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Gut and Liver is an international journal of gastroenterology, focusing on the gastrointestinal tract, liver, biliary tree, pancreas, motility, and neurogastroenterology. Gut atnd Liver delivers up-to-date, authoritative papers on both clinical and research-based topics in gastroenterology. The Journal publishes original articles, case reports, brief communications, letters to the editor and invited review articles in the field of gastroenterology. The Journal is operated by internationally renowned editorial boards and designed to provide a global opportunity to promote academic developments in the field of gastroenterology and hepatology. +MORE
Yong Chan Lee |
Professor of Medicine Director, Gastrointestinal Research Laboratory Veterans Affairs Medical Center, Univ. California San Francisco San Francisco, USA |
Jong Pil Im | Seoul National University College of Medicine, Seoul, Korea |
Robert S. Bresalier | University of Texas M. D. Anderson Cancer Center, Houston, USA |
Steven H. Itzkowitz | Mount Sinai Medical Center, NY, USA |
All papers submitted to Gut and Liver are reviewed by the editorial team before being sent out for an external peer review to rule out papers that have low priority, insufficient originality, scientific flaws, or the absence of a message of importance to the readers of the Journal. A decision about these papers will usually be made within two or three weeks.
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Bo Kyung Yang, Byung Ju Do, Eun Jung Kim, Ji Un Lee, Mi Hee Kim, Jin Gu Kang, Hyoung Su Kim, Kyung Ho Kim, Myoung Kuk Jang, Jin Heon Lee, Hak Yang Kim, and Woon Geon Shin*
Department of Internal Medicine, Hallym University College of Medicine, Seoul, Korea.
Correspondence to: Woon Geon Shin. Division of Gastroenterology, Department of Internal Medicine, Hallym University Kangdong Sacred Heart Hospital, Hallym University College of Medicine, 150 Seongan-ro, Gangdong-gu, Seoul 134-701, Korea. Tel: +82-2-2225-2814, Fax: +82-2-2224-2690, sgun91@medimail.co.kr
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
Gut Liver 2014;8(1):41-48. https://doi.org/10.5009/gnl.2014.8.1.41
Published online November 5, 2013, Published date January 29, 2014
Copyright © Gut and Liver.
As the incidence rate of and mortality from pseudomembranous colitis (PMC) are increasing worldwide, it is important to study the simple predictive risk factors for PMC among patients with hospital-acquired diarrhea (HAD). This study focused on identifying the clinical risk factors that can easily predict PMC.
The presumed HAD patients were prospectively recruited at the Hallym University Kangdong Sacred Heart Hospital.
Age of 70 and older (adjusted odds ratio [OR], 1.76; 95% confidence interval [CI], 1.12 to 0.75), use of proton pump inhibitors (adjusted OR, 4.07; 95% CI, 2.512 to 6.57), use of cephalosporins (adjusted OR, 2.99; 95% CI, 1.82 to 4.94), and underlying cancer (adjusted OR, 1.72; 95% CI, 1.04 to 2.82) were independent risk factors for PMC in the multivariate logistic regression analysis. The prevalence of PMC was very low in the patients with HAD who exhibited no risk factors.
The risk factors for PMC in patients with HAD included cephalosporin use, proton pump inhibitor use, old age, and cancer. Considering the strongly negative predictive values of these risk factors, endoscopic evaluation can be delayed in patients with HAD without risk of developing PMC.
Keywords: Enterocolitis, pseudomembranous,
There are many causes of hospital-acquired diarrhea (HAD), including medications, nasogastric tube feeding, bowel ischemia, or constipation causing pseudodiarrhea. Antibiotics are the most common cause of HAD. Recently, the incidence of antibiotic-associated diarrhea (AAD) has increased rapidly due to use of broad-spectrum antibiotics.1 In the preantibiotic era, pseudomembranous colitis (PMC) was associated with ischemic cardiovascular insufficiency, colonic obstructions, heavy metal intoxication, sepsis, shock, or uremia.2 Since the 1970s,
The clinical spectrum of HAD associated with antimicrobial agents varies from simple antibiotic-associated diarrhea (SAAD) to fatal PMC. Compared with SAAD or CDAD, PMC has a poor prognosis and more severe clinical manifestations, such as ascites and transmural inflammation of the colon,8 although severe CDAD can be associated with significant mortality.9,10 For these reasons, medical treatments, such as oral administration of metronidazole or vancomycin, are usually recommended for
Considering that the early diagnosis of PMC and urgent appropriate treatment are clinically crucial, it is important to assess simple predictors for PMC among HAD patients; however, many studies have focused on risk factors of AAD or CDAD. To the best of our knowledge, no prospective study has examined the risk factors of PMC. However, Lee et al.12 published a retrospective study assessing risk factors of PMC in 2006. The aim of this study was to identify the risk factors of PMC that can be easily applied to the treatment of patients with HAD.
