Hospital admissions due to adverse drug reactions in the elderly. A meta-analysis
T. J. Oscanoa, F. Lizaraso & Alfonso Carvajal
European Journal of Clinical Pharmacology ISSN 0031-6970 Eur J Clin Pharmacol DOI 10.1007/s00228-017-2225-3
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Author's personal copy Eur J Clin Pharmacol DOI 10.1007/s00228-017-2225-3
PHARMACOEPIDEMIOLOGY AND PRESCRIPTION
Hospital admissions due to adverse drug reactions in the elderly. A meta-analysis T. J. Oscanoa 1,2 & F. Lizaraso 3 & Alfonso Carvajal 4,5
Received: 11 January 2017 / Accepted: 20 February 2017 # Springer-Verlag Berlin Heidelberg 2017
Abstract Introduction It is currently admitted that adverse drug reactions (ADRs) account for a great burden of disease. Of particular concern are ADR-induced hospital admissions, particularly in the elderly; they receive most of the medications and they are the most prone to develop ADRs. Therefore, our aim was to carry out a study of ADR-induced hospital admissions focused on the elderly population. Methods For the purpose, a systematic review and metaanalysis was performed of those studies addressing ADRinduced hospital admissions in patients over 60 years of age. A computerized search of the literature was carried out in the main databases. The search spans from 1988 to 2015. A pooled prevalence figure was calculated with 95% CIs; heterogeneity was also explored. Results The final number of selected articles was 42; all of them were published between January 1988 and August 2015. The overall average percentage of hospital admissions was 8.7% (95% CI, 7.6–9.8%). NSAIDs are one of the medication classes more frequently related to these admissions (percentages range from 2.3 to 33.3%). Inappropriate medication as a risk factor
was studied in nine studies, four found a statistically significant relationship between those medications and hospital admissions. Conclusions Circa one in ten hospital admissions of older patients are due to ADRs. A great burden of disease is due to a few and identifiable medication classes; in most of the cases, the reactions are well known and probably preventable. A sense of purpose and determination is needed by health authorities to face this problem. Doctors, on their part, should be aware when prescribing some specific identifiable medications to these patients. Key points 1. One in ten hospital admissions in older patients are due to ADRs; NSAIDs are the medications the most related with these admissions, followed by other common medications used in patients of this age, such as beta-blockers. 2. A great burden of disease is due to medications that are intended to cure or alleviate disease; this burden of disease is not only painful for the patients but also costly. 3. Identified risk factors are particular medication classes and polymedication. In most of the cases, reactions are probably preventable.
* Alfonso Carvajal
[email protected]
Keywords Hospital admissions . ADRs . Elderly patients . Meta-analysis
1
2
Departamento de Farmacología de la Facultad de Medicina de la Universidad Nacional Mayor de San Marcos, Lima District, Peru Centro de Investigación de Seguridad de Medicamentos de la Facultad de Medicina de la Universidad de San Martín de Porres, Calandrias, Peru
3
Instituto de Investigación de la Facultad de Medicina de la Universidad de San Martín de Porres, Calandrias, Peru
4
Centro de Estudios sobre la Seguridad de los Medicamentos (CESME), Universidad de Valladolid, Valladolid, Spain
5
School of Medicine, Ramón y Cajal, 7, 47005 Valladolid, Spain
Introduction According to a recent and comprehensive definition, adverse drug reactions (ADRs) are Bnoxious and unintended responses to medicinal products^ [1]. These responses may arise from use of the product within or outside the terms of the marketing authorization or from occupational exposure; conditions of use outside the marketing authorization include off-label use, overdose, misuse, abuse, and medication errors. It has been
Author's personal copy Eur J Clin Pharmacol
largely observed that older adults are particularly prone to develop such reactions; among the main reasons would be age-related changes in pharmacokinetics and pharmacodynamics, the existence of comorbidities, and polypharmacy, commonly defined as the use of five or more regular medicines. Elderly adults are the major consumers of medicines. For instance, it has been estimated in Ireland that the prevalence of polypharmacy increased, from 1997 to 2012, from 17.8 to 60.4% in those aged ≥65 years [2]. This trend is quite similar in other countries [3, 4]. ADRs have been recently estimated to cause 10–20% of hospital admissions in geriatric units [5, 6]. Hospital admissions related to ADRs have been previously investigated; for instance, in a systematic review of 25 observational studies, the percentage of admissions due to ADRs was 4% for children, 6% for adults, and 11% for older adults [7, 8]. A list of potentially inappropriate medications in older patients has been recently proposed and widely used [9, 10]; accordingly, medications with a negative benefit-risk balance for these patients would be included. Currently, it is of interest to know whether medications included in this list are related to more hospital admissions in older adults; previous studies have not been consistent at this regard [11, 12]. In addition, since geriatric population is an increasingly large group all over the world, and much vulnerable to ADRs, it is also of particular importance to learn the extent of this problem in this population to better establishing a prevention strategy. Therefore, the aim of the present study is to further learn the frequency of hospital admissions due to ADRs in elderly adults, to ascertain the offending medications and the risk factors to account for.
