuretics (25.35%), angiotensin converting enzyme (ACE) inhibitor (7.64%), anti-anemic (7.07%) and anti-coagulant (6.94%) were frequently prescribed drug classes in the pediatric cardiology unit.

A total of 64 different drugs were prescribed 1232 times. Commonly prescribed drugs included furosemide (13.97%), spironolactone (11.29%), co-amoxiclav (10.32%), captopril (9.34%), cefazolin (5.69%), aspirin (4.87%), paracetamol (4.31%), iron (3.82%), folic acid (2.92%) and ceftriaxone (2.68%). Of the total patients, 17.12% were prescribed drugs in sub-therapeutic doses and 0.97% in overdoses. Intravenous drugs prescribed frequently in sub-therapeutics doses included furosemide (163 times) and co-amoxiclav (116 times) while oral drugs included captopril (134 times) and spironolactone (124 times). Frequently prescribed intravenous drug in over doses included furosemide (11 times) and cefazolin (10 times) while oral drugs included captopril (13 times) and spironolactone (8 times),

3.3 CSDDIs

A total of 71 drug pairs were prescribed which resulted in a total of 444 DDIs. Of these, 127 (28.60%) were CSDDIs. Out of 10 frequently observed DDIs nine were clinically significant DDI. The clinically significant DDI pairs included captopril + furosemide (20.27%), spironolactone + captopril (14.41%), aspirin + furosemide (11.26%), artemether + metronidazole (8.55%), digoxn + spironolactone (7.65%), diazepam + phenytoin (7.43%), aspirin + spironolactone (5.63%), aspirin + prednisolone (1.35%) and aspirin + ibuprofen (1.12%), Of all the CSDDIs, infant (41.26%) and children (39.68%) age groups were frequently exposed to these DDIs as compared to adolescents.

3.4 OL drug use

At least one OL drug was prescribed to 228 (91.2%) patients corresponding to a total of 44.59% OL drugs in total prescribed drugs. Dose (43.35%) and indication (22.22%) were the most common categories for off label drug use. Other observed reasons for off label use were indication-dose (12.02%), age (7.83%), administration form (5.28%), different dose-administration form (3.64%), age-administration from-dose (2.73%), age-dose (2.55%) and age-administration form (0.36%). Most frequently prescribed OL drugs and their OL categories which also contributed to clinically significant DDI in pediatric cardiology ward are listed in Table 2.

Table 2

Frequencies of OL categories of prevalently prescribed OL drugs and their contribution to clinically significant DDIs
Drugs	Age	Indication	Dose	Administration form	Age, Dose	Indication, Dose	Administration form, Dose	Total
Furosemide	-	80	195	-	11	43	-	329	(81)
Spironolactone	18	69	156	-	3	31	-	277	(79)
Co amoxiclav	-	52	133	26	-	33	18	262	(45)
Captopril	-	51	162	-	-	28	-	241	(73)
Cefazolin	-	26	102	-	-	8	-	136	(49)
Aspirin	-	31	74	-	-	8	-	113	(48)
Paracetamol	29	-	60	7	12	-	8	116	(10)
Iron	-	-	57	-	-	-	-	57	(16)
Folic acid	-	19	49	-	-	38	-	106	(12)
Propranolol	4	15	17	-	1	22	-	59	(03)

Inappropriate dose was also prevalent reason for off label drug use in all the age groups as shown in Fig. 1.

The drugs which were frequently prescribed and also attributed to CSDDIs are shown in Fig. 2

3.5 Regression analysis

Univariate regression analysis reported adolescent group to be 9.7 times significantly (OR 9.7; CI 3.026–31.500) more likely to experience a clinically significant DDI. Similarly, patients prescribed > 5 drugs were also 4.2 times significantly (OR 4.202; CI 2.413–7.317) more likely to experience a clinically significant DDI. However, patients who did not receive off label drugs were significantly less likely (OR 0.281; CI0.081-0.979) to experience a clinically significant DDI as presented in Table 3.