The HAD is defined as defecation of watery or loose stool more than three times a day for more than two days that started more than 48 hours after admission. SAAD was defined as antibiotic-related diarrhea without any other cause, and CDAD was defined as a positive result on a stool
The study included adult patients 20 years or older with HAD. The exclusion criteria were as follows: 1) other causes of diarrhea, such as stool softeners, gastrointestinal (GI)-motility drugs, or anticancer drugs; 2) other GI disease-causing diarrhea, such as inflammatory bowel disease; and 3) diarrhea with an indefinite cause.
The HAD patients were recruited prospectively by consultation from the various medical or surgical departments, such as cardiology, orthopedics, neurosurgery, and general surgery, in Hallym University Kangdong Sacred Heart Hospital from June 2007 to September 2011.
In total, 1,508 patients with HAD were detected after admission. Among these patients, 88 were excluded from the study because they had GI disease causing diarrhea other than AAD, CDAD, or PMC (n=24) or were taking medicine causing diarrhea such as stool softeners, GI motility drugs (n=37), or anticancer drugs (n=19). Some patients were found to suffer from HAD with an indefinite cause (n=8). We depict the diagnostic flow chart applied in this study in Fig. 1.
The study protocol and exemption of informed consent were approved by the Institutional Review Board of the Kangdong Sacred Heart Hospital.
The enrolled patients were divided into PMC and non-PMC groups to assess predictors for diagnosing PMC. In addition, predictors for
In total, 1,420 patients were analyzed (mean age, 66 years; 47.25% were female). The PMC group consisted of 104 patients and the non-PMC group was composed of 1,316 patients. Of 23 parameters, nine were significantly associated with PMC after univariate analysis. The mean number of administered antibiotics before starting diarrhea was 3.77 and 2.87 in the PMC and non-PMC groups, respectively (p=0.001). The use of cephalosporins (70/104, 67.31% vs 441/1,316, 33.51%) and clindamycin (13/104, 12.50% vs 87/1,316, 6.61%) was more common in the PMC group than in the non-PMC group; both differences were statistically significant (cephalosporins, p<0.0001; clindamycin, p=0.013). The PMC group was significantly older than the non-PMC group (69.77 vs 61.62 years; p<0.0001), reflecting the increasing incidence of PMC with age. The number of postoperative patients was greater in the PMC group (44/104, 42.31% vs 393/1,316, 29.86%; p=0.004). The patients were also divided by surgery type (orthopedic: PMC 18.27%, non-PMC, 9.12%, p=0.002; otorhinolaryngologic: PMC 8.65%, non-PMC 4.79%, p=0.04). The number of PPI use in the PMC group was significantly more than that of the non-PMC group (41/104, 39.42% vs 145/1,316, 11.02%; p<0.0001), although there is no significant difference between the two groups in terms of the dose or length of PPI administration. Regarding underlying disease, 28.85% (30/104) of the PMC group and only 17.02% (224/1,316) of the non-PMC group had cancer (p=0.002). Chronic renal failure was more common in the PMC group than in the non-PMC group (11/104, 10.58% vs 81/1,316, 6.16%; p=0.04), and cerebrovascular disease was more common in the PMC group than in the non-PMC group (17/104, 16.35% vs 130/1,316, 9.88%; p=0.02) (Table 1).
Multivariate logistic regression analysis was performed for these nine variables. Age greater than 70 years (adjusted odds ratio [OR], 1.76; 95% confidence interval [CI], 1.12 to 2.75; p=0.01), use of PPI (adjusted OR, 4.07; 95% CI, 2.52 to 6.59; p<0.0001), use of cephalosporins (adjusted OR, 2.99; 95% CI, 1.82 to 4.94; p<0.0001), and underlying cancer (adjusted OR, 1.72; 95% CI, 1.04 to 2.82; p=0.03) were the predictors of PMC (Table 2).
To determine how well the final model predicted PMC, we developed risk groups based on the number of predictive clinical factors. When no predictors were present, 1.54% (7/454) of the patients developed PMC; when only one was present, 5.39% (29/538) developed PMC; when two, three, and four were present, 10.42% (32/307), 29.73% (33/111), and 30.0% (3/10) developed PMC, respectively. There was a significant difference in the morbidity rate of PMC between the group with no predictors and that with one or more predictors (OR, 7.13; 95% CI, 3.28 to 15.48; p<0.0001) (Table 3).