Method A systematic review and a meta-analysis of observational studies addressing hospitalizations due to ADRs in elderly population were conducted. Literature search and selection of the studies A computerized search of the published literature was carried out in Google Scholar and different databases and sources, including PubMed and the Database of Abstracts of Systematic Reviews from the Cochrane Library; a fully recursive search of reference lists of all reviewed articles and of retrieved primary studies was also performed to find references not identified in the computerized searches. The search spans from January 1988 to August 2015; the search combined five types of keywords related to age, adverse reactions, admission to hospital, drugs, and study design (available on request). Titles and abstracts of all identified studies were carefully reviewed; unrelated studies were discarded and those potentially eligible
were examined by two different reviewers (TJO and AC) for their inclusion. Selection was performed independently and blindly, according to inclusion and exclusion criteria. Inclusion criteria was observational studies assessing the risk of being hospitalized due to an ADR in patients over 60 years old; when the prevalence with its confidence interval was not directly reported in the original publication, this should provide enough data to calculate a percentage of hospital admissions (i.e., number of patients who had an ADR requiring hospital admission as a numerator and number of patients admitted to hospital during the study period as a denominator) with their corresponding 95% confidence intervals. Studies focused on ADRs related to particular medications or classes, or particular conditions or presentations were excluded, as were studies only focused on poisonings or drug abuse. Data extraction By using a common data extraction template, all relevant information was independently abstracted from the selected studies by both reviewers. Information refers to (i) study characteristics—names of the authors, institutions, geographical location, year of publication, duration, type of hospital, design, sample size, care setting at the hospital, and method and setting for ADRs identification (interview, clinical records, others); (ii) ADRs characteristics—definition, clinical manifestations, percentage of hospital admissions due to ADRs, health professional who assessed causality, and methods used (Naranjo [13]; WHO-UMC [14]; Hallas [15]; French scale [16]; Karch-Lasagna [17]); and (iii) medications—offending drug and inappropriateness of the medication used (Beers [9, 10]; STOPP [18]; PRISCUS criteria [19]). Some particular definitions were adopted for the present study. For old adult, the one by the WHO [20], ADR was the one defined by the current European legislation [1] but, for operational purposes, the one stated in the studies included in the meta-analysis; hospitalizations included inpatient admissions (attended patients at the hospital or formally admitted), observation admissions (time-limited assessment, treatment, and reassessment, typically lasting from 64 >64 >60 >64 >64 >64 >70 >74 70 >64 >64 >64 >65 >64 >60 >64 >64 >68 >65 >65 >64 >64 >69 >79 >64 >64 >64 >64 >60 >64 >60 >64 >74
6 6 9 36 24 36 12 2 36 12 6 5 9 2 60 24 13 4 4 2 12 17 49 48 7 48 1 36 22 12 12 3 3
>65 3 >64 4 elderly 9 >64 12 >75 >60 >64 >69
12 5 16 42
All wards Medical wards Medical wards Medical wards
>65
72
ED
P prospective, R retrospective, ED emergency department a
ADR, this term is used in a broad sense to refer to ADRs
rooms and specific units of hospitalization. To assess causality, the most frequently used algorithms were Naranjo, 34.1%; WHO-UMC, 17.1%; Hallas, 9.7%; and French scale, 5%. Hospital admissions All selected studies had information upon hospital admissions. The forest plot shows the figures of admissions due to ADRs for those studies included (Fig. 2).