Table 3

Predictors for drug interactions in pediatric cardiology ward
Variables	Unadjusted odds ratio		Adjusted odds ratio
Variables		P-Value	OR (CI)	P-Value	OR (CI)
Gender
Male	0.253	1.359 (0.803–2.299)	0.421	0.787 (0.439–1.411)
Female	Reference		Reference
Age groups
Infants	0.021**	0.256 (0.080–0.814	0.040**	0.223 (0.053–0.931)
Children	0.107	0.376 (0.115–1.234)	0.147	0.338 (0.078–1.462)
Adolescent	Reference		Reference
Prescribed drugs
Less than 4 drugs	0.000***	0.146 (0.084–0.254)	0.000***	0.165 (0.090–0.302)
4 or more drugs	Reference		Reference
Hospital Stay
Less than 4 days	0.024**	0.553 (0.330–0.926)	0.895	1.042 (0.565–1.923)
4 or more days	Reference		Reference
Off label
Absent	0.006**	0.234 (0.0830.656)	0.081*	0.356 (0.112–1.135)
Present	Reference		Reference
significant at p < 0.1 significant at p < 0.05 *significant at p < 0.01*
OR = Odds Ratio, CI = Confidence interval

Multivariate regression analysis shows adolescent group to be 12.7 times significantly (OR 12.795; CI 3.077–53.198) more likely to experience a clinically significant DDI. Similarly, patient prescribed > 5 drugs were also 3.5 times significantly (OR 3.544; CI 1.906–6.589) more likely to experience a clinically significant DDI (Table 3).

Multiple factors are involved in pediatric population being under represented in clinical trials. [5] Thus therapy is based on clinical experience of the physician and extrapolation of adult data, leading to the use of drugs not labelled for use in pediatrics [6]. Additionally, they are also exposed to a high number of CSDDIs. Studies have reported multiple risk factors for DDIs, [13, 15] but to the best of our knowledge, off label drug use has not been used as risk factor for CSDDIs. Drugs that contributed to CSDDIs as well as prescribed in off label manner could lead to an increased risk of ADRs, deteriorate the condition of patient and increase the length of hospital stay. [16, 17].

Current study reported the prevalence of OL drugs and CSDDIs to be 44.5% and 25.6% respectively. A total of 91.2% patients were prescribed at least one off label drug. The results are congruent with a Serbian study which was conducted in cardiology setting and reported 47% of all the drugs prescribed were off label. [18] Another study performed in France reported off label drug prescription to be 37.6%. [19] A German study where 415 pediatric patients were assessed for off label prescriptions, reported 31% off label prescriptions in cardiovascular drugs. [20] A cross-sectional study carried out to examine off label drug utilization for antihypertensive drugs, reported 50% of drugs prescribed as off label in children. [20] The variation among different countries in prevalence of off label prescriptions is possibly due to the different design and method of studies.

The prevalence of DDIs in the pediatric cardiology ward was observed to be 52.8%, while 25.6% of the total observed DDIs were clinically significant. Another study conducted at pediatric intensive care unit of tertiary care center of Pakistan in 2017 reported 59% DDIs. Out of total DDIs, 34% were CSDDIs [9] Similarly a study in USA reported 49% of the hospitalized children had DDIs and 41% of these were clinically significant [8]. Difference in the study population and drugs may be the reason for the differences in the prevalence of CSDDIs.

Pediatric cardiac care has evolved as a distinct discipline in well-established cardiac programs in developed countries but physicians still face challenges in pediatric cardiac treatment due to presence of several factors including multiple congenital malformations, low birth weight, prematurity, intrauterine growth restriction, and CHD type in pediatric population [21] Unfortunately the epidemiology of heart failure in pediatric populations is very poorly established especially in developing countries. High prevalence of cardiomyopathies in developing regions like Pakistan is because of multiple factors in which rheumatic heart disease and poor screening program in pediatrics are most common [22]. Extension of screening in pediatrics should be considered with interest in the light of the higher prevalence of the disease and relative clarity of subclinical cardiac morbidities that could be more easily diagnosed in the clinical practice and burden of disease can be minimized in our region.