The positive predictive value (PPV) and the negative predictive value (NPV) of age older than 70 years were 0.11 and 0.94, respectively. The PPV and NPV were 0.22 and 0.95 for PPI use, 0.14 and 0.96 for the use of cephalosporins, and 0.12 and 0.94 for underlying cancer, respectively. The NPV was better than the PPV for all of the evaluated predictors of PMC. For predicting PMC, the sensitivity and the specificity of age older than 70 years were 45.00% and 60.49%, respectively. They were 39.42% and 88.98% for PPI use, 67.31% and 66.49% for the use of cephalosporins, and 28.85% and 82.98% for underlying cancer, respectively (Table 4).
The
Multivariate logistic regression analysis was performed for the 15 significantly associated variables. Age older than 66 years (adjusted OR, 1.66, 95% CI, 1.23 to 2.44; p=0.001), number of used antibiotics (adjusted OR, 1.08; 95% CI, 1.02 to 1.15; p=0.009), sex (adjusted OR, 1.38, 95% CI, 1.03 to 1.86; p=0.03), use of PPI (adjusted OR, 1.92; 95% CI, 1.34 to 2.75; p<0.0001), use of cephalosporins (adjusted OR, 1.87; 95% CI, 1.37 to 2.55; p<0.0001), underlying cancer (adjusted OR, 1.58; 95% CI, 1.13 to 2.22; p=0.008), and cerebrovascular disease (adjusted OR, 1.55; 95% CI, 1.03 to 2.33; p=0.04) were the predictors of
To determine how well the final model predicted
The PPV and NPV of age older than 66 years were 0.30 and 0.82, respectively. The PPV and NPV were 0.28 and 0.86 for the number of antibiotics used; 0.26 and 0.80 for female sex, 0.39 and 0.79 for use of PPI, 0.35 and 0.83 for use of cephalosporins, 0.31 and 0.79 for underlying cancer, and 0.35 and 0.78 for underlying cerebrovascular disease, respectively. The NPV was better than the PPV for all of the evaluated predictors of
When HAD patients are in poor clinical condition, it is impossible to wait for the result of
This study design focuses on the predictors that can easily predict PMC in a clinical setting. The independent predictors of PMC were old age (≥70 years), use of PPI, use of cephalosporins, and history of cancer. Additionally, the predictors of CDAD were old age (≥66 years), use of PPI, use of cephalosporins, history of cancer, number of used antibiotics, female sex, and previous history of CVA. The good NPVs of the independent predictors (0.94 to 0.96) suggest that the patients without any of the predictors described above may not have a risk of PMC. Importantly, the fewer predictors the HAD patients had, the lower the risk of PMC or CDAD. We depict the suggested algorithm (based on these results) in Fig. 2. This preemptive treatment algorithm may not be applicable to all HAD patients without risk factors for PMC. In fact, among 104 patients with PMC, seven patients did not have any risk factor and three patients showed negative toxin assay, though there was no patient that showed both negative toxin assay and did not have any risk factor. However, sigmoidoscopy or colonoscopy cannot be done in a considerable proportion of hospitalized patients with diarrhea because of their medical conditions. The suggested algorithm may be more valuable in those situations. In brief, if HAD patients may have acute infectious diarrhea (fever >38.5℃, severe abdominal pain, bloody diarrhea, severe volume depletion, diarrhea lasting >48 hours, compromised immune system or age >70 years), endoscopy should be considered first, according to the well-known recommendation of textbooks;13,14 however, when endoscopy is not available because of the patients' conditions, without the predictors of PMC revealed in this study, antibiotic treatment may become delayed in HAD patients until the results of the
The well-known predictors associated with CDAD are grouped into host and drug factors. Age older than 65, severe underlying disease, compromised immune system, history of GI surgery, history of stay at an intensive care unit, long duration of stay and insertion of nasogastric tube are noted host factors.11,15 The type of antibiotics, length of antibiotic course, and history of using multiple antibiotics are drug factors.16
In patients that use PPI, there were approximately 4- and 2-fold increases in the risk for PMC and CDAD, respectively. PPI use showed the highest AOR for both PMC and CDAD in this comparison. The single case-control study reported that patients with PPI had a 2.5-times higher risk of CDAD compared with those without PPI.17 A meta-analysis conducted in 2012 showed a 65% increase in the incidence of CDAD among PPI users;18 however, the association between use of PPI and the development of CDAD has not been conclusive until now because the results of some reports do not coincide.1,19,20 Although the mechanism of this association between PPI and
In addition, elderly patients were prone to CDAD and PMC. This result of the present study was similar in this respect to that of another study.21 Elderly patients, compared with younger patients, are more likely to be exposed to