The overall average percentage of admissions was 8.7% (95% CI, 7.6–9.8%). In 14 studies, there was information upon medicines causing hospitalization (Table 2); NSAIDs were one of the classes most frequently related to hospital admissions (percentages range from 2.5 to 33.3%); other related classes were beta-blockers (1.8–66.7%), antibiotics (1.1– 22.2%), oral anticoagulants (3.3–55.6%), digoxin (1.6–
Author's personal copy Eur J Clin Pharmacol Random effects Study
Prev (95% CI)
% Weight
Grymonpre 1988
0.0962 ( 0.0774, 0.1168)
2.4622
Courtman 1995
0.1067 ( 0.0617, 0.1616)
1.8695
Cunningham 1997
0.0475 ( 0.0352, 0.0615)
2.4866
Raschetti
0.0422 ( 0.0346, 0.0506)
2.5728
Chan 2001 Tirado 2001
0.1333 ( 0.0930, 0.1795) 0.0721 ( 0.0529, 0.0941)
2.0985 2.3958
Malhotra 2001
0.0675 ( 0.0484, 0.0895)
2.3836
Onder 2002
0.0339 ( 0.0319, 0.0361)
2.6331
Caamaño 2005
0.0460 ( 0.0431, 0.0491)
2.6303
Passarelli 2005
0.1129 ( 0.0710, 0.1628)
1.9810
Laroche 2006 Tipping 2006
0.0996 ( 0.0869, 0.1131) 0.2012 ( 0.1677, 0.2369)
2.5602 2.3568
van de Hooft 2006
0.0295 ( 0.0288, 0.0301)
2.6381
Budnitz 2006
0.0248 ( 0.0235, 0.0261)
2.6359
Arulmani 2007
0.1447 ( 0.0939, 0.2040)
1.9008
Franceschi 2008
0.0581 ( 0.0476, 0.0695)
2.5489
Chan 2008 Schuler 2008
0.0069 ( 0.0061, 0.0079) 0.1013 ( 0.0772, 0.1282)
2.6335 2.3689
Alexopoulou 2008
0.1461 ( 0.1112, 0.1848)
2.2483
Van der Hooft 2008
0.0881 ( 0.0809, 0.0956)
2.6108
Wawruch 2009
0.0783 ( 0.0581, 0.1013)
2.3921
Rogers 2009
0.0293 ( 0.0149, 0.0482)
2.2922
Helldén 2009
0.1429 ( 0.0916, 0.2030)
1.8838
Olivier 2009
0.0837 ( 0.0653, 0.1040)
2.4469
Somer 2010
0.1273 ( 0.0707, 0.1968)
1.6911
Budnitz 2011
0.0400 ( 0.0399, 0.0402)
2.6388
Hamilton 2011
0.2633 ( 0.2288, 0.2994)
2.3921
Varallo 2011 Conforti 2012
0.1948 ( 0.1524, 0.2410) 0.1114 ( 0.0929, 0.1315)
2.1977 2.4882
Marcum 2012
0.1003 ( 0.0788, 0.1241)
2.4181
Wierenga 2012
0.2574 ( 0.2243, 0.2920)
2.4065
de Paepe 2012
0.2250 ( 0.1395, 0.3236)
1.4915
Ma 2012
0.0740 ( 0.0665, 0.0819)
2.6024
Wu 2012
0.0075 ( 0.0074, 0.0076)
2.6388
De Paula 2012 Dorman 2013
0.2268 ( 0.2186, 0.2351) 0.2877 ( 0.2415, 0.3363)
2.6222 2.2435
Kongkaew 2013
0.1079 ( 0.0954, 0.1211)
2.5682
Pedros 2014
0.0599 ( 0.0507, 0.0698)
2.5717
Chen 2014
0.0089 ( 0.0077, 0.0103)
2.6309
Amado 2014 Bayoumi 2014
0.0756 ( 0.0451, 0.1130) 0.0290 ( 0.0288, 0.0292)
2.0949 2.6387
Henschel 2015
0.1000 ( 0.0969, 0.1031)
2.6342
Overall
0.0868 ( 0.0757, 0.0985)
100.0000
Q=158191.54, p=0.00, I2=100% 0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
Prev
Fig. 2 Hospital admissions due to ADRs in older patients. Forest plot
18.8%), ACE inhibitors (5.5–23.4%), anticancer drugs (1.5– 9.1%), calcium entry blockers (1.0–8.3%), opioids (1.5– 18.8%), and oral antidiabetics (4.5–22.2%). The number of medications was identified as a statistically significant risk factor for hospital admissions in all the 22 studies addressing this topic; the number of comorbidities was significant in 4 out of 13, female sex was in 6 out of 21 and age in 6 out of 22. Renal failure was significant in 4 out of 8 studies. Inappropriate medication as a risk factor was assessed in 9 studies (Table 3); a statistically significant relationship between those medications and hospital admissions was observed in four studies. Several sources of heterogeneity among the studies were explored (see Table 4); as for the type of study, prospective studies identified a higher percentage of ADRs admissions; regarding sample size, those having a larger number of patients showed lower percentages; and the studies carried out
with databases found also lower percentages compared to studies using other sources. When considering location, the studies carried out in Latin America, Australia, and Africa found higher percentages of hospital admissions compared to those carried out in North America, Europe, or Asia.