Anti-bacterial was the most prevalent therapeutic categories in cardiology ward. The reason for high prevalence of anti-bacterial drug class may be the high prevalence of respiratory infectious disease (pneumonia) present in the study population. Aspirin was the most frequently reported drug involved in CSDDIs, and was also one of the frequently prescribed off label drug. Drugs when are prescribed as OL or are involved in a clinically significant DDI pose greater risk of ADRs. Various study reported an increased risk of ADRs when a patient is exposed to OL prescriptions. [17, 23, 24] Similarly presence of clinically significant drug interactions also pose a higher risk of an ADR. A research revealed significant difference between the chldren who had ADRs with the presence of DDIs to children without ADRs in absence of DDIs [25]A Croatian study also validated this significant relationship [26].

Dose (43.35%) and indication (22.22%) were the prevalent reasons for off label drug use while a prospective study conducted in pediatric cardiology ward in Serbia also observed dose (26%) and age (21%) as the most common reason for off label drug use [18] The major problem in treatment of pediatric cardiac disorders was lack of pediatric pharmaceutical formulations of cardiovascular drugs. In pediatrics, 75% of the prescribed drugs were prepared from adult dosage forms [27].

Age group, number of prescribed drugs and off label use of drugs were found to be significant for drug interactions in univariate model while only age group and number of prescribed drugs were significantly associated with CSDDIs in multivariate model. A similar relationship has also been reported by other pediatric studies [7, 28, 29]. Off label drug use was also found to be a significant predictor for DDIs in the univariate model, and is also known to be associated with ADRs, however, it became insignificant in the multivariate model. This may be because of the inclusion of a single cardiology ward, not having sufficient patients to display a significant association. The relationship could be tested in a multicenter study in the future for better insight.

Lack of pediatric pharmaceutical formulations of cardiovascular drugs and previously mentioned notable facts emphasize that some interventions must be performed, like monitoring of plasma concentrations, laboratory tests and dose adjustments etc. Many problems exist which restrict clinical trials in cardiovascular drugs for pediatrics, including low prevalence of pediatric cardiovascular diseases as compared with adult cardiovascular disease, disease heterogeneity, lack of research infrastructure, ethical consideration in pediatric research, and difficulty in identifying appropriate clinical end points [30].

Therefore, conducting research at pediatric cardiology ward is difficult, as majority of regimens used in this population are not well documented. The decisions regarding the therapy are most often based on extrapolation from adult studies, observational data, or clinician experience. A drug used as off label and has also contributed to drug interaction should be replaced by a safer one, while suitable strategies should be introduced during the usage of these drugs.

Current research adds a new predictor for the CSDDIs especially for pediatric population. Furthermore, the study also identified common drugs prescribed in pediatric cardiology, significantly involved in CSDDIs.

4.1 Limitations

The study was conducted at a single center and limited to pediatric cardiology ward, so further multicenter studies are required to evaluate DDIs particularly in relevance to off label drug use in other pediatric departments as well.

Our study highlights the high prevalence of OL prescribing and CSDDIs. Off label drugs were significantly associated with CSDDIs, which is a new finding and has not been associated previously. Appropriate guidelines must be developed and implemented by health regulatory agencies to avoid the complexities caused in pharmacotherapy of cardiac disorders in children.

6.1 Ethics approval: The study was approved by the ethical committees of the Hayatabad Medical Complex, Peshawar through letter number 8075-79/HMC. Ethical principles under the declaration of Helsinki were followed.

6.2 Consent to participate: The written informed consent was obtained from the participant.

6.3 Data Availability: Data will be available upon request.

6.4 Acknowledgement: The authors like to acknowledge the Hayatabad Medical Complex, Peshawar for providing necessary permission for the data collection.