Interestingly, no type of surgery increased the risk of PMC and CDAD in this study; however, there were reports that GI surgery, which is known to contribute to changes in the normal intestinal flora due to the required pretreatment (e.g., bowel preparation, nasogastric tube insertion, and empirical antibiotic use), increases the risk of CDAD.15,16,22 Moreover, McCarter et al.23 reported that for pretreated patients, the risk of CDAD was 4.2 times higher than that of the control group, regardless of the type of surgery. Furthermore, probiotic use was not an independent preventive factor in the multiple logistic regression analysis, although some studies showed that probiotics might help to prevent
In this study, surprisingly, female sex was another independent predictor of
There are several limitations in this study. First, PMC may have been misclassified as CDAD because not all enrolled HAD patients underwent colonoscopy because of poor general condition or patient refusal. Therefore, the PPVs of PMC predictors might be underestimated; however, considering that most patients with PMC are in debilitated condition, unjustified endoscopic examination would be harmful and unethical because bowel preparation or air inflation during endoscopy could aggravate the colonic inflammation. Second, this study did not investigate the performance of cancer patients. The performance of cancer patients is varied. Some patients with localized curable cancer show normal performance, but others may perform very poorly due to progression of the cancer or systemic chemotherapy. Although there was approximately a 1.5-fold increase in the risk for both PMC and CDAD in cancer patients, this result could be altered if the performance scale of the cancer patients was to be evaluated. Third, selection bias is a possibility, although this study was conducted prospectively. We could not include nasogastric-tube feeding as a variable (although it is reported as a CDAD predictor in other studies) because we classified the patients with tube feeding as having other or indefinite causes of diarrhea and excluded these patients in the study design.
In conclusion, the independent predictors of PMC in HAD patients were PPI use, cephalosporins use, old age (≥70 years), and history of cancer. In particular, PPI use had the highest adjusted OR (4.07) for PMC. Therefore, we suggest the implementation of a preemptive management algorithm; based on the good NPVs of these predictors, endoscopic evaluation can be delayed in HAD patients without any predictors of PMC.
*Endoscopic evaluation was performed, if possible, before the results of the toxin assay became available for the patients with severe abdominal pain, dehydration, bloody diarrhea, or fever.
CRP, C-reactive protein; CBC, complete blood cell count; LFT, liver function test.
Data are presented as mean±SD or number (%).
PMC, pseudomembranous colitis; GS, general surgery; OS, orthopedic surgery; OBGY, obstetrics and gynecology; ENT, ear, nose, and throat (otolaryngology); NS, neurosurgery; CS, chest surgery; PPI, proton pump inhibitor; DM, diabetes mellitus; CRF, chronic renal failure; CVA, cerebrovascular accident.
*Duration of hospital stay indicates days until the onset of diarrhea after admission.
PMC, pseudomembranous colitis; GS, general surgery; OS, orthopedic surgery; OBGY, obstetrics and gynecology; ENT, ear, nose, and throat (otolaryngology); NS, neurosurgery; CS, chest surgery; PPI, proton pump inhibitor; DM, diabetes mellitus; CRF, chronic renal failure; CVA, cerebrovascular accident.
*Duration of hospital stay indicates days until the onset of diarrhea after admission.
OR, odds ratio; CI, confidence interval; PMC, pseudomembranous colitis; PPI, proton pump inhibitor; CVA, cerebrovascular accident.
*Evidence for selecting elderly patients: Age increases both the sensitivity and specificity of the receiver operating characteristic curve.
PMC, pseudomembranous colitis; GS, general surgery; OS, orthopedic surgery; OBGY, obstetrics and gynecology; ENT, ear, nose, and throat (otolaryngology); NS, neurosurgery; CS, chest surgery; PPI, proton pump inhibitor; DM, diabetes mellitus; CRF, chronic renal failure; CVA, cerebrovascular accident.
*Duration of hospital stay indicates days until the onset of diarrhea after admission.
Data are presented as number (%).
PMC, pseudomembranous colitis.
*Odds ratio 7.1279, 95% confidence interval 3.2822 to 15.4795, p<0.0001; †Odds ratio 3.0068, 95% confidence interval 1.933 to 4.678, p<0.0001; ‡p<0.0001; §There is no patient who exhibits all of the
PMC, pseudomembranous colitis; GS, general surgery; OS, orthopedic surgery; OBGY, obstetrics and gynecology; ENT, ear, nose, and throat (otolaryngology); NS, neurosurgery; CS, chest surgery; PPI, proton pump inhibitor; DM, diabetes mellitus; CRF, chronic renal failure; CVA, cerebrovascular accident.
*Duration of hospital stay indicates days until the onset of diarrhea after admission.
Data are presented as percentage (number). A, the number of PMC or
PPV, positive predictive value; NPV, negative predictive value; PMC, pseudomembranous colitis; PPI, proton pump inhibitor; CVA, cerebrovascular accident.