Discussion This meta-analysis upon ADR-induced admissions in older patients presents three main findings. First, the percentage of admissions due to this cause in this particular group of age has been accurately estimated in 8.7% (95% CI, 7.%–9.8%). Second, the ten top classes of medicines associated with admission in this age were NSAIDs, beta-blockers, antibiotics, oral anticoagulants, digoxin, ACE inhibitors, calcium antagonists, anticancer drugs, opioids, and oral antidiabetics. Third,
Author's personal copy Eur J Clin Pharmacol Table 2 Hospital admissions due to ADRs. Medication classes and clinical symptoms
Study
NSAIDS (n = 13) Conforti (2012) [36]
Class ADRs/total ADRs (%) [total sample]
Clinical presentation
5/114 (4.4%) [1023]
Anemia
Marcum (2012) [51]
4/68 (5.9%) [678]
Gastric ulcer, acute renal failure,
Wawruch (2009) [65] Tirado (2001) [61]
4/47 (8.5%) [600] 10/44 (22.7%) [610]
Hypersensitivity, GI disturbances GI bleeding, pancytopenia, acute renal failure
Courtman (1995) [37] Somer (2010) [59]
5/16 (31.3%) [150] 2/14 (14.3%) [110]
GI bleeding, epigastric pain, gastropathy. GI bleeding, abdominal pain, stomach irritation
Rogers (2009) [57]
1/12 (8.3%) [409]
GI bleeding
de Paepe (2012) [39]
6/18 (33.3%) [80]
Franceschi (2008) [42]
23/102 (22.5%) [1756]
Anemia, renal impairment, bleeding, hypertension, hepatitis Hypertension, gastrointestinal bleeding, peptic ulcer, gastritis, porphyria, urticaria
Dorman (2013) [41]
4/101 (4.0%) [351]
GI bleeding, ulcer, anemia, left-heart decompensation (etoroxib), acute renal failure, hypertensive crisis (piroxicam)
Hamilton (2011) [44]
4/158 (2.5%) [600]
Gastritis/peptic ulcer disease
Schuler (2008) [58] Chen (2014) [35]
8/55 (14.5%) [543] 9/184 (4.9%) [20,628]
Ulcer, heart failure, acute renal failure Tarry stool, abdominal pain, upper GI bleeding, fever, fatigue, acute or chronic renal insufficiency, skin rash, dyspnea
Beta-blockers (n = 8) Conforti (2012) [29]
2/114 (1.8%) [1023]
Syncope
Marcum (2012) [51] Wawruch (2009) [65] Rogers (2009) [57] de Paepe (2012) [39]
7/68 (10.3%) [678] 6/47 (12.8%) [600] 1/12 (8.3) [409] 12/18 (66.7%) [80]
Bradycardia/heart block, fall Fall, hypotension, cardiac arrhythmias Postural hypotension Hypotension, bradycardia, syncope, fatigue,
Franceschi (2008) [42]
1/102 (1%) [1756]
COPD exacerbation, hypoglycemia unawareness Bradycardia, syncope
Hamilton (2011) [44] Schuler (2008) [58] Antibiotics (n = 8)
4/158 (2.5%) [600] 8/55 (14.5%) [543]
Bradycardia Bradycardia
Conforti (2012) [36] Marcum (2012) [51] Wawruch (2009) [55] Courtman (1995) [37] de Paepe (2012) [39] Franceschi (2008) [42] Helldén (2009) [45] Chen (2014) [35] Warfarine (n = 7) Conforti (2012) [36] Marcum (2012) (51) Wawruch (2009) [65] Tirado (2001) [61] de Paepe (2012) [39] Schuler (2008) [58] Chen (2014) [35]
13/114 (11.4%) [1023] 4/68 (5.9%) [678] 2/47 (4.3%) [600] 1/16 (6.3%) [150]
Diarrhea, vomiting, renal failure Clostridium difficile Hypersensitivity Diarrhea
4/18 (22.2%) [80] 3/102 (2.9%) [1756] 1/22 (4.5%) [154] 2/184 (1.1%) [20,628]
Vomiting, diarrhea, allergy Urticaria Seizures (metronidazole) Stevens–Johnson syndrome (gemifloxacin), skin rash
10/114 (8.8%) [1023] 3/68 (4.4%) [678] 7/47 (14.9%) [600] 2/44 (4.5%) [610] 10/18 (55.6%) [80] 17/55 (30.9%) [543] 6/184 (3.3%) [20,628]
INR increase, anemia Gastrointestinal bleeding Bleeding Gastrointestinal bleeding High INR, bleeding Bleeding, over-anticoagulation Tarry stool, upper gastrointestinal bleeding, dyspnea, coagulopathy
2/68 (2.9%) [678]
Bradycardia/heart block
Digoxine (n = 7) Marcum (2012) [51]
Author's personal copy Eur J Clin Pharmacol Table 2 (continued) Study
Class ADRs/total ADRs (%) [total sample]