6.5 Authors Contribution:

Conception, design and supervision by MA. Data acquisition by: NS and SA. Data analysis and interpretation by: AA, SA. Drafting the main manuscript by MA, AF, NS, SA, KB. Revision and edited by: MA, AA, KB. All authors read and approved the final version of the manuscript.

6.6 Funding: None

6.7 Conflict of Interest Disclosures: N/A

Sidney, S., et al., Recent trends in cardiovascular mortality in the United States and public health goals. JAMA cardiology, 2016. 1(5): p. 594-599. doi:10.1001/jamacardio.2016.1326.
Meliota, G., et al., Off-label use of cardiovascular drugs in the home therapy of children with congenital or acquired heart disease. The American journal of cardiology, 2022. 166: p. 131-137. https://doi.org/10.1016/j.amjcard.2021.11.029.
Bucci-Rechtweg, C., Enhancing the pediatric drug development framework to deliver better pediatric therapies tomorrow. Clinical therapeutics, 2017. 39(10): p. 1920-1932. https://doi.org/10.1016/j.clinthera.2017.07.043
Joseph, P.D., J.C. Craig, and P.H. Caldwell, Clinical trials in children. British journal of clinical pharmacology, 2015. 79(3): p. 357-369. https://doi.org/10.1111/bcp.12305
Thomsen, M.D.T., Global pediatric drug development. Current Therapeutic Research, 2019. 90: p. 135-142. https://doi.org/10.1016/j.curtheres.2019.02.001
Dunne, J., et al., Extrapolation of adult data and other data in pediatric drug-development programs. Pediatrics, 2011. 128(5): p. e1242-e1249. https://doi.org/10.1542/peds.2010-3487
Dai, D., et al., Epidemiology of polypharmacy and potential drug-drug interactions among pediatric patients in intensive care units of US Children’s Hospitals. Pediatric critical care medicine: a journal of the Society of Critical Care Medicine and the World Federation of Pediatric Intensive and Critical Care Societies, 2016. 17(5): p. e218. DOI: 10.1097/PCC.0000000000000684
Feinstein, J., et al., Potential drug− drug interactions in infant, child, and adolescent patients in Children’s hospitals. Pediatrics, 2015. 135(1): p. e99-e108. https://doi.org/10.1542/peds.2014-2015
Ismail, M., et al., Potential drug-drug interactions in pediatric patients admitted to intensive care unit of Khyber Teaching Hospital, Peshawar, Pakistan: A cross-sectional study. Journal of critical care, 2017. 40: p. 243-250. https://doi.org/10.1016/j.jcrc.2017.04.028
Association, G.A.o.t.W.M., World Medical Association Declaration of Helsinki: ethical principles for medical research involving human subjects. The Journal of the American College of Dentists, 2014. 81(3): p. 14-18.
Machin, D., et al., Sample sizes for clinical, laboratory and epidemiology studies. 2018: John Wiley & Sons.
Williams, K., et al., Standard 6: age groups for pediatric trials. Pediatrics, 2012. 129(Supplement_3): p. S153-S160. https://doi.org/10.1542/peds.2012-0055I
Saiyed, M.M., T. Lalwani, and D. Rana, Off-label medicine use in pediatric inpatients: a prospective observational study at a tertiary care hospital in India. International journal of pediatrics, 2014. 2014(1): 415815. https://doi.org/10.1111/jphs.12286
Shakeel, F., et al., Identification of clinically significant drug-drug interactions in cardiac intensive care units of two tertiary care hospitals in Peshawar, Pakistan. Tropical Journal of Pharmaceutical Research, 2016. 15(10): p. 2289-2295. https://doi.org/10.4314/tjpr.v15i10.31
Yackey, K., et al., Off-label medication prescribing patterns in pediatrics: an update. Hospital Pediatrics, 2019. 9(3): p. 186-193. https://doi.org/10.1542/hpeds.2018-0168
El Morabet, N., et al., Prevalence and preventability of drug‐related hospital readmissions: a systematic review. Journal of the American Geriatrics Society, 2018. 66(3): p. 602-608. https://doi.org/10.1111/jgs.15244