PMC, pseudomembranous colitis; GS, general surgery; OS, orthopedic surgery; OBGY, obstetrics and gynecology; ENT, ear, nose, and throat (otolaryngology); NS, neurosurgery; CS, chest surgery; PPI, proton pump inhibitor; DM, diabetes mellitus; CRF, chronic renal failure; CVA, cerebrovascular accident.
*Duration of hospital stay indicates days until the onset of diarrhea after admission.
Gut Liver 2014; 8(1): 41-48
Published online January 29, 2014 https://doi.org/10.5009/gnl.2014.8.1.41
Copyright © Gut and Liver.
Bo Kyung Yang, Byung Ju Do, Eun Jung Kim, Ji Un Lee, Mi Hee Kim, Jin Gu Kang, Hyoung Su Kim, Kyung Ho Kim, Myoung Kuk Jang, Jin Heon Lee, Hak Yang Kim, and Woon Geon Shin*
Department of Internal Medicine, Hallym University College of Medicine, Seoul, Korea.
Correspondence to: Woon Geon Shin. Division of Gastroenterology, Department of Internal Medicine, Hallym University Kangdong Sacred Heart Hospital, Hallym University College of Medicine, 150 Seongan-ro, Gangdong-gu, Seoul 134-701, Korea. Tel: +82-2-2225-2814, Fax: +82-2-2224-2690, sgun91@medimail.co.kr
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
As the incidence rate of and mortality from pseudomembranous colitis (PMC) are increasing worldwide, it is important to study the simple predictive risk factors for PMC among patients with hospital-acquired diarrhea (HAD). This study focused on identifying the clinical risk factors that can easily predict PMC.
The presumed HAD patients were prospectively recruited at the Hallym University Kangdong Sacred Heart Hospital.
Age of 70 and older (adjusted odds ratio [OR], 1.76; 95% confidence interval [CI], 1.12 to 0.75), use of proton pump inhibitors (adjusted OR, 4.07; 95% CI, 2.512 to 6.57), use of cephalosporins (adjusted OR, 2.99; 95% CI, 1.82 to 4.94), and underlying cancer (adjusted OR, 1.72; 95% CI, 1.04 to 2.82) were independent risk factors for PMC in the multivariate logistic regression analysis. The prevalence of PMC was very low in the patients with HAD who exhibited no risk factors.
The risk factors for PMC in patients with HAD included cephalosporin use, proton pump inhibitor use, old age, and cancer. Considering the strongly negative predictive values of these risk factors, endoscopic evaluation can be delayed in patients with HAD without risk of developing PMC.
Keywords: Enterocolitis, pseudomembranous,
There are many causes of hospital-acquired diarrhea (HAD), including medications, nasogastric tube feeding, bowel ischemia, or constipation causing pseudodiarrhea. Antibiotics are the most common cause of HAD. Recently, the incidence of antibiotic-associated diarrhea (AAD) has increased rapidly due to use of broad-spectrum antibiotics.1 In the preantibiotic era, pseudomembranous colitis (PMC) was associated with ischemic cardiovascular insufficiency, colonic obstructions, heavy metal intoxication, sepsis, shock, or uremia.2 Since the 1970s,
The clinical spectrum of HAD associated with antimicrobial agents varies from simple antibiotic-associated diarrhea (SAAD) to fatal PMC. Compared with SAAD or CDAD, PMC has a poor prognosis and more severe clinical manifestations, such as ascites and transmural inflammation of the colon,8 although severe CDAD can be associated with significant mortality.9,10 For these reasons, medical treatments, such as oral administration of metronidazole or vancomycin, are usually recommended for
Considering that the early diagnosis of PMC and urgent appropriate treatment are clinically crucial, it is important to assess simple predictors for PMC among HAD patients; however, many studies have focused on risk factors of AAD or CDAD. To the best of our knowledge, no prospective study has examined the risk factors of PMC. However, Lee et al.12 published a retrospective study assessing risk factors of PMC in 2006. The aim of this study was to identify the risk factors of PMC that can be easily applied to the treatment of patients with HAD.
The HAD is defined as defecation of watery or loose stool more than three times a day for more than two days that started more than 48 hours after admission. SAAD was defined as antibiotic-related diarrhea without any other cause, and CDAD was defined as a positive result on a stool
The study included adult patients 20 years or older with HAD. The exclusion criteria were as follows: 1) other causes of diarrhea, such as stool softeners, gastrointestinal (GI)-motility drugs, or anticancer drugs; 2) other GI disease-causing diarrhea, such as inflammatory bowel disease; and 3) diarrhea with an indefinite cause.
The HAD patients were recruited prospectively by consultation from the various medical or surgical departments, such as cardiology, orthopedics, neurosurgery, and general surgery, in Hallym University Kangdong Sacred Heart Hospital from June 2007 to September 2011.