Clinical presentation
Wawruch (2009) [65]
3/47 (6.4%) [600]
Cardiac arrhythmias
Courtman (1995) [37] de Paepe (2012) [39]
3/16 (18.8%) [150] 2/18(11.1%) [80]
Bradycardia, arrhythmia, nausea vomiting, weakness Bradycardia, syncope
Franceschi (2008) [42]
11/102 (10.8%) [1756]
Schuler (2008) [58]
5/55 (9.1%) [543]
Bradycardia, nausea, vomiting, anorexia, delirium, heart failure Bradycardia
Chen (2014) [35]
3/184 (1.6%) [20,628]
Poor appetite, high degree, atrio-ventricular block , hypotension
ACE inhibitors (n = 7) Conforti (2012) [36]
18/114 (15.8%) [1023]
Hyponatremia, hyperkalemia, syncope, renal failure
4/68 (5.9%) [678] 11/47(23.4%) [600]
Hypotension, fall, acute kidney injury Fall, hypotension, hyperkalemia, cough
Marcum (2012) [51] Wawruch (2009) [65] Tirado (2001) [61]
5/44(11.4%) [610]
Renal failure, hyperkalemia
Courtman (1995) [37] Franceschi (2008) [42]
2/16 (12.5%) [150] 7/102 (6.9%) [1756]
Hypotension, hyperkalemia Syncope
Schuler (2008) [58]
3/55 (5.5%) [543]
Neutropenia
4/114 (3.5%) [1023] 1/68 (1.5%) [678] 4/44 (9.1%) [610] 1/12 (8.3%) [409] 2/102 (2.0%) [1756] 1/55 (1.8%) [543]
Anemia Fall Pantocytopenia Blood dyscrasia Pancyitopenia, tremor, asthenia Pancyitopenia
Anti-tumorals (n = 7) Conforti (2012) [36] Marcum (2012) [51] Tirado (2001) [61] Rogers (2009) [57] Franceschi (2008) [42] Schuler (2008) [58]
Chen (2014) [35] 6/184 (3.3%) [20,628] Calcium entry blockers (n = 7) Conforti (2012) [36] 2/114 (1.8%) [1023] Marcum (2012) [51] 2/68 (2.9%) [678] Wawruch (2009) [65] 4/47(8.5%) [600]
Fever, diarrhea, vomiting, skin rash
Rogers (2009) [57] de Paepe (2012) [39] Franceschi (2008) [42] Helldén (2009) [45] Opioids(n = 7)
1/12 (8.3%) [409] 1/18 (5.6%) [80] 1/102 (1.0%) [1756] 1/22 (4.5%) [154]
Heart failure Oedema Syncope Hypotonia/vertigo/fracture (verapamil)
1/68 (1.5%) [678] 1/47 (2.1%) [600] 3/16 (18.8%) [150] 1/14 (7.1%) [23] 1/22 (4.5%) [154]
Fall, mental status changes GI disturbances Confusion Somnolence Vertigo/fracture (tramadol), confusion/hallucinations (ethylmorphine HCL)
16/158 (10.1%) [600] 3/55 (5.5%) [543]
Falls, constipation Constipation, nausea
4/114 (4.5%) [1023] 7/68 (10.3%) [678] 3/44 (6.8%) [610] 1/14 (7.1%) [110] 4/18 (22.2%) [80] 12/184 (6.5%) [20,628]
Hypoglycemia Hypoglycemia, acidosis Hypoglycemia Hypoglycemia Hypoglycemia, acidosis Hypoglycemia, altered mental status, AMS, fatigue, cold sweating
Marcum (2012) [51] Wawruch (2009) [65] Courtman (1995) [37] Somer (2010) [59] Helldén(2009) [45] Hamilton (2011) [44] Schuler (2008) [58] Oral antidiabetics (n = 6) Conforti (2012) [36] Marcum (2012) [51] Tirado (2001) [61] Somer (2010) [59] de Paepe (2012) [39] Chen (2014) [35]
Syncope Bradycardia/heart block, congestive heart failure Fall, hypotension, cardiac arrhythmias
Author's personal copy Eur J Clin Pharmacol Table 3 Hospital admissions due to ADRs in older patients. Relationship between inappropriate medications and hospital admissions
Study
Results/criteria
Dorman et al., 2013 Henschel et al., 2015
OR, 1.99 (95% CI 1.23–3.52)/PRISCUS OR, 1.46 (95% CI 1.16–1.84)/PRISCUS OR, 1.85 (95% CI 1.51–2.26)/STOPP OR, 1.28 (95% CI 0.94–1.72)/Beers
Hamilton et al., 2011a Hamilton et al., 2011a Passarelli et al., 2005
OR, 2.32 (95% CI, 1.17–4.59)/Beers
Varallo et al., 2011 Laroche et al., 2006
OR, 1.00 (95% CI 0.50–2.10)/Beers OR, 1.00 (95% CI 0.80–1.30)/Beers
Somer et al., 2010
No relationship between of inappropriate drugs and hospital admission (P < 0.534)/Beersb There was a correlation (rho 0.09, P = 0.035) /Beers
Schuler et al., 2008
Table 4 Percentages of hospital admissions due to ADRs in older patients. Subgroup analysis
a