Pratico, A.D., et al., Off-label use of drugs and adverse drug reactions in pediatric units: a prospective, multicenter study. Current drug safety, 2018. 13(3): p. 200-207. https://doi.org/10.2174/1574886313666180619120406
Bajcetic, M., et al., Off label and unlicensed drugs use in paediatric cardiology. European journal of clinical pharmacology, 2005. 61: p. 775-779. https://doi.org/10.1007/s00228-005-0981-y
Palmaro, A., et al., Off-label prescribing in pediatric outpatients. Pediatrics, 2015. 135(1): p. 49-58. https://doi.org/10.1542/peds.2014-0764
Hsien, L., et al., Off-label drug use among hospitalised children: identifying areas with the highest need for research. Pharmacy world & science, 2008. 30: p. 497-502. https://doi.org/10.1007/s11096-008-9193-8
Dawson, A.L., et al., Factors associated with late detection of critical congenital heart disease in newborns. Pediatrics, 2013. 132(3): p. e604-e611. https://doi.org/10.1542/peds.2013-1002
Kumar, M., et al., Prevalence of rheumatic heart disease in Pakistan: a meta-analysis study. J Res Med Dent Sci, 2022. 10(2): p. 79-81.
Good, C.B. and W.F. Gellad, Off-label drug use and adverse drug events: turning up the heat on off-label prescribing. JAMA Internal Medicine, 2016. 176(1): p. 63-64. doi:10.1001/jamainternmed.2015.6068
Smithburger, P.L., et al., A multicenter evaluation of off-label medication use and associated adverse drug reactions in adult medical intensive care units. Critical care medicine, 2015. 43(8): p. 1612. doi: 10.1097/CCM.0000000000001022
Bebitoğlu, B.T., et al., Evaluation of potential drug-drug interactions in a pediatric population. Turkish Archives of Pediatrics/Türk Pediatri Arşivi, 2020. 55(1): p. 30. https://doi.org/10.14744%2FTurkPediatriArs.2019.60938
Joseph, B., J.X. Scott, and M. Rajanandh, Surveillance of adverse drug reactions and drug–drug interactions with pediatric oncology patients in a south Indian tertiary care hospital. Journal of Oncology Pharmacy Practice, 2020. 26(5): p. 1103-1109. https://doi.org/10.1177/1078155219882081
Gerrard, S.E., et al., Innovations in pediatric drug formulations and administration technologies for low resource settings. Pharmaceutics, 2019. 11(10): p. 518. https://doi.org/10.3390/pharmaceutics11100518
Getachew, H., et al., Potential drug–drug interactions in pediatric wards of Gondar University Hospital, Ethiopia: A cross sectional study. Asian Pacific Journal of Tropical Biomedicine, 2016. 6(6): p. 534-538. https://doi.org/10.1016/j.apjtb.2016.04.002
Fernández de Palencia Espinosa, M.A., et al., Pharmacoepidemiological study of drug–drug interactions in onco-hematological pediatric patients. International journal of clinical pharmacy, 2014. 36: p. 1160-1169. https://doi.org/10.1007/s11096-014-0011-1
Hampl, S.E., et al., Clinical practice guideline for the evaluation and treatment of children and adolescents with obesity. Pediatrics, 2023. 151(2): p. e2022060640. https://doi.org/10.1542/peds.2022-060640

No competing interests reported.

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Prevalence of drug-drug interactions in pediatrics with cardiac disorders receiving off label drugs- a cross-sectional study

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Abstract

Figures

1. Introduction

2. Methods

2.1 Ethical Consent

2.2 Patient selection

2.3 Definition of variables

2.4 Statistical analysis

3. Results

3.1 Patient demographics

3.2 Prescribed drugs and dosing

3.3 CSDDIs

3.4 OL drug use

3.5 Regression analysis

4. Discussion

4.1 Limitations

5. Conclusion

Declarations

References

Additional Declarations

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