In total, 1,508 patients with HAD were detected after admission. Among these patients, 88 were excluded from the study because they had GI disease causing diarrhea other than AAD, CDAD, or PMC (n=24) or were taking medicine causing diarrhea such as stool softeners, GI motility drugs (n=37), or anticancer drugs (n=19). Some patients were found to suffer from HAD with an indefinite cause (n=8). We depict the diagnostic flow chart applied in this study in Fig. 1.
The study protocol and exemption of informed consent were approved by the Institutional Review Board of the Kangdong Sacred Heart Hospital.
The enrolled patients were divided into PMC and non-PMC groups to assess predictors for diagnosing PMC. In addition, predictors for
In total, 1,420 patients were analyzed (mean age, 66 years; 47.25% were female). The PMC group consisted of 104 patients and the non-PMC group was composed of 1,316 patients. Of 23 parameters, nine were significantly associated with PMC after univariate analysis. The mean number of administered antibiotics before starting diarrhea was 3.77 and 2.87 in the PMC and non-PMC groups, respectively (p=0.001). The use of cephalosporins (70/104, 67.31% vs 441/1,316, 33.51%) and clindamycin (13/104, 12.50% vs 87/1,316, 6.61%) was more common in the PMC group than in the non-PMC group; both differences were statistically significant (cephalosporins, p<0.0001; clindamycin, p=0.013). The PMC group was significantly older than the non-PMC group (69.77 vs 61.62 years; p<0.0001), reflecting the increasing incidence of PMC with age. The number of postoperative patients was greater in the PMC group (44/104, 42.31% vs 393/1,316, 29.86%; p=0.004). The patients were also divided by surgery type (orthopedic: PMC 18.27%, non-PMC, 9.12%, p=0.002; otorhinolaryngologic: PMC 8.65%, non-PMC 4.79%, p=0.04). The number of PPI use in the PMC group was significantly more than that of the non-PMC group (41/104, 39.42% vs 145/1,316, 11.02%; p<0.0001), although there is no significant difference between the two groups in terms of the dose or length of PPI administration. Regarding underlying disease, 28.85% (30/104) of the PMC group and only 17.02% (224/1,316) of the non-PMC group had cancer (p=0.002). Chronic renal failure was more common in the PMC group than in the non-PMC group (11/104, 10.58% vs 81/1,316, 6.16%; p=0.04), and cerebrovascular disease was more common in the PMC group than in the non-PMC group (17/104, 16.35% vs 130/1,316, 9.88%; p=0.02) (Table 1).
Multivariate logistic regression analysis was performed for these nine variables. Age greater than 70 years (adjusted odds ratio [OR], 1.76; 95% confidence interval [CI], 1.12 to 2.75; p=0.01), use of PPI (adjusted OR, 4.07; 95% CI, 2.52 to 6.59; p<0.0001), use of cephalosporins (adjusted OR, 2.99; 95% CI, 1.82 to 4.94; p<0.0001), and underlying cancer (adjusted OR, 1.72; 95% CI, 1.04 to 2.82; p=0.03) were the predictors of PMC (Table 2).
To determine how well the final model predicted PMC, we developed risk groups based on the number of predictive clinical factors. When no predictors were present, 1.54% (7/454) of the patients developed PMC; when only one was present, 5.39% (29/538) developed PMC; when two, three, and four were present, 10.42% (32/307), 29.73% (33/111), and 30.0% (3/10) developed PMC, respectively. There was a significant difference in the morbidity rate of PMC between the group with no predictors and that with one or more predictors (OR, 7.13; 95% CI, 3.28 to 15.48; p<0.0001) (Table 3).
The positive predictive value (PPV) and the negative predictive value (NPV) of age older than 70 years were 0.11 and 0.94, respectively. The PPV and NPV were 0.22 and 0.95 for PPI use, 0.14 and 0.96 for the use of cephalosporins, and 0.12 and 0.94 for underlying cancer, respectively. The NPV was better than the PPV for all of the evaluated predictors of PMC. For predicting PMC, the sensitivity and the specificity of age older than 70 years were 45.00% and 60.49%, respectively. They were 39.42% and 88.98% for PPI use, 67.31% and 66.49% for the use of cephalosporins, and 28.85% and 82.98% for underlying cancer, respectively (Table 4).