In the same study two criteria were used, STOPP and Beers
b
Only a small percentage of the drugs used, before admission and at discharge, were inappropriate
% Hospital admissions due to ADRs (CI95%)
I2
Subgroup
Studies (n)
Type of study Prospective Retrospective
31 11
9.75 (7.71–11.99) 6.55 (4.77–8.58)
99 100
22 20
13.13 (10.19–16.36) 5.32 (4.13–6.64)
94 100
1
20.12 (16.77–23.69)
5 1 23 12 4
4.28 (1.93–7.43) 13.33 (9.30–17.95) 10.16 (7.95–12.61) 7.24 (5.40–9.32) 4.20 (3.16–5.38)
100 100 100
4 4
4.43 (2.18–7.37) 14.70 (8.10–22.78)
100 95
30 6 5
8.82 (7.46–10.28) 12.59 (8.18–17.76) 5.95 (3.56–8.88)
99 93 100
1
2.48 (2.35–2.61)
12 6 6 30 36
6.80 (4.61–9.83 ) 3.72 (1.59–6.63) 12.00 (7.19–17.79) 9.35 (8.06–10.73) 9.74 (8.50–11.04)
100 100 96 100 100
42 37
8.68 (7.57–9.85) 8.10 (6.98–9.30)
100 100
Sample size 60 years >65 years
99
a Overall percentage of admissions was 8.7% (95% CI, 7.6–9.8%); when excluding the study by Budnitz et al. (2006)—the one with the highest sample, carried out in a spontaneous reporting database (Bodd man out^)—the overall percentage was 8.8 (CI 95%, 7.6–10.1)
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those medications currently considered as Bpotentially inappropriate^ were not always associated with hospital admissions. Our estimate of a prevalence of almost 9% of admissions in this age group is lower, but consistent, with the estimates by Beijer and de Blaey [68] and Alhawassi et al. [69]. The metaanalysis by Beijer and de Blaey comprises patients of different ages (total number of studies, 68) and, in a subset of patients older than 65 years (n = 17), a fourfold risk of ADR-induced hospital admissions was found when comparing to the rest (16.6 vs. 4.1%); the analyzed period goes only from 1987 up to 1990. More recently, the meta-analysis by Alhawassi et al. [69] including 14 studies found a percentage of admissions due to ADRs of 10.0% (95% CI, 7.2–12.8%) in patients over 65 years of age; this latter study identifies a figure of one admission in ten as due to ADRs, not far from ours. In our meta-analysis, we include—for the first time—the pharmacological classes presumably associated with these admissions. At this regard, NSAIDs appear as the first offending class; one in ten ADRs leading to admissions is related to this class (2.3–33.3%). These reactions are well known: upper gastrointestinal bleeding, hypertension, coronary events, and renal failure [70–72]. Intriguingly, most symptoms resulting in hospital admissions might be somehow preventable; this would be the case of hypotension due to beta-blockers, ACE inhibitors or calcium antagonists; hypoglycemia due to oral antidiabetics; bleeding due to oral anticoagulants; or bradycardia due to digoxin. In fact, to avoid hypotension due to antihypertensive medications, the new guides have changed the levels to consider hypertension control, i.e., now, the systolic pressure is recommended to be maintained between 140 and 160 mmHg for older adults [73]; similarly, for hypoglycemia due to oral antidiabetics, it is recommend a tailored objective level of glycated hemoglobin (HbA1c) based on life expectancy and an overall geriatric assessment; this assessment should consider the patient capacity to measure glycemia and to early recognize signs of hypoglycemia [74]. Like with digoxin, surveillance includes the adequate dosage considering the renal function and a possible hypokalemia [75]. Careful identification of particular groups at risk of bleeding should be done before starting medication with warfarin; in addition, this drug should be tightly monitored and titrated according to the INR [76, 77]. Four out of 9 studies addressing the