The
Multivariate logistic regression analysis was performed for the 15 significantly associated variables. Age older than 66 years (adjusted OR, 1.66, 95% CI, 1.23 to 2.44; p=0.001), number of used antibiotics (adjusted OR, 1.08; 95% CI, 1.02 to 1.15; p=0.009), sex (adjusted OR, 1.38, 95% CI, 1.03 to 1.86; p=0.03), use of PPI (adjusted OR, 1.92; 95% CI, 1.34 to 2.75; p<0.0001), use of cephalosporins (adjusted OR, 1.87; 95% CI, 1.37 to 2.55; p<0.0001), underlying cancer (adjusted OR, 1.58; 95% CI, 1.13 to 2.22; p=0.008), and cerebrovascular disease (adjusted OR, 1.55; 95% CI, 1.03 to 2.33; p=0.04) were the predictors of
To determine how well the final model predicted
The PPV and NPV of age older than 66 years were 0.30 and 0.82, respectively. The PPV and NPV were 0.28 and 0.86 for the number of antibiotics used; 0.26 and 0.80 for female sex, 0.39 and 0.79 for use of PPI, 0.35 and 0.83 for use of cephalosporins, 0.31 and 0.79 for underlying cancer, and 0.35 and 0.78 for underlying cerebrovascular disease, respectively. The NPV was better than the PPV for all of the evaluated predictors of
When HAD patients are in poor clinical condition, it is impossible to wait for the result of
This study design focuses on the predictors that can easily predict PMC in a clinical setting. The independent predictors of PMC were old age (≥70 years), use of PPI, use of cephalosporins, and history of cancer. Additionally, the predictors of CDAD were old age (≥66 years), use of PPI, use of cephalosporins, history of cancer, number of used antibiotics, female sex, and previous history of CVA. The good NPVs of the independent predictors (0.94 to 0.96) suggest that the patients without any of the predictors described above may not have a risk of PMC. Importantly, the fewer predictors the HAD patients had, the lower the risk of PMC or CDAD. We depict the suggested algorithm (based on these results) in Fig. 2. This preemptive treatment algorithm may not be applicable to all HAD patients without risk factors for PMC. In fact, among 104 patients with PMC, seven patients did not have any risk factor and three patients showed negative toxin assay, though there was no patient that showed both negative toxin assay and did not have any risk factor. However, sigmoidoscopy or colonoscopy cannot be done in a considerable proportion of hospitalized patients with diarrhea because of their medical conditions. The suggested algorithm may be more valuable in those situations. In brief, if HAD patients may have acute infectious diarrhea (fever >38.5℃, severe abdominal pain, bloody diarrhea, severe volume depletion, diarrhea lasting >48 hours, compromised immune system or age >70 years), endoscopy should be considered first, according to the well-known recommendation of textbooks;13,14 however, when endoscopy is not available because of the patients' conditions, without the predictors of PMC revealed in this study, antibiotic treatment may become delayed in HAD patients until the results of the
The well-known predictors associated with CDAD are grouped into host and drug factors. Age older than 65, severe underlying disease, compromised immune system, history of GI surgery, history of stay at an intensive care unit, long duration of stay and insertion of nasogastric tube are noted host factors.11,15 The type of antibiotics, length of antibiotic course, and history of using multiple antibiotics are drug factors.16
In patients that use PPI, there were approximately 4- and 2-fold increases in the risk for PMC and CDAD, respectively. PPI use showed the highest AOR for both PMC and CDAD in this comparison. The single case-control study reported that patients with PPI had a 2.5-times higher risk of CDAD compared with those without PPI.17 A meta-analysis conducted in 2012 showed a 65% increase in the incidence of CDAD among PPI users;18 however, the association between use of PPI and the development of CDAD has not been conclusive until now because the results of some reports do not coincide.1,19,20 Although the mechanism of this association between PPI and
In addition, elderly patients were prone to CDAD and PMC. This result of the present study was similar in this respect to that of another study.21 Elderly patients, compared with younger patients, are more likely to be exposed to
Interestingly, no type of surgery increased the risk of PMC and CDAD in this study; however, there were reports that GI surgery, which is known to contribute to changes in the normal intestinal flora due to the required pretreatment (e.g., bowel preparation, nasogastric tube insertion, and empirical antibiotic use), increases the risk of CDAD.15,16,22 Moreover, McCarter et al.23 reported that for pretreated patients, the risk of CDAD was 4.2 times higher than that of the control group, regardless of the type of surgery. Furthermore, probiotic use was not an independent preventive factor in the multiple logistic regression analysis, although some studies showed that probiotics might help to prevent
In this study, surprisingly, female sex was another independent predictor of
There are several limitations in this study. First, PMC may have been misclassified as CDAD because not all enrolled HAD patients underwent colonoscopy because of poor general condition or patient refusal. Therefore, the PPVs of PMC predictors might be underestimated; however, considering that most patients with PMC are in debilitated condition, unjustified endoscopic examination would be harmful and unethical because bowel preparation or air inflation during endoscopy could aggravate the colonic inflammation. Second, this study did not investigate the performance of cancer patients. The performance of cancer patients is varied. Some patients with localized curable cancer show normal performance, but others may perform very poorly due to progression of the cancer or systemic chemotherapy. Although there was approximately a 1.5-fold increase in the risk for both PMC and CDAD in cancer patients, this result could be altered if the performance scale of the cancer patients was to be evaluated. Third, selection bias is a possibility, although this study was conducted prospectively. We could not include nasogastric-tube feeding as a variable (although it is reported as a CDAD predictor in other studies) because we classified the patients with tube feeding as having other or indefinite causes of diarrhea and excluded these patients in the study design.
In conclusion, the independent predictors of PMC in HAD patients were PPI use, cephalosporins use, old age (≥70 years), and history of cancer. In particular, PPI use had the highest adjusted OR (4.07) for PMC. Therefore, we suggest the implementation of a preemptive management algorithm; based on the good NPVs of these predictors, endoscopic evaluation can be delayed in HAD patients without any predictors of PMC.
*Endoscopic evaluation was performed, if possible, before the results of the toxin assay became available for the patients with severe abdominal pain, dehydration, bloody diarrhea, or fever.
CRP, C-reactive protein; CBC, complete blood cell count; LFT, liver function test.
Table 1 Univariate Analysis of Risk Factors for Pseudomembranous Colitis or
Data are presented as mean±SD or number (%).
PMC, pseudomembranous colitis; GS, general surgery; OS, orthopedic surgery; OBGY, obstetrics and gynecology; ENT, ear, nose, and throat (otolaryngology); NS, neurosurgery; CS, chest surgery; PPI, proton pump inhibitor; DM, diabetes mellitus; CRF, chronic renal failure; CVA, cerebrovascular accident.
*Duration of hospital stay indicates days until the onset of diarrhea after admission.
PMC, pseudomembranous colitis; GS, general surgery; OS, orthopedic surgery; OBGY, obstetrics and gynecology; ENT, ear, nose, and throat (otolaryngology); NS, neurosurgery; CS, chest surgery; PPI, proton pump inhibitor; DM, diabetes mellitus; CRF, chronic renal failure; CVA, cerebrovascular accident.
*Duration of hospital stay indicates days until the onset of diarrhea after admission.
Table 2 Multivariate Regression Analysis of Risk Factors for Pseudomembranous Colitis or
OR, odds ratio; CI, confidence interval; PMC, pseudomembranous colitis; PPI, proton pump inhibitor; CVA, cerebrovascular accident.
*Evidence for selecting elderly patients: Age increases both the sensitivity and specificity of the receiver operating characteristic curve.
PMC, pseudomembranous colitis; GS, general surgery; OS, orthopedic surgery; OBGY, obstetrics and gynecology; ENT, ear, nose, and throat (otolaryngology); NS, neurosurgery; CS, chest surgery; PPI, proton pump inhibitor; DM, diabetes mellitus; CRF, chronic renal failure; CVA, cerebrovascular accident.
*Duration of hospital stay indicates days until the onset of diarrhea after admission.
Table 3 Model for Predicting Pseudomembranous Colitis and
Data are presented as number (%).
PMC, pseudomembranous colitis.
*Odds ratio 7.1279, 95% confidence interval 3.2822 to 15.4795, p<0.0001; †Odds ratio 3.0068, 95% confidence interval 1.933 to 4.678, p<0.0001; ‡p<0.0001; §There is no patient who exhibits all of the
PMC, pseudomembranous colitis; GS, general surgery; OS, orthopedic surgery; OBGY, obstetrics and gynecology; ENT, ear, nose, and throat (otolaryngology); NS, neurosurgery; CS, chest surgery; PPI, proton pump inhibitor; DM, diabetes mellitus; CRF, chronic renal failure; CVA, cerebrovascular accident.
*Duration of hospital stay indicates days until the onset of diarrhea after admission.
Table 4 Positive Predictive Value, Negative Predictive Value, Sensitivity, and Specificity of the Risk Factors for Pseudomembranous Colitis and
Data are presented as percentage (number). A, the number of PMC or
PPV, positive predictive value; NPV, negative predictive value; PMC, pseudomembranous colitis; PPI, proton pump inhibitor; CVA, cerebrovascular accident.
PMC, pseudomembranous colitis; GS, general surgery; OS, orthopedic surgery; OBGY, obstetrics and gynecology; ENT, ear, nose, and throat (otolaryngology); NS, neurosurgery; CS, chest surgery; PPI, proton pump inhibitor; DM, diabetes mellitus; CRF, chronic renal failure; CVA, cerebrovascular accident.
*Duration of hospital stay indicates days until the onset of diarrhea after admission.