relationship between inappropriate medications and hospital admissions due to ADRs did not found a statistically significant association. There is no a clear explanation for these conflicting results. It seems that focusing solely on these medications to avoid reactions ending in admissions would not be the best strategy; moreover, focusing on a closed list makes appear the rest of the medications as safe. As a matter of fact, in an older patient, whatever medication whose benefit-risk balance has not been carefully assessed and then monitored may cause an ADR;
i.e., beta-blockers, with a well-established benefit-risk balance and known benefits in term of survival in heart failure and coronary disease, can easily cause syncope and require admission [78]. In this study, patients older than 60 years have been included for analysis in spite of the current operational definition of older person, i.e., that which consider these persons as 65 years old and over. We did that in accordance with the WHO [20]; it is remarked that, for developing countries in Africa, this age would be 50 to 55 years, and, for instance, in India, it would be 58 years; on the opposite side, for Japan, the adult operational definition has been proposed to be those of 75 years old or over [79], life expectancy would in fact account for this operational definitions. An additional limitation of the present meta-analysis is that we have included studies with different operational definitions of ADR; most used the WHO definition [14]. For those studies including all ages we have separated those with an age of 60 years or more. Since most of the patients were having several medications, our study was unable to evaluate those specific reactions due to interactions; this probably requires a special study. Finally, we ascribe reactions to classes instead to particular medications; most of the reactions are reported in this manner in the literature; additionally, most of them are class reactions. A high degree of heterogeneity was found among the studies; the big gap was determined by the sample size: those studies having more than 1000 patients had lower percentages of admissions. One possible explanation is that the studies with greater sample sizes are those carried out in databases in the USA; thus, sample size is hiding other possible influences such as information bias. Since prospective studies are more reliable, a figure greater than our overall estimate would be closer to the real one. Our estimate of admissions for the different locations probably reflects the facts as they are; it is believable that a higher proportion occurs in Latin America compared to Europe. In summary, circa one in ten hospital admissions in older patients are due to ADRs; NSAIDs are the medications the most related with these admissions, followed by other common medications such as beta-blockers; and usual criteria of inappropriate medications are not useful to avoid hospital admissions. Oddly enough, a great burden of disease is due to medications that are intended to cure or alleviate disease; this burden of disease is not only painful for the patients but costly. Identified risk factors are particular medication classes and polymedication. In most of the cases, reactions are probably preventable. A sense of purpose and determination are needed by health authorities to face this problem. Acknowledgment This research was funded by the European Commission under the Erasmus Mundus Lindo Grant; the Postdoctoral Grant (TJO) at the University of Valladolid (Spain) spanned from December 2014 to 30th May 2015